A correlational study to determine the correlation of clinical, ultrasonographic and biochemical markers with histopathological findings of various ovarian masses in rural hospitals

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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. Methods 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. Expected outcome 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. " } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/13-351", "name": "A correlational study to determine the correlation of clinical, ultrasonographic..." } } ] } Home Browse A correlational study to determine the correlation of clinical, ultrasonographic... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Sahu S and Shrivastava D. A correlational study to determine the correlation of clinical, ultrasonographic and biochemical markers with histopathological findings of various ovarian masses in rural hospitals [version 1; peer review: awaiting peer review] . F1000Research 2024, 13 :351 ( https://doi.org/10.12688/f1000research.144055.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Study Protocol A correlational study to determine the correlation of clinical, ultrasonographic and biochemical markers with histopathological findings of various ovarian masses in rural hospitals [version 1; peer review: awaiting peer review] Shreya Sahu https://orcid.org/0009-0005-8731-7979 1 , Deepti Shrivastava 1 Shreya Sahu https://orcid.org/0009-0005-8731-7979 1 , Deepti Shrivastava 1 PUBLISHED 23 Apr 2024 Author details Author details 1 Obstetrics and Gynaecology, Datta Meghe Institute of Higher Education and Research, Wardha, 442001, India Shreya Sahu Roles: Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing Deepti Shrivastava Roles: Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing OPEN PEER REVIEW REVIEWER STATUS AWAITING PEER REVIEW This article is included in the Datta Meghe Institute of Higher Education and Research collection. Abstract Background 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. Methods 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. Expected outcome 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. READ ALL READ LESS Keywords Ovarian masses, Histopathological findings, Ultrasonographic markers, Clinical correlation, Rural healthcare, Diagnostic accuracy Corresponding Author(s) Shreya Sahu ( [email protected] ) Close Corresponding author: Shreya Sahu Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2024 Sahu S and Shrivastava D. 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: Sahu S and Shrivastava D. A correlational study to determine the correlation of clinical, ultrasonographic and biochemical markers with histopathological findings of various ovarian masses in rural hospitals [version 1; peer review: awaiting peer review] . F1000Research 2024, 13 :351 ( https://doi.org/10.12688/f1000research.144055.1 ) First published: 23 Apr 2024, 13 :351 ( https://doi.org/10.12688/f1000research.144055.1 ) Latest published: 23 Apr 2024, 13 :351 ( https://doi.org/10.12688/f1000research.144055.1 ) Introduction 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. 1 However, in resource-constrained rural hospital setups, unique challenges often affect the diagnostic and prognostic processes. 2 Ovarian masses are a diverse group of lesions, ranging from benign cysts to malignant tumours, each necessitating a distinct diagnostic and therapeutic approach. 3 The early identification and accurate characterization of these masses are paramount in determining the most suitable treatment strategies. In this rural hospital setting, the study endeavours to address the need for improved diagnostic accuracy through a comprehensive analysis of clinical, ultrasonographic, and biochemical markers, coupled with the gold standard of histopathological examination. 4 This investigation holds particular significance given the unique patient demographics, healthcare infrastructure, and resource limitations characteristic of rural areas. 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. Aim 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. Objectives 1. To assess the clinical features of ovarian masses amongst women attending a rural hospital setup. 2. 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). 3. To interpret the value of CA 125 among study participants. 4. To confirm histopathologically the characteristics and features of ovarian masses amongst study participants. 5. To correlate and analyse different clinical, ultrasonographic, biochemical, and histopathological features of ovarian masses amongst study participants. Methods Study design 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. Study population 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. Place of study 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). Inclusion criteria Female participants of any age group who meet the following criteria will be eligible for inclusion in the study: 1. History of pressure symptoms. 2. History of dysfunctional menstrual bleeding. 3. Ovarian pathology, including dermoid, endometriosis, or malignancies. 4. Incidental ultrasound imaging findings of ovarian masses. 5. Willingness to participate in the study. Exclusion criteria Participants will be excluded from the study if they meet any of the following criteria: 1. Ovarian masses with acute abdomen, such as rupture or torsion. 2. Participants with pelvic masses who have undergone cystectomy of ovarian cysts. 3. Pre-existing co-morbidities like uncontrolled/overt Diabetes mellitus, uncontrolled hypertension, and pre-existing tuberculosis. 