[version 1; peer review: awaiting peer review]
No competing interests were disclosed.
Ovarian masses are a significant health concern among women, and their accurate diagnosis and characterization are paramount for effective management. This study protocol outlines a correlational investigation into the relationship between clinical, ultrasonographic, and biochemical markers and histopathological findings of ovarian masses in rural hospitals.
The study employs a correlational research design and will be conducted within the Department of Obstetrics and Gynecology at a rural hospital affiliated with Datta Meghe Institute of Higher Education and Research. The study population will comprise women of all ages diagnosed with ovarian masses. Clinical evaluations, ultrasonography, biochemical investigations, preoperative workup, and histopathological examinations will be conducted to gather data. The sample size will be determined based on statistical and practical considerations, yielding approximately 60 participants.
The study expects to yield valuable insights into the diagnostic and prognostic indicators for ovarian masses. The data collected will enable the correlation of clinical symptoms, ultrasonographic findings, CA 125 levels, and histopathological characteristics, contributing to enhanced diagnostic accuracy, improved patient care, and potentially reduced healthcare costs in rural healthcare settings.
Ovarian masses represent a significant medical concern among women, impacting their health and quality of life. In both rural and urban healthcare settings, accurate diagnosis and appropriate management of ovarian masses are pivotal to ensure timely intervention and improved patient outcomes.
Ovarian masses are a diverse group of lesions, ranging from benign cysts to malignant tumours, each necessitating a distinct diagnostic and therapeutic approach.
The primary objective of this study is to discern the correlation and analyse the interplay between various markers and the histopathological characteristics of ovarian masses. By achieving this, we aspire to enhance the ability of healthcare providers in rural settings to make informed decisions, ultimately improving the care and management of women with ovarian masses. Furthermore, this research may contribute to the development of diagnostic models that encompass clinical, ultrasonographic, and biochemical elements, potentially leading to more efficient and cost-effective diagnostic procedures.
The aim of this study is to investigate the correlation between clinical, ultrasonographic, and biochemical markers with histopathological examination findings of ovarian masses in women diagnosed with ovarian masses.
To assess the clinical features of ovarian masses amongst women attending a rural hospital setup. To evaluate ultrasonographic findings of ovarian masses in study participants and score them based on Risk of Malignancy Index (RMI) and International Ovarian Tumor Analysis (IOTA). To interpret the value of CA 125 among study participants. To confirm histopathologically the characteristics and features of ovarian masses amongst study participants. To correlate and analyse different clinical, ultrasonographic, biochemical, and histopathological features of ovarian masses amongst study participants.
This study will employ a correlational research design to investigate the correlation between clinical, ultrasonographic, and biochemical markers with histopathological examination findings of ovarian masses in women diagnosed with ovarian masses. Duration of the study will be 2023–2024 of period.
The study population will consist of women of any age who have been diagnosed with ovarian masses. These women will be recruited from the patient population attending a rural hospital or clinics that serve as a primary healthcare centre for the surrounding rural community.
The current research will be conducted at the Department of Obstetrics and Gynecology within the rural hospital setup of Datta Meghe Institute of Higher Education and Research (DMIHER).
Female participants of any age group who meet the following criteria will be eligible for inclusion in the study:
History of pressure symptoms. History of dysfunctional menstrual bleeding. Ovarian pathology, including dermoid, endometriosis, or malignancies. Incidental ultrasound imaging findings of ovarian masses. Willingness to participate in the study.
Participants will be excluded from the study if they meet any of the following criteria:
Ovarian masses with acute abdomen, such as rupture or torsion. Participants with pelvic masses who have undergone cystectomy of ovarian cysts. Pre-existing co-morbidities like uncontrolled/overt Diabetes mellitus, uncontrolled hypertension, and pre-existing tuberculosis. Participants who are not willing to participate in the study.
The data collection process for the correlational study on the correlation of clinical, ultrasonographic, and biochemical markers with histopathological findings of various ovarian masses in a rural hospital setup will involve a systematic approach to gather relevant information from the study participants. Here is a detailed description of the data collection process:
The sample size for this study will be determined using a formula that considers various factors including specificity (Spec), alpha (A), estimation error (e), and prevalence (prev) as follows:
Where:
z
2 is the critical value for a two-tailed test at a significance level of alpha (A). Spec is the estimation of specificity. e is the estimation error (10% or 0.1). prev is the prevalence (8.4 per 100,000 or 0.0084).
Additionally, we must consider practical aspects related to patient recruitment, follow-up, and potential loss to follow-up. Based on these practical considerations:
The number of women with ovarian masses presenting at the rural hospital setup as new patients is estimated to be 5-7 per month. Since the study duration is 24 months, the potential number of participants for the entire study period is 5-7 participants per month * 24 months = 120 participants. It is estimated that there may be a 30% loss due to factors like follow-up loss, non-consenting patients due to the rural hospital setup, and loss due to non-fulfilment of pre-operative fitness for surgery. Additionally, it is expected that 10% of patients may be lost due to advanced disease that does not allow surgical intervention or due to economic constraints preventing them from affording the operation.
Considering the above factors, the current sample size for this study is estimated to be approximately 60 participants.
The statistical methods employed in this study encompass a multifaceted approach to data analysis. To begin with, descriptive statistics will be used to provide an informative summary of the study population’s characteristics, including measures such as mean, standard deviation, median, interquartile range, and percentages. This will offer an essential overview of demographic and clinical features. Moreover, correlation analysis will play a pivotal role in this research, examining the relationships between various variables. This will involve calculating correlation coefficients, utilizing the Pearson correlation for linear associations and the Spearman’s rank correlation for non-linear connections. Additionally, a rigorous sample size calculation formula will be applied, factoring in parameters like specificity, alpha, estimation error, and prevalence. Statistical software packages like SPSS version 23 will be harnessed for data analysis, facilitating data manipulation, hypothesis testing, and generating comprehensive statistical reports.
The Institutional Ethics Committee of Datta Meghe Institute of Higher Education and Research (DU) has granted its approval to the study protocol (Reference number: DMIHER (DU)/IEC/2022/105. Date:21-07-2022). Prior to commencing the study, we will obtain written informed consent from all participants, providing them with a comprehensive explanation of the study’s objectives.
After the completion of the study, we will publish in an indexed journal or conferences.
The study has not yet started after publication of protocol we will start recruitment in the study.
The management of ovarian masses remains a complex and critical aspect of women’s healthcare, and this study protocol focuses on unravelling the intricate web of clinical, ultrasonographic, and biochemical markers in correlation with histopathological findings in a rural hospital setting.
The findings of this study are expected to hold implications for both diagnosis and patient care. Early diagnosis of ovarian masses is vital for timely and appropriate interventions, which can significantly impact patient outcomes. The clinical evaluation, ultrasonography, and biochemical markers collectively contribute to the identification of suspicious masses and help in triaging patients. The role of CA 125 has been widely discussed in the literature. CA 125 has been suggested as a potential biomarker for ovarian cancer, although it is known to have limitations in specificity. Therefore, its integration with other markers is of interest in improving diagnostic accuracy and differentiating benign from malignant masses.
Ultrasonography is an indispensable tool in characterizing ovarian masses and determining their potential malignancy. It is recognized that ultrasound findings, such as size, vascularity, and echotexture, play a crucial role in the risk stratification of these masses. The Risk of Malignancy Index (RMI) and International Ovarian Tumor Analysis (IOTA) criteria, which will be applied in this study, are established methods for refining the diagnosis and assisting in the decision-making process regarding the management of ovarian masses.
The histopathological examination remains the gold standard for confirming the characteristics and nature of ovarian masses. It provides definitive information regarding benign or malignant nature, which guides clinical decisions. This alignment between imaging and pathology has been emphasized as essential for high-quality patient care and surgical planning.
The rural healthcare context introduces unique challenges, such as limited access to specialized diagnostic tools and expertise. These challenges are critical as delayed diagnosis and intervention can result in adverse outcomes. Rural healthcare disparities have been well-documented, highlighting the need for research to bridge these gaps.
To address these challenges, the study protocol emphasizes not only the diagnostic aspects but also the ethical considerations, ensuring informed consent and privacy protection for the participants. Additionally, the sample size estimation considers both statistical and practical considerations to ensure that the study is adequately powered to draw meaningful conclusions.
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