Assessment of anticancer drug utilization pattern and patients’ survival—A single center experience from Saudi Arabia

Ahmed Badheeb; Manea Al Munjem; Faisal Ahmed; Huda Aljedaani; Nouf Assiri; Akrm Abdulaziz; Abdullah Abubakar; Mohammad AlQurayshah; Mohamed Badheeb

doi:10.12688/f1000research.147910.1

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Research Article

Assessment of anticancer drug utilization pattern and patients’ survival—A single center experience from Saudi Arabia

[version 1; peer review: 2 approved with reservations]

Ahmed Badheeb ^1,2, Manea Al Munjem³, Faisal Ahmed⁴, [...] Huda Aljedaani³, Nouf Assiri³, Akrm Abdulaziz³, Abdullah Abubakar⁵, Mohammad AlQurayshah⁶, Mohamed Badheeb⁷

Ahmed Badheeb ^1,2, Manea Al Munjem³, [...] Faisal Ahmed⁴, Huda Aljedaani³, Nouf Assiri³, Akrm Abdulaziz³, Abdullah Abubakar⁵, Mohammad AlQurayshah⁶, Mohamed Badheeb⁷

PUBLISHED 31 May 2024

Author details Author details

¹ Oncology, Hadhramout University, Al Mukalla, Hadhramaut Governorate, Yemen
² Department of Oncology, King Khaled Hospital, Najran, Saudi Arabia
³ Pharmacy, King Khaled Hospital, Najran, Saudi Arabia
⁴ Urology, Ibb University, Ibb, Ibb Governorate, Yemen
⁵ Ophthalmology, King Khaled Hospital, Najran, Saudi Arabia
⁶ Department of Internal Medicine, College of Medicine, Najran University, Najran, Saudi Arabia
⁷ Internal Medicine, Yale New Haven Health System, New Haven, Bridgeport, USA

Ahmed Badheeb
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Manea Al Munjem
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Supervision, Validation, Writing – Original Draft Preparation

Faisal Ahmed
Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Project Administration, Software, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Huda Aljedaani
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Resources, Supervision, Validation, Writing – Original Draft Preparation

Nouf Assiri
Roles: Conceptualization, Data Curation, Funding Acquisition, Investigation, Project Administration, Resources, Software, Writing – Review & Editing

Akrm Abdulaziz
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Software

Abdullah Abubakar
Roles: Conceptualization, Investigation, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation

Mohammad AlQurayshah
Roles: Conceptualization, Formal Analysis, Investigation, Project Administration, Resources, Software, Supervision, Visualization, Writing – Review & Editing

Mohamed Badheeb
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Oncology gateway.

Abstract

Background

In recent years, various advancements in anticancer therapy have led to the development of multiple regimens and protocols. This study endeavors to provide an extensive evaluation of anticancer therapy prescription patterns in correlation with patient outcomes.

Methods

From June 2014 to April 2022, we included adult cancer patients who received anticancer therapy in our cancer center. Collected data encompassed demographic characteristics of patients and cancer, chemotherapy protocols or agents, antiemetics, drug side effects, and the patient’s last status. The prescribed drugs were assessed using the Essential Medicines List, while the prescription’s rationality was determined using the World Health Organization indicators.

Results

The mean age was 55.16 ± 17.04 years, with 56.4% of the patients being males. Gastrointestinal (29.7%) and breast (25.8%) cancers were the most common malignancies. The main protocols included a combination of Adriamycin and cyclophosphamide (20.1%) and folinic acid, fluorouracil, and oxaliplatin-based (FOLFOX) regimen (13.5%). The most frequently used drugs were doxorubicin (14.0%), cyclophosphamide (13.3%), and docetaxel (9.9%). The majority of patients also did not report any acute adverse events related to chemotherapy (81.1%). Antiemetics, mainly metoclopramide-based, were used in 76.07% of cases. Remarkably, 86.7% of anticancer agents were from the EML, and 90.1% were prescribed generically.

Conclusion

In this study, gastrointestinal cancers were the most prevalent cancers observed, with more preponderance among males. Most anticancer agents were taken from the essential drug list, with the majority being prescribed under generic names, indicating rational use.

Keywords

chemotherapy, anticancer, drug use pattern, Najran, Saudi Arabia.

Corresponding author: Ahmed Badheeb

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2024 Badheeb A et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Badheeb A, Al Munjem M, Ahmed F et al. Assessment of anticancer drug utilization pattern and patients’ survival—A single center experience from Saudi Arabia [version 1; peer review: 2 approved with reservations]. F1000Research 2024, 13:560 (https://doi.org/10.12688/f1000research.147910.1) First published: 31 May 2024, 13:560 (https://doi.org/10.12688/f1000research.147910.1) Latest published: 24 Jul 2025, 13:560 (https://doi.org/10.12688/f1000research.147910.2)

Introduction

Cancer perpetuates a significant cause of mortality and morbidity on a global scale, despite a notable decrement in mortality rates, evidencing a 33% reduction since 1991. Moreover, an estimated 10 million deaths annually are anticipated to be cancer-related.¹^,² The Middle Eastern regions, albeit with lower cancer incidence rates, are far from exempt from this burden, and projections delineate an ascendant trend in incidence.³ According to studies from the Arab world, these regions have a higher mortality-to-incidence ratio, which is exacerbated by limited cancer surveillance, implying a higher rate of undiagnosed cases.⁴ Saudi Arabia has seen an increase in cancer cases, with diagnoses increasing from about 20,000 to more than 27,000 between 2018 and 2020, respectively.⁵ Recent advancements in cancer research have sharpened diagnostic accuracy, facilitated earlier cancer detection, and thereby contributed to an increased prevalence rate. Furthermore, the advent of multi-modality therapeutic interventions, such as chemotherapy, targeted therapy, radiation, and surgery, has enriched the repertoire of cancer management resources.⁶^,⁷ However, these interventions may cause adverse events ranging from mild symptoms (e.g., gastrointestinal discomfort and hair loss) to severe ones (e.g., life-threatening organ dysfunction).⁷ Consequently, prudent anticancer therapy selection necessitates a thorough evaluation of potential benefits, risks, and overall survival projections.⁶^,⁷

To aid in the meticulous selection of anticancer therapies, the World Health Organization (WHO) launched a regional initiative known as the WHO Model List of Essential Medicines, also known as the Essential Medicines List (EML).⁸ This initiative is critical in choosing optimal, cost-effective, population-based therapies, with updates being made bi-annually. It is also particularly promising for low- and middle-income countries, which bear the brunt of the cancer burden.⁹ Such an initiative is paramount in a time characterized by a rapid influx of drugs, burgeoning clinical trials, and swiftly evolving guidelines. Additionally, previous studies have uncovered a high degree of variability in adherence to therapeutic recommendations, as high as 61%, with negligible differences in patient factors that may influence the cancer therapy selection.¹⁰ The architecture of cancer treatment protocols customarily entails a comprehensive institutional and literature review, which is aligned with national agency approval, e.g., Food and Drug Administration, and buttressed by expert panel assessments. Nonetheless, the practicability of these methodologies may be circumscribed to nations with higher income strata, cutting-edge research centers, and institutions equipped to undertake clinical trials, leaving others at a disadvantage.¹¹ Hence, the promulgation of an international model could significantly ameliorate this gap. Within this framework, we aim to identify the chemotherapy patterns in Najran, one of Saudi Arabia’s 13 regions, and assess its adherence to the EML as recommended by the WHO.

Methods

Study design

A retrospective observational study conducted between June 2014 and April 2022 at King Khaled Hospital (KKH) in Najran City, Saudi Arabia included all adult patients with cancer regardless of the stage or treatment type. On March 13, 2022, the Ethics Research Committees of King Khalid Hospital approved this study (ID: 2022-11 E), which was carried out in compliance with the Helsinki Declaration. Due to the anonymous retrospective nature of the study, written informed consent from the included patients was not required. The patients were all monitored for the duration of the study. The study included by default all adult patients, defined as >18 years old, with an established pathological diagnosis of cancer who were managed in our cancer center. The pathological confirmation requires tissue sampling that’s obtained on the basis of the tumor nature and site, typically through minimally invasive procedures (e.g., fine-needle aspiration, core biopsy) or excisional tissue (i.e., postoperative). We excluded patients with no pathological confirmation, in addition to patients who were non-recipients of chemotherapy, diagnosed but referred or managed out of cancer center, had incomplete records, lost during follow-up, or those without consent to participate were excluded.

Study variables

The variables included in this research included patient demographics (age and gender), diagnosis year, concurrent comorbidities, cancer location and stage (metastatic and non-metastatic), treatment intent, delay before initiating chemotherapy, chemotherapy regimens and agents, antiemetic use, drug side-effects manifestation, patient final status (survivors and non-survivors) and the last follow-up duration. Utilizing logistic regression analysis, we investigated the variables impacting survival rates. The study’s dependent variables were delineated by WHO prescribing, patient care, and health facility indicators,¹² with socio-demographic traits (age and gender) acting as predictor variables. Metrics such as the average number of drugs per encounter and the percentages of drugs named generically, encounters involving drug prescription, as well as prescribed drugs from the essential drugs list were computed to provide a granular insight into prescribing trends.

Study outcome

This study primarily evaluated the prescribing trends of anticancer drugs.

Statistical analysis

Upon concluding the study, the WHO core prescribing indicators were compiled to ascertain the prevalence of polypharmacy, the proportion of prescriptions entailing injectables, and the percentage of drugs enlisted on the EML.¹³ All statistical evaluations were conducted using Statistical Package for Social Sciences (IBM SPSS Statistics for Windows, version 21.0, Armonk, NY: IBM Corp.). Continuous variables were depicted as mean values and standard deviations, while categorical variables were illustrated through frequency and percentage. Data normalcy was gauged using the Kolmogorov-Smirnov test. A p-value of less than 0.05 was acknowledged as statistically significant.

