ArticleJournal of ovarian research2026
Exploring the optimal cutoff point and genomic characteristics for PARP inhibitor maintenance therapy in early recurrence of ovarian cancer.
Article in Journal of ovarian research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundOvarian cancer is the deadliest gynecological malignancy. The advent of poly-adenosine diphosphate ribose polymerase (PARP) inhibitors has transformed the treatment paradigm for ovarian cancer, significantly improving survival outcomes. However, some patients inevitably experience disease recurrence during maintenance therapy with PARP inhibitor. Currently, there is no established definition for early recurrence with PARP inhibitor.
methodsThis retrospective study analyzed ovarian cancer patients who received first-line PARP inhibitor maintenance therapy between March 2020 and April 2024. The optimal cutoff point for early recurrence was calculated using the maximally selected rank statistic. The logistic regression was employed to evaluate risk factors for early recurrence. Targeted sequencing of 437 cancer-related genes was performed on 37 ovarian cancer samples.
resultsAmong the 174 enrolled patients, 59 (33.9%) experienced recurrence. The optimal cutoff point for defining early recurrence was 11.37 months (median progression-free survival [PFS], 9.0 vs. not reached [NR], P < 0.001). For clinical convenience, this cutoff point was defined as 12 months. High-risk predictors for early recurrence included receiving neoadjuvant chemotherapy, maximal cytoreductive surgery with residual disease, and not achieving complete response (CR) to chemotherapy. Patients with early recurrence exhibit frequent mutations in MTOR, SMARCB1 and ZNF217, and have a higher tumor mutational burden (TMB).
conclusionsAccording to the results of this study, the optimal cutoff point for defining early recurrence was 12 months. Identifying high-risk predictors for early recurrence can facilitate prognosis stratification and guide treatment decisions.
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