Characteristics and potential predictors of prematurely terminated interventional clinical trials for ovarian cancer in the ClinicalTrials.gov database

Given the high heterogeneity and low therapeutic responsiveness of ovarian cancer, there are unique challenges and barriers to successfully completing clinical trials. However, little is known about the status of trial completion and termination in this field. This study aimed to evaluate the landscape of completed and prematurely terminated trials in ovarian cancer and to assess the reasons and potential predictors associated with termination. We conducted a cross-sectional analysis of interventional clinical trials for ovarian cancer registered on ClinicalTrials.gov between 2003 and 2022. Characteristics were compared between terminated and completed trials using χ2 or Fisher’s exact tests. The associations with termination were determined using logistic regression, with model performance assessed through a receiver operating characteristic curve and the Hosmer–Lemeshow goodness-of-fit test. A total of 1420 interventional clinical trials for ovarian cancer were included, of which 294 (20.70%) were prematurely terminated. Terminations were more frequent in drug/biological (89.46%), phase 2 (57.14%), parallel (34.01%), and single-center (41.84%) trials and had a larger median planned sample size (median 56, IQR 36–100). A small portion of trials were terminated due to futility of efficacy (19.39%) and safety issues (6.80%). Conduct- or logistical-related reasons accounted for 58.50% of the terminations, and the reasons for 15.31% were unknown. A multivariable analysis identified that phase 2 (OR 1.50, 95% CI 1.04–2.14), a parallel design (OR 2.14, 95% CI 1.31–3.51), and a larger planned sample size (versus Q1: Q2: OR 1.78, 95% CI 1.11–2.84; Q3: OR 2.22, 95% CI 1.38–3.57; Q4: OR 2.19, 95% CI 1.24–3.87) increased the risk of premature termination. Meanwhile, multicenter trials reduced the risk (OR 0.31, 95% CI 0.21–0.47). The termination rate of interventional clinical trials for ovarian cancer was high, mainly due to conduct-related or logistical issues rather than efficacy or safety concerns. The planned sample size, trial phase, number of centers and interventional group design were associated with termination. The reasons and predictors for termination should be considered during trial design and planning according to the type of cancer, thereby increasing the likelihood of trial completion and facilitating the best available care for patients.