4. Participants who are not willing to participate in the study. Bias 1. Selection bias: As the study population is drawn from a single rural hospital setup, there may be limitations in obtaining a representative sample of women with ovarian masses. This could lead to selection bias, and the study findings may not be fully generalizable to the broader population of women with similar conditions. Efforts should be made to ensure that the study sample is as diverse and representative as possible to minimize the impact of selection bias on the study’s validity. 2. Information bias: The accuracy and completeness of the clinical, ultrasonographic, and biochemical data may be subject to information bias. Data collection methods should be standardized and validated to minimize this type of bias. Outcome 1. Correlation of clinical features: The study aims to identify and correlate clinical features in women with ovarian masses. The outcome will provide information about the most common clinical symptoms associated with these masses, which can aid in early diagnosis and timely intervention. 2. Ultrasonographic findings: The evaluation of ultrasonographic findings, including the application of Risk of Malignancy Index (RMI) 5 and International Ovarian Tumor Analysis (IOTA), 6 is expected to enhance the accuracy of differentiating between benign and malignant ovarian masses. 3. CA 125 levels: The interpretation of CA 125 levels among study participants will help in understanding the role of this biochemical marker in the assessment of ovarian masses. 7 4. Histopathological confirmation: Histopathological examination is the gold standard for confirming the characteristics and features of ovarian masses. The study’s outcome will provide accurate diagnoses and help in distinguishing between different types of ovarian masses, such as dermoid, endometriosis, and malignancies. 5. Correlation and analysis: The primary objective of this study is to establish correlations and analyse the relationship between clinical, ultrasonographic, biochemical, and histopathological features. The outcome will provide valuable data on how these factors interrelate, potentially leading to a more comprehensive understanding of ovarian masses and their management. 6. Clinical relevance: The study’s findings can have significant clinical relevance. They may help healthcare providers in rural hospital settings make informed decisions regarding the diagnosis and treatment of ovarian masses, thus improving patient care. 7. Enhanced diagnostic tools: The study may contribute to the development of a diagnostic framework that combines clinical, ultrasonographic, and biochemical markers to enhance the accuracy and efficiency of diagnosing ovarian masses. 8. Patient outcomes: Ultimately, the study’s results may lead to better patient outcomes by facilitating early detection of ovarian masses, enabling timely surgical intervention when needed, and improving the overall management of these conditions in rural hospital settings. 9. Reduced healthcare costs: If the study shows that a combination of clinical, ultrasonographic, and biochemical markers can lead to more accurate diagnoses, it may lead to cost savings by reducing unnecessary diagnostic procedures and surgeries. Data collection process 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: Patient recruitment: Potential study participants will be identified among women attending the rural hospital or clinics affiliated with Datta Meghe Institute of Higher Education and Research (DMIHER). Participants will be approached by the research team and informed about the study. Informed consent will be obtained from those willing to participate. Clinical evaluation: A thorough clinical evaluation of each participant will be conducted. This will include a detailed medical history, physical examination, and assessment of clinical symptoms related to ovarian masses. Data will be collected on pressure symptoms, dysfunctional menstrual bleeding, and other relevant clinical features. Ultrasonography: Participants with suspected ovarian masses will undergo ultrasonographic examination. This examination will assess the characteristics of the ovarian masses, including size, location, vascularity, and echotexture. Risk of Malignancy Index (RMI) and International Ovarian Tumor Analysis (IOTA) criteria will be applied to evaluate and score ultrasonographic findings. Biochemical investigations: Blood samples will be collected from participants for the measurement of CA 125 levels. CA 125 is a biochemical marker often associated with ovarian masses. The levels will be analyzed in the laboratory. Preoperative workup: Prior to any surgical intervention, participants will undergo a preoperative workup to assess their fitness for surgery. This may include evaluating their general health, cardiovascular status, and any other factors that may influence the surgical outcome. Histopathological evaluation: For participants undergoing surgery (laparoscopically or via open access), a tissue section of the ovarian mass will be collected during the procedure. These tissue samples will be sent to the laboratory for histopathological examination. The examination will confirm the diagnosis and provide detailed information about the characteristics of the ovarian masses, including whether they are benign or malignant. Data recording: All data collected during the clinical evaluation, ultrasonography, biochemical investigations, and histopathological examination will be carefully recorded in a structured database. Data will include demographic information, clinical features, ultrasonographic findings, CA 125 levels, and histopathological results. Quality