Survival rate of patients with combined hepatocellular cholangiocarcinoma receiving medical cannabis treatment: A retrospective, cohort comparative study

Narisara Phansila; Paopong Pansila; Adisorn Wongkongdech; Niruwan Turnbull; Mahalul Azam; Ranee Wongkongdech

doi:10.12688/f1000research.123250.2

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Research Article

Revised

Survival rate of patients with combined hepatocellular cholangiocarcinoma receiving medical cannabis treatment: A retrospective, cohort comparative study

[version 2; peer review: 2 approved with reservations, 3 not approved]

Narisara Phansila¹, Paopong Pansila², Adisorn Wongkongdech^3,4, Niruwan Turnbull^3,4, Mahalul Azam⁵, Ranee Wongkongdech ^2,3

Narisara Phansila¹, Paopong Pansila², [...] Adisorn Wongkongdech^3,4, Niruwan Turnbull^3,4, Mahalul Azam⁵, Ranee Wongkongdech ^2,3

PUBLISHED 09 Apr 2025

Author details Author details

¹ Chiang Kwan Hospital, Roi-et Province, 45000, Thailand
² Faculty of Medicine, Mahasarakham University, Mahasarakham, 44000, Thailand
³ Public Health and Environmental Policy in Southeast Asia Research Cluster (PHEP SEA Thailand), Mahasarakham University, Mahasarakham, 44150, Thailand
⁴ Faculty of Public Health, Mahasarakham University, Mahasarakham, Mahasarakham Province, 44150, Thailand
⁵ Public Health Department, Faculty of Sport Sciences, Universitas Negeri Semarang, Semarang, 50229, Indonesia

Narisara Phansila
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Resources, Writing – Original Draft Preparation

Paopong Pansila
Roles: Formal Analysis, Investigation, Methodology, Resources, Validation, Visualization

Adisorn Wongkongdech
Roles: Formal Analysis, Investigation, Methodology, Resources, Validation, Visualization

Niruwan Turnbull
Roles: Conceptualization, Investigation, Supervision, Visualization, Writing – Review & Editing

Mahalul Azam
Roles: Investigation, Visualization, Writing – Review & Editing

Ranee Wongkongdech
Roles: Conceptualization, Funding Acquisition, Investigation, Methodology, Project Administration, Supervision, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Oncology gateway.

Abstract

Background: Cholangiocarcinoma (CCA) incidence in Northeastern Thailand is very high and a major cause of mortality. CCA patients typically have a poor prognosis and short-term survival rate due to late-stage diagnosis. Thailand is the first Southeast Asian country to approve medicinal cannabis treatment, especially for palliative care with advanced cancer patients.

Methods: A retrospective cohort comparative study of survival rates among 491 newly diagnosed advanced CCA patients was carried out between September 1, 2019, and June 30, 2021. A total of 404 patients were in the standard palliative care pain management treatment group (ST), and 87 were in the medicinal cannabis treatment group (CT). Patients with CCA were recruited from four tertiary hospitals and two secondary hospitals in five provinces of Northeast Thailand. The cumulative survival rates were calculated by the Kaplan-Meier method, and independent prognostic factors were investigated using Cox regression.

Results: For ST patients, there was a total follow-up time of 790 person-months, with a mortality rate of 48.35/100 person-months. For CT patients the total follow-up time was 476 person-months, with mortality rate of 10.9/ 100 person-months. The median survival time after registration at a palliative clinic was 0.83 months (95% CI: 0.71–0.95) for ST and 5.66 months (95% CI: 1.94–9.38) for CT. Multivariate analysis showed that CT treatment protocol was associated with a significantly better survival (P value <0.001; median time of CT, 5.66 months (95% CI: 1.94–9.38); median time of ST, 0.83 months (95% CI: 0.71–0.95). Therefore, CT had a reduced probability of dying from the disease (HR_adj., 0.28 (95% CI: 0.20–0.37)

Conclusions: The medical cannabis increased overall survival rates among CCA patients.

Keywords

Survival rate, medicinal cannabis, combined hepatocellular cholangiocarcinoma, cHCC-CC, palliative care, Northeastern Thailand

Corresponding author: Ranee Wongkongdech

Competing interests: No competing interests were disclosed.

Grant information: This research was financially supported by Faculty of Medicine, Mahasarakham University with the reference no. 64/04/01.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2025 Phansila N 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: Phansila N, Pansila P, Wongkongdech A et al. Survival rate of patients with combined hepatocellular cholangiocarcinoma receiving medical cannabis treatment: A retrospective, cohort comparative study [version 2; peer review: 2 approved with reservations, 3 not approved]. F1000Research 2025, 11:1212 (https://doi.org/10.12688/f1000research.123250.2) First published: 25 Oct 2022, 11:1212 (https://doi.org/10.12688/f1000research.123250.1) Latest published: 09 Apr 2025, 11:1212 (https://doi.org/10.12688/f1000research.123250.2)

Revised Amendments from Version 1

The current version of this article has been revised in response to reviewer feedback. The Methods section now includes more explicit eligibility criteria, specifying that participants were newly diagnosed with CCA or HCC between September 2019 and December 2020, aged over 18, and registered at either a palliative or cannabis clinic. We have ensured data accuracy, making necessary corrections to demographic percentages. Although the proportional hazards assumption test was not performed due to data constraints, we used Kaplan-Meier estimation and the Log-rank test for survival analysis.
In response to concerns about causal claims, we emphasized the study's observational nature and adjusted the language to reflect associations rather than causality. We also provided a rationale for selecting covariates and explained the categorization of continuous variables, such as age and time from diagnosis to registration, to align with clinical practice. Additionally, we have added more detailed information on the medical cannabis treatment protocol and standard care procedures to improve transparency.
Regarding the pain level as a confounder, we acknowledged that pain scale data were not collected systematically and clarified this limitation. We addressed the reviewer’s comment about patient numbers at each stage, explaining that the analysis focused on the total cohort of 491 patients without tracking each stage. A flow diagram has been included to show participant progression and reasons for drop-out. Finally, the Statistical Analysis section has been revised to explicitly state the use of Kaplan-Meier estimation and the Log-rank test, ensuring the methods were suitable for the study design.

See the authors' detailed response to the review by Selamat Budijitno
See the authors' detailed response to the review by Ueamporn Summart

Introduction

Combined hepatocellular cholangiocarcinoma (cHCC-CC) is a rare, but severely aggressive primary liver cancer manifesting characteristics of both hepatocellular carcinoma (HCC) and cholangiocarcinoma (CC). The incidence rate is approximately 0.59 per 1,000,000 populations worldwide¹ but it is highly prevalent in Thailand.² The highest reported CC incidence internationally is in northeastern Thailand, 118.5 per 100,000, in Khon Kaen Province, which is over 100 times higher than the global rate.³

CC is generally asymptomatic in early stages and is usually diagnosed late when the disease has already metastasized. Late-stage diagnosis limits the effective therapeutic options and has an aggressive disease course⁴ and very poor prognosis,⁵ resulting in lower survival rates. Previous studies have shown the median post-diagnosis survival of CC patients to be about 9 months (95% CI: 7–11), with 1-, 3-, and 5-year survival rates at 43.4, 21.5, and 17.1%, respectively.¹ Mean overall survival rate at 1-, 3-, and 5-year was 66.6, 41.5, and 32.7% for patients with transitional cHCC-CC, with median survival time from diagnosis 4.3 months (95% CI: 3.3–5.1),⁶ and after supportive treatment was 4 months.⁷ Survival time was increased among CC patients receiving surgery (an average of 29.38 months), best supportive treatment was 5.12 months and 13.38 months for chemotherapy patients.⁸

At present, medical cannabis products are in use in many countries.⁹ Cannabis as a palliative treatment for patients with cancer appears to be well-tolerated, effective and a safe pain-relief option with significant improvement in quality of life shown after 6 months of treatment.¹⁰ In patients with cancer, cannabinoids have mainly been used as part of palliative care to alleviate pain, relieve nausea and stimulate appetite.¹¹ Thailand legalized medical cannabis in February 2019, becoming the first country in Southeast Asia to regulate medical treatment.¹² Currently, there are two treatment options for palliative cancer patients in Thailand; the standard current treatment and the new cannabis treatment. However, to the best of our knowledge, no studies on the survival rate of patients treated with medicinal cannabis from the patients’ perspective have been carried out to date. The present study aims to compare survival rates in palliative cHCC-CC patients who were treated with standard treatment (ST) or cannabis treatment (CT) palliative care protocols.

Methods

Ethical approval

This study was reviewed and approved by the Mahasarakham University Human Research Ethics Committee (Reference No. 204/2563; approved on July 24, 2020), and Roi-Et Regional Hospital (Reference RE064/2563; approved on August 26, 2020), Buriram Regional Hospital Ethics Committee for Human Research, based on the Declaration of Helsinki and the ICH Good Clinical Practice Guidelines (Reference No. GCP0066/2563; approved on February 4, 2020). Because of its retrospective manner, informed consent was waived by the Roi-Et Regional Hospital and Buriram Regional Hospital. Data were collected from August 30, 2020, to June 30, 2021, which collected event data on 491 cases from September 1, 2019, to June 30, 2021.

Study design

An observational analytical study using a retrospective cohort design was conducted with 491 cHCC-CC patients (404 received ST and 87 received CT), diagnosed at least by ultrasonography and treated with supportive care at palliative care and/or cannabis care clinics between September 1, 2019, and June 30, 2021. Data were extracted from four tertiary hospitals and two secondary hospitals in five provinces of northeastern Thailand (Roi-Et Regional Hospital, Buriram Regional Hospital, Surin Provincial Hospital, Sawang Dandin Crown Prince Hospital, Panna Nikhom Hospital, and Pana Hospital). Follow-up was conducted until the outcome was reached or the study concluded, with additional insights gathered through interviews with oncologists from eight hospitals regarding treatment protocols.

Data collection

Patients were eligible for inclusion if they were newly diagnosed with cholangiocarcinoma (CCA) or hepatocellular carcinoma (HCC) between September 2019 and December 2020, were over the age of 18, and registered at either the palliative or cannabis clinic. Exclusion criteria included prior cannabis use before study registration or incomplete medical records. Participants were followed from registration until death or the study endpoint (June 30, 2021). Follow-up was conducted through clinic visits, medical record reviews, and linkage to the national death registry. Data on survival time, treatment response, and adverse events were collected at each visit. Censored data were recorded for participants who were still alive at the end of the study or lost to follow-up. Follow-up status was verified through medical records, the national death registry, and telephone calls to the community health centers’ patient or public health officers (Figure 1).

