TY - JOUR
T1 - Nomogram to predict cycle-one serious drug-related toxicity in phase I oncology trials
AU - Hyman, David M.
AU - Eaton, Anne A.
AU - Gounder, Mrinal M.
AU - Smith, Gary L.
AU - Pamer, Erika G.
AU - Hensley, Martee L.
AU - Spriggs, David R.
AU - Ivy, Percy
AU - Iasonos, Alexia
PY - 2014/2/20
Y1 - 2014/2/20
N2 - 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.
AB - 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.
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U2 - 10.1200/JCO.2013.49.8808
DO - 10.1200/JCO.2013.49.8808
M3 - Article
C2 - 24419130
AN - SCOPUS:84898545465
SN - 0732-183X
VL - 32
SP - 519
EP - 526
JO - Journal of Clinical Oncology
JF - Journal of Clinical Oncology
IS - 6
ER -