Efficacy and Safety of PARP Inhibitor Therapy in Advanced Ovarian Cancer: A Systematic Review and Network Meta-analysis of Randomized Controlled Trials


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Abstract

Aims:This study aims to evaluate the efficacy and safety of PARP inhibitor therapy in advanced ovarian cancer and identify the optimal treatment for the survival of patients.

Background:The diversity of PARP inhibitors makes clinicians confused about the optimal strategy and the most effective BRCAm mutation-based regimen for the survival of patients with advanced ovarian cancer.

Objectives:The objective of this study is to compare the effects of various PARP inhibitors alone or in combination with other agents in advanced ovarian cancer.

Methods:PubMed, Embase, Cochrane Library, and Web of Science were searched for relevant studies on PARP inhibitors for ovarian cancer. Bayesian network meta-analysis was performed using Stata 15.0 and R 4.0.4. The primary outcome was the overall PFS, and the secondary outcomes included OS, AE3, DISAE, and TFST.

Results:Fifteen studies involving 5,788 participants were included. The Bayesian network metaanalysis results showed that olaparibANDAI was the most beneficial in prolonging overall PFS and non-BRCAm PFS, followed by niraparibANDAI. However, for BRCAm patients, olaparibTR might be the most effective, followed by niraparibANDAI. Olaparib was the most effective for the OS of BRCAm patients. AI, olaparibANDAI, and veliparibTR were more likely to induce grade 3 or higher adverse events. AI and olaparibANDAI were more likely to cause DISAE.

Conclusion:PARP inhibitors are beneficial to the survival of patients with advanced ovarian cancer. The olaparibTR is the most effective for BRCAm patients, whereas olaparibANDAI and niraparibANDAI are preferable for non-BRCAm patients.

Other:More high-quality studies are desired to investigate the efficacy and safety of PARP inhibitors in patients with other genetic performances.

About the authors

Juying Chen

Department of Pharmacy, Guangzhou Concord Cancer Center

Author for correspondence.
Email: info@benthamscience.net

Xiaozhe Wu

Department of Pharmacy, Guangzhou Concord Cancer Center

Email: info@benthamscience.net

Hongzhe Wang

Department of Oncology, Shanghai Jiahui International Hospital

Email: info@benthamscience.net

Xiaoshan Lian

Department of Pharmacy, Shenzhen New Frontier United Family Hospital

Email: info@benthamscience.net

Bing Li

Department of Pharmacy, Guangzhou Concord Cancer Center

Email: info@benthamscience.net

Xiangbo Zhan

Department of Gynecology, Guangzhou Concord Cancer Center

Email: info@benthamscience.net

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