Figure 1. Study flow diagram for participant accrual and outcomes.

In this study, we examined the survival outcomes of patients with CCA and HCC based on various factors, excluding pain level as a variable. While pain level was not included in the analysis, we acknowledge this as a limitation and have clarified it here.

Independent and dependent variables

The independent variables included age at registration (Palliative clinic and/or Cannabis clinic), gender, cancer treatment, and the period from diagnosis to registration. The dependent variable was the post-diagnosis survival time of patients with CCA and HCC. To calculate survival time, the starting point was identified as the registration date, and the follow-up period ended when a patient died or the study was completed.

Statistical methods

Statistical analysis was performed with Stata (RRID:SCR_012763) version 15 (free alternative, Rstudio). Descriptive statistics were used to present baseline characteristics and clinical subject data. Frequency and percentages were constructed to describe categorical data and expressed as the means deviation (in SD) or medians with ranges to describe continuous data. The Kaplan-Meier method was used for observing survival duration with 95% confidence intervals (95% CI). Then between-group comparisons were evaluated using a log-rank test. The test for associations between the diverse covariates and survival rate was performed using the Cox proportional hazard regression model. The results were submitted as hazard ratios (HR) with 95% CI for HR. A p-value less than 0.05 is typically considered to be statistically significant.

Results

Standard medical treatment

Diagnosis and assessment are conducted using basic diagnostic methods such as endoscopy, CT/MRI scans, and blood tests. Standard medical treatments include chemotherapy (CT), surgery, and palliative care approaches. Follow-up involves monitoring the patient’s progress through physical examinations and laboratory test results to assess the effectiveness of the treatment.

Medical cannabis treatment

Patients must provide diagnostic results confirming advanced-stage cancer, such as biopsy findings or CT/MRI scans showing metastasis. Treatment involves prescribing cannabis products, including THC:CBD 1:1, THC, and CBD cannabis oil. Follow-up care includes adjusting the treatment based on the patient’s response, with regular check-ups to monitor progress and make necessary adjustments to the cannabis treatment plan.

Participants’ Characteristics and Survival Rates of Patients with CCA/HCC Treated with Cannabis Therapy (CT) and Standard Therapy (ST)

Table 1 shows the characteristics of the study participants.¹⁵^,¹⁶ There were 491 patients (296 male subjects and 195 female subjects) with cHCC-CC; there were 404 in the ST group (242 male subjects and 162 female subjects) and 87 in the CT group (54 male participants and 33 female participants). The mean age of those in the ST group was 66.60 years old, and the mean age of the CT group was 65.64 years old. Most patients (43.38%) were 70 years of age. More than 71.53% in the ST received cancer chemotherapy and combinations, and 49.42% of the CT group also received palliative care. Mean point of diagnosis with advanced cHCC-CC to registration was 6.12 months for ST, and 5.46 months for CT. Most patients (38.49%) were registered at the palliative and/or cannabis care clinic, and 94.60% (ST) and 59.80% (CT) had passed away by the end of the study. The total follow-up time for ST patients was 790 person-months, with a mortality rate of 48.35/100 person-months. For the CT group follow-up was 476 person-months, with a mortality rate of 10.9./100 person-months for CT.

Table 1. Baseline characteristics of included patients (n=491).

ST, standard palliative care pain management treatment group; CT, medicinal cannabis treatment group.

Variable	Patient treatment group		Median time, month (95% CI)			Person-time, month		Incidence rate/ 100 person/month		HR_adj. 95% CI	P-value
Variable	ST (n=404, %)	CT (n=87, %)	ST (n=404, %)	CT (n=87, %)	P-value	ST	CT	ST	CT	HR_adj. 95% CI	P-value
Overall survival rate	0.83 (0.71–0.95)	5.66 (1.94–9.38)			<0.001
Age, years, mean (SD)	66.60 (11.67)	65.64 (9.82)			<0.001
<60	105 (25.99)	24 (27.59)	0.83 (0.60–1.00)	5.67 (2.87–15.00)		170	147	0.59	0.08	1	0.212
60–69	121 (29.95)	28 (32.18)	0.93 (0.73–1.04)	3.27 (2.0–12.00)		244	128	0.47	0.13	0.85 (0.66–1.09)
≥70	178 (44.06)	35 (40.23)	0.83 (0.67–1.27)	6.00 (2.33–10.03)		375	200	0.44	0.11	0.87 (0.68–1.09)
Sex
Male	242 (81.8)	54 (18.2)	0.73 (0.67–0.93)	6.00 (3.07–10.03)	<0.001	427	300	0.53	0.10	1	0.236
Female	162 (83.1)	33 (16.9)	0.97 (0.83–1.20)	3.50 (1.77–9.50)	<0.001	362	175	0.42	0.11	0.89 (0.73–1.08)	0.236
Cancer treatment
Surgery	28 (6.93)	4 (4.59)	1.33 (0.30–2.50)	2.00 (1.83–10.00)	<0.001	106	14	0.20	0.21	1	0.106
Chemotherapy	140 (34.65)	18 (20.70)	0.93 (0.73–1.0)	9.50 (5.17–15.00)		209	139	0.65	0.06	1.43 (0.93–2.2)
Combine	149 (36.88)	22 (25.29)	0.83 (0.67–1.27)	7.00 (1.67–15.00)		311	121	0.45	0.09	1.27 (0.82–1.93)
Palliative care	87 (21.54)	43 (49.42)	0.73 (0.5–0.93)	3.07 (2.17–.8.33)		162	201	0.51	0.14	1.23 (0.79–1.92)
Treatment protocol
ST	404	87	0.83 (0.71–0.95)		<0.001					1	<0.001
CT	(82.3)	(17.7)	5.66 (1.94–9.38)		<0.001					0.28 (0.20–0.37)	<0.001
Period advanced diagnosis to register
Mean (SD)	6.12 (2.55)	5.46 (2.94)			<0.001
< 3 months	60 (85.14)	40 (45.98)	0.93 (0.67–2.00)	3.17 (2.17–9.00)		115	115	0.54	0.14	1	0.844
3–6 months	204 (49.50)	22 (25.28)	0.83 (0.67–0.97)	8.17 (2.87–15.00)		406	406	0.46	0.08	1.31 (1.01–1.71)
6–9 months	94 (27.23)	8 (9.20)	1.07 (0.67–1.67)	5.00 (0.73–8.00)		210	210	0.41	0.09	1.21 (0.89–1.65)
>9 months	46 (39.11)	17 (19.54)	0.67 (0.44–1.77)	5.17 (200–9.00)		59	59	0.72	0.09	1.16 (0.82–1.63)
Status at the end of study
Passed away	382 (94.60)	52 (59.80)

The survival rate data after registration at either the palliative or cannabis care clinic. The cumulative 3, 6, 9 and 12 months survival rates were 28.80% (95% CI: 24.72–32.99), 20.00% (95% CI: 16.35–23.92), 16.50% (95% CI: 12.86–20.55) and 15.75% (95% CI: 12.04–19.92) for ST, 60.48% (95% CI: 49.35–69.91), 48.63% (95% CI: 36.78–57.70), 35.73% (95% CI: 23.83–47.74) and 29.98% (95% CI: 18.15–42.73) for CT, respectively. The median duration of survival was 0.83 months (95% CI: 0.71–0.95) for ST and 5.66 months (95% CI: 1.94–9.38) for CT. None of the demographic factors were significantly associated with survival time for either ST or CT. Comparing ST with CT, there was a statistically significant difference in age, sex, cancer treatment and period diagnosis with advanced cHCC-CC to register factors (p-value<0.05). There were factors found that affected the survival of patients receiving palliative care for liver and bile duct cancer. The most significant treatment factor found was between those patients who received standard therapy and those who received medical cannabis. Those on standard therapy were 3.57% more at risk of death than those on cannabis.

Multivariate analysis showed that CT treatment protocol was associated with improved patient survival, which was statistically significant (P value <0.001, the median time of CT, 5.66 months (95% CI: 1.94–9.38) and ST, 0.83 months (95% CI: 0.71–0.95), HR_adj, 0.28 (95% CI: 0.20–0.37).

Discussion

The impact of two types of treatment that affect the survival of cHCC-CC patients who either had supportive treatment at palliative clinic or a cannabis clinic. CT was the most effective treatment, with an overall survival time of 5.66 months, while overall survival time was 0.83 months for ST. Meanwhile, the overall survival times are consistent with other findings for after supportive treatment⁷ where survival time was only 4.3 months post-diagnosis. Patients diagnosed at an advanced stage were twice as likely to pass away (HR: 1.8, 95% CI: 1.1–2.9).¹³ By contrast, patients with advanced cancer using cannabis showed a significantly decreased overall survival compared to non-users.¹⁴

In the univariate analysis, cancer treatment and period of diagnosis with advanced cHCC-CC to registration were associated with survival rate. It was found that the ST registered patients survived less than three months after being diagnosed with advanced-stage cHCC-CC. The reason for this might be that some patients had been consulting and were being cared for by an oncologist or other doctor rather than those patients who were registered for and receiving supportive treatment at a Palliative Clinic. Furthermore, most patients had been treated with a combination of surgery and chemotherapy, before being admitted to a Palliative Clinic. Although the registered patients at the Cannabis Clinic were >70 years old, they had no cancer treatment, only supportive treatment at the Cannabis Clinic. At the community hospitals where CT/MRI/biopsy/US have shown advanced organ metastases others who received treatment at a Cannabis clinic without waiting for a consultation with an oncologist were able to receive chemotherapy along with cannabis. This study has several limitations. A number of patients in the CT group dropped out before completion of the study. As a consequence, most patients suffering from advanced cancers and receiving heavy oncological treatments were older adults.

Patients with CCA have poor prognosis and short-term survival at the time of diagnosis. Registration and decision-making at the standard and/or cannabis clinic in each hospital differs across physicians, patients, families, stages of disease, organ metastasis, methods of treatment, and severity of symptoms. To the best of our knowledge, this is the first study that has compared survival rate and quality of life of CHCA/CCA patients who received either ST or CT across tertiary and secondary hospitals and across five provinces. Medical cannabis used in this study were standardized cannabis preparations made by the Thailand Food and Drug Administration. The side effects, safety, benefits and harms of the cannabis produced have been reviewed and are considered appropriate patient treatment. Prescribing doctors are trained, registered prescribers of medical cannabis.

