Analysis of progression-free survival in oncology trials: some common statistical issues.
With the advent of ever more effective second and third line cancer treatments and the growing use of 'crossover' trial designs in oncology, in which patