Analysis of Drug Clinical Trials in Obstetrics and Gynecology: A Five-Year Retrospective Study from a Public Tertiary Specialty Hospital in China

Summary

The current protocol aims to systematically outline the scope, current trends, and treatment focus of interventional drug clinical trials in obstetrics and gynecology at the leading tertiary hospitals in China, and to identify gaps in women's health research and guide the equitable prioritization of further trials.

Abstract

Women remain underrepresented in clinical drug development despite their unique biological characteristics and growing disease burden. In China, this disparity is particularly concerning given the rising incidence of gynecologic conditions such as uterine cancer. This study examined the profile and trends of obstetrics and gynecology (OBGYN) drug trials conducted at a large tertiary specialty hospital in China. A retrospective review of interventional drug trials registered between 2019 and 2023 was conducted using data from the Chinese Clinical Trial Registry (ChiCTR) and the hospital’s Clinical Trial Management System. All eligible trials conducted at the Women’s Hospital, School of Medicine, and Zhejiang University were included. Information on trial design, year of initiation, clinical specialty, drug category, and primary indication was extracted and analyzed descriptively. A total of 59 interventional drug trials were identified. The trial volume increased from 4 studies in 2019 to 11 in 2023, representing 176% growth. Most trials were domestic multicenter studies (68%), and 71% remained ongoing at the end of 2023. Gynecologic oncology accounted for the largest proportion of trials (44%), followed by gynecology (29%). Ovarian cancer was the leading oncologic indication, while endometriosis and assisted reproduction were the most common benign conditions studied. Antibody–drug conjugates, poly(ADP-ribose) polymerase (PARP) inhibitors, and programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors predominated in oncology trials, whereas hormonal and microbial therapies were more common in non-oncologic studies. OBGYN drug research in China has expanded substantially, with a strong focus on gynecologic cancers and chronic gynecologic conditions. However, maternal health-related drug development remains limited. Continued and systematic monitoring of ChiCTR data may help support more balanced and equitable research priorities across women’s health.

Introduction

Women experience various sex-specific gynecological conditions, including endometriosis, ovarian cancer, cervical cancer, and vaginal diseases^1,2, which require consideration of disease-specific pathophysiology and therapeutic factors in clinical trial design³. The occurrence, course, and prognosis of these diseases can be quite different from those dominating in men, highlighting the historical limitations of extrapolating findings from predominantly male-based clinical research to women-specific health conditions and therapeutic responses. Such biological differences have significant impacts on pharmacokinetics, pharmacodynamics, and drug response, hence, influence drug absorption, distribution, metabolism, efficacy, and adverse event patterns^4,5.

Among biological factors, numerous other factors affect international clinical trials, including genetics, environment, and diet across various populations; the healthcare system; the regulatory environment; and institutional research capabilities. Variability in genetic makeup, disease rates, and medication intake is a significant cause of differences in the risk-benefit profile of therapies, and hence the need for area-specific clinical trial outcomes⁶. Although international trial registries can provide general information about the performance of clinical research, they may lack verification of trial status, specialty-level detail, and a precise description of site-level participation. This means that analyses based on the registry could misclassify the trial's progress, overestimate activity, or fail to reflect institutional research priorities.

This research fills a methodological gap by providing results from a single-site, cross-verified portfolio analysis of interventional drug trials based on both public trial registries and an institutional Clinical Trial Management System (CTMS). A tertiary specialized women’s hospital was selected because these institutions function as major referral and research centers for complex gynecologic, oncologic, reproductive, and obstetric conditions, and therefore represent key sites for women’s health drug development and clinical trial activity in China. The single-center focus enables accurate validation of dimensions such as trial status, leadership, specialty distribution, and therapeutic focus that cannot be reliably captured in registry-only studies. Cross-verification of CTMS helps correct irregularities in trial activity, completion, and departmental allocation, thereby improving data accuracy and interpretability.

The primary justification for the analysis is to benchmark institutional clinical trial activity, identify therapeutic- and specialty-level prioritization, and define temporal trends in drug development in women's health. The proposed study provides an empirically based overview of the changing clinical research environment at one of the largest tertiary obstetrics and gynecology hospitals in China by systematically investigating trial volume, indications, drug classes, and department distribution. The results should be helpful for strategic planning, resource allocation, and prioritizing future trials in women-oriented clinical research.