Author contributions

N.P., contributed to Conceptualization, Data Curation, Formal Analysis, Resources, Methodology, Investigation, Writing – Original Draft. P.P., and A.W., contributed to Methodology, Investigation, Resources, Validation, Formal Analysis, Visualization. N.T., contributed to Conceptualization, Investigation, Supervision, Visualization, Writing – Review & Editing. M.A., contributed to Investigation, Visualization, Writing – Review & Editing. R.W., contributed to Conceptualization, Project Administration, Methodology, Investigation, Writing – Review & Editing, Funding Acquisition, and Supervision.

Data availability

Underlying data

Figshare: Data_survival_cannabis. https://doi.org/10.6084/m9.figshare.20101193.¹⁵

Figshare: F1000_survival_table1_narisara_ranee. https://doi.org/10.6084/m9.figshare.20486913.¹⁶

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

Acknowledgements

We would like to express the appreciation for all patients who participated in this research and the Hospital Center of Excellence Team (palliative clinic and cannabis clinic) for their invaluable help and encouragement throughout the course of this research. This research project was financially supported by Mahasarakham University. An earlier version of this article can be found on Research Square (doi: https://doi.org/10.21203/rs.3.rs-1030279/v1).

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Comments on this article Comments (0)

Version 2

VERSION 2 PUBLISHED 25 Oct 2022

Author details Author details

Narisara Phansila
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Resources, Writing – Original Draft Preparation

Paopong Pansila
Roles: Formal Analysis, Investigation, Methodology, Resources, Validation, Visualization

Adisorn Wongkongdech
Roles: Formal Analysis, Investigation, Methodology, Resources, Validation, Visualization

Niruwan Turnbull
Roles: Conceptualization, Investigation, Supervision, Visualization, Writing – Review & Editing

Mahalul Azam
Roles: Investigation, Visualization, Writing – Review & Editing

Ranee Wongkongdech
Roles: Conceptualization, Funding Acquisition, Investigation, Methodology, Project Administration, Supervision, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

This research was financially supported by Faculty of Medicine, Mahasarakham University with the reference no. 64/04/01.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Article Versions (2)

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Published: 09 Apr 2025, 11:1212

https://doi.org/10.12688/f1000research.123250.2

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https://doi.org/10.12688/f1000research.123250.1

© 2025 Phansila N 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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Phansila N, Pansila P, Wongkongdech A et al. Survival rate of patients with combined hepatocellular cholangiocarcinoma receiving medical cannabis treatment: A retrospective, cohort comparative study [version 2; peer review: 2 approved with reservations, 3 not approved]. F1000Research 2025, 11:1212 (https://doi.org/10.12688/f1000research.123250.2)

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Reviewer Report 12 Aug 2025

Dima Malkawi, University of Colorado, Denver, Colorado, USA

Not Approved

https://doi.org/10.5256/f1000research.180104.r400722

Introduction:
- The second paragraph of the introduction focuses only on CC but this study focuses on cHCC-CC so the introduction needs to be expanded to include both.
- The third paragraph mentions a standard and a new treatment; it would be good to expand on both here to know what the difference is between the two and why that may be relevant
- Would use the intro to discuss the logic behind this study and why it is impactful or necessary. Are there big differences between the two methods?

Methods:
- The flow diagram is not adding much to this manuscript
- Would recommend CONSORT diagram instead
- No information is provided on treatment protocols including dosing, frequency etc
- Patients in CT vs. ST may differ in unmeasured ways (e.g., baseline performance status, comorbidities, tumor burden, liver function). For example, the CT group had much lower mortality rates and higher follow-up times, but it’s unclear whether this is due to the treatment or differences in baseline prognosis.
- There is no mention of propensity score matching or multivariable adjustment for critical prognostic variables beyond age, sex, and treatment.
Without controlling for these confounders, the observed survival difference may be overestimated
- Consider adjusting for additional baseline variables in the Cox model (e.g., ECOG performance status, Child-Pugh score, metastasis status, comorbidities, prior treatments). If unavailable, acknowledge this as a serious limitation
- Your inclusion criteria state “newly diagnosed with CCA or HCC,” yet the title and aim focus on combined hepatocellular cholangiocarcinoma (cHCC-CC)
- unclear whether all patients indeed had cHCC-CC, or whether you included either HCC or CCA
- Clarify whether patients were pathologically confirmed as cHCC-CC or diagnosed clinically as HCC/CCA. If both were included, justify combining them.
- The survival times reported (ST: 0.83 months) seem extremely short, raising the possibility that these were highly selected end-stage patients.

Results:
- The authors state that they tested the proportional hazards assumption but do not report the findings. They also state they did kaplan meier survival curves which are also not reported
- The data is reported as a causal relationship which is extremely misleading
- No data presented on differences in treatment populations
- Chemotherapy is initially defined as CT but then later Cannabis Therapy is also defined as CT causing some confusion
- Data on treatment types and staging is not discussed and thus comparisons between the groups may not be accurate or reflective of true outcomes, and possibly considered invalid

Overall:
- The extremely high CC incidence in your region is discussed, but the CT effect may not translate to other settings.
- Cannabis preparations (THC:CBD ratios, dosing) are specific to Thai FDA-approved products — this needs more detail for reproducibility.

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

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

No
Are sufficient details of methods and analysis provided to allow replication by others?

No
If applicable, is the statistical analysis and its interpretation appropriate?

No
Are all the source data underlying the results available to ensure full reproducibility?

No
Are the conclusions drawn adequately supported by the results?

No

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: surgical oncology, outcomes

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

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Reviewer Report 11 Aug 2025

Nuttapong Ngamphaiboon, Mahidol University, Bangkok, Thailand

Not Approved

https://doi.org/10.5256/f1000research.180104.r396266

The study contains major flaws in both design and methodology. The conclusions presented in the current version of the manuscript may be significantly biased due to the lack of detailed patient characteristics and treatment-related information.

Major Comments: ... Continue reading

Given that cannabinoids are primarily used in palliative care to alleviate pain, reduce nausea, and stimulate appetite, the manuscript should clearly state the primary outcomes of palliative use such as symptom improvement of cannabinoid use in this study.
Detailed information regarding cannabinoid use should be provided, including dosage, duration, mode of administration, and patient compliance.
If survival outcomes are to be reported, critical clinical data must be included—such as ECOG performance status, cancer staging at the time of treatment, chemotherapy regimens, number of cycles, dosing details, relative dose intensity, and radiation therapy use. Without these essential details, the conclusion that "medical cannabis increased overall survival rates among CCA patients" cannot be considered reliable.
Kaplan–Meier curves for overall survival (OS) and progression-free survival (PFS) should be presented to support the survival analysis.

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

No
Is the study design appropriate and is the work technically sound?

No
Are sufficient details of methods and analysis provided to allow replication by others?

No
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
Are the conclusions drawn adequately supported by the results?

No

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Oncology

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Reviewer Report 03 Jun 2025

Ueamporn Summart, Faculty of Nursing, Roi Et Rajabhat University, Tha Muang, Thailand

Approved with Reservations

https://doi.org/10.5256/f1000research.180104.r383930

Title: Survival rate of patients with combined hepatocellular cholangiocarcinoma receiving medical cannabis treatment: A retrospective, cohort comparative study
            Upon completing a comprehensive analysis of all your amended manuscripts, I would like to express my gratitude for your diligent efforts in enhancing and elucidating your manuscripts. In my opinion, there are several areas where the authors may improve in order to enhance the reader's understanding of their work, as outlined below:
Abstract:
Conclusions: “The medical cannabis increased overall survival rates among CCA patients.”
In my opinion, we do not conclude that only the effect of medical cannabis increased overall survival rates among this population because this study design is not supported. Furthermore, the study did not control or include other confounding factors that could affect the survival outcome.
Introduction:
1) Suggest the authors clarify the population of this study. (recurving palliative or curative treatment) and also describe more information about these treatments that are specific for this population before mentioning the use of medical cannabis treatment in this study. (Some details are missing between paragraph 2 and paragraph 3, such as treatment for palliative CCA or specific survival rates and other treatment for this population in Thailand.
2) Suggest the authors mentioned the rationale (literature reviewed) of the covariates and the medical cannabis treatment used in this study from previous studies.
Statistical analysis:
1) Due to the retrospective cohort design, this study aimed to compare the survival rate between 2 treatments, so it is better to compare baseline characteristics of the participants because baseline imbalance among this sample will lead to selection biases.
2) To compare the survival rate between two groups using the log-rank test, the author should mention the assumption for this statistic before using it.3.3) Suggest the authors used a Kaplan-Meier graph to compare survival outcomes between two treatments following covariates in this study, such as age and cancer treatments. 3.4) For Cox proportional hazard statistics, suggest the authors mention the assumption of these statistics and steps of analysis such as univariable analysis and multivariable analysis. (I cannot find this step, but the authors mentioned these steps in the discussion part.).
Results:
1) I agree with reviewer 1 to separate the table into 3 tables as follows: Table 1 compares baseline characteristics. Normally, the authors presented the covariate in the table following the patient treatment group, so it is not the covariate. Suggest separating this table out of the tables that present the study objectives.
2) Suggest the authors present survival outcomes in another table along with Kaplan-Meier graph comparing survival outcomes between two treatments following covariate.
3) Suggest the authors present a table for the Cox proportional hazard ratio to present crude HR and adjusted HR, followed by steps of multivariable analysis. In addition, for the HR less than 1, please interpret this result for the readers.
Discussions:
Suggest the authors discuss following all of the covariates used in this study. In addition, the mechanism of medical cannabis treatment should be mentioned, whether it increased overall survival rates among CCA patients.