Results

In this study, there were 289 (56.4%) male patients among the 512 included cases. The mean age was 55.16 ± 17.04 years, and the majority of patients were considered middle-aged (178 cases, 34.8%). Most of them (87.9%) were Najran City residents. Also, 218 of them (42.5%) were diagnosed in 2020-2021. The patients’ demographic characteristics are provided in Table 1. Gastrointestinal cancer was the most prevalent in our cohort at 29.7%, followed by breast cancer accounting for 25.8% of malignancies. In addition, 46.7% of the patients had distant metastasis. All the study cohorts received chemotherapy in Najran, and about 16.7% received further treatment in other centers within SA. Curative treatment was given to 315 (61.5%) patients, while palliative chemotherapy was provided for 197 (38.4%). Moreover, 75.4% of our patients (386 cases) received definitive treatment within 6 weeks or less, while 4.3% had it for more than 6 weeks and 20.3% for an undetermined duration. Furthermore, 297 (58%) patients had a comorbid condition; among these, 122 (23.8%) had diabetes alone or with other comorbidities, while 103 (20.11%) had hypertension alone or with other comorbidities. Other comorbid conditions included thyroid disease in 10 (2%) patients and chronic obstructive pulmonary disease in seven (1.4%) others. Doxorubicin hydrochloride [Adriamycin and cyclophosphamide] (AC) was the most commonly used protocol in 11.1% of the patients, followed by folinic acid, fluorouracil, and oxaliplatin-based (FOLFOX) regimens in 7.4%, XELOX-based regimens (combination of capecitabine with oxaliplatin) in 5.7%, and R-CHOP (rituximab [Rituxan], cyclophosphamide [Cytoxan], doxorubicin [Adriamycin], vincristine [Oncovin], and prednisone) in 4.3% of our study cohorts. Moreover, the most commonly involved medications in our study were doxorubicin (14.0%), cyclophosphamide (13.3%), and docetaxel (9.9%) (Table 2). Furthermore, the majority of our patients (81.1%) did not report any acute adverse events related to chemotherapy; hypersensitivity reactions (e.g., itching, skin rashes, and shortness of breath) and anaphylactic shock were reported in only 1.3% of our patients. Other documented side effects included neutropenic fever (2.5%) and delayed skin reaction (1.2%). In addition, a documented medication shortage or unavailability was observed in only 8.4% of patients, with BCG (Bacillus Calmette-Guerin) (0.8%), aprepitant (0.6%), and gemcitabine (0.6%) accounting for the most frequently unavailable medications. The most commonly used antiemetic was a metoclopramide-based regimen, which was noted in 82.6% of patients (Table 3).

Table 1. Demographic characteristics of patients, cancer site, and treatment features.

Variables	N (%)
Age (year), mean ± SD	55.16 ± 17.04
Gender
Male	289 (56.4%)
Female	223 (43.6%)
Cancer site
Gastrointestinal system	152 (29.7%)
Colorectal cancer	78 (51.32%)
Gastric cancer	32 (21.05%)
Pancreatic cancer	20 (13.16%)
Hepatocellular cancer	7 (4.61%)
Other	15 (9.87%)
Breast cancer	132 (25.8%)
Hematological cancer	87 (17%)
Lymphoma	67 (77%)
Leukemia	10 (11.5%)
Myeloma	10 (11.5%)
Head, neck, and respiratory tract cancers	53 (10.35%)
Nasopharyngeal cancer	15 (28.3%)
Lung cancer	23 (43.4%)
Central nervous system cancer	3 (5.7%)
Other cancers	12 (22.6%)
Female reproductive	39 (7.6%)
Ovarian cancer	24 (61.5%)
Endometrial cancer	13 (33.3%)
Other female reproductive cancer	2 (5.1%)
Male urologic cancer	28 (5.5%)
Prostate cancer	20 (71.4%)
Testicular cancer	7 (25%)
Other male urologic cancers	1 (3.6%)
Bladder cancer	19 (3.7%)
Distance metastasis	239 (46.7%)

Table 2. Prescription pattern of each anticancer drug.

Class/Action	Drug name	N (%)
Alkylating Agents	Cyclophosphamide	74 (13.3%)
	Carboplatin	49 (8.8%)
	Oxaliplatin	49 (8.8%)
	Cisplatin	41 (7.4%)
	Ifosfamide	12 (2.2%)
Antitumor Antibiotics	Doxorubicin	78 (14.0%)
	Bleomycin	11 (2.0%)
	Epirubicin *	9 (1.6%)
Plant Alkaloids and Antimitotics	Vinblastine	12 (2.2%)
Plant Alkaloids and Antimitotics	Vinorelbine	4 (0.7%)
Topoisomerase Inhibitors	Irinotecan	20 (3.6%)
Topoisomerase Inhibitors	Etoposide	14 (2.5%)
Antimetabolites	5-Fluorouracil	45 (8.1%)
	Capecitabine	45 (8.1%)
	Gemcitabine	43 (7.7%)
	Methotrexate	6 (1.1%)
Hormones and Antagonists	Tamoxifen	41 (7.4%)
	Leuprorelin	41 (7.4%)
	Letrozole	19 (3.4%)
	Bicalutamide *	9 (1.6%)
Immunotherapies	Nivolumab	17 (3.1%)
	Pembrolizumab	6 (1.1%)
	Durvalumab *	1 (0.2%)
Targeted Therapies	Trastuzumab	33 (5.9%)
	Bevacizumab	24 (4.3%)
	Rituximab	20 (3.6%)
	Cetuximab *	8 (1.4%)
	Panitumumab *	7 (1.3%)
	Others^†	13 (2.4%)
Others	Docetaxel	55 (9.9%)
	Paclitaxel	49 (8.8%)
	Leucovorin *	42 (7.6%)
	Goserelin	13 (2.3%)
	Denosumab *	10 (1.8%)
	Bortezomib	6 (1.1%)
	Others^‡	14 (2.6%

† Others: Palbociclib *, Lenalidomide, Imatinib, Crizotinib *, Lenvatinib *.

‡ Others: Ramucirumab *, BCG, Thalidomide, Dacarbazine *, Olaparib *.

Table 3. Prescription pattern of each adjuvant drug.

Variables	N (%)
Dexamethasone	501 (90.1%)
Metoclopramide	423 (76.07%)
Ondansetron	412 (74.1%)
Furosemide	55 (9.9%)
Aprepitant	42 (7.6%)
Pantoprazole	42 (7.6%)
Zoledronic acid	12 (2.2%)
Multivitamins	4 (0.7%)
Netupitant/palonosetron	4 (0.7%)

Anticancer drugs utilization

A total of 1,021 anticancer drugs were administered to this study’s 512 participants. On average, each patient received 1.99 anticancer drugs. As for the drug utilization pattern, 61.32% of patients (314 individuals) were prescribed a single anticancer drug, while the rest received a combination of multiple anticancer drugs, as detailed in Table 4.

Table 4. Results of drug use core indicators and ideal WHO standards.

Prescribing indicators	In-patient	Reference value⁷
Average number of drugs per encounter	1.99	<2
Percentage of drugs by generic names	90.1%	100%
Percentage of drugs prescribed from national essential drug list	86.7%	85.3%
Number of adjuvant/supportive drugs prescribed per patient	2.91
Number of drugs prescribed per patient	4.91

Discussion

Cancer imposes an extremely high burden on the healthcare system, with high medication costs that are projected to increase further, especially among patients diagnosed in the later stage of the illness.¹⁴ Targeting more efficient, cost-effective therapies is crucial to providing cancer care that suits the nation’s needs; such interventions require a meticulous assessment of drug utilization patterns to ensure health equity, consistency, and coherence.¹⁵ In our cancer center, more than 22 types of cancer were observed, and 45 anticancer drugs were prescribed. In this study, the most commonly used protocols included doxorubicin hydrochloride (Adriamycin) and cyclophosphamide (11.1%), followed by FOLFOX-based (7.4%), XELOX-based (5.7%), and R-CHOP regimens (4.3%). This pattern occurred due to the variety of cancers that affect patients in our geographical area, which is also consistent with the prevalence of cancers treated with these protocols.¹⁶^–¹⁸

Doxorubicin, cyclophosphamide, and docetaxel accounted for the most commonly involved chemotherapeutic agents in our study, which is related to the prevalence of gastrointestinal and breast cancers that were predominant in our cohorts in SA.¹³^,¹⁸ Different chemotherapeutic agents may be used variably depending on the cancer institute’s focus or specialization, or the incidence of cancer in the involved region. For instance, in a study involving metastasis cancer drug utilization patterns, cisplatin (58%) and 5-fluorouracil (41%) were two of the most prescribed anticancer drugs, followed by doxorubicin.¹⁹ In another study, Aggarwal et al. revealed that paclitaxel, cisplatin, and 5-Fluorouracil (PCF) were the most commonly used agents; however, among the study population, oral cavity was the most common cancer site for which the PCF regimen was used.²⁰ Moreover, similar studies found that platinum-based or taxane-based chemotherapy groups appeared to be the most commonly used agents,⁷^,²¹ with variation in the selected agents explained in part by availability, insurance coverage, physician experience or training, and cost.

In this study, 1,021 anticancer agents were prescribed among the 512 patients, corresponding to a drug-to-patient ratio of 1.99. Individualized analysis, however, showed that 314 (61.32%) of the patients received only a single agent. Our findings were similar to those of previous studies, such as Bepari et al.,⁷ but it is slightly higher compared to research conducted by Kumar et al., which had a drug-to-patient ratio of 1.73. Of note, their sample size was smaller than ours, and about 43.5% of their participants received single-agent therapy.²² Nevertheless, Kumar et al.’s findings were drastically higher than those of Dave et al., with only 5.4% of their patients receiving single-agent chemotherapy. The latter study, however, had a different cancer rate, with lung and oropharyngeal cancers accounting for over 50% of cases.²³ In our study, 86.7% of the agents used were from the EML, slightly surpassing the rates reported in previous studies, which ranged from 80%-82%.⁷^,²⁴ Our findings revealed that 92.4% of the medications provided in our cancer center were also on the Saudi Food and Drug Authority’s essential medications list.²⁵ This indicates that our institution is doing commendable work in providing cancer patients with optimal, readily available, and cost-effective therapy.

Over 90% of the agents used on our patients were prescribed by generic name. In a Mathew et al. study,²⁴ however, an extremely low rate (8%) of generic drug use was reported; this is in contrast to the higher rates (76.6%) of generic formulary use in a study by Bepari et al.⁷ Moreover, a retrospective analysis of the findings of four clinical trials found that the genericization of various anticancer agents allowed for a remarkable decrease in medication costs.²⁶ This can be particularly crucial for cancer patients, as any financial optimization may permit financial resources to be redirected to another aspect of care.

Adjuvant therapy is crucial among cancer patients, particularly for the prevention or management of nausea and vomiting, which can affect 40-90% of them depending on chemotherapeutic agents or biological factors, such as being female, being of younger age, or having polymorphisms in the 5-HT3 receptors (e.g., 3B receptor gene).²⁷^,²⁸ In our study cohort, the most commonly used antiemetic was a metoclopramide-based regimen, which was used in 76.07% of patients. Similarly, in the Bepari et al. study, antiemetics were the most commonly prescribed pre-chemotherapy drugs.⁷ Furthermore, most of the patients in their study were prescribed adjuvant steroids, combined with chemotherapy, to minimize the chemotherapy medications’ adverse effects such as nausea and vomiting.²⁹

Study limitations

The retrospective design of our study renders it susceptible to selection and attrition biases. Additionally, as a single-center study, the sample is limited to a geographic location that might not be representative of the overall country's population, which limits the generalizability of the study. Furthermore, the data were extracted from patients' medical records, which depends on the accuracy of documentation. Lastly, the factors evaluated are susceptible to confounding bias, which is attributed to unadjusted variables.

Conclusions

In this study, gastrointestinal cancers were the most prevalent cancers observed, with more preponderance among males. Doxorubicin, cyclophosphamide, and docetaxel were the most frequently used cytotoxic drugs, while the most commonly used adjuvant drugs were antiemetics. Over 86.7% of anticancer agents were taken from the essential drug list, with 90.1% prescribed under generic names, indicating rational use.

Ethical considerations

On March 13, 2022, the Ethics Research Committees of King Khalid Hospital approved this study (ID: 2022-11 E), which was carried out in compliance with the Helsinki Declaration. Due to the anonymous retrospective nature of the study, written informed consent from the included patients was not required.

