David M. Hyman, Anne A. Eaton, Mrinal M. Gounder, Erika G. Pamer, Martee L. Hensley, David R. Spriggs, and Alexia Iasonos, Memorial Sloan-Kettering Cancer Center; David M. Hyman, Mrinal M. Gounder, Martee L. Hensley, David R. Spriggs, and Alexia Iasonos, Weill Cornell Medical College, New York, NY; and Gary L. Smith and Percy Ivy, National Cancer Institute, Bethesda, MD.
J Clin Oncol. 2014 Feb 20;32(6):519-26. doi: 10.1200/JCO.2013.49.8808. Epub 2014 Jan 13.
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.
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.
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).
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.
并非所有接受 I 期临床试验的患者对严重药物相关毒性(SDRT)具有同等易感性。我们的目标是开发一种列线图来预测周期 I SDRT 的风险,以便更好地选择适合 I 期临床试验的患者。
使用前瞻性维护的 2000 年至 2010 年间参加癌症治疗药物评估计划赞助的 I 期临床试验的实体瘤患者数据库。SDRT 定义为归因于研究药物的至少可能的 4 级血液学毒性或 3 级以上非血液学毒性。使用逻辑回归检验候选因素与周期 I SDRT 的相关性。最终模型或列线图基于临床和统计学意义进行选择,并通过内部 bootstrap 技术验证,在外部独立数据集进行验证。
对 127 项试验中纳入的 3104 名患者的数据进行分析以构建列线图。在多变量模型中,东部肿瘤协作组表现状态、白细胞计数、肌酐清除率、白蛋白、天冬氨酸转氨酶、研究药物数量、生物研究药物(是与否)和剂量(相对于最大给药量)是周期 I SDRT 的显著预测因子。除剂量外,所有显著因素均包含在最终的列线图中。该模型通过内部(bootstrap 调整后的一致性指数,0.60)和外部(一致性指数,0.64)验证。
该列线图可用于在入组时准确预测患者发生 SDRT 的风险。排除 SDRT 风险高的患者应提高 I 期临床试验的安全性和效率。