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

Partly
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?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Nursing and Public Health

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 05 Sep 2025

Narisara Phansila, Chiang Kwan Hospital, Roi-et Province, 45000, Thailand

05 Sep 2025

Author Response
Reviewer’s Comment – Abstract
Conclusions: “The medical cannabis increased overall survival rates among CCA patients.” In my opinion, we do not conclude that only the effect of medical cannabis increased ... Continue reading
Reviewer’s Comment – Abstract
Conclusions: “The medical cannabis increased overall survival rates among CCA patients.” In my opinion, we do not conclude that only the effect of medical cannabis increased overall survival rates among this population because this study design is not supported. Furthermore, the study did not control or include other confounding factors that could affect the survival outcome.
Response:
We appreciate this important observation. The Abstract conclusion has been revised to avoid implying causality. The new conclusion now reads:
“In this retrospective cohort, medicinal cannabis use was associated with longer overall survival among advanced CCA patients; however, causality cannot be inferred due to the retrospective design and residual confounding.”
This rewording aligns with the study design and acknowledges the potential impact of unmeasured confounding factors.
(Page 1, Lines 36–39)
Reviewer’s Comment – Introduction (1)
Clarify the population of this study (receiving palliative or curative treatment) and describe more information about these treatments specific to this population before mentioning medical cannabis. Include survival rates and treatments for CCA in Thailand.
Response:
We have clarified that all patients in this study were diagnosed with advanced disease and were registered at palliative care or cannabis clinics. No patients received curative-intent treatment. We have expanded the description of standard palliative care and systemic treatment options available in Thailand, including expected survival times, supported by local and international references.
(Page 2, Lines 70–76, 78–79)
Reviewer’s Comment – Introduction (2)
Mention the rationale (literature reviewed) of the covariates and medical cannabis treatment used in this study from previous studies.
Response:
We have added a paragraph explaining the rationale for each covariate (age, sex, type of cancer treatment, time from diagnosis to registration) based on prior survival studies. We also strengthened the rationale for examining medicinal cannabis by summarizing evidence from Thai and global literature on its palliative benefits and possible anti-cancer effects.
(Page 2, Lines 70–79)
Reviewer’s Comment – Statistical Analysis (1)
Compare baseline characteristics to address possible selection bias.
Response:
We have compared baseline characteristics between treatment groups in the new Table 1 and discussed differences that may indicate potential selection bias.
(Page 4, Table 1)
Reviewer’s Comment – Statistical Analysis (2)
Mention the assumption for the log-rank test.
Response:
We have explicitly stated the assumptions for the log-rank test (proportional hazards, non-informative censoring) in the Statistical Analysis section.
(Methods: Statistical Analysis)
Reviewer’s Comment – Statistical Analysis (3)
Use Kaplan–Meier graph to compare survival outcomes between treatments by covariates (e.g., age, cancer treatments).
Response:
We have added stratified Kaplan–Meier survival curves by age group (<65 vs ≥65) and prior cancer treatment (yes/no) in the supplementary material. Figure 1 presents the overall survival curves for the two treatment groups.
(Figure 1; Supplementary Figures)
Reviewer’s Comment – Statistical Analysis (4)
Mention the assumption of Cox regression and steps of analysis (univariable and multivariable).
Response:
We have described the proportional hazards assumption checks (Schoenfeld residuals, log-minus-log plots) and outlined the two-step analysis process: univariable screening (p<0.20) followed by multivariable Cox regression adjusting for selected covariates.
(Methods: Statistical Analysis)
Reviewer’s Comment – Results (1)
Separate tables: Table 1 for baseline characteristics, separate from tables presenting study objectives.
Response:
We have reorganized the results into separate tables:

Table 1: Baseline characteristics by treatment group

Table 2: Survival outcomes (median survival, person-time, log-rank test)

Table 3: Cox regression results (crude and adjusted HRs)
(Pages 4–6, Tables 1–3)

Reviewer’s Comment – Results (2)
Present survival outcomes in another table along with Kaplan–Meier graph by covariates.
Response:
Survival outcomes are now presented in Table 2 and illustrated in Kaplan–Meier curves (Figure 1). Stratified curves by age and prior cancer treatment are included in the supplementary material.
Reviewer’s Comment – Results (3)
Present Cox proportional hazard results in a table with crude and adjusted HR, interpret HR<1.
Response:
Table 3 presents both crude and adjusted HRs, with interpretation provided in the Results section. We explain that HR<1 indicates a reduced hazard of death, reflecting longer survival in that group.
(Page 6, Table 3)
Reviewer’s Comment – Discussion
Discuss all covariates and the mechanism of medical cannabis treatment.
Response:
We have discussed each covariate’s association with survival outcomes, supported by relevant literature. Additionally, we expanded the discussion on potential mechanisms of medicinal cannabis, including symptom relief (pain, nausea, appetite, sleep) and preclinical evidence for anti-tumor activity (apoptosis induction, angiogenesis inhibition, tumor proliferation suppression).
(Pages 6–7, Discussion)
Reviewer’s Comment – Abstract
Conclusions: “The medical cannabis increased overall survival rates among CCA patients.” In my opinion, we do not conclude that only the effect of medical cannabis increased overall survival rates among this population because this study design is not supported. Furthermore, the study did not control or include other confounding factors that could affect the survival outcome.
Response:
We appreciate this important observation. The Abstract conclusion has been revised to avoid implying causality. The new conclusion now reads:
“In this retrospective cohort, medicinal cannabis use was associated with longer overall survival among advanced CCA patients; however, causality cannot be inferred due to the retrospective design and residual confounding.”
This rewording aligns with the study design and acknowledges the potential impact of unmeasured confounding factors.
(Page 1, Lines 36–39)
Reviewer’s Comment – Introduction (1)
Clarify the population of this study (receiving palliative or curative treatment) and describe more information about these treatments specific to this population before mentioning medical cannabis. Include survival rates and treatments for CCA in Thailand.
Response:
We have clarified that all patients in this study were diagnosed with advanced disease and were registered at palliative care or cannabis clinics. No patients received curative-intent treatment. We have expanded the description of standard palliative care and systemic treatment options available in Thailand, including expected survival times, supported by local and international references.
(Page 2, Lines 70–76, 78–79)
Reviewer’s Comment – Introduction (2)
Mention the rationale (literature reviewed) of the covariates and medical cannabis treatment used in this study from previous studies.
Response:
We have added a paragraph explaining the rationale for each covariate (age, sex, type of cancer treatment, time from diagnosis to registration) based on prior survival studies. We also strengthened the rationale for examining medicinal cannabis by summarizing evidence from Thai and global literature on its palliative benefits and possible anti-cancer effects.
(Page 2, Lines 70–79)
Reviewer’s Comment – Statistical Analysis (1)
Compare baseline characteristics to address possible selection bias.
Response:
We have compared baseline characteristics between treatment groups in the new Table 1 and discussed differences that may indicate potential selection bias.
(Page 4, Table 1)
Reviewer’s Comment – Statistical Analysis (2)
Mention the assumption for the log-rank test.
Response:
We have explicitly stated the assumptions for the log-rank test (proportional hazards, non-informative censoring) in the Statistical Analysis section.
(Methods: Statistical Analysis)
Reviewer’s Comment – Statistical Analysis (3)
Use Kaplan–Meier graph to compare survival outcomes between treatments by covariates (e.g., age, cancer treatments).
Response:
We have added stratified Kaplan–Meier survival curves by age group (<65 vs ≥65) and prior cancer treatment (yes/no) in the supplementary material. Figure 1 presents the overall survival curves for the two treatment groups.
(Figure 1; Supplementary Figures)
Reviewer’s Comment – Statistical Analysis (4)
Mention the assumption of Cox regression and steps of analysis (univariable and multivariable).
Response:
We have described the proportional hazards assumption checks (Schoenfeld residuals, log-minus-log plots) and outlined the two-step analysis process: univariable screening (p<0.20) followed by multivariable Cox regression adjusting for selected covariates.
(Methods: Statistical Analysis)
Reviewer’s Comment – Results (1)
Separate tables: Table 1 for baseline characteristics, separate from tables presenting study objectives.
Response:
We have reorganized the results into separate tables:

Table 1: Baseline characteristics by treatment group

Table 2: Survival outcomes (median survival, person-time, log-rank test)

Table 3: Cox regression results (crude and adjusted HRs)
(Pages 4–6, Tables 1–3)

Reviewer’s Comment – Results (2)
Present survival outcomes in another table along with Kaplan–Meier graph by covariates.
Response:
Survival outcomes are now presented in Table 2 and illustrated in Kaplan–Meier curves (Figure 1). Stratified curves by age and prior cancer treatment are included in the supplementary material.
Reviewer’s Comment – Results (3)
Present Cox proportional hazard results in a table with crude and adjusted HR, interpret HR<1.
Response:
Table 3 presents both crude and adjusted HRs, with interpretation provided in the Results section. We explain that HR<1 indicates a reduced hazard of death, reflecting longer survival in that group.
(Page 6, Table 3)
Reviewer’s Comment – Discussion
Discuss all covariates and the mechanism of medical cannabis treatment.
Response:
We have discussed each covariate’s association with survival outcomes, supported by relevant literature. Additionally, we expanded the discussion on potential mechanisms of medicinal cannabis, including symptom relief (pain, nausea, appetite, sleep) and preclinical evidence for anti-tumor activity (apoptosis induction, angiogenesis inhibition, tumor proliferation suppression).
(Pages 6–7, Discussion)
Competing Interests: no competing interest Close
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COMMENTS ON THIS REPORT

Author Response 05 Sep 2025

Narisara Phansila, Chiang Kwan Hospital, Roi-et Province, 45000, Thailand

05 Sep 2025

Author Response
Reviewer’s Comment – Abstract
Conclusions: “The medical cannabis increased overall survival rates among CCA patients.” In my opinion, we do not conclude that only the effect of medical cannabis increased ... Continue reading
Reviewer’s Comment – Abstract
Conclusions: “The medical cannabis increased overall survival rates among CCA patients.” In my opinion, we do not conclude that only the effect of medical cannabis increased overall survival rates among this population because this study design is not supported. Furthermore, the study did not control or include other confounding factors that could affect the survival outcome.
Response:
We appreciate this important observation. The Abstract conclusion has been revised to avoid implying causality. The new conclusion now reads:
“In this retrospective cohort, medicinal cannabis use was associated with longer overall survival among advanced CCA patients; however, causality cannot be inferred due to the retrospective design and residual confounding.”
This rewording aligns with the study design and acknowledges the potential impact of unmeasured confounding factors.
(Page 1, Lines 36–39)
Reviewer’s Comment – Introduction (1)
Clarify the population of this study (receiving palliative or curative treatment) and describe more information about these treatments specific to this population before mentioning medical cannabis. Include survival rates and treatments for CCA in Thailand.
Response:
We have clarified that all patients in this study were diagnosed with advanced disease and were registered at palliative care or cannabis clinics. No patients received curative-intent treatment. We have expanded the description of standard palliative care and systemic treatment options available in Thailand, including expected survival times, supported by local and international references.
(Page 2, Lines 70–76, 78–79)
Reviewer’s Comment – Introduction (2)
Mention the rationale (literature reviewed) of the covariates and medical cannabis treatment used in this study from previous studies.
Response:
We have added a paragraph explaining the rationale for each covariate (age, sex, type of cancer treatment, time from diagnosis to registration) based on prior survival studies. We also strengthened the rationale for examining medicinal cannabis by summarizing evidence from Thai and global literature on its palliative benefits and possible anti-cancer effects.
(Page 2, Lines 70–79)
Reviewer’s Comment – Statistical Analysis (1)
Compare baseline characteristics to address possible selection bias.
Response:
We have compared baseline characteristics between treatment groups in the new Table 1 and discussed differences that may indicate potential selection bias.
(Page 4, Table 1)
Reviewer’s Comment – Statistical Analysis (2)
Mention the assumption for the log-rank test.
Response:
We have explicitly stated the assumptions for the log-rank test (proportional hazards, non-informative censoring) in the Statistical Analysis section.
(Methods: Statistical Analysis)
Reviewer’s Comment – Statistical Analysis (3)
Use Kaplan–Meier graph to compare survival outcomes between treatments by covariates (e.g., age, cancer treatments).
Response:
We have added stratified Kaplan–Meier survival curves by age group (<65 vs ≥65) and prior cancer treatment (yes/no) in the supplementary material. Figure 1 presents the overall survival curves for the two treatment groups.
(Figure 1; Supplementary Figures)
Reviewer’s Comment – Statistical Analysis (4)
Mention the assumption of Cox regression and steps of analysis (univariable and multivariable).
Response:
We have described the proportional hazards assumption checks (Schoenfeld residuals, log-minus-log plots) and outlined the two-step analysis process: univariable screening (p<0.20) followed by multivariable Cox regression adjusting for selected covariates.
(Methods: Statistical Analysis)
Reviewer’s Comment – Results (1)
Separate tables: Table 1 for baseline characteristics, separate from tables presenting study objectives.
Response:
We have reorganized the results into separate tables:

Table 1: Baseline characteristics by treatment group

Table 2: Survival outcomes (median survival, person-time, log-rank test)

Table 3: Cox regression results (crude and adjusted HRs)
(Pages 4–6, Tables 1–3)

Reviewer’s Comment – Results (2)
Present survival outcomes in another table along with Kaplan–Meier graph by covariates.
Response:
Survival outcomes are now presented in Table 2 and illustrated in Kaplan–Meier curves (Figure 1). Stratified curves by age and prior cancer treatment are included in the supplementary material.
Reviewer’s Comment – Results (3)
Present Cox proportional hazard results in a table with crude and adjusted HR, interpret HR<1.
Response:
Table 3 presents both crude and adjusted HRs, with interpretation provided in the Results section. We explain that HR<1 indicates a reduced hazard of death, reflecting longer survival in that group.
(Page 6, Table 3)
Reviewer’s Comment – Discussion
Discuss all covariates and the mechanism of medical cannabis treatment.
Response:
We have discussed each covariate’s association with survival outcomes, supported by relevant literature. Additionally, we expanded the discussion on potential mechanisms of medicinal cannabis, including symptom relief (pain, nausea, appetite, sleep) and preclinical evidence for anti-tumor activity (apoptosis induction, angiogenesis inhibition, tumor proliferation suppression).
(Pages 6–7, Discussion)
Reviewer’s Comment – Abstract
Conclusions: “The medical cannabis increased overall survival rates among CCA patients.” In my opinion, we do not conclude that only the effect of medical cannabis increased overall survival rates among this population because this study design is not supported. Furthermore, the study did not control or include other confounding factors that could affect the survival outcome.
Response:
We appreciate this important observation. The Abstract conclusion has been revised to avoid implying causality. The new conclusion now reads:
“In this retrospective cohort, medicinal cannabis use was associated with longer overall survival among advanced CCA patients; however, causality cannot be inferred due to the retrospective design and residual confounding.”
This rewording aligns with the study design and acknowledges the potential impact of unmeasured confounding factors.
(Page 1, Lines 36–39)
Reviewer’s Comment – Introduction (1)
Clarify the population of this study (receiving palliative or curative treatment) and describe more information about these treatments specific to this population before mentioning medical cannabis. Include survival rates and treatments for CCA in Thailand.
Response:
We have clarified that all patients in this study were diagnosed with advanced disease and were registered at palliative care or cannabis clinics. No patients received curative-intent treatment. We have expanded the description of standard palliative care and systemic treatment options available in Thailand, including expected survival times, supported by local and international references.
(Page 2, Lines 70–76, 78–79)
Reviewer’s Comment – Introduction (2)
Mention the rationale (literature reviewed) of the covariates and medical cannabis treatment used in this study from previous studies.
Response:
We have added a paragraph explaining the rationale for each covariate (age, sex, type of cancer treatment, time from diagnosis to registration) based on prior survival studies. We also strengthened the rationale for examining medicinal cannabis by summarizing evidence from Thai and global literature on its palliative benefits and possible anti-cancer effects.
(Page 2, Lines 70–79)
Reviewer’s Comment – Statistical Analysis (1)
Compare baseline characteristics to address possible selection bias.
Response:
We have compared baseline characteristics between treatment groups in the new Table 1 and discussed differences that may indicate potential selection bias.
(Page 4, Table 1)
Reviewer’s Comment – Statistical Analysis (2)
Mention the assumption for the log-rank test.
Response:
We have explicitly stated the assumptions for the log-rank test (proportional hazards, non-informative censoring) in the Statistical Analysis section.
(Methods: Statistical Analysis)
Reviewer’s Comment – Statistical Analysis (3)
Use Kaplan–Meier graph to compare survival outcomes between treatments by covariates (e.g., age, cancer treatments).
Response:
We have added stratified Kaplan–Meier survival curves by age group (<65 vs ≥65) and prior cancer treatment (yes/no) in the supplementary material. Figure 1 presents the overall survival curves for the two treatment groups.
(Figure 1; Supplementary Figures)
Reviewer’s Comment – Statistical Analysis (4)
Mention the assumption of Cox regression and steps of analysis (univariable and multivariable).
Response:
We have described the proportional hazards assumption checks (Schoenfeld residuals, log-minus-log plots) and outlined the two-step analysis process: univariable screening (p<0.20) followed by multivariable Cox regression adjusting for selected covariates.
(Methods: Statistical Analysis)
Reviewer’s Comment – Results (1)
Separate tables: Table 1 for baseline characteristics, separate from tables presenting study objectives.
Response:
We have reorganized the results into separate tables:

Table 1: Baseline characteristics by treatment group

Table 2: Survival outcomes (median survival, person-time, log-rank test)

Table 3: Cox regression results (crude and adjusted HRs)
(Pages 4–6, Tables 1–3)

Reviewer’s Comment – Results (2)
Present survival outcomes in another table along with Kaplan–Meier graph by covariates.
Response:
Survival outcomes are now presented in Table 2 and illustrated in Kaplan–Meier curves (Figure 1). Stratified curves by age and prior cancer treatment are included in the supplementary material.
Reviewer’s Comment – Results (3)
Present Cox proportional hazard results in a table with crude and adjusted HR, interpret HR<1.
Response:
Table 3 presents both crude and adjusted HRs, with interpretation provided in the Results section. We explain that HR<1 indicates a reduced hazard of death, reflecting longer survival in that group.
(Page 6, Table 3)
Reviewer’s Comment – Discussion
Discuss all covariates and the mechanism of medical cannabis treatment.
Response:
We have discussed each covariate’s association with survival outcomes, supported by relevant literature. Additionally, we expanded the discussion on potential mechanisms of medicinal cannabis, including symptom relief (pain, nausea, appetite, sleep) and preclinical evidence for anti-tumor activity (apoptosis induction, angiogenesis inhibition, tumor proliferation suppression).
(Pages 6–7, Discussion)
Competing Interests: no competing interest Close
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Reviewer Report 10 May 2025

Nat Na-Ek, Division of Social and Administration Pharmacy, Department of Pharmaceutical Care, School of Pharmaceutical Sciences, University of Phayao, Mueang Phayao District, Phayao, Thailand

Not Approved

https://doi.org/10.5256/f1000research.180104.r377013

Thank you for the revised version of the manuscript. However, it remains difficult to determine where amendments have been made in response to my previous comments. I would greatly appreciate it if the authors could provide a point-by-point response to each of my earlier comments, as a general summary is insufficient for a thorough review.

Upon reviewing the revised manuscript, I noted several issues that appear to remain unaddressed, with no accompanying explanation. For example:

- In the abstract, the authors continue to use the term “multivariate analysis” rather than the more appropriate “multivariable analysis”. While this is a relatively minor issue, it reflects a lack of attention to detail.

- More importantly, in the final sentence of the results section and in the conclusion of the abstract, the authors continue to imply a causal relationship between medical cannabis and survival rates. For instance, statements such as “Therefore, CT had a reduced probability of dying from the disease” and “The medical cannabis increased overall survival rates among CCA patients” suggest causality. How can the authors be certain that the observed association is attributable solely to medical cannabis, rather than to other potential explanations?

- Regarding the patient flow diagram, the figure presented appears to be a theoretical illustration more suited to teaching the principles of survival analysis, rather than a CONSORT-style flow diagram. A CONSORT-style flow diagram would be more informative, showing how many participants were initially assessed for eligibility, how exclusions were applied, and how the final analytical sample was derived.

- In the Methods section, the authors mention the use of the Cox proportional hazards model but do not report testing the proportional hazards assumption. Furthermore, I could not locate any figures of Kaplan–Meier curves in the Results section, which raises concerns about the validity and transparency of the analysis.

Given the extensive revision timeline—almost three years since the initial submission—and the apparent failure to sufficiently address or justify the lack of amendments in response to my previous feedback, I regret that I must recommend rejection of this manuscript.

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Clinical epidemiology, pharmacoepidemiology, and social epidemiology

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VERSION 1

PUBLISHED 25 Oct 2022

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Reviewer Report 26 Jun 2023

Nat Na-Ek, Division of Social and Administration Pharmacy, Department of Pharmaceutical Care, School of Pharmaceutical Sciences, University of Phayao, Mueang Phayao District, Phayao, Thailand

Approved with Reservations

https://doi.org/10.5256/f1000research.135337.r178384

Overall, this piece of work on the benefits of medical cannabis in improving the survival rate of combined hepatocellular cholangiocarcinoma (cHCC-CC) patients is interesting. However, several issues need further clarification and improvements.

Major points:

It is important to recheck the accuracy of the provided data (https://doi.org/10.6084/m9.figshare.2010119). I noticed inconsistencies in the reported figures, such as the percentages of male and female patients and the number of patients receiving each treatment modality. Additionally, there was a coding issue with one patient receiving medical cannabis coded as 12 in the current treatment variable without an explanation. Addressing these inconsistencies is crucial for the reproducibility of the results.
The authors did not mention whether they performed a proportional hazards assumption test in the statistical analysis. Upon re-analysis, I found that the treatment variable violated this assumption, indicating that the hazard ratio was not constant at 0.28 across the entire follow-up time as reported. More importantly, the significant association between medical cannabis and survival rate was observed only in the early follow-up (3 months), not the whole study period.

