JMIR Publications

ABSTRACT

Background:

Predicting serious hematological adverse events from poly (ADP-ribose) polymerase inhibitors (PARPis) would allow us to prioritize ovarian cancer patients at higher risk for more intensive care, ultimately lowering the morbidity and preventing them from premature termination of medication.

Objective:

To explore the risk factors for serious hematological adverse events in ovarian cancer patients receiving PARPis treatment and to develop a risk prediction model for it.

Methods:

Prospective clinical data was collected on ovarian cancer patients who received PARPis treatment at Guangxi Medical University Affiliated Tumor Hospital from December 2018 to August 2024. Divided into SAEs group and non-SAEs group based on the occurrence of serious hematological adverse events. Variable differences were screened using the x2 test or Fisher’s exact test. Multivariate logistic regression was employed to determine independent factors influencing serious hematological adverse events in ovarian cancer patients. A predictive model for serious blood-related complications in ovarian cancer treatment was developed from identified independent risk factors using R software. Evaluate the clinical net benefit, calibration ability and predictive ability of the model using the decision curve, calibration curve and receiver operating characteristic (ROC) curve respectively.

Results:

70 ovarian cancer patients receiving PARPis treatment were included in this study. Among them, 16 patients experienced serious hematological adverse events, with decreases in RBC and Hb being the most common. Multiple logistic regression's findings revealed that lymph node metastasis [OR=0.149, 95% CI (0.026, 0.835), P=.03], Ccr≤60 ml/min [OR=0.042, 95% CI (0.006, 0.320), P=.002], RBC≤3.3×1012/L [OR=0.206, 95% CI (0.043, 0.981), P=.047] and combination therapy with VEGF inhibitors [OR=0.148, 95% CI (0.029, 0.762), P=.02] were independent influencing factors for PARPis serious hematological adverse events in ovarian cancer patients. With an area under the ROC curve of 0.874 (95% CI: 0.793-0.955), the internal validation of the risk prediction model constructed using these criteria indicates that it has great clinical benefits and accuracy.

Conclusions:

Lymph node metastasis, Ccr≤60 ml/min, RBC≤3.3×1012/L, and combination therapy with VEGFis are independent risk factors for PARPis serious hematological adverse events in ovarian cancer patients. The risk prediction model established based on these factors demonstrates good predictive value.