Nomogram to Predict Cycle-One Serious Drug-Related Toxicity in Phase I Oncology Trials
Cette étude évalue la performance d'un nomogramme, développé à partir des données de 127 essais incluant au total 3 104 patients atteints d'une tumeur solide, pour prédire le risque de toxicité sévère associée à un cycle de traitement médicamenteux dans le cadre d'essais cliniques de phase I
Purpose : All patients in phase I trials do not have equivalent susceptibility to serious drug-related toxicity (SDRT). Our goal was to develop a nomogram to predict the risk of cycle-one SDRT to better select appropriate patients for phase I trials.
Patients and Methods : The prospectively maintained database of patients with solid tumor enrolled onto Cancer Therapeutics Evaluation Program–sponsored phase I trials activated between 2000 and 2010 was used. SDRT was defined as a grade ≥ 4 hematologic or grade ≥ 3 nonhematologic toxicity attributed, at least possibly, to study drug(s). Logistic regression was used to test the association of candidate factors to cycle-one SDRT. A final model, or nomogram, was chosen based on both clinical and statistical significance and validated internally using a bootstrapping technique and externally in an independent data set.
Results : Data from 3,104 patients enrolled onto 127 trials were analyzed to build the nomogram. In a model with multiple covariates, Eastern Cooperative Oncology Group performance status, WBC count, creatinine clearance, albumin, AST, number of study drugs, biologic study drug (yes v no), and dose (relative to maximum administered) were significant predictors of cycle-one SDRT. All significant factors except dose were included in the final nomogram. The model was validated both internally (bootstrap-adjusted concordance index, 0.60) and externally (concordance index, 0.64).
Conclusion : This nomogram can be used to accurately predict a patient’s risk for SDRT at the time of enrollment. Excluding patients at high risk for SDRT should improve the safety and efficiency of phase I trials.
Journal of Clinical Oncology , résumé, 2014