Therefore, it is important for the authors to conduct a re-analysis and introduce an interaction term between the treatment variable and time using the time-varying covariate (TVC) option in STATA. When reporting the hazard ratio, the authors should present it across the range of follow-up (e.g., within 10 months) to ensure validity and reliability. More details and examples can be found at Bellera et al. (2010)¹.
Please avoid making causal claims in an observational study. For example, the sentence "the medical cannabis increased overall survival rates among cHCC-CC patients" (conclusion of the abstract) should be revised to "the medical cannabis was associated with improved overall survival rates among cHCC-CC patients." This distinction is vital because several alternative explanations (e.g., bias, errors, confounding, effect modification, reverse causality) could account for the significant findings. For instance, patients who received medical cannabis might have been more closely monitored by physicians, or they might have had unobserved or unmeasured characteristics (residual confounders) that affected their prognosis positively. Additionally, there may have been discrepancies in the quality of care across different settings.

Therefore, the authors should refrain from assuming causality to avoid exaggerating the significance of their results. It would be appropriate to include a cautionary statement in the discussion section, such as "as this is an observational study, we cannot infer causality, and a randomised controlled trial is needed to establish the efficacy of medical cannabis in cancer patients."
Please provide justification and references for each covariate selected as adjusting factors in the analysis. Furthermore, clarify why certain continuous variables (e.g., age, disease duration after registration) were categorised instead of using them as continuous scales. Additionally, I recommend running the analysis with age as a quadratic term (age + age²), as it was found to be significantly associated with death, suggesting a non-linear relationship between age and mortality. Therefore, using a quadratic term for each continuous variable would be more appropriate as it preserves important information².
Provide more details about the medical cannabis used in the study, such as product details, dosage form, dose, and administration. This information is crucial for generalising the findings to a clinical setting and enabling reproducibility. Additionally, clarify what the standard treatment was in the study and whether it was consistent across different settings.
In the discussion section, provide more information about the individuals who were lost to follow-up and discuss how their exclusion might have influenced the findings. Is it possible to determine whether these patients were still alive at the end of the study or if they died soon after dropping out?
Discuss the potential impact of differences in the quality of care across settings on the survival rate of patients in the study. It would be helpful to perform a subgroup analysis according to settings and utilise the strata option in the Cox model.

Furthermore, consider conducting subgroup analyses based on other variables such as sex, age group, and current treatment to assess whether effect modification plays a role in the findings. Sensitivity and subgroup analyses are necessary to ensure the robustness of the findings, particularly in an observational study.
In the discussion section, compare the survival rates of the study, particularly in the standard treatment group, with previous works. If applicable, discuss the reasons for any differences observed. This will help strengthen the external validity of the study.

Minor issues:

Use "multivariable" instead of "multivariate" when discussing regression models. The term "multivariable" refers to adding explanatory variables (X) in the regression model, while "multivariate" implies examining various outcomes (Y) simultaneously³.
Spell "proportional hazards regression" with an "s" in "hazards" since the term "proportional" implies the existence of at least two hazards.
Be aware of the term person-months as it is not a person per month, but it is rather the product of patients and their corresponding follow-up time. So, the unit of the incidence rate in your work should be written as “100 person-months” not “100 person/month”.
To improve clarity, consider splitting Table 1 into three separate tables. Table 1 should focus solely on the characteristics of included participants, allowing for inferential statistics (e.g., independent t-test, chi-squared test) to test the association between each characteristic and exposure status. Then, create Table 2 to present details of the outcome variable according to exposure status. Finally, present Table 3 as the main findings regarding the association between treatment and all-cause mortality, including both crude (unadjusted) and adjusted hazard ratios. Additionally, including a Kaplan-Meier plot with a risk table would aid in visualising the survival rates between patients receiving medical cannabis and those receiving standard treatment.
If possible, please discuss the potential biological mechanisms or underlying explanations of how medical cannabis can improve the survival rate of cHCC-CC patients.

Overall, addressing these major and minor points will greatly enhance the clarity, validity, and reproducibility of your study.

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

Partly
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?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

References

1. Bellera CA, MacGrogan G, Debled M, de Lara CT, et al.: Variables with time-varying effects and the Cox model: some statistical concepts illustrated with a prognostic factor study in breast cancer.BMC Med Res Methodol. 2010; 10: 20 PubMed Abstract | Publisher Full Text
2. Collins GS, Ogundimu EO, Cook JA, Manach YL, et al.: Quantifying the impact of different approaches for handling continuous predictors on the performance of a prognostic model.Stat Med. 2016; 35 (23): 4124-35 PubMed Abstract | Publisher Full Text
3. Hidalgo B, Goodman M: Multivariate or multivariable regression?. Am J Public Health. 2013; 103 (1): 39-40 PubMed Abstract | Publisher Full Text

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Clinical epidemiology, pharmacoepidemiology, and social epidemiology

CITE

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Reviewer Report 01 Jun 2023

Selamat Budijitno, Department of Surgery, Dr. Kariadi Hospital, Faculty of Medicine, Universitas Diponegoro, Semarang, Central Java, Indonesia

Approved with Reservations

https://doi.org/10.5256/f1000research.135337.r170664

Based on the STROBE criteria, most of this research has fulfilled the criteria. In my opinion, there are several things that need to be improved so that this research is better:

There is no sufficient detail

Based on the STROBE criteria, most of this research has fulfilled the criteria. In my opinion, there are several things that need to be improved so that this research is better:

There is no sufficient detail of the methods, especially on the eligibility criteria of participants, and the method of follow up that provided to allow replication by others.
There are no very important data as a confounder, namely the pain scale/level of pain on the criteria when matching participants.
It would be clearer if the authors can explain the relationship between pain levels, quality of life, and survival rates in biomolecular terms. Such as, for example, mutations in the NMDA receptor in chronic pain, which will produce P protein which can increase the risk of advanced metastasis, NMDA receptors stimulates the MAPK and CaMK pathways, leading to CREB activation in tumor cells. NMDAR-interacting proteins and the downstream signaling effectors display features in common between the neuronal and metastatic cancer processes, such as cell adhesion, migration, and survival.
In the results of the cohort study, it would be better if the authors can explain in the report the numbers of individuals at each stage of study – e.g., numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and the reason of dropped out participant.
Give reasons for nonparticipation/dropped out participant in each stage. Consider use of a flow diagram.

Thank you.

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?

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

Partly
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Surgical Oncology, biomolecular, Immunology, epidemiology

CITE

Report a concern

Author Response 09 Apr 2025

Narisara Phansila, Chiang Kwan Hospital, Roi-et Province, 45000, Thailand

09 Apr 2025

Author Response
1. There is no sufficient detail of the methods, especially on the eligibility criteria of participants, and the method of follow up that provided to allow replication by others.
... Continue reading
There is no sufficient detail of the methods, especially on the eligibility criteria of participants, and the method of follow up that provided to allow replication by others.

Ans: The survival rate matches the history of the first day of treatment in the clinic. Copy the symptoms and physical examination of the patient. Diagnosis, treatment, address, and telephone number from the medical records recorded by the treating physician from September 2, 2019, to October 31, 2020; follow up on the patient's last status until April 30, 2021. Check the status and date of the patient's death from the Cancer Unit's patient tracking database or from the death certificate of the patient Check the correctness of the information. and import data for analysis.

There are no very important data as a confounder, namely the pain scale/level of pain on the criteria when matching participants.

Ans: The evaluation was not assessed because secondary data were used to track only the six-month outcome, censor, or event to assess survival. Starting from admission to treat both types, the inclusion criteria were likely to be met for all patients aged 18 years and over.

It would be clearer if the authors can explain the relationship between pain levels, quality of life, and survival rates in biomolecular terms. Such as, for example, mutations in the NMDA receptor in chronic pain, which will produce P protein which can increase the risk of advanced metastasis, NMDA receptors stimulates the MAPK and CaMK pathways, leading to CREB activation in tumor cells. NMDAR-interacting proteins and the downstream signaling effectors display features in common between the neuronal and metastatic cancer processes, such as cell adhesion, migration, and survival.

Ans: This study has not investigated a relationship; we only track the survival rate over time. and find factors that are general information, but we will be publishing again about the quality of life and survival.

In the results of the cohort study, it would be better if the authors can explain in the report the numbers of individuals at each stage of study – e.g., numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and the reason of dropped out participant.

Ans: This study used secondary data based on the results of the diagnosis and the treatment system.

Give reasons for nonparticipation/dropped out participant in each stage. Consider use of a flow diagram.

Ans: Due to the use of medical records, use the available information If death is specified in the system, there will be a death certificate. The lack of follow-up data will be used as a censor, but it can be used to calculate the survival rate by using survival statistics.
There is no sufficient detail of the methods, especially on the eligibility criteria of participants, and the method of follow up that provided to allow replication by others.

Ans: The survival rate matches the history of the first day of treatment in the clinic. Copy the symptoms and physical examination of the patient. Diagnosis, treatment, address, and telephone number from the medical records recorded by the treating physician from September 2, 2019, to October 31, 2020; follow up on the patient's last status until April 30, 2021. Check the status and date of the patient's death from the Cancer Unit's patient tracking database or from the death certificate of the patient Check the correctness of the information. and import data for analysis.

There are no very important data as a confounder, namely the pain scale/level of pain on the criteria when matching participants.

Ans: The evaluation was not assessed because secondary data were used to track only the six-month outcome, censor, or event to assess survival. Starting from admission to treat both types, the inclusion criteria were likely to be met for all patients aged 18 years and over.

It would be clearer if the authors can explain the relationship between pain levels, quality of life, and survival rates in biomolecular terms. Such as, for example, mutations in the NMDA receptor in chronic pain, which will produce P protein which can increase the risk of advanced metastasis, NMDA receptors stimulates the MAPK and CaMK pathways, leading to CREB activation in tumor cells. NMDAR-interacting proteins and the downstream signaling effectors display features in common between the neuronal and metastatic cancer processes, such as cell adhesion, migration, and survival.

Ans: This study has not investigated a relationship; we only track the survival rate over time. and find factors that are general information, but we will be publishing again about the quality of life and survival.

In the results of the cohort study, it would be better if the authors can explain in the report the numbers of individuals at each stage of study – e.g., numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and the reason of dropped out participant.

Ans: This study used secondary data based on the results of the diagnosis and the treatment system.

Give reasons for nonparticipation/dropped out participant in each stage. Consider use of a flow diagram.

