Development and Validation of a Clinical Prediction Model for Paclitaxel Hypersensitivity Reaction on the Basis of Real-World Data: Pac-HSR Score

PURPOSEPaclitaxel is effective chemotherapy against various cancers but can cause hypersensitivity reaction (HSR). This study aimed to identify predictors associated with paclitaxel HSR and develop a clinical prediction model to guide clinical decisions.METHODSData were collected from the medical records database of Rajavithi Hospital. Patients with cancer treated with paclitaxel from 2015 to 2022 were included, and a multivariable logistic regression analysis identified predictors associated with paclitaxel HSR. The scoring system was transformed and calibrated on the basis of diagnostic parameters. Discrimination and calibration performances were assessed. Internal validation was conducted using bootstrap resampling with 1,000 replications.RESULTSThis study involved 3,708 patients with cancer, with an incidence of paclitaxel HSR of 10.11%. An 11-predictor-based Pac-HSR scoring system was developed, involving the following factors: younger age; poor Eastern Cooperative Oncology Group performance status; previous history of paclitaxel HSR; medication allergy history; chronic obstructive airway disease; lung and cervical cancers; high actual dose of paclitaxel; no diphenhydramine premedication; low hemoglobin level; high WBC count; and high absolute lymphocyte count. The C-statistics was 0.73 (95% CI, 0.70 to 0.76), indicating acceptable discrimination. The P value of the Hosmer-Lemeshow goodness-of-fit test was 0.751. The ratio of observed and expected values was 1.00, indicating good calibration. At a cutoff point of 8, specificity was 75.28% and sensitivity was 57.07%. Internal validation indicated good performance with minimal bias, and decision curve analysis demonstrated improved prediction with the use of this scoring system in clinical decision making.CONCLUSIONThis study developed the 11-predictor-based Pac-HSR scoring system for predicting paclitaxel HSR in patients with cancer. High-risk patients identified by this score should be prioritized for close monitoring and early treatment prophylaxis.