Effectiveness and Safety of Niraparib as First-line Maintenance Therapy for Ovarian Cancer: a Real-world Study

Overview

In order to explore the real situation of niraparib in clinical application more comprehensively and deeply, we conducted the first multicenter, real-world study in China. This large observational study used real-world data to assess the effectiveness and safety of niraparib as maintenance therapy in patients with advanced ovarian cancer (AOC) in China and investigated clinical factors associated with prolonged benefits of niraparib so as to achieve the maximum clinical benefit of patients.

This is a retrospective multicentric study including advanced ovarian cancer patients that have used niraparib as first-line maintenance therapy after chemotherapy from fourteen hospitals in China between January 2019 and December 2021. The database lock-time was on December 31, 2022. All data were retrieved from the patients' medical records. Clinical data, including patient demographics, clinicopathological characteristics, residual disease after primary surgery, genetic-testing results and so on, were collected. Missing information was supplemented by telephone follow-up or face-to-face inquiries (only for patients who were alive and accessible). The incidence of AEs, as well as dose reductions, dose interruption, and discontinuation of treatment due to AEs were recorded.All analyses were performed on the safety population. The categorical variables were described as a frequency and percentage, and the continuous variables were described as a median and range. No formal sample size calculation was performed since the study was exploratory. Survival analyses were conducted using the Kaplan-Meier method and log-rank test. 95% confidence intervals (CIs) were calculated using the Clopper-Pearson method. Univariate and multivariate Cox regression models were established to determine factors that could affect the PFS for patients receiving niraparib maintenance treatment. Missing data were assigned as unknown for the univariate and multivariate analysis. The method of cox analysis was stepwise regression, and the screening criterion was Akaike Information Criterion (AIC). A P-value of \<0.05 was considered statistically significant. Descriptive statistics (number and percentage) were used to summarize the safety data by treatment. Statistical analyses were performed using the R software version 4.2.2 (R Project for Statistical Computing).

Conditions

Interventions

Eligibility

Locations (1)

Outcomes