Ans: Due to the use of medical records, use the available information If death is specified in the system, there will be a death certificate. The lack of follow-up data will be used as a censor, but it can be used to calculate the survival rate by using survival statistics.
Competing Interests: No Competing of interests Close
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COMMENTS ON THIS REPORT

Author Response 09 Apr 2025

Narisara Phansila, Chiang Kwan Hospital, Roi-et Province, 45000, Thailand

09 Apr 2025

Author Response
1. There is no sufficient detail of the methods, especially on the eligibility criteria of participants, and the method of follow up that provided to allow replication by others.
... Continue reading
There is no sufficient detail of the methods, especially on the eligibility criteria of participants, and the method of follow up that provided to allow replication by others.

Ans: The survival rate matches the history of the first day of treatment in the clinic. Copy the symptoms and physical examination of the patient. Diagnosis, treatment, address, and telephone number from the medical records recorded by the treating physician from September 2, 2019, to October 31, 2020; follow up on the patient's last status until April 30, 2021. Check the status and date of the patient's death from the Cancer Unit's patient tracking database or from the death certificate of the patient Check the correctness of the information. and import data for analysis.

There are no very important data as a confounder, namely the pain scale/level of pain on the criteria when matching participants.

Ans: The evaluation was not assessed because secondary data were used to track only the six-month outcome, censor, or event to assess survival. Starting from admission to treat both types, the inclusion criteria were likely to be met for all patients aged 18 years and over.

It would be clearer if the authors can explain the relationship between pain levels, quality of life, and survival rates in biomolecular terms. Such as, for example, mutations in the NMDA receptor in chronic pain, which will produce P protein which can increase the risk of advanced metastasis, NMDA receptors stimulates the MAPK and CaMK pathways, leading to CREB activation in tumor cells. NMDAR-interacting proteins and the downstream signaling effectors display features in common between the neuronal and metastatic cancer processes, such as cell adhesion, migration, and survival.

Ans: This study has not investigated a relationship; we only track the survival rate over time. and find factors that are general information, but we will be publishing again about the quality of life and survival.

In the results of the cohort study, it would be better if the authors can explain in the report the numbers of individuals at each stage of study – e.g., numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and the reason of dropped out participant.

Ans: This study used secondary data based on the results of the diagnosis and the treatment system.

Give reasons for nonparticipation/dropped out participant in each stage. Consider use of a flow diagram.

Ans: Due to the use of medical records, use the available information If death is specified in the system, there will be a death certificate. The lack of follow-up data will be used as a censor, but it can be used to calculate the survival rate by using survival statistics.
There is no sufficient detail of the methods, especially on the eligibility criteria of participants, and the method of follow up that provided to allow replication by others.

Ans: The survival rate matches the history of the first day of treatment in the clinic. Copy the symptoms and physical examination of the patient. Diagnosis, treatment, address, and telephone number from the medical records recorded by the treating physician from September 2, 2019, to October 31, 2020; follow up on the patient's last status until April 30, 2021. Check the status and date of the patient's death from the Cancer Unit's patient tracking database or from the death certificate of the patient Check the correctness of the information. and import data for analysis.

There are no very important data as a confounder, namely the pain scale/level of pain on the criteria when matching participants.

Ans: The evaluation was not assessed because secondary data were used to track only the six-month outcome, censor, or event to assess survival. Starting from admission to treat both types, the inclusion criteria were likely to be met for all patients aged 18 years and over.

It would be clearer if the authors can explain the relationship between pain levels, quality of life, and survival rates in biomolecular terms. Such as, for example, mutations in the NMDA receptor in chronic pain, which will produce P protein which can increase the risk of advanced metastasis, NMDA receptors stimulates the MAPK and CaMK pathways, leading to CREB activation in tumor cells. NMDAR-interacting proteins and the downstream signaling effectors display features in common between the neuronal and metastatic cancer processes, such as cell adhesion, migration, and survival.

Ans: This study has not investigated a relationship; we only track the survival rate over time. and find factors that are general information, but we will be publishing again about the quality of life and survival.

In the results of the cohort study, it would be better if the authors can explain in the report the numbers of individuals at each stage of study – e.g., numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and the reason of dropped out participant.

Ans: This study used secondary data based on the results of the diagnosis and the treatment system.

Give reasons for nonparticipation/dropped out participant in each stage. Consider use of a flow diagram.

Ans: Due to the use of medical records, use the available information If death is specified in the system, there will be a death certificate. The lack of follow-up data will be used as a censor, but it can be used to calculate the survival rate by using survival statistics.
Competing Interests: No Competing of interests Close
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Version 2

VERSION 2 PUBLISHED 25 Oct 2022

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Version 2 (revision) 09 Apr 25		read	read	read	read
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Selamat Budijitno, Universitas Diponegoro, Semarang, Indonesia
Nat Na-Ek, University of Phayao, Mueang Phayao District, Thailand
Ueamporn Summart, Roi Et Rajabhat University, Tha Muang, Thailand
Nuttapong Ngamphaiboon, Mahidol University, Bangkok, Thailand
Dima Malkawi, University of Colorado, Denver, USA

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3 Views

12 Aug 2025 | for Version 2

Dima Malkawi, University of Colorado, Denver, Colorado, USA

3 Views Cite this report Responses(0)

Not Approved

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

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

No
Are sufficient details of methods and analysis provided to allow replication by others?

No
If applicable, is the statistical analysis and its interpretation appropriate?

No
Are all the source data underlying the results available to ensure full reproducibility?

No
Are the conclusions drawn adequately supported by the results?

No

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

surgical oncology, outcomes

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6 Views

11 Aug 2025 | for Version 2

Nuttapong Ngamphaiboon, Mahidol University, Bangkok, Thailand

6 Views Cite this report Responses(0)

Not Approved

Given that cannabinoids are primarily used in palliative care to alleviate pain, reduce nausea, and stimulate appetite, the manuscript should clearly state the primary outcomes of palliative use such as symptom improvement of cannabinoid use in this study.
Detailed information regarding cannabinoid use should be provided, including dosage, duration, mode of administration, and patient compliance.
If survival outcomes are to be reported, critical clinical data must be included—such as ECOG performance status, cancer staging at the time of treatment, chemotherapy regimens, number of cycles, dosing details, relative dose intensity, and radiation therapy use. Without these essential details, the conclusion that "medical cannabis increased overall survival rates among CCA patients" cannot be considered reliable.
Kaplan–Meier curves for overall survival (OS) and progression-free survival (PFS) should be presented to support the survival analysis.

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

No
Is the study design appropriate and is the work technically sound?

No
Are sufficient details of methods and analysis provided to allow replication by others?

No
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
Are the conclusions drawn adequately supported by the results?

No

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Oncology

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10 Views

03 Jun 2025 | for Version 2

Ueamporn Summart, Faculty of Nursing, Roi Et Rajabhat University, Tha Muang, Thailand

10 Views Cite this report Responses(1)

Approved With Reservations

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

Partly
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?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Nursing and Public Health

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Author Response

05 Sep 2025

Narisara Phansila, Chiang Kwan Hospital, Roi-et Province, 45000, Thailand

Reviewer’s Comment – Abstract
Conclusions: “The medical cannabis increased overall survival rates among CCA patients.” In my opinion, we do not conclude that only the effect of medical cannabis increased overall survival rates among this population because this study design is not supported. Furthermore, the study did not control or include other confounding factors that could affect the survival outcome.
Response:
We appreciate this important observation. The Abstract conclusion has been revised to avoid implying causality. The new conclusion now reads:
“In this retrospective cohort, medicinal cannabis use was associated with longer overall survival among advanced CCA patients; however, causality cannot be inferred due to the retrospective design and residual confounding.”
This rewording aligns with the study design and acknowledges the potential impact of unmeasured confounding factors.
(Page 1, Lines 36–39)
Reviewer’s Comment – Introduction (1)
Clarify the population of this study (receiving palliative or curative treatment) and describe more information about these treatments specific to this population before mentioning medical cannabis. Include survival rates and treatments for CCA in Thailand.
Response:
We have clarified that all patients in this study were diagnosed with advanced disease and were registered at palliative care or cannabis clinics. No patients received curative-intent treatment. We have expanded the description of standard palliative care and systemic treatment options available in Thailand, including expected survival times, supported by local and international references.
(Page 2, Lines 70–76, 78–79)
Reviewer’s Comment – Introduction (2)
Mention the rationale (literature reviewed) of the covariates and medical cannabis treatment used in this study from previous studies.
Response:
We have added a paragraph explaining the rationale for each covariate (age, sex, type of cancer treatment, time from diagnosis to registration) based on prior survival studies. We also strengthened the rationale for examining medicinal cannabis by summarizing evidence from Thai and global literature on its palliative benefits and possible anti-cancer effects.
(Page 2, Lines 70–79)
Reviewer’s Comment – Statistical Analysis (1)
Compare baseline characteristics to address possible selection bias.
Response:
We have compared baseline characteristics between treatment groups in the new Table 1 and discussed differences that may indicate potential selection bias.
(Page 4, Table 1)
Reviewer’s Comment – Statistical Analysis (2)
Mention the assumption for the log-rank test.
Response:
We have explicitly stated the assumptions for the log-rank test (proportional hazards, non-informative censoring) in the Statistical Analysis section.
(Methods: Statistical Analysis)
Reviewer’s Comment – Statistical Analysis (3)
Use Kaplan–Meier graph to compare survival outcomes between treatments by covariates (e.g., age, cancer treatments).
Response:
We have added stratified Kaplan–Meier survival curves by age group (<65 vs ≥65) and prior cancer treatment (yes/no) in the supplementary material. Figure 1 presents the overall survival curves for the two treatment groups.
(Figure 1; Supplementary Figures)
Reviewer’s Comment – Statistical Analysis (4)
Mention the assumption of Cox regression and steps of analysis (univariable and multivariable).
Response:
We have described the proportional hazards assumption checks (Schoenfeld residuals, log-minus-log plots) and outlined the two-step analysis process: univariable screening (p<0.20) followed by multivariable Cox regression adjusting for selected covariates.
(Methods: Statistical Analysis)
Reviewer’s Comment – Results (1)
Separate tables: Table 1 for baseline characteristics, separate from tables presenting study objectives.
Response:
We have reorganized the results into separate tables:

Table 1: Baseline characteristics by treatment group
Table 2: Survival outcomes (median survival, person-time, log-rank test)
Table 3: Cox regression results (crude and adjusted HRs)
(Pages 4–6, Tables 1–3)

Reviewer’s Comment – Results (2)
Present survival outcomes in another table along with Kaplan–Meier graph by covariates.
Response:
Survival outcomes are now presented in Table 2 and illustrated in Kaplan–Meier curves (Figure 1). Stratified curves by age and prior cancer treatment are included in the supplementary material.
Reviewer’s Comment – Results (3)
Present Cox proportional hazard results in a table with crude and adjusted HR, interpret HR<1.
Response:
Table 3 presents both crude and adjusted HRs, with interpretation provided in the Results section. We explain that HR<1 indicates a reduced hazard of death, reflecting longer survival in that group.
(Page 6, Table 3)
Reviewer’s Comment – Discussion
Discuss all covariates and the mechanism of medical cannabis treatment.
Response:
We have discussed each covariate’s association with survival outcomes, supported by relevant literature. Additionally, we expanded the discussion on potential mechanisms of medicinal cannabis, including symptom relief (pain, nausea, appetite, sleep) and preclinical evidence for anti-tumor activity (apoptosis induction, angiogenesis inhibition, tumor proliferation suppression).
(Pages 6–7, Discussion)

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Reviewer Report

9 Views

10 May 2025 | for Version 2

Nat Na-Ek, Division of Social and Administration Pharmacy, Department of Pharmaceutical Care, School of Pharmaceutical Sciences, University of Phayao, Mueang Phayao District, Phayao, Thailand

9 Views Cite this report Responses(0)

Not Approved

Competing Interests

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Reviewer Expertise

Clinical epidemiology, pharmacoepidemiology, and social epidemiology

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26 Views

26 Jun 2023 | for Version 1

Nat Na-Ek, Division of Social and Administration Pharmacy, Department of Pharmaceutical Care, School of Pharmaceutical Sciences, University of Phayao, Mueang Phayao District, Phayao, Thailand

26 Views Cite this report Responses(0)

Approved With Reservations

It is important to recheck the accuracy of the provided data (https://doi.org/10.6084/m9.figshare.2010119). I noticed inconsistencies in the reported figures, such as the percentages of male and female patients and the number of patients receiving each treatment modality. Additionally, there was a coding issue with one patient receiving medical cannabis coded as 12 in the current treatment variable without an explanation. Addressing these inconsistencies is crucial for the reproducibility of the results.
The authors did not mention whether they performed a proportional hazards assumption test in the statistical analysis. Upon re-analysis, I found that the treatment variable violated this assumption, indicating that the hazard ratio was not constant at 0.28 across the entire follow-up time as reported. More importantly, the significant association between medical cannabis and survival rate was observed only in the early follow-up (3 months), not the whole study period.

Therefore, it is important for the authors to conduct a re-analysis and introduce an interaction term between the treatment variable and time using the time-varying covariate (TVC) option in STATA. When reporting the hazard ratio, the authors should present it across the range of follow-up (e.g., within 10 months) to ensure validity and reliability. More details and examples can be found at Bellera et al. (2010)¹.
Please avoid making causal claims in an observational study. For example, the sentence "the medical cannabis increased overall survival rates among cHCC-CC patients" (conclusion of the abstract) should be revised to "the medical cannabis was associated with improved overall survival rates among cHCC-CC patients." This distinction is vital because several alternative explanations (e.g., bias, errors, confounding, effect modification, reverse causality) could account for the significant findings. For instance, patients who received medical cannabis might have been more closely monitored by physicians, or they might have had unobserved or unmeasured characteristics (residual confounders) that affected their prognosis positively. Additionally, there may have been discrepancies in the quality of care across different settings.

Therefore, the authors should refrain from assuming causality to avoid exaggerating the significance of their results. It would be appropriate to include a cautionary statement in the discussion section, such as "as this is an observational study, we cannot infer causality, and a randomised controlled trial is needed to establish the efficacy of medical cannabis in cancer patients."
Please provide justification and references for each covariate selected as adjusting factors in the analysis. Furthermore, clarify why certain continuous variables (e.g., age, disease duration after registration) were categorised instead of using them as continuous scales. Additionally, I recommend running the analysis with age as a quadratic term (age + age²), as it was found to be significantly associated with death, suggesting a non-linear relationship between age and mortality. Therefore, using a quadratic term for each continuous variable would be more appropriate as it preserves important information².
Provide more details about the medical cannabis used in the study, such as product details, dosage form, dose, and administration. This information is crucial for generalising the findings to a clinical setting and enabling reproducibility. Additionally, clarify what the standard treatment was in the study and whether it was consistent across different settings.
In the discussion section, provide more information about the individuals who were lost to follow-up and discuss how their exclusion might have influenced the findings. Is it possible to determine whether these patients were still alive at the end of the study or if they died soon after dropping out?
Discuss the potential impact of differences in the quality of care across settings on the survival rate of patients in the study. It would be helpful to perform a subgroup analysis according to settings and utilise the strata option in the Cox model.

Furthermore, consider conducting subgroup analyses based on other variables such as sex, age group, and current treatment to assess whether effect modification plays a role in the findings. Sensitivity and subgroup analyses are necessary to ensure the robustness of the findings, particularly in an observational study.
In the discussion section, compare the survival rates of the study, particularly in the standard treatment group, with previous works. If applicable, discuss the reasons for any differences observed. This will help strengthen the external validity of the study.

Minor issues:

Use "multivariable" instead of "multivariate" when discussing regression models. The term "multivariable" refers to adding explanatory variables (X) in the regression model, while "multivariate" implies examining various outcomes (Y) simultaneously³.
Spell "proportional hazards regression" with an "s" in "hazards" since the term "proportional" implies the existence of at least two hazards.
Be aware of the term person-months as it is not a person per month, but it is rather the product of patients and their corresponding follow-up time. So, the unit of the incidence rate in your work should be written as “100 person-months” not “100 person/month”.
To improve clarity, consider splitting Table 1 into three separate tables. Table 1 should focus solely on the characteristics of included participants, allowing for inferential statistics (e.g., independent t-test, chi-squared test) to test the association between each characteristic and exposure status. Then, create Table 2 to present details of the outcome variable according to exposure status. Finally, present Table 3 as the main findings regarding the association between treatment and all-cause mortality, including both crude (unadjusted) and adjusted hazard ratios. Additionally, including a Kaplan-Meier plot with a risk table would aid in visualising the survival rates between patients receiving medical cannabis and those receiving standard treatment.
If possible, please discuss the potential biological mechanisms or underlying explanations of how medical cannabis can improve the survival rate of cHCC-CC patients.

Overall, addressing these major and minor points will greatly enhance the clarity, validity, and reproducibility of your study.

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

Partly
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?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

References

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Clinical epidemiology, pharmacoepidemiology, and social epidemiology

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Reviewer Report

41 Views

01 Jun 2023 | for Version 1

Selamat Budijitno, Department of Surgery, Dr. Kariadi Hospital, Faculty of Medicine, Universitas Diponegoro, Semarang, Central Java, Indonesia

41 Views Cite this report Responses(1)

Approved With Reservations

Based on the STROBE criteria, most of this research has fulfilled the criteria. In my opinion, there are several things that need to be improved so that this research is better:

There is no sufficient detail of the methods, especially on the eligibility criteria of participants, and the method of follow up that provided to allow replication by others.
There are no very important data as a confounder, namely the pain scale/level of pain on the criteria when matching participants.
It would be clearer if the authors can explain the relationship between pain levels, quality of life, and survival rates in biomolecular terms. Such as, for example, mutations in the NMDA receptor in chronic pain, which will produce P protein which can increase the risk of advanced metastasis, NMDA receptors stimulates the MAPK and CaMK pathways, leading to CREB activation in tumor cells. NMDAR-interacting proteins and the downstream signaling effectors display features in common between the neuronal and metastatic cancer processes, such as cell adhesion, migration, and survival.
In the results of the cohort study, it would be better if the authors can explain in the report the numbers of individuals at each stage of study – e.g., numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and the reason of dropped out participant.
Give reasons for nonparticipation/dropped out participant in each stage. Consider use of a flow diagram.

Thank you.

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?

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

Partly
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Surgical Oncology, biomolecular, Immunology, epidemiology

Respond to this report

Responses (1)

Author Response

09 Apr 2025

Narisara Phansila, Chiang Kwan Hospital, Roi-et Province, 45000, Thailand

There is no sufficient detail of the methods, especially on the eligibility criteria of participants, and the method of follow up that provided to allow replication by others.

Ans: The survival rate matches the history of the first day of treatment in the clinic. Copy the symptoms and physical examination of the patient. Diagnosis, treatment, address, and telephone number from the medical records recorded by the treating physician from September 2, 2019, to October 31, 2020; follow up on the patient's last status until April 30, 2021. Check the status and date of the patient's death from the Cancer Unit's patient tracking database or from the death certificate of the patient Check the correctness of the information. and import data for analysis.
There are no very important data as a confounder, namely the pain scale/level of pain on the criteria when matching participants.

Ans: The evaluation was not assessed because secondary data were used to track only the six-month outcome, censor, or event to assess survival. Starting from admission to treat both types, the inclusion criteria were likely to be met for all patients aged 18 years and over.
It would be clearer if the authors can explain the relationship between pain levels, quality of life, and survival rates in biomolecular terms. Such as, for example, mutations in the NMDA receptor in chronic pain, which will produce P protein which can increase the risk of advanced metastasis, NMDA receptors stimulates the MAPK and CaMK pathways, leading to CREB activation in tumor cells. NMDAR-interacting proteins and the downstream signaling effectors display features in common between the neuronal and metastatic cancer processes, such as cell adhesion, migration, and survival.

Ans: This study has not investigated a relationship; we only track the survival rate over time. and find factors that are general information, but we will be publishing again about the quality of life and survival.
In the results of the cohort study, it would be better if the authors can explain in the report the numbers of individuals at each stage of study – e.g., numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and the reason of dropped out participant.

Ans: This study used secondary data based on the results of the diagnosis and the treatment system.
Give reasons for nonparticipation/dropped out participant in each stage. Consider use of a flow diagram.

Ans: Due to the use of medical records, use the available information If death is specified in the system, there will be a death certificate. The lack of follow-up data will be used as a censor, but it can be used to calculate the survival rate by using survival statistics.

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Competing Interests

No Competing of 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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Survival rate of patients with combined hepatocellular cholangiocarcinoma receiving medical cannabis treatment: A retrospective, cohort comparative study

Abstract

Keywords

Revised Amendments from Version 1

Introduction

Methods

Ethical approval

Study design

Data collection

Figure 1. Study flow diagram for participant accrual and outcomes.

Independent and dependent variables

Statistical methods

Results

Standard medical treatment

Medical cannabis treatment

Participants’ Characteristics and Survival Rates of Patients with CCA/HCC Treated with Cannabis Therapy (CT) and Standard Therapy (ST)

Table 1. Baseline characteristics of included patients (n=491).

Discussion

Author contributions

Data availability

Underlying data

Acknowledgements

References

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