The primary objective of this study was to systematically characterize the profile, temporal trends, therapeutic focus, and specialty distribution of interventional drug clinical trials conducted in obstetrics and gynecology at a large tertiary women’s hospital in China between 2019 and 2023. We hypothesized that the institutional trial portfolio would show increasing concentration in gynecologic oncology and chronic gynecologic conditions, with comparatively limited representation of maternal health therapeutics.

Protocol

This study involved secondary analysis of de-identified, publicly available registry data and institutional administrative records. In accordance with institutional guidelines and national regulations, the Ethics Committee of the Women's Hospital, School of Medicine, Zhejiang University, waived ethical approval, as the study did not involve human participants, identifiable personal data, or interventional procedures. A formal waiver reference number was not issued for this study.

Study design and data sources
A retrospective review of interventional drug trials registered between 2019 and 2023 was conducted. The analysis period was restricted to trials registered by December 31, 2023, because this was the latest year for which complete registry and institutional CTMS verification were available during data extraction and analysis. Two complementary data sources were used:

1. The National Drug Clinical Trial Registration and Information Disclosure Platform (ChiCTR), which serves as China's official registry for interventional drug trials. In 2013, the National Medical Products Administration introduced the official national registry platform (http://www.chinadrugtrials.org.cn), which requires all interventional clinical trials in China to be registered in accordance with the WHO Trial Registration Data Set⁷.
2. The institutional Clinical Trial Management System (CTMS), which provides lifecycle monitoring of trials conducted at the Women's Hospital, School of Medicine, Zhejiang University (https://gcp.womanhospital.cn). This system records project initiation, project execution milestones, project monitoring activities, regulatory submissions, and final archiving, enabling specific time and status tracking⁸.

Data retrieval from ChiCTR and CTMS was initially conducted by the lead investigator using predefined search criteria and institutional identifiers. To improve reliability, a randomly selected subset of extracted records and classifications was independently verified by a second reviewer. Discrepancies regarding trial status, timelines, or institutional participation were resolved through manual review of archival records and consultation with a senior investigator.

Stage 1: ChiCTR platform screening
The advanced search function of ChiCTR was used to identify interventional drug trials for which the Women's Hospital, School of Medicine, Zhejiang University was listed as a participating institution. The search was restricted to records registered between 2013 and 2023. Information extracted included trial identifier, first public posting date, primary completion date, sponsor, phase, intervention type, target condition, and recruitment status. This was done to ensure that all drug trials registered with the regulator were exhaustively identified⁹.

Stage 2: CTMS cross-verification and temporal alignment
Trials identified through ChiCTR were cross-verified using institutional CTMS records. The CTMS trial creation date was used to represent trial initiation, whereas the trial archiving date represented study completion or termination. For trials conducted before 2019, paper records were manually reviewed to determine the on-site completion date. Trials were excluded if they were completed before 2019 or registered on or after January 1, 2024. This cross-verification procedure ensured the accuracy of timelines and minimized misclassification of trial activity phases. The overall process of trial identification, screening, CTMS cross-verification, eligibility assessment, and final inclusion is summarized in Supplementary Figure 1.

In CTMS records, “completed” trials were defined as studies that fulfilled the planned recruitment, follow-up, and archival procedures in accordance with protocol requirements, whereas “terminated” trials were discontinued before planned completion due to administrative, sponsor-related, operational, or recruitment-related reasons.

Data extraction:
A standardized data extraction form and predefined coding manual were developed before data collection to ensure consistency across variables and data sources. Initial extraction was performed by the lead investigator, and a randomly selected subset of extracted variables was independently verified by a second reviewer as part of quality-control procedures.

Extracted variables were standardized and compiled into a structured Excel database, and included: 1) temporal metrics, including trial initiation and completion dates; 2) trial scope and status, including multicenter participation and institutional role; and (3) therapeutic information, including drug category, target disease or condition, and specialty department. These variables were selected to characterize temporal trends, specialty distribution, and the therapeutic focus of the institutional drug trial portfolio.

