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Poster session 12

1868P - Development and validation of a clinical prediction model for paclitaxel hypersensitivity reaction: Pac-HSR score

Date

14 Sep 2024

Session

Poster session 12

Topics

Supportive Care and Symptom Management

Tumour Site

Presenters

Radasar Sukphinetkul

Citation

Annals of Oncology (2024) 35 (suppl_2): S1077-S1114. 10.1016/annonc/annonc1612

Authors

R. Sukphinetkul, S. Sa-nguansai, S. Payapwattanawong, P. Tienchaiananda, K. Maneenil

Author affiliations

  • Oncology Unit, Department Of Medicine, Rajavithi Hospital, College of Medicine, Rangsit University, 10400 - Bangkok/TH

Resources

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Abstract 1868P

Background

Paclitaxel is effective chemotherapy against various cancers but can cause hypersensitivity reaction (HSR), ranging from mild to life-threatening condition. Identifying predictors for paclitaxel HSR is crucial for patient management. This study aimed to identify predictors associated with paclitaxel HSR and develop a clinical prediction model to guide a clinical decision.

Methods

Data were retrospectively collected from the medical records database. Cancer patients treated with paclitaxel at Rajavithi Hospital from 2015 to 2022 were included. A multivariable logistic regression analysis identified predictors associated with paclitaxel HSR. The scoring system was transformed and calibrated based on diagnostic parameters. Discrimination and calibration performances were assessed using concordance (C) statistic, Hosmer-Lemeshow goodness-of-fit test, and observed and expected values (O/E) ratio. Internal validation was conducted using bootstrap resampling with 1,000 replications.

Results

The analysis involved 3,708 cancer patients, with an incidence of paclitaxel HSR at 10.11%. An 11-predictor-based Pac-HSR scoring system was developed including, younger age, poor ECOG performance status, previous history of paclitaxel HSR, medication allergy history, chronic obstructive airway disease, lung and cervical cancer, high actual dose of paclitaxel, no diphenhydramine premedication, low hemoglobin (Hb) level, high white blood cell (WBC) count, and high absolute lymphocyte count (ALC). The C-statistics was 0.73 (95% CI: 0.70 – 0.76), indicating acceptable discrimination. The p-value of the Hosmer-Lemeshow goodness-of-fit test was 0.751, and the O/E ratio was 1.00, indicating good calibration. At a cut-off point of 8, specificity was 75.28% and sensitivity was 57.07%. Internal validation indicated good performance with the minimal bias. Decision curve analysis demonstrated improved prediction of paclitaxel HSR with the use of this scoring system in clinical decision-making.

Conclusions

This study developed the Pac-HSR scoring system for predicting paclitaxel HSR in cancer patients. High-risk patients based on this score should be prioritized for close monitoring and early treatment prophylaxis.

Clinical trial identification

(Research No. 66138, REC No. 171/2566).

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

Rajavithi Hospital, College of Medicine, Rangsit University.

Disclosure

All authors have declared no conflicts of interest.

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