control: Quality control measures will be in place to ensure the accuracy and consistency of data collection. This may include regular training and calibration of personnel involved in data collection. Data analysis: Once data collection is complete, the collected data will be subjected to statistical analysis. This analysis will involve using appropriate statistical tests, such as Pearson correlation, to explore the relationships between clinical, ultrasonographic, biochemical, and histopathological variables. Ethical considerations: Throughout the data collection process, ethical principles will be strictly adhered to, including obtaining informed consent from participants, ensuring confidentiality, and safeguarding the privacy of the participants. Sample size calculation 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: Sample size N = z 2 ∗ Spec 1 − Spec / e 2 ∗ 1 − prev 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: 1. The number of women with ovarian masses presenting at the rural hospital setup as new patients is estimated to be 5-7 per month. 2. 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. 3. 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. 4. 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. Statistical methods 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. Ethical considerations 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. Dissemination After the completion of the study, we will publish in an indexed journal or conferences. Study status The study has not yet started after publication of protocol we will start recruitment in the study. Discussion 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. 8 The study design and its objectives are framed against the backdrop of a healthcare scenario marked by resource limitations, making the exploration of these markers more significant. 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. 9 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. 10 , 11 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. 12 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. 13 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. Data availability No data are associated with this article. References 1. Vanderpuye VD, Clemenceau JRV, Temin S, et al. : Assessment of Adult Women With Ovarian Masses and Treatment of Epithelial Ovarian Cancer: ASCO Resource-Stratified Guideline. JCO Glob. Oncol. 2021; 7 : 1032–1066. PubMed Abstract | Publisher Full Text | Free Full Text 2. Anticona Huaynate CF, Pajuelo Travezaño MJ, Correa M, et al. : Diagnostics barriers and innovations in rural areas: insights from junior medical doctors on the frontlines of rural care in Peru. BMC Health Serv. Res. 2015; 15 : 454. PubMed Abstract | Publisher Full Text | Free Full Text 3. Ovarian cyst - Causes. nhs.uk.2018. Accessed: May 15, 2023. Reference Source Reference Source 4. Subramanian S, Mallia MB, Shinto AS, et al. : Clinical Management of Liver Cancer in India and Other Developing Nations: A Focus on Radiation Based Strategies. Oncol. Ther. 2021; 9 : 273–295. PubMed Abstract | Publisher Full Text | Free Full Text 5. Appendix: Risk of malignancy index (RMI I)|Ovarian cancer: recognition and initial management|Guidance|NICE: 2011. Accessed: October 18, 2023. Reference Source 6. Bullivant E: (Radiology): The International Ovarian Tumour Analysis (IOTA) criteria. 7. Charkhchi P, Cybulski C, Gronwald J, et al. : CA125 and Ovarian Cancer: A Comprehensive Review. Cancers (Basel). 2020; 12 : 3730. PubMed Abstract | Publisher Full Text | Free Full Text 8. Ionescu CA, Matei A, Navolan D, et al. : Correlation of ultrasound features and the Risk of Ovarian Malignancy Algorithm score for different histopathological subtypes of benign adnexal masses. Medicine (Baltimore). 2018; 97 : e11762. PubMed Abstract | Publisher Full Text | Free Full Text 9. Bast RC, Feeney M, Lazarus H, et al. : Reactivity of a monoclonal antibody with human ovarian carcinoma. J. Clin. Invest. 1981; 68 : 1331–1337. PubMed Abstract | Publisher Full Text | Free Full Text 10. Timmerman D, Testa AC, Bourne T, et al. : Logistic regression model to distinguish between the benign and malignant adnexal mass before surgery: a multicenter study by the International Ovarian Tumor Analysis Group. J. Clin. Oncol. 2005; 23 : 8794–8801. PubMed Abstract | Publisher Full Text 11. Jacobs I, Oram D, Fairbanks J, et al. : A risk of malignancy index incorporating CA 125, ultrasound and menopausal status for the accurate preoperative diagnosis of ovarian cancer. Br. J. Obstet. Gynaecol. 1990; 97 : 922–929. PubMed Abstract | Publisher Full Text 12. Kinkel K, Lu Y, Mehdizade A, et al. : Indeterminate ovarian mass at US: incremental value of second imaging test for characterization--meta-analysis and Bayesian analysis. Radiology. 2005; 236 : 85–94. PubMed Abstract | Publisher Full Text 13. Vaseghi F, Yarmohammadian MH, Raeisi A: Interprofessional Collaboration Competencies in the Health System: A Systematic Review. Iran. J. Nurs. Midwifery Res. 2022; 27 : 496–504. PubMed Abstract | Publisher Full Text | Free Full Text Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 23 Apr 2024 ADD YOUR COMMENT Comment Author details Author details 1 Obstetrics and Gynaecology, Datta Meghe Institute of Higher Education and Research, Wardha, 442001, India Shreya Sahu Roles: Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing Deepti Shrivastava Roles: Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (1) version 1 Published: 23 Apr 2024, 13:351 https://doi.org/10.12688/f1000research.144055.1 Copyright © 2024 Sahu S and Shrivastava D. 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