Data processing and quality control
Variable definitions, classification rules, and missing data handling
To ensure reproducibility and transparency, a predefined variable dictionary and explicit classification rules were applied consistently across both data sources (ChiCTR and CTMS) (Supplementary Table 1). Investigational therapies were categorized according to their primary pharmacologic mechanism and therapeutic class using Anatomical Therapeutic Chemical (ATC)-aligned classification principles and investigator consensus review.

Missing data assessment
Missingness was quantified for all key analytical variables. There were no missing data for trial identification number, specialty department, or trial scope. Variables with incomplete information were documented during data cleaning and verification procedures.

Data cleaning
ChiCTR identifiers were used as the primary keys to identify and remove duplicate records. Records with missing or inconsistent temporal information (e.g., trial initiation or completion dates) were identified by comparing the ChiCTR and CTMS datasets. These records were subsequently verified using archived institutional documentation, including trial initiation forms, regulatory correspondence, monitoring reports, and study closure records. When sufficient documentation was available, the missing dates were corrected and updated in the analytical database; otherwise, the original record was retained and flagged for review. A review was conducted for outliers (more than 3 standard deviations from the project duration median). These procedures were implemented to improve the integrity, completeness, and reliability of the dataset in accordance with best practices for retrospective observational research¹⁰.

Quality assurance
To improve reliability, 20% of the included trials were randomly selected using computer-generated random sampling for independent validation of extracted variables and trial classifications by a second reviewer. Inter-rater agreement between reviewers was excellent (Cohen’s κ = 0.92), indicating a very high level of classification consistency. Discrepancies were resolved through consultation with a senior investigator.

Statistical analysis
Descriptive statistics were used to summarize the trial portfolio over five years. The analytical domains and portfolio metrics evaluated in this study are summarized in Table 1. The analytical domains evaluated in this study included: (1) trial volume and distribution, including annual trial volume, specialty distribution, multicenter participation, institutional role, and trial status; (2) therapeutic focus, including drug classes and disease indications; and (3) temporal trends in annual trial initiation.

Trend analysis
annual trial volume over time, with corresponding 95% confidence intervals. Descriptive statistics were used to summarize trial characteristics, specialty distribution, therapeutic focus, multicenter participation, institutional role, and trial status. The analysis was performed using SPSS v27.0.¹¹ and R v4.3.2¹².

Reporting guidelines:
This study is reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies. A completed STROBE checklist indicating the location of each recommended item in the manuscript is provided as Supplementary Table 2.

Results

Analysis of drug clinical trials conducted at Women's Hospital, School of Medicine, Zhejiang University, from January 1, 2019, to December 31, 2023, identified a total of 59 projects. These comprised 40 domestic multicenter trials (68%) and 19 international multicenter trials (32%). The hospital served mainly as a participating site (57, 97%). By December 31, 2023, 42 trials were ongoing (Table 2). Formal subgroup comparisons between ongoing and completed trials were not performed due to the limited samp...

Discussion

This descriptive portfolio analysis summarizes 59 interventional drug clinical trials conducted at a tertiary obstetrics and gynecology hospital in China over five years. Although the limited sample size limits the strength of the inference, the results provide a validated institutional picture of women's health-oriented drug development and demonstrate how registry data, when cross-validated with institutional Clinical Trial Management Systems (CTMS), can be used to benchmark trials and strategize.

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Chinese Clinical Trial Registry (ChiCTR) – Drug Clinical Trial Registration and Information Publicity Platform	http://www.chinadrugtrials.org.cn	National Medical Products Administration (NMPA), China	Used to identify registered drug clinical trials and obtain trial registration information for data extraction
Hospital Clinical Trial Management System (CTMS)	https://gcp.womanhospital.cn	Women’s Hospital, School of Medicine, Zhejiang University	Used to retrieve clinical trial records, monitor study progress, and verify trial-related information.
IBM SPSS Statistics for Windows, Version 27.0	Version 27.0	IBM Corp., Armonk, NY, USA	Used for descriptive statistics, linear regression, and χ² analysis
Microsoft Excel	Microsoft365 Excel	Microsoft Corporation	Used for standardized data extraction, variable coding, and data organization
R Statistical Software	Version 4.3.2	R Foundation for Statistical Computing, Vienna, Austria	Used for statistical analysis and trend modeling
STROBE Statement Checklist	https://www.strobe-statement.org/	EQUATOR Network	Reporting guideline for cross-sectional observational studies