AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (1.4 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Article | Open Access

Progression-Free Survival with PARP Inhibitors According to Clinical Risk in Patients with Ovarian Cancer: An Indirect Comparison Using Reconstructed Data

Lorenzo Gasperoni1( )Luna Del Bono2Alberto Farolfi3Andrea Messori4,5Vera Damuzzo5,6
Pharmaceutical Department, USL Toscana Centro, Prato, Italy
Department of Pharmacy, School of Specialization in Hospital Pharmacy, University of Pisa, Pisa, Italy
Medical Oncology, Breast & GYN Unit, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, Meldola, Italy
HTA Unit, Regional Health Service, Firenze, Italy
Italian Society of Clinical Pharmacy and Therapeutics (SIFaCT), Torino, Italy
Hospital Pharmacy Department, Azienda Ulss 2 Marca Trevigiana, Treviso, Italy
Show Author Information

Abstract

Background

Poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi) are established maintenance treatments in ovarian cancer, but comparative efficacy across genetic profiles and relapse risk categories remains unclear. The aim of this study was to compare the efficacy of different PARPi as maintenance therapy in ovarian cancer across genetic profiles and relapse risk categories using reconstructed individual patient data (IPD) from randomized trials (RCTs).

Methods

IPD were reconstructed using the IPDfromKM method from published Kaplan-Meier curves of RCTs stratified by clinical risk subgroup. Progression-free survival (PFS) was the primary endpoint. Three comparisons were performed: Breast Cancer gene (BRCA)+ high-risk, Homologous Recombination Deficiency (HRD)+/BRCAwt high-risk, and BRCA+ low-risk populations. Restricted Mean Survival Time (RMST) was calculated as a supplementary measure, with curves truncated at 66 months.

Results

In the BRCA+ high-risk population, olaparib monotherapy (median PFS 41.2 months) and olaparib plus bevacizumab (median PFS 42.5 months) demonstrated the greatest PFS benefit, marginally outperforming niraparib (median PFS 31.2 months). RMST analysis showed a 14-month advantage for olaparib plus bevacizumab over bevacizumab alone. In the HRD+/BRCAwt high-risk population, olaparib plus bevacizumab and niraparib showed comparable efficacy, with no statistically significant inter-treatment difference. In the BRCA+ low-risk population, olaparib plus bevacizumab showed superior HR versus olaparib monotherapy, without reaching statistical significance. RMST analysis also indicated an advantage of 8.5 months for the combination, though this did not reach statistical significance.

Conclusions

PARPi treatment benefit in ovarian cancer is meaningfully influenced by genetic profile and relapse risk, supporting biomarker-driven treatment selection in clinical practice.

References

【1】
【1】
 
 
Oncology Research
Article number: 14

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Gasperoni L, Del Bono L, Farolfi A, et al. Progression-Free Survival with PARP Inhibitors According to Clinical Risk in Patients with Ovarian Cancer: An Indirect Comparison Using Reconstructed Data. Oncology Research, 2026, 34(7): 14. https://doi.org/10.32604/or.2026.077700

13

Views

0

Downloads

0

Crossref

0

Web of Science

0

Scopus

Received: 15 December 2025
Accepted: 21 April 2026
Published: 16 June 2026
© The Author 2026.

This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.