Role of Sensitivity Analyses in Assessing Progression-Free Survival in Late-Stage Oncology Trials

• Published in: Journal of clinical oncology Vol. 27; no. 35; pp. 5958 - 5964
• Main Authors: Bhattacharya, Suman, Fyfe, Gwen, Gray, Robert J., Sargent, Daniel J.
• Format: Journal Article
• Language: English
• Published: United States American Society of Clinical Oncology 10.12.2009
• Subjects: Bias; Clinical Trials, Phase III as Topic - statistics & numerical data; Data Interpretation, Statistical; Disease Progression; Disease-Free Survival; Endpoint Determination; Humans; Neoplasms - mortality; Neoplasms - therapy; Research Design - statistics & numerical data; Time Factors; Treatment Outcome
• ISSN: 0732-183X; 1527-7755; 1527-7755
• DOI: 10.1200/JCO.2009.22.4329

Sensitivity analysis is an important statistical technique that assesses whether the results of phase III trials are robust and likely to be generalizable. Until recently, sensitivity analyses were rarely included in phase III trials, and they remain poorly understood by many oncologists. Sensitivity analyses are critical to understanding the strength of conclusions made in the primary analysis of a late-stage clinical trial. They examine the influence of protocol design errors, unintended biases, deviations from assumptions underlying statistical models, and any unanticipated treatment delivery or practice patterns on trial results. In trials with complex or subjective end points, they also allow an understanding of the extent to which a positive outcome is driven by a single, possibly subjective, and therefore biased, element of an end point. The purposes of this article are to explain how sensitivity analyses are performed, to discuss areas of a clinical trial where sensitivity analyses should focus, and to illuminate the importance of this technique in the rigorous evaluation of late-stage clinical trial data, using specific examples. This article focuses on late-stage trials that use progression-free survival or time to progression as their primary end point, because sensitivity analyses are particularly important in these cases for which the end point is potentially subject to bias. Three sources of potential bias are explored: assessment time, symptomatic (ie, nonradiologic) disease progression, and missing data. For each source of potential bias, case studies are presented to highlight the role that sensitivity analyses play in determining whether the trial's conclusions are robust.