Data availability

Underlying data

Figshare: Assessment of anticancer drug utilization pattern and patients’ survival—A single center experience from Saudi Arabia. figshare. Dataset. https://doi.org/10.6084/m9.figshare.25387114.v2.³⁰

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC0).

Acknowledgments

None.

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Version 2

VERSION 2 PUBLISHED 31 May 2024

Author details Author details

Huda Aljedaani
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Resources, Supervision, Validation, Writing – Original Draft Preparation

Nouf Assiri
Roles: Conceptualization, Data Curation, Funding Acquisition, Investigation, Project Administration, Resources, Software, Writing – Review & Editing

Akrm Abdulaziz
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Software

Abdullah Abubakar
Roles: Conceptualization, Investigation, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation

Mohammad AlQurayshah
Roles: Conceptualization, Formal Analysis, Investigation, Project Administration, Resources, Software, Supervision, Visualization, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

The author(s) declared that no grants were involved in supporting this work.

Article Versions (2)

version 2

Revised

Published: 24 Jul 2025, 13:560

https://doi.org/10.12688/f1000research.147910.2

version 1

Published: 31 May 2024, 13:560

https://doi.org/10.12688/f1000research.147910.1

© 2024 Badheeb A et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Badheeb A, Al Munjem M, Ahmed F et al. Assessment of anticancer drug utilization pattern and patients’ survival—A single center experience from Saudi Arabia [version 1; peer review: 2 approved with reservations]. F1000Research 2024, 13:560 (https://doi.org/10.12688/f1000research.147910.1)

NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.

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Reviewer Report 02 Apr 2025

Shouki Bazarbashi, Alfaisal University, Riyadh, Riyadh Province, Saudi Arabia

Approved with Reservations

https://doi.org/10.5256/f1000research.162157.r297655

The study provides valuable data on chemotherapy utilization patterns from a specific region in Saudi Arabia. However, the most significant issue remains the disconnect regarding the survival analysis mentioned in the Methods but absent in the Results and Discussion. Addressing this is crucial.
The Methods explicitly state, "Utilizing logistic regression analysis, we investigated the variables impacting survival rates." However, there are no results presented for this analysis in the Results section, and no discussion of survival findings in the Discussion section

Action Needed: You must either:

a) Include the results of the logistic regression for survival in the Results section and fully discuss these findings (which factors significantly impacted survival in your cohort?) in the Discussion section. The Conclusion should also briefly reflect this key finding.
b) If the survival analysis was ultimately not performed, or if the results were inconclusive/unreliable and thus omitted, you must remove the sentence mentioning the logistic regression for survival analysis from the Methods section. The title might also need adjustment if survival is no longer a reported component. Leaving the mention in Methods without presenting results/discussion is a significant flaw.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

No source data required
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: GI cancer, GU cancer, clinical trials

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Author Response 24 Jul 2025

Dr Badheeb, Oncology, Hadhramout University, Al Mukalla, Yemen

24 Jul 2025

Author Response

Dear editor and reviewers of F1000 journal
We thank the reviewers for their valuable feedback and constructive suggestions, which have significantly improved the clarity and rigor of our manuscript. Below, ... Continue reading Dear editor and reviewers of F1000 journal
We thank the reviewers for their valuable feedback and constructive suggestions, which have significantly improved the clarity and rigor of our manuscript. Below, we provide a point-by-point response to each comment. All changes have been highlighted in the revised manuscript.
Reviewer 1: Shouki Bazarbashi
Comment 1:
“The most significant issue remains the disconnect regarding the survival analysis mentioned in the Methods but absent in the Results and Discussion. The Methods explicitly state, ‘Utilizing logistic regression analysis, we investigated the variables impacting survival rates.’ However, there are no results presented for this analysis in the Results section, and no discussion of survival findings in the Discussion section. Action Needed: You must either: a) Include the results of the logistic regression for survival in the Results section and fully discuss these findings (which factors significantly impacted survival in your cohort?) in the Discussion section. The Conclusion should also briefly reflect this key finding. b) If the survival analysis was ultimately not performed, or if the results were inconclusive/unreliable and thus omitted, you must remove the sentence mentioning the logistic regression for survival analysis from the Methods section. The title might also need adjustment if survival is no longer a reported component. Leaving the mention in Methods without presenting results/discussion is a significant flaw.”
Response:
Thank you. We agree with the reviewer that including the survival analysis is beyond the scope of the study. Thus, we revised the methods section to reflect the unintentional inclusion (see Methods, page 3-6, from starting patients and method to Statistical Analysis paragraph). In addition, we implemented the following changes:
•   Revised the manuscript title to: “Anticancer Drug Utilization and Prescription Practices in a Saudi Cancer Center (2014–2022)” (see Title Page).
•   Added a limitation in the Discussion: “The retrospective design precluded survival outcome analysis due to inconsistent follow-up documentation, representing an important area for future prospective studies” (see Discussion, page 8, last paragraph).
Dear editor and reviewers of F1000 journal
We thank the reviewers for their valuable feedback and constructive suggestions, which have significantly improved the clarity and rigor of our manuscript. Below, we provide a point-by-point response to each comment. All changes have been highlighted in the revised manuscript.
Reviewer 1: Shouki Bazarbashi
Comment 1:
“The most significant issue remains the disconnect regarding the survival analysis mentioned in the Methods but absent in the Results and Discussion. The Methods explicitly state, ‘Utilizing logistic regression analysis, we investigated the variables impacting survival rates.’ However, there are no results presented for this analysis in the Results section, and no discussion of survival findings in the Discussion section. Action Needed: You must either: a) Include the results of the logistic regression for survival in the Results section and fully discuss these findings (which factors significantly impacted survival in your cohort?) in the Discussion section. The Conclusion should also briefly reflect this key finding. b) If the survival analysis was ultimately not performed, or if the results were inconclusive/unreliable and thus omitted, you must remove the sentence mentioning the logistic regression for survival analysis from the Methods section. The title might also need adjustment if survival is no longer a reported component. Leaving the mention in Methods without presenting results/discussion is a significant flaw.”
Response:
Thank you. We agree with the reviewer that including the survival analysis is beyond the scope of the study. Thus, we revised the methods section to reflect the unintentional inclusion (see Methods, page 3-6, from starting patients and method to Statistical Analysis paragraph). In addition, we implemented the following changes:
•   Revised the manuscript title to: “Anticancer Drug Utilization and Prescription Practices in a Saudi Cancer Center (2014–2022)” (see Title Page).
•   Added a limitation in the Discussion: “The retrospective design precluded survival outcome analysis due to inconsistent follow-up documentation, representing an important area for future prospective studies” (see Discussion, page 8, last paragraph).
Competing Interests: No competing interests were disclosed. Close
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COMMENTS ON THIS REPORT

Author Response 24 Jul 2025

Dr Badheeb, Oncology, Hadhramout University, Al Mukalla, Yemen

24 Jul 2025

Author Response

Dear editor and reviewers of F1000 journal
We thank the reviewers for their valuable feedback and constructive suggestions, which have significantly improved the clarity and rigor of our manuscript. Below, ... Continue reading Dear editor and reviewers of F1000 journal
We thank the reviewers for their valuable feedback and constructive suggestions, which have significantly improved the clarity and rigor of our manuscript. Below, we provide a point-by-point response to each comment. All changes have been highlighted in the revised manuscript.
Reviewer 1: Shouki Bazarbashi
Comment 1:
“The most significant issue remains the disconnect regarding the survival analysis mentioned in the Methods but absent in the Results and Discussion. The Methods explicitly state, ‘Utilizing logistic regression analysis, we investigated the variables impacting survival rates.’ However, there are no results presented for this analysis in the Results section, and no discussion of survival findings in the Discussion section. Action Needed: You must either: a) Include the results of the logistic regression for survival in the Results section and fully discuss these findings (which factors significantly impacted survival in your cohort?) in the Discussion section. The Conclusion should also briefly reflect this key finding. b) If the survival analysis was ultimately not performed, or if the results were inconclusive/unreliable and thus omitted, you must remove the sentence mentioning the logistic regression for survival analysis from the Methods section. The title might also need adjustment if survival is no longer a reported component. Leaving the mention in Methods without presenting results/discussion is a significant flaw.”
Response:
Thank you. We agree with the reviewer that including the survival analysis is beyond the scope of the study. Thus, we revised the methods section to reflect the unintentional inclusion (see Methods, page 3-6, from starting patients and method to Statistical Analysis paragraph). In addition, we implemented the following changes:
•   Revised the manuscript title to: “Anticancer Drug Utilization and Prescription Practices in a Saudi Cancer Center (2014–2022)” (see Title Page).
•   Added a limitation in the Discussion: “The retrospective design precluded survival outcome analysis due to inconsistent follow-up documentation, representing an important area for future prospective studies” (see Discussion, page 8, last paragraph).
Dear editor and reviewers of F1000 journal
We thank the reviewers for their valuable feedback and constructive suggestions, which have significantly improved the clarity and rigor of our manuscript. Below, we provide a point-by-point response to each comment. All changes have been highlighted in the revised manuscript.
Reviewer 1: Shouki Bazarbashi
Comment 1:
“The most significant issue remains the disconnect regarding the survival analysis mentioned in the Methods but absent in the Results and Discussion. The Methods explicitly state, ‘Utilizing logistic regression analysis, we investigated the variables impacting survival rates.’ However, there are no results presented for this analysis in the Results section, and no discussion of survival findings in the Discussion section. Action Needed: You must either: a) Include the results of the logistic regression for survival in the Results section and fully discuss these findings (which factors significantly impacted survival in your cohort?) in the Discussion section. The Conclusion should also briefly reflect this key finding. b) If the survival analysis was ultimately not performed, or if the results were inconclusive/unreliable and thus omitted, you must remove the sentence mentioning the logistic regression for survival analysis from the Methods section. The title might also need adjustment if survival is no longer a reported component. Leaving the mention in Methods without presenting results/discussion is a significant flaw.”
Response:
Thank you. We agree with the reviewer that including the survival analysis is beyond the scope of the study. Thus, we revised the methods section to reflect the unintentional inclusion (see Methods, page 3-6, from starting patients and method to Statistical Analysis paragraph). In addition, we implemented the following changes:
•   Revised the manuscript title to: “Anticancer Drug Utilization and Prescription Practices in a Saudi Cancer Center (2014–2022)” (see Title Page).
•   Added a limitation in the Discussion: “The retrospective design precluded survival outcome analysis due to inconsistent follow-up documentation, representing an important area for future prospective studies” (see Discussion, page 8, last paragraph).
Competing Interests: No competing interests were disclosed. Close
Report a concern

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Reviewer Report 07 Jan 2025

Pouyan Ebrahimi, Babol University of Medical Science, Babol, Iran

Approved with Reservations

https://doi.org/10.5256/f1000research.162157.r354091

This study evaluates the utilization patterns of anticancer drugs and their correlation with patient outcomes in a single cancer center in Saudi Arabia from 2014 to 2022. The findings reveal that gastrointestinal and breast cancers were the most prevalent, with doxorubicin, cyclophosphamide, and docetaxel being the most frequently used cytotoxic agents. Over 86% of prescribed medications were listed in the WHO Essential Medicines List, indicating rational drug use. The study emphasizes the importance of adhering to standardized treatment protocols while highlighting the need for improved regional cancer management strategies. However, please consider the following comments for the purpose of completing and improving the article.
Topic:
1. Considering that no survival analysis has been conducted and data such as patient survival rates or analyses related to factors influencing survival are unavailable, I recommend titling the study as "Anticancer Drug Utilization and Prescription Practices in a Saudi Cancer Center (2014–2022)."

Abstract:
2. A critical point to address throughout the manuscript, particularly in the abstract, is avoiding the use of "we" or "our" in academic writing. Instead, adopt a more formal tone. For example, in the methodology section of the abstract, replace "our cancer center" with the specific name of the center where the data was collected.

3. Please include the type of tools or software used for data analysis in the methodology section of the abstract.

4. Clearly state the type of study conducted in the methodology section.

5. In the results section, ensure the total number of cases evaluated is explicitly mentioned.

6. Given the clinical importance of metastatic cases, include the number of patients with metastases in the abstract.

7. Adjust the keywords according to MeSH terminology. Suggested keywords include "Survival," "Drug Utilization," and "Neoplasms."

Introduction:
8. The introduction is well-written; however, in the final paragraph, please elaborate on why the results of this study are important compared to similar studies.

Method:
9. Considering the long data collection period and the potential changes in drug utilization patterns, please specify in the methodology section which protocols or guidelines were used for prescribing drugs to patients during different years, ideally in intervals (e.g., every four years).

10. The sentence “those without consent to participate were excluded” seems inconsistent, as you previously mentioned that no consent was obtained due to the retrospective nature of the study. Please revise this statement for clarity.

11. The exclusion criteria mention that patients lost to follow-up were excluded, but the study design does not appear to include variables requiring follow-up, such as patient survival. Did you mean therapeutic follow-up? If so, please specify the duration and method of follow-up in the methodology section.

12. Please move the explanation regarding logistic regression mentioned in the Study Variables section to the Statistical Analysis section. Additionally, clarify whether the regression analysis was univariate or multivariate. Specify which variable(s) were independent and which were dependent in this analysis.

Result:
13. It is recommended to adjust Table 2 to include drug prescription patterns by year. Alternatively, if necessary, a separate table could be provided to address this. This addition would clarify which anticancer drugs were most frequently prescribed during each year.

14. The text states that 512 cases were evaluated; however, the total number of patients in Table 1 sums to 510. Does this discrepancy indicate that the cancer site was unidentified for two patients? Please clarify.

15. The results section does not discuss logistic regression analysis or mention odds ratios (OR). It seems that this analysis was not performed. If the authors intended Table 4 to represent logistic regression analysis, it appears to have been incorrectly designed. I recommend revising the table by clearly identifying the variables included in the model, providing OR values, 95% confidence intervals, and reference categories. The table should be formatted and written in alignment with standard academic practices.

Discussion:
The discussion section is well-written but requires deeper evaluation. For instance:

16. Why are certain drugs more commonly prescribed in this region? Are there specific socioeconomic, cultural, or healthcare-related factors driving this pattern?

17. How do the results of this study compare to other regional or international studies, particularly in terms of drug utilization patterns and patient outcomes?

18. Finally, based on the findings of this study, what recommendations can you provide to other researchers, clinicians, or policymakers to improve cancer treatment strategies?

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Given my familiarity with similar studies conducted in this field, I am well acquainted with the data collection methods and analyses employed in this study. Additionally, my ongoing research in cancer treatments provides valuable insights, enabling me to effectively contribute to reviewing the oncological aspects of this study.

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Report a concern

Author Response 02 Aug 2025

Dr Badheeb, Oncology, Hadhramout University, Al Mukalla, Yemen

02 Aug 2025

Author Response

Dear editor and reviewers of F1000 journal
We thank the reviewers for their valuable feedback and constructive suggestions, which have significantly improved the clarity and rigor of our manuscript. Below, ... Continue reading Dear editor and reviewers of F1000 journal
We thank the reviewers for their valuable feedback and constructive suggestions, which have significantly improved the clarity and rigor of our manuscript. Below, we provide a point-by-point response to each comment. All changes have been highlighted in the revised manuscript.

Reviewer 2: Pouyan Ebrahimi
Comment 1:
“Considering that no survival analysis has been conducted and data such as patient survival rates or analyses related to factors influencing survival are unavailable, I recommend titling the study as ‘Anticancer Drug Utilization and Prescription Practices in a Saudi Cancer Center (2014–2022).’”
Response:
Thank you.
The title has been revised as recommended (see Title Page). In addition, the methods section was revised to reflect these changes.
Comment 2:
“A critical point to address throughout the manuscript, particularly in the abstract, is avoiding the use of ‘we’ or ‘our’ in academic writing. Instead, adopt a more formal tone. For example, in the methodology section of the abstract, replace ‘our cancer center’ with the specific name of the center where the data was collected.”
Response:
Thank you.
The manuscript was revised using passive construction. (see Abstract, page 1; Methods, pages 3-6).
Comment 3:
“Please include the type of tools or software used for data analysis in the methodology section of the abstract.”
Response:
The methodology section of the Abstract now specifies: “Statistical analysis was performed using SPSS version 21 (IBM Corp., Armonk, NY)” (see Abstract and statistical analysis section, page 1).
Comment 4:
“Clearly state the type of study conducted in the methodology section.”
Response:
The Abstract now clearly states: “This was a retrospective, descriptive study…” (see Abstract, page X).
Comment 5:
“In the results section, ensure the total number of cases evaluated is explicitly mentioned.”
Response:
The total number of cases (N = 512) is now clearly stated in the Results section (see Results, page X, paragraph Y).
Comment 6:
“Given the clinical importance of metastatic cases, include the number of patients with metastases in the abstract.”
Response:
The Abstract now includes the number and percentage of patients with metastatic disease (see Abstract, page 1).
Comment 7:
“Adjust the keywords according to MeSH terminology. Suggested keywords include ‘Survival,’ ‘Drug Utilization,’ and ‘Neoplasms.’”
Response:
Keywords have been revised to conform to MeSH terminology (see Keywords, page 1).
Comment 8:
“In the final paragraph of the introduction, please elaborate on why the results of this study are important compared to similar studies.”
Response:
The Introduction has been expanded to emphasize the significance of our findings in the context of regional and international literature (see Introduction, page 2, final paragraph).
Comment 9:
“Please specify in the methodology section which protocols or guidelines were used for prescribing drugs to patients during different years, ideally in intervals (e.g., every four years).”
Response:
The Methods section now details the prescribing protocols and guideline updates used during the study period, including major changes in 2015 and 2019 (see Methods, page 5).
The revised section is "Prescribing Protocols and Guidelines
Anticancer drug prescriptions were guided primarily by the National Comprehensive Cancer Network (NCCN) clinical practice guidelines, adapted regionally in accordance with Saudi Food and Drug Authority (SFDA) formularies. To account for temporal changes in prescribing practices, the study period was divided into three intervals reflecting major protocol updates:
•   2014–2016: Prescriptions adhered to NCCN guidelines version 2.2014, with regional adaptations emphasizing anthracycline-based regimens for breast cancer and fluoropyrimidine-based regimens for gastrointestinal malignancies.
•   2017–2019: Following the 2017 NCCN update and SFDA formulary revisions, targeted therapies such as trastuzumab and bevacizumab were increasingly incorporated. Anthracycline protocols were refined to optimize dosing schedules.
•   2020–2022: The most recent period reflected adoption of immunotherapies (e.g., nivolumab, pembrolizumab) following their regulatory approval in Saudi Arabia, alongside continued adherence to updated NCCN and SFDA guidelines. Annual formulary reviews ensured alignment with the WHO Essential Medicines List (EML).

Comment 10:
“The sentence ‘those without consent to participate were excluded’ seems inconsistent, as you previously mentioned that no consent was obtained due to the retrospective nature of the study. Please revise this statement for clarity.”
Response:
This inconsistency has been corrected. The Methods now state: “Due to the retrospective design, informed consent was not required” (see Methods, page 3).
Comment 11:
“The exclusion criteria mention that patients lost to follow-up were excluded, but the study design does not appear to include variables requiring follow-up, such as patient survival. Did you mean therapeutic follow-up? If so, please specify the duration and method of follow-up in the methodology section.”
Response:
The exclusion criteria have been clarified to specify: “Patients with incomplete treatment records or undocumented therapeutic regimens were excluded” (see Methods, page X).
Comment 12:
“Please move the explanation regarding logistic regression mentioned in the Study Variables section to the Statistical Analysis section. Additionally, clarify whether the regression analysis was univariate or multivariate. Specify which variable(s) were independent and which were dependent in this analysis.”
Response:
As logistic regression was not performed, all references have been removed from the manuscript (see Methods and Statistical Analysis sections).
Comment 13:
“It is recommended to adjust Table 2 to include drug prescription patterns by year. Alternatively, if necessary, a separate table could be provided to address this.”
Response:
A new figure with 4 subheadings has been added to present annual prescription trends. Key temporal findings are now summarized in the Results section (see Results, pages 6-7 and 13).
Please also see the legend of Figure 1"
C. Temporal Trends in Drug Class Utilization
Grouped bar chart showing annual utilization rates of major drug classes across three epochs (2014–2016, 2017–2019, 2020–2022). Error bars represent 95% confidence intervals calculated by the binomial exact method. Statistically significant trends are annotated (Mantel-Haenszel χ² test: p<0.01 for antimetabolites, p<0.05 for immunotherapies). The dashed horizontal line indicates mean utilization across all periods (29.8%)."

Comment 14:
“The text states that 512 cases were evaluated; however, the total number of patients in Table 1 sums to 510. Does this discrepancy indicate that the cancer site was unidentified for two patients? Please clarify.”
Response:
You may say, the 2 cases were of unidentified cancer., and were removed from the total analysis. Alternatively, you can say the patients had an unidentified primary cancer site and were thus included with distant metastasis cases, which was modified to “Distant metastasis and Unidentified primary site” The text and Table 1 have been clarified to indicate that two patients had an unidentified cancer site (see Table 1 and Results, page 14).
Comment 15:
“The results section does not discuss logistic regression analysis or mention odds ratios (OR). It seems that this analysis was not performed. If the authors intended Table 4 to represent logistic regression analysis, it appears to have been incorrectly designed. I recommend revising the table by clearly identifying the variables included in the model, providing OR values, 95% confidence intervals, and reference categories. The table should be formatted and written in alignment with standard academic practices.”
Response:
As logistic regression was not performed, all related content and tables have been removed or revised to present only descriptive statistics (see Results and Table 4).
Comment 16:
“Why are certain drugs more commonly prescribed in this region? Are there specific socioeconomic, cultural, or healthcare-related factors driving this pattern?”
Response:
The Discussion now addresses regional prescribing patterns, including socioeconomic and supply chain factors (see Discussion, page 8, line 210).
The added paragraph is "Regional prescribing patterns of anticancer drugs in Saudi Arabia are influenced by multiple socioeconomic and supply chain factors. Studies, including our own, show that drug utilization is shaped not only by clinical guidelines but also by institutional policies, drug availability, and economic considerations (1). Socioeconomic factors play a key role: high generic drug utilization rates (around 90%) reflect institutional efforts to contain costs and improve access in a healthcare system balancing limited resources and rising cancer incidence (2). Patient affordability and insurance coverage also affect prescribing choices, with cost-effective regimens favored when possible. Additionally, cultural preferences and physician familiarity with certain regimens influence utilization patterns. Supply chain constraints significantly impact drug availability and prescribing. Periodic shortages of key agents such as BCG, aprepitant, and gemcitabine have been documented in Saudi centers, leading to treatment modifications or delays (2, 3). These shortages stem from global manufacturing issues, importation delays, and local distribution challenges. Such disruptions necessitate regional stockpiling strategies and formulary adjustments to maintain continuity of care (4). Moreover, regulatory policies and formulary updates guided by the Saudi FDA and alignment with the WHO Essential Medicines List ensure rational and standardized prescribing but also limit access to some novel agents, affecting utilization trends (5). For example, targeted therapies and immunotherapies have seen gradual uptake following regulatory approvals and guideline incorporation during the study period (6). In summary, regional prescribing patterns in Saudi Arabia reflect a complex interplay of guideline adherence, economic constraints, drug availability, and healthcare infrastructure. Addressing supply chain vulnerabilities and socioeconomic barriers is essential to optimize cancer treatment outcomes in the region.

Comment 17:
“How do the results of this study compare to other regional or international studies, particularly in terms of drug utilization patterns and patient outcomes?”
Response:
Comparative analysis with regional and international data has been added to the all-Discussion sections.

Comment 18:
“What recommendations can you provide to improve cancer treatment strategies?”
Response:
Three evidence-based recommendations are now included in the Discussion (see Discussion, page 7-9, and clinical implication section).
Additional Revisions:
•   All MeSH keywords standardized (see Keywords).
•   Supplemental Figures provided.
•   Table discrepancies resolved and all tables reformatted for clarity and compliance.
We hope these revisions adequately address all reviewer concerns and have further improved the manuscript’s academic quality. Thank you for your constructive feedback.
Sincerely,
Ahmed Badheeb
Dear editor and reviewers of F1000 journal
We thank the reviewers for their valuable feedback and constructive suggestions, which have significantly improved the clarity and rigor of our manuscript. Below, we provide a point-by-point response to each comment. All changes have been highlighted in the revised manuscript.

Reviewer 2: Pouyan Ebrahimi
Comment 1:
“Considering that no survival analysis has been conducted and data such as patient survival rates or analyses related to factors influencing survival are unavailable, I recommend titling the study as ‘Anticancer Drug Utilization and Prescription Practices in a Saudi Cancer Center (2014–2022).’”
Response:
Thank you.
The title has been revised as recommended (see Title Page). In addition, the methods section was revised to reflect these changes.
Comment 2:
“A critical point to address throughout the manuscript, particularly in the abstract, is avoiding the use of ‘we’ or ‘our’ in academic writing. Instead, adopt a more formal tone. For example, in the methodology section of the abstract, replace ‘our cancer center’ with the specific name of the center where the data was collected.”
Response:
Thank you.
The manuscript was revised using passive construction. (see Abstract, page 1; Methods, pages 3-6).
Comment 3:
“Please include the type of tools or software used for data analysis in the methodology section of the abstract.”
Response:
The methodology section of the Abstract now specifies: “Statistical analysis was performed using SPSS version 21 (IBM Corp., Armonk, NY)” (see Abstract and statistical analysis section, page 1).
Comment 4:
“Clearly state the type of study conducted in the methodology section.”
Response:
The Abstract now clearly states: “This was a retrospective, descriptive study…” (see Abstract, page X).
Comment 5:
“In the results section, ensure the total number of cases evaluated is explicitly mentioned.”
Response:
The total number of cases (N = 512) is now clearly stated in the Results section (see Results, page X, paragraph Y).
Comment 6:
“Given the clinical importance of metastatic cases, include the number of patients with metastases in the abstract.”
Response:
The Abstract now includes the number and percentage of patients with metastatic disease (see Abstract, page 1).
Comment 7:
“Adjust the keywords according to MeSH terminology. Suggested keywords include ‘Survival,’ ‘Drug Utilization,’ and ‘Neoplasms.’”
Response:
Keywords have been revised to conform to MeSH terminology (see Keywords, page 1).
Comment 8:
“In the final paragraph of the introduction, please elaborate on why the results of this study are important compared to similar studies.”
Response:
The Introduction has been expanded to emphasize the significance of our findings in the context of regional and international literature (see Introduction, page 2, final paragraph).
Comment 9:
“Please specify in the methodology section which protocols or guidelines were used for prescribing drugs to patients during different years, ideally in intervals (e.g., every four years).”
Response:
The Methods section now details the prescribing protocols and guideline updates used during the study period, including major changes in 2015 and 2019 (see Methods, page 5).
The revised section is "Prescribing Protocols and Guidelines
Anticancer drug prescriptions were guided primarily by the National Comprehensive Cancer Network (NCCN) clinical practice guidelines, adapted regionally in accordance with Saudi Food and Drug Authority (SFDA) formularies. To account for temporal changes in prescribing practices, the study period was divided into three intervals reflecting major protocol updates:
•   2014–2016: Prescriptions adhered to NCCN guidelines version 2.2014, with regional adaptations emphasizing anthracycline-based regimens for breast cancer and fluoropyrimidine-based regimens for gastrointestinal malignancies.
•   2017–2019: Following the 2017 NCCN update and SFDA formulary revisions, targeted therapies such as trastuzumab and bevacizumab were increasingly incorporated. Anthracycline protocols were refined to optimize dosing schedules.
•   2020–2022: The most recent period reflected adoption of immunotherapies (e.g., nivolumab, pembrolizumab) following their regulatory approval in Saudi Arabia, alongside continued adherence to updated NCCN and SFDA guidelines. Annual formulary reviews ensured alignment with the WHO Essential Medicines List (EML).

Comment 10:
“The sentence ‘those without consent to participate were excluded’ seems inconsistent, as you previously mentioned that no consent was obtained due to the retrospective nature of the study. Please revise this statement for clarity.”
Response:
This inconsistency has been corrected. The Methods now state: “Due to the retrospective design, informed consent was not required” (see Methods, page 3).
Comment 11:
“The exclusion criteria mention that patients lost to follow-up were excluded, but the study design does not appear to include variables requiring follow-up, such as patient survival. Did you mean therapeutic follow-up? If so, please specify the duration and method of follow-up in the methodology section.”
Response:
The exclusion criteria have been clarified to specify: “Patients with incomplete treatment records or undocumented therapeutic regimens were excluded” (see Methods, page X).
Comment 12:
“Please move the explanation regarding logistic regression mentioned in the Study Variables section to the Statistical Analysis section. Additionally, clarify whether the regression analysis was univariate or multivariate. Specify which variable(s) were independent and which were dependent in this analysis.”
Response:
As logistic regression was not performed, all references have been removed from the manuscript (see Methods and Statistical Analysis sections).
Comment 13:
“It is recommended to adjust Table 2 to include drug prescription patterns by year. Alternatively, if necessary, a separate table could be provided to address this.”
Response:
A new figure with 4 subheadings has been added to present annual prescription trends. Key temporal findings are now summarized in the Results section (see Results, pages 6-7 and 13).
Please also see the legend of Figure 1"
C. Temporal Trends in Drug Class Utilization
Grouped bar chart showing annual utilization rates of major drug classes across three epochs (2014–2016, 2017–2019, 2020–2022). Error bars represent 95% confidence intervals calculated by the binomial exact method. Statistically significant trends are annotated (Mantel-Haenszel χ² test: p<0.01 for antimetabolites, p<0.05 for immunotherapies). The dashed horizontal line indicates mean utilization across all periods (29.8%)."

Comment 14:
“The text states that 512 cases were evaluated; however, the total number of patients in Table 1 sums to 510. Does this discrepancy indicate that the cancer site was unidentified for two patients? Please clarify.”
Response:
You may say, the 2 cases were of unidentified cancer., and were removed from the total analysis. Alternatively, you can say the patients had an unidentified primary cancer site and were thus included with distant metastasis cases, which was modified to “Distant metastasis and Unidentified primary site” The text and Table 1 have been clarified to indicate that two patients had an unidentified cancer site (see Table 1 and Results, page 14).
Comment 15:
“The results section does not discuss logistic regression analysis or mention odds ratios (OR). It seems that this analysis was not performed. If the authors intended Table 4 to represent logistic regression analysis, it appears to have been incorrectly designed. I recommend revising the table by clearly identifying the variables included in the model, providing OR values, 95% confidence intervals, and reference categories. The table should be formatted and written in alignment with standard academic practices.”
Response:
As logistic regression was not performed, all related content and tables have been removed or revised to present only descriptive statistics (see Results and Table 4).
Comment 16:
“Why are certain drugs more commonly prescribed in this region? Are there specific socioeconomic, cultural, or healthcare-related factors driving this pattern?”
Response:
The Discussion now addresses regional prescribing patterns, including socioeconomic and supply chain factors (see Discussion, page 8, line 210).
The added paragraph is "Regional prescribing patterns of anticancer drugs in Saudi Arabia are influenced by multiple socioeconomic and supply chain factors. Studies, including our own, show that drug utilization is shaped not only by clinical guidelines but also by institutional policies, drug availability, and economic considerations (1). Socioeconomic factors play a key role: high generic drug utilization rates (around 90%) reflect institutional efforts to contain costs and improve access in a healthcare system balancing limited resources and rising cancer incidence (2). Patient affordability and insurance coverage also affect prescribing choices, with cost-effective regimens favored when possible. Additionally, cultural preferences and physician familiarity with certain regimens influence utilization patterns. Supply chain constraints significantly impact drug availability and prescribing. Periodic shortages of key agents such as BCG, aprepitant, and gemcitabine have been documented in Saudi centers, leading to treatment modifications or delays (2, 3). These shortages stem from global manufacturing issues, importation delays, and local distribution challenges. Such disruptions necessitate regional stockpiling strategies and formulary adjustments to maintain continuity of care (4). Moreover, regulatory policies and formulary updates guided by the Saudi FDA and alignment with the WHO Essential Medicines List ensure rational and standardized prescribing but also limit access to some novel agents, affecting utilization trends (5). For example, targeted therapies and immunotherapies have seen gradual uptake following regulatory approvals and guideline incorporation during the study period (6). In summary, regional prescribing patterns in Saudi Arabia reflect a complex interplay of guideline adherence, economic constraints, drug availability, and healthcare infrastructure. Addressing supply chain vulnerabilities and socioeconomic barriers is essential to optimize cancer treatment outcomes in the region.

Comment 17:
“How do the results of this study compare to other regional or international studies, particularly in terms of drug utilization patterns and patient outcomes?”
Response:
Comparative analysis with regional and international data has been added to the all-Discussion sections.

Comment 18:
“What recommendations can you provide to improve cancer treatment strategies?”
Response:
Three evidence-based recommendations are now included in the Discussion (see Discussion, page 7-9, and clinical implication section).
Additional Revisions:
•   All MeSH keywords standardized (see Keywords).
•   Supplemental Figures provided.
•   Table discrepancies resolved and all tables reformatted for clarity and compliance.
We hope these revisions adequately address all reviewer concerns and have further improved the manuscript’s academic quality. Thank you for your constructive feedback.
Sincerely,
Ahmed Badheeb
Competing Interests: we did not have any competing interests Close
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COMMENTS ON THIS REPORT

Author Response 02 Aug 2025

Dr Badheeb, Oncology, Hadhramout University, Al Mukalla, Yemen

02 Aug 2025

Author Response

Dear editor and reviewers of F1000 journal
We thank the reviewers for their valuable feedback and constructive suggestions, which have significantly improved the clarity and rigor of our manuscript. Below, ... Continue reading Dear editor and reviewers of F1000 journal
We thank the reviewers for their valuable feedback and constructive suggestions, which have significantly improved the clarity and rigor of our manuscript. Below, we provide a point-by-point response to each comment. All changes have been highlighted in the revised manuscript.

Reviewer 2: Pouyan Ebrahimi
Comment 1:
“Considering that no survival analysis has been conducted and data such as patient survival rates or analyses related to factors influencing survival are unavailable, I recommend titling the study as ‘Anticancer Drug Utilization and Prescription Practices in a Saudi Cancer Center (2014–2022).’”
Response:
Thank you.
The title has been revised as recommended (see Title Page). In addition, the methods section was revised to reflect these changes.
Comment 2:
“A critical point to address throughout the manuscript, particularly in the abstract, is avoiding the use of ‘we’ or ‘our’ in academic writing. Instead, adopt a more formal tone. For example, in the methodology section of the abstract, replace ‘our cancer center’ with the specific name of the center where the data was collected.”
Response:
Thank you.
The manuscript was revised using passive construction. (see Abstract, page 1; Methods, pages 3-6).
Comment 3:
“Please include the type of tools or software used for data analysis in the methodology section of the abstract.”
Response:
The methodology section of the Abstract now specifies: “Statistical analysis was performed using SPSS version 21 (IBM Corp., Armonk, NY)” (see Abstract and statistical analysis section, page 1).
Comment 4:
“Clearly state the type of study conducted in the methodology section.”
Response:
The Abstract now clearly states: “This was a retrospective, descriptive study…” (see Abstract, page X).
Comment 5:
“In the results section, ensure the total number of cases evaluated is explicitly mentioned.”
Response:
The total number of cases (N = 512) is now clearly stated in the Results section (see Results, page X, paragraph Y).
Comment 6:
“Given the clinical importance of metastatic cases, include the number of patients with metastases in the abstract.”
Response:
The Abstract now includes the number and percentage of patients with metastatic disease (see Abstract, page 1).
Comment 7:
“Adjust the keywords according to MeSH terminology. Suggested keywords include ‘Survival,’ ‘Drug Utilization,’ and ‘Neoplasms.’”
Response:
Keywords have been revised to conform to MeSH terminology (see Keywords, page 1).
Comment 8:
“In the final paragraph of the introduction, please elaborate on why the results of this study are important compared to similar studies.”
Response:
The Introduction has been expanded to emphasize the significance of our findings in the context of regional and international literature (see Introduction, page 2, final paragraph).
Comment 9:
“Please specify in the methodology section which protocols or guidelines were used for prescribing drugs to patients during different years, ideally in intervals (e.g., every four years).”
Response:
The Methods section now details the prescribing protocols and guideline updates used during the study period, including major changes in 2015 and 2019 (see Methods, page 5).
The revised section is "Prescribing Protocols and Guidelines
Anticancer drug prescriptions were guided primarily by the National Comprehensive Cancer Network (NCCN) clinical practice guidelines, adapted regionally in accordance with Saudi Food and Drug Authority (SFDA) formularies. To account for temporal changes in prescribing practices, the study period was divided into three intervals reflecting major protocol updates:
•   2014–2016: Prescriptions adhered to NCCN guidelines version 2.2014, with regional adaptations emphasizing anthracycline-based regimens for breast cancer and fluoropyrimidine-based regimens for gastrointestinal malignancies.
•   2017–2019: Following the 2017 NCCN update and SFDA formulary revisions, targeted therapies such as trastuzumab and bevacizumab were increasingly incorporated. Anthracycline protocols were refined to optimize dosing schedules.
•   2020–2022: The most recent period reflected adoption of immunotherapies (e.g., nivolumab, pembrolizumab) following their regulatory approval in Saudi Arabia, alongside continued adherence to updated NCCN and SFDA guidelines. Annual formulary reviews ensured alignment with the WHO Essential Medicines List (EML).

Comment 10:
“The sentence ‘those without consent to participate were excluded’ seems inconsistent, as you previously mentioned that no consent was obtained due to the retrospective nature of the study. Please revise this statement for clarity.”
Response:
This inconsistency has been corrected. The Methods now state: “Due to the retrospective design, informed consent was not required” (see Methods, page 3).
Comment 11:
“The exclusion criteria mention that patients lost to follow-up were excluded, but the study design does not appear to include variables requiring follow-up, such as patient survival. Did you mean therapeutic follow-up? If so, please specify the duration and method of follow-up in the methodology section.”
Response:
The exclusion criteria have been clarified to specify: “Patients with incomplete treatment records or undocumented therapeutic regimens were excluded” (see Methods, page X).
Comment 12:
“Please move the explanation regarding logistic regression mentioned in the Study Variables section to the Statistical Analysis section. Additionally, clarify whether the regression analysis was univariate or multivariate. Specify which variable(s) were independent and which were dependent in this analysis.”
Response:
As logistic regression was not performed, all references have been removed from the manuscript (see Methods and Statistical Analysis sections).
Comment 13:
“It is recommended to adjust Table 2 to include drug prescription patterns by year. Alternatively, if necessary, a separate table could be provided to address this.”
Response:
A new figure with 4 subheadings has been added to present annual prescription trends. Key temporal findings are now summarized in the Results section (see Results, pages 6-7 and 13).
Please also see the legend of Figure 1"
C. Temporal Trends in Drug Class Utilization
Grouped bar chart showing annual utilization rates of major drug classes across three epochs (2014–2016, 2017–2019, 2020–2022). Error bars represent 95% confidence intervals calculated by the binomial exact method. Statistically significant trends are annotated (Mantel-Haenszel χ² test: p<0.01 for antimetabolites, p<0.05 for immunotherapies). The dashed horizontal line indicates mean utilization across all periods (29.8%)."

Comment 14:
“The text states that 512 cases were evaluated; however, the total number of patients in Table 1 sums to 510. Does this discrepancy indicate that the cancer site was unidentified for two patients? Please clarify.”
Response:
You may say, the 2 cases were of unidentified cancer., and were removed from the total analysis. Alternatively, you can say the patients had an unidentified primary cancer site and were thus included with distant metastasis cases, which was modified to “Distant metastasis and Unidentified primary site” The text and Table 1 have been clarified to indicate that two patients had an unidentified cancer site (see Table 1 and Results, page 14).
Comment 15:
“The results section does not discuss logistic regression analysis or mention odds ratios (OR). It seems that this analysis was not performed. If the authors intended Table 4 to represent logistic regression analysis, it appears to have been incorrectly designed. I recommend revising the table by clearly identifying the variables included in the model, providing OR values, 95% confidence intervals, and reference categories. The table should be formatted and written in alignment with standard academic practices.”
Response:
As logistic regression was not performed, all related content and tables have been removed or revised to present only descriptive statistics (see Results and Table 4).
Comment 16:
“Why are certain drugs more commonly prescribed in this region? Are there specific socioeconomic, cultural, or healthcare-related factors driving this pattern?”
Response:
The Discussion now addresses regional prescribing patterns, including socioeconomic and supply chain factors (see Discussion, page 8, line 210).
The added paragraph is "Regional prescribing patterns of anticancer drugs in Saudi Arabia are influenced by multiple socioeconomic and supply chain factors. Studies, including our own, show that drug utilization is shaped not only by clinical guidelines but also by institutional policies, drug availability, and economic considerations (1). Socioeconomic factors play a key role: high generic drug utilization rates (around 90%) reflect institutional efforts to contain costs and improve access in a healthcare system balancing limited resources and rising cancer incidence (2). Patient affordability and insurance coverage also affect prescribing choices, with cost-effective regimens favored when possible. Additionally, cultural preferences and physician familiarity with certain regimens influence utilization patterns. Supply chain constraints significantly impact drug availability and prescribing. Periodic shortages of key agents such as BCG, aprepitant, and gemcitabine have been documented in Saudi centers, leading to treatment modifications or delays (2, 3). These shortages stem from global manufacturing issues, importation delays, and local distribution challenges. Such disruptions necessitate regional stockpiling strategies and formulary adjustments to maintain continuity of care (4). Moreover, regulatory policies and formulary updates guided by the Saudi FDA and alignment with the WHO Essential Medicines List ensure rational and standardized prescribing but also limit access to some novel agents, affecting utilization trends (5). For example, targeted therapies and immunotherapies have seen gradual uptake following regulatory approvals and guideline incorporation during the study period (6). In summary, regional prescribing patterns in Saudi Arabia reflect a complex interplay of guideline adherence, economic constraints, drug availability, and healthcare infrastructure. Addressing supply chain vulnerabilities and socioeconomic barriers is essential to optimize cancer treatment outcomes in the region.

Comment 17:
“How do the results of this study compare to other regional or international studies, particularly in terms of drug utilization patterns and patient outcomes?”
Response:
Comparative analysis with regional and international data has been added to the all-Discussion sections.

Comment 18:
“What recommendations can you provide to improve cancer treatment strategies?”
Response:
Three evidence-based recommendations are now included in the Discussion (see Discussion, page 7-9, and clinical implication section).
Additional Revisions:
•   All MeSH keywords standardized (see Keywords).
•   Supplemental Figures provided.
•   Table discrepancies resolved and all tables reformatted for clarity and compliance.
We hope these revisions adequately address all reviewer concerns and have further improved the manuscript’s academic quality. Thank you for your constructive feedback.
Sincerely,
Ahmed Badheeb
Dear editor and reviewers of F1000 journal
We thank the reviewers for their valuable feedback and constructive suggestions, which have significantly improved the clarity and rigor of our manuscript. Below, we provide a point-by-point response to each comment. All changes have been highlighted in the revised manuscript.

Reviewer 2: Pouyan Ebrahimi
Comment 1:
“Considering that no survival analysis has been conducted and data such as patient survival rates or analyses related to factors influencing survival are unavailable, I recommend titling the study as ‘Anticancer Drug Utilization and Prescription Practices in a Saudi Cancer Center (2014–2022).’”
Response:
Thank you.
The title has been revised as recommended (see Title Page). In addition, the methods section was revised to reflect these changes.
Comment 2:
“A critical point to address throughout the manuscript, particularly in the abstract, is avoiding the use of ‘we’ or ‘our’ in academic writing. Instead, adopt a more formal tone. For example, in the methodology section of the abstract, replace ‘our cancer center’ with the specific name of the center where the data was collected.”
Response:
Thank you.
The manuscript was revised using passive construction. (see Abstract, page 1; Methods, pages 3-6).
Comment 3:
“Please include the type of tools or software used for data analysis in the methodology section of the abstract.”
Response:
The methodology section of the Abstract now specifies: “Statistical analysis was performed using SPSS version 21 (IBM Corp., Armonk, NY)” (see Abstract and statistical analysis section, page 1).
Comment 4:
“Clearly state the type of study conducted in the methodology section.”
Response:
The Abstract now clearly states: “This was a retrospective, descriptive study…” (see Abstract, page X).
Comment 5:
“In the results section, ensure the total number of cases evaluated is explicitly mentioned.”
Response:
The total number of cases (N = 512) is now clearly stated in the Results section (see Results, page X, paragraph Y).
Comment 6:
“Given the clinical importance of metastatic cases, include the number of patients with metastases in the abstract.”
Response:
The Abstract now includes the number and percentage of patients with metastatic disease (see Abstract, page 1).
Comment 7:
“Adjust the keywords according to MeSH terminology. Suggested keywords include ‘Survival,’ ‘Drug Utilization,’ and ‘Neoplasms.’”
Response:
Keywords have been revised to conform to MeSH terminology (see Keywords, page 1).
Comment 8:
“In the final paragraph of the introduction, please elaborate on why the results of this study are important compared to similar studies.”
Response:
The Introduction has been expanded to emphasize the significance of our findings in the context of regional and international literature (see Introduction, page 2, final paragraph).
Comment 9:
“Please specify in the methodology section which protocols or guidelines were used for prescribing drugs to patients during different years, ideally in intervals (e.g., every four years).”
Response:
The Methods section now details the prescribing protocols and guideline updates used during the study period, including major changes in 2015 and 2019 (see Methods, page 5).
The revised section is "Prescribing Protocols and Guidelines
Anticancer drug prescriptions were guided primarily by the National Comprehensive Cancer Network (NCCN) clinical practice guidelines, adapted regionally in accordance with Saudi Food and Drug Authority (SFDA) formularies. To account for temporal changes in prescribing practices, the study period was divided into three intervals reflecting major protocol updates:
•   2014–2016: Prescriptions adhered to NCCN guidelines version 2.2014, with regional adaptations emphasizing anthracycline-based regimens for breast cancer and fluoropyrimidine-based regimens for gastrointestinal malignancies.
•   2017–2019: Following the 2017 NCCN update and SFDA formulary revisions, targeted therapies such as trastuzumab and bevacizumab were increasingly incorporated. Anthracycline protocols were refined to optimize dosing schedules.
•   2020–2022: The most recent period reflected adoption of immunotherapies (e.g., nivolumab, pembrolizumab) following their regulatory approval in Saudi Arabia, alongside continued adherence to updated NCCN and SFDA guidelines. Annual formulary reviews ensured alignment with the WHO Essential Medicines List (EML).

Comment 10:
“The sentence ‘those without consent to participate were excluded’ seems inconsistent, as you previously mentioned that no consent was obtained due to the retrospective nature of the study. Please revise this statement for clarity.”
Response:
This inconsistency has been corrected. The Methods now state: “Due to the retrospective design, informed consent was not required” (see Methods, page 3).
Comment 11:
“The exclusion criteria mention that patients lost to follow-up were excluded, but the study design does not appear to include variables requiring follow-up, such as patient survival. Did you mean therapeutic follow-up? If so, please specify the duration and method of follow-up in the methodology section.”
Response:
The exclusion criteria have been clarified to specify: “Patients with incomplete treatment records or undocumented therapeutic regimens were excluded” (see Methods, page X).
Comment 12:
“Please move the explanation regarding logistic regression mentioned in the Study Variables section to the Statistical Analysis section. Additionally, clarify whether the regression analysis was univariate or multivariate. Specify which variable(s) were independent and which were dependent in this analysis.”
Response:
As logistic regression was not performed, all references have been removed from the manuscript (see Methods and Statistical Analysis sections).
Comment 13:
“It is recommended to adjust Table 2 to include drug prescription patterns by year. Alternatively, if necessary, a separate table could be provided to address this.”
Response:
A new figure with 4 subheadings has been added to present annual prescription trends. Key temporal findings are now summarized in the Results section (see Results, pages 6-7 and 13).
Please also see the legend of Figure 1"
C. Temporal Trends in Drug Class Utilization
Grouped bar chart showing annual utilization rates of major drug classes across three epochs (2014–2016, 2017–2019, 2020–2022). Error bars represent 95% confidence intervals calculated by the binomial exact method. Statistically significant trends are annotated (Mantel-Haenszel χ² test: p<0.01 for antimetabolites, p<0.05 for immunotherapies). The dashed horizontal line indicates mean utilization across all periods (29.8%)."

Comment 14:
“The text states that 512 cases were evaluated; however, the total number of patients in Table 1 sums to 510. Does this discrepancy indicate that the cancer site was unidentified for two patients? Please clarify.”
Response:
You may say, the 2 cases were of unidentified cancer., and were removed from the total analysis. Alternatively, you can say the patients had an unidentified primary cancer site and were thus included with distant metastasis cases, which was modified to “Distant metastasis and Unidentified primary site” The text and Table 1 have been clarified to indicate that two patients had an unidentified cancer site (see Table 1 and Results, page 14).
Comment 15:
“The results section does not discuss logistic regression analysis or mention odds ratios (OR). It seems that this analysis was not performed. If the authors intended Table 4 to represent logistic regression analysis, it appears to have been incorrectly designed. I recommend revising the table by clearly identifying the variables included in the model, providing OR values, 95% confidence intervals, and reference categories. The table should be formatted and written in alignment with standard academic practices.”
Response:
As logistic regression was not performed, all related content and tables have been removed or revised to present only descriptive statistics (see Results and Table 4).
Comment 16:
“Why are certain drugs more commonly prescribed in this region? Are there specific socioeconomic, cultural, or healthcare-related factors driving this pattern?”
Response:
The Discussion now addresses regional prescribing patterns, including socioeconomic and supply chain factors (see Discussion, page 8, line 210).
The added paragraph is "Regional prescribing patterns of anticancer drugs in Saudi Arabia are influenced by multiple socioeconomic and supply chain factors. Studies, including our own, show that drug utilization is shaped not only by clinical guidelines but also by institutional policies, drug availability, and economic considerations (1). Socioeconomic factors play a key role: high generic drug utilization rates (around 90%) reflect institutional efforts to contain costs and improve access in a healthcare system balancing limited resources and rising cancer incidence (2). Patient affordability and insurance coverage also affect prescribing choices, with cost-effective regimens favored when possible. Additionally, cultural preferences and physician familiarity with certain regimens influence utilization patterns. Supply chain constraints significantly impact drug availability and prescribing. Periodic shortages of key agents such as BCG, aprepitant, and gemcitabine have been documented in Saudi centers, leading to treatment modifications or delays (2, 3). These shortages stem from global manufacturing issues, importation delays, and local distribution challenges. Such disruptions necessitate regional stockpiling strategies and formulary adjustments to maintain continuity of care (4). Moreover, regulatory policies and formulary updates guided by the Saudi FDA and alignment with the WHO Essential Medicines List ensure rational and standardized prescribing but also limit access to some novel agents, affecting utilization trends (5). For example, targeted therapies and immunotherapies have seen gradual uptake following regulatory approvals and guideline incorporation during the study period (6). In summary, regional prescribing patterns in Saudi Arabia reflect a complex interplay of guideline adherence, economic constraints, drug availability, and healthcare infrastructure. Addressing supply chain vulnerabilities and socioeconomic barriers is essential to optimize cancer treatment outcomes in the region.

Comment 17:
“How do the results of this study compare to other regional or international studies, particularly in terms of drug utilization patterns and patient outcomes?”
Response:
Comparative analysis with regional and international data has been added to the all-Discussion sections.

Comment 18:
“What recommendations can you provide to improve cancer treatment strategies?”
Response:
Three evidence-based recommendations are now included in the Discussion (see Discussion, page 7-9, and clinical implication section).
Additional Revisions:
•   All MeSH keywords standardized (see Keywords).
•   Supplemental Figures provided.
•   Table discrepancies resolved and all tables reformatted for clarity and compliance.
We hope these revisions adequately address all reviewer concerns and have further improved the manuscript’s academic quality. Thank you for your constructive feedback.
Sincerely,
Ahmed Badheeb
Competing Interests: we did not have any competing interests Close
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Version 2

VERSION 2 PUBLISHED 31 May 2024

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Version 1 31 May 24	read	read

Pouyan Ebrahimi, Babol University of Medical Science, Babol, Iran
Shouki Bazarbashi, Alfaisal University, Riyadh, Saudi Arabia
Muhammad Aamir, Huanggang Normal University, Huanggang, China

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Reviewer Report

2 Views

04 Sep 2025 | for Version 2

Muhammad Aamir, Huanggang Normal University, Huanggang, China

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Approved With Reservations

This study provides an important retrospective evaluation of anticancer drug prescribing patterns in a southern Saudi oncology center, with a specific focus on adherence to the WHO Essential Medicines List (EML). The manuscript offers valuable insights into real-world prescribing behaviors, formulary alignment, and resource-based limitations. The authors have responded comprehensively to earlier review feedback, which has improved the manuscript. However, a few limitations and areas for enhancement remain.

The study is limited to one hospital, reducing its generalizability. Inclusion of other centers would strengthen the conclusions and applicability of findings across regions.
The omission of survival, progression, or quality-of-life data limits the ability to correlate drug use with patient outcomes, which is key to evaluating the impact of prescribing practices.
The retrospective approach is vulnerable to missing data and documentation biase specially regarding adverse events and treatment delays, potentially underestimating their frequency.
Earlier versions mentioned survival analysis via logistic regression but didn’t include results. While this has been corrected, it highlights the need for tighter alignment between methods and results in future submissions.
While drug shortages are acknowledged, the study could benefit from more specific discussion on root causes (e.g., procurement bottlenecks, regulatory delays).
The temporal evolution of drug classes is well described, but an expanded analysis on the drivers behind those trends (e.g., new approvals, local policy changes) would add context.
While antiemetic use is described, stratifying by emetogenic potential of the chemotherapy or regimen type would have strengthened this section.
Although cost-effectiveness is discussed, the study lacks data or references to actual economic evaluations, limiting the strength of that conclusion.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Not applicable
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

AI in Healthcare

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3 Views

22 Aug 2025 | for Version 2

Pouyan Ebrahimi, Babol University of Medical Science, Babol, Iran

3 Views Cite this report Responses(0)

Approved

I would like to thank the authors for their appropriate responses to my questions. In my opinion, the study is currently at an appropriate level and can be considered for indexing

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Given my familiarity with similar studies conducted in this field, I am well acquainted with the data collection methods and analyses employed in this study. Additionally, my ongoing research in cancer treatments provides valuable insights, enabling me to effectively contribute to reviewing the oncological aspects of this study.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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Reviewer Report

9 Views

02 Apr 2025 | for Version 1

Shouki Bazarbashi, Alfaisal University, Riyadh, Riyadh Province, Saudi Arabia

9 Views Cite this report Responses(1)

Approved With Reservations

Action Needed: You must either:

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

No source data required
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

GI cancer, GU cancer, clinical trials

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Author Response

24 Jul 2025

Dr Badheeb, Oncology, Hadhramout University, Al Mukalla, Yemen

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Competing Interests

No competing interests were disclosed.

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9 Views

07 Jan 2025 | for Version 1

Pouyan Ebrahimi, Babol University of Medical Science, Babol, Iran

9 Views Cite this report Responses(1)

Approved With Reservations

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

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Author Response

02 Aug 2025

Dr Badheeb, Oncology, Hadhramout University, Al Mukalla, Yemen

Dear editor and reviewers of F1000 journal
We thank the reviewers for their valuable feedback and constructive suggestions, which have significantly improved the clarity and rigor of our manuscript. Below, we provide a point-by-point response to each comment. All changes have been highlighted in the revised manuscript.

Reviewer 2: Pouyan Ebrahimi
Comment 1:
“Considering that no survival analysis has been conducted and data such as patient survival rates or analyses related to factors influencing survival are unavailable, I recommend titling the study as ‘Anticancer Drug Utilization and Prescription Practices in a Saudi Cancer Center (2014–2022).’”
Response:
Thank you.
The title has been revised as recommended (see Title Page). In addition, the methods section was revised to reflect these changes.
Comment 2:
“A critical point to address throughout the manuscript, particularly in the abstract, is avoiding the use of ‘we’ or ‘our’ in academic writing. Instead, adopt a more formal tone. For example, in the methodology section of the abstract, replace ‘our cancer center’ with the specific name of the center where the data was collected.”
Response:
Thank you.
The manuscript was revised using passive construction. (see Abstract, page 1; Methods, pages 3-6).
Comment 3:
“Please include the type of tools or software used for data analysis in the methodology section of the abstract.”
Response:
The methodology section of the Abstract now specifies: “Statistical analysis was performed using SPSS version 21 (IBM Corp., Armonk, NY)” (see Abstract and statistical analysis section, page 1).
Comment 4:
“Clearly state the type of study conducted in the methodology section.”
Response:
The Abstract now clearly states: “This was a retrospective, descriptive study…” (see Abstract, page X).
Comment 5:
“In the results section, ensure the total number of cases evaluated is explicitly mentioned.”
Response:
The total number of cases (N = 512) is now clearly stated in the Results section (see Results, page X, paragraph Y).
Comment 6:
“Given the clinical importance of metastatic cases, include the number of patients with metastases in the abstract.”
Response:
The Abstract now includes the number and percentage of patients with metastatic disease (see Abstract, page 1).
Comment 7:
“Adjust the keywords according to MeSH terminology. Suggested keywords include ‘Survival,’ ‘Drug Utilization,’ and ‘Neoplasms.’”
Response:
Keywords have been revised to conform to MeSH terminology (see Keywords, page 1).
Comment 8:
“In the final paragraph of the introduction, please elaborate on why the results of this study are important compared to similar studies.”
Response:
The Introduction has been expanded to emphasize the significance of our findings in the context of regional and international literature (see Introduction, page 2, final paragraph).
Comment 9:
“Please specify in the methodology section which protocols or guidelines were used for prescribing drugs to patients during different years, ideally in intervals (e.g., every four years).”
Response:
The Methods section now details the prescribing protocols and guideline updates used during the study period, including major changes in 2015 and 2019 (see Methods, page 5).
The revised section is "Prescribing Protocols and Guidelines
Anticancer drug prescriptions were guided primarily by the National Comprehensive Cancer Network (NCCN) clinical practice guidelines, adapted regionally in accordance with Saudi Food and Drug Authority (SFDA) formularies. To account for temporal changes in prescribing practices, the study period was divided into three intervals reflecting major protocol updates:
•   2014–2016: Prescriptions adhered to NCCN guidelines version 2.2014, with regional adaptations emphasizing anthracycline-based regimens for breast cancer and fluoropyrimidine-based regimens for gastrointestinal malignancies.
•   2017–2019: Following the 2017 NCCN update and SFDA formulary revisions, targeted therapies such as trastuzumab and bevacizumab were increasingly incorporated. Anthracycline protocols were refined to optimize dosing schedules.
•   2020–2022: The most recent period reflected adoption of immunotherapies (e.g., nivolumab, pembrolizumab) following their regulatory approval in Saudi Arabia, alongside continued adherence to updated NCCN and SFDA guidelines. Annual formulary reviews ensured alignment with the WHO Essential Medicines List (EML).

Comment 10:
“The sentence ‘those without consent to participate were excluded’ seems inconsistent, as you previously mentioned that no consent was obtained due to the retrospective nature of the study. Please revise this statement for clarity.”
Response:
This inconsistency has been corrected. The Methods now state: “Due to the retrospective design, informed consent was not required” (see Methods, page 3).
Comment 11:
“The exclusion criteria mention that patients lost to follow-up were excluded, but the study design does not appear to include variables requiring follow-up, such as patient survival. Did you mean therapeutic follow-up? If so, please specify the duration and method of follow-up in the methodology section.”
Response:
The exclusion criteria have been clarified to specify: “Patients with incomplete treatment records or undocumented therapeutic regimens were excluded” (see Methods, page X).
Comment 12:
“Please move the explanation regarding logistic regression mentioned in the Study Variables section to the Statistical Analysis section. Additionally, clarify whether the regression analysis was univariate or multivariate. Specify which variable(s) were independent and which were dependent in this analysis.”
Response:
As logistic regression was not performed, all references have been removed from the manuscript (see Methods and Statistical Analysis sections).
Comment 13:
“It is recommended to adjust Table 2 to include drug prescription patterns by year. Alternatively, if necessary, a separate table could be provided to address this.”
Response:
A new figure with 4 subheadings has been added to present annual prescription trends. Key temporal findings are now summarized in the Results section (see Results, pages 6-7 and 13).
Please also see the legend of Figure 1"
C. Temporal Trends in Drug Class Utilization
Grouped bar chart showing annual utilization rates of major drug classes across three epochs (2014–2016, 2017–2019, 2020–2022). Error bars represent 95% confidence intervals calculated by the binomial exact method. Statistically significant trends are annotated (Mantel-Haenszel χ² test: p<0.01 for antimetabolites, p<0.05 for immunotherapies). The dashed horizontal line indicates mean utilization across all periods (29.8%)."

Comment 14:
“The text states that 512 cases were evaluated; however, the total number of patients in Table 1 sums to 510. Does this discrepancy indicate that the cancer site was unidentified for two patients? Please clarify.”
Response:
You may say, the 2 cases were of unidentified cancer., and were removed from the total analysis. Alternatively, you can say the patients had an unidentified primary cancer site and were thus included with distant metastasis cases, which was modified to “Distant metastasis and Unidentified primary site” The text and Table 1 have been clarified to indicate that two patients had an unidentified cancer site (see Table 1 and Results, page 14).
Comment 15:
“The results section does not discuss logistic regression analysis or mention odds ratios (OR). It seems that this analysis was not performed. If the authors intended Table 4 to represent logistic regression analysis, it appears to have been incorrectly designed. I recommend revising the table by clearly identifying the variables included in the model, providing OR values, 95% confidence intervals, and reference categories. The table should be formatted and written in alignment with standard academic practices.”
Response:
As logistic regression was not performed, all related content and tables have been removed or revised to present only descriptive statistics (see Results and Table 4).
Comment 16:
“Why are certain drugs more commonly prescribed in this region? Are there specific socioeconomic, cultural, or healthcare-related factors driving this pattern?”
Response:
The Discussion now addresses regional prescribing patterns, including socioeconomic and supply chain factors (see Discussion, page 8, line 210).
The added paragraph is "Regional prescribing patterns of anticancer drugs in Saudi Arabia are influenced by multiple socioeconomic and supply chain factors. Studies, including our own, show that drug utilization is shaped not only by clinical guidelines but also by institutional policies, drug availability, and economic considerations (1). Socioeconomic factors play a key role: high generic drug utilization rates (around 90%) reflect institutional efforts to contain costs and improve access in a healthcare system balancing limited resources and rising cancer incidence (2). Patient affordability and insurance coverage also affect prescribing choices, with cost-effective regimens favored when possible. Additionally, cultural preferences and physician familiarity with certain regimens influence utilization patterns. Supply chain constraints significantly impact drug availability and prescribing. Periodic shortages of key agents such as BCG, aprepitant, and gemcitabine have been documented in Saudi centers, leading to treatment modifications or delays (2, 3). These shortages stem from global manufacturing issues, importation delays, and local distribution challenges. Such disruptions necessitate regional stockpiling strategies and formulary adjustments to maintain continuity of care (4). Moreover, regulatory policies and formulary updates guided by the Saudi FDA and alignment with the WHO Essential Medicines List ensure rational and standardized prescribing but also limit access to some novel agents, affecting utilization trends (5). For example, targeted therapies and immunotherapies have seen gradual uptake following regulatory approvals and guideline incorporation during the study period (6). In summary, regional prescribing patterns in Saudi Arabia reflect a complex interplay of guideline adherence, economic constraints, drug availability, and healthcare infrastructure. Addressing supply chain vulnerabilities and socioeconomic barriers is essential to optimize cancer treatment outcomes in the region.

Comment 17:
“How do the results of this study compare to other regional or international studies, particularly in terms of drug utilization patterns and patient outcomes?”
Response:
Comparative analysis with regional and international data has been added to the all-Discussion sections.

Comment 18:
“What recommendations can you provide to improve cancer treatment strategies?”
Response:
Three evidence-based recommendations are now included in the Discussion (see Discussion, page 7-9, and clinical implication section).
Additional Revisions:
•   All MeSH keywords standardized (see Keywords).
•   Supplemental Figures provided.
•   Table discrepancies resolved and all tables reformatted for clarity and compliance.
We hope these revisions adequately address all reviewer concerns and have further improved the manuscript’s academic quality. Thank you for your constructive feedback.
Sincerely,
Ahmed Badheeb

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Competing Interests

we did not have any competing interests

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

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[30] 30. Badheeb Aa F: Assessment of Anticancer Drug Utilization Pattern from a hospital-based cancer registry—A Single Center Experience from Saudi Arabia Mendeley Data.

Assessment of anticancer drug utilization pattern and patients’ survival—A single center experience from Saudi Arabia

Abstract

Background

Methods

Results

Conclusion

Keywords

Introduction

Methods

Study design

Study variables

Study outcome

Statistical analysis

Results

Table 1. Demographic characteristics of patients, cancer site, and treatment features.

Table 2. Prescription pattern of each anticancer drug.

Table 3. Prescription pattern of each adjuvant drug.

Anticancer drugs utilization

Table 4. Results of drug use core indicators and ideal WHO standards.

Discussion

Study limitations

Conclusions

Ethical considerations

Data availability

Underlying data

Acknowledgments

References

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