Early Trial Discontinuation in Toxicity-Driven, Dose-Escalating, Phase I Cancer Trials: Occurrence, Outcomes and Predict
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ORIGINAL RESEARCH ARTICLE
Early Trial Discontinuation in Toxicity-Driven, Dose-Escalating, Phase I Cancer Trials: Occurrence, Outcomes and Predictive Factors Sophie Cousin1 • Philippe A. Cassier2 • Carlos Gomez-Roca3 • Nicolas Isambert4 • Nuria Kotecki-Borghesi1 • Sylvie Zanetta4 • Louis Tassy2 • Anne-Laure Simonet-Lamm4 • Eleonora De Maio3 • Catherine Terret2 • Juliette Bouchet3 • Jean-Pierre Delord3 • Nicolas Penel1,5 Published online: 20 October 2015 Ó Springer International Publishing Switzerland 2015
Abstract Introduction The selection of patients for phase I cancer trials remains challenging. Patients who dropout of the trial before completion need to be replaced and this can result in significant delays to trial completion. Objective The objective of this study was to identify patients enrolled in phase I oncology trials who were unable to complete the minimum evaluation period of the trial, and to use these data to develop a predictive model of risk factors for patient replacement. Patients and Methods We retrospectively reviewed all consecutive patients who were enrolled in dose-escalating
This work was presented in part at the 50th American Society of Clinical Oncology (ASCO) Annual Meeting, Chicago, IL, USA, from 30 May to 2 June 2014 (abstract no. 3035). & Nicolas Penel [email protected]; [email protected] 1
Medical Oncology Department, Centre Oscar Lambret, 3, rue F Combemale, 59020 Lille Cedex, France
2
Medical Oncology Department, Centre Le´on Be´rard, Lyon, France
3
Medical Oncology Department, Institut Claudius Regaud, Toulouse, France
4
Medical Oncology Department, Centre Georges-Franc¸ois Leclerc, Dijon, France
5
Clinical Research and Methodological Platform of SIRIC OncoLille Consortium, Research Unit EA2694, Lille-Nordde-France University, Medical School, Lille, France
phase I cancer trials at four medical centers in France between May 2003 and May 2013. Replacement was defined as trial discontinuation before 6 weeks, without the occurrence of dose-limiting toxicity. Using logistic regression and decision-tree analyses, we developed a predictive model to identify patients who were at high risk for replacement, and also their common risk factors. This model was designed to provide maximum specificity and a negative predictive value. Results Of 332 patients enrolled in the study, 16 had to be replaced (4.8 %). The median overall survival time was 45 days for the patients who were replaced versus 480 days for the patients who were not replaced (p \ 0.0001). In the univariate analysis, the risk factors for replacement included Eastern Cooperative Oncology Group performance status (ECOG-PS) = 2 [odds ratio (OR) 11], Royal Marsden Score (RMS) = 3 (OR 29), and enrollment in a study investigating multiple agents (OR 7). Multivariate analysis retained PS C2 and RMS = 3 as independent predictive factors for replacement. The following two patient subgroups were identified: low risk of replacement (RMS B2 and PS B1) and high risk of replacement (RMS = 3 or PS C2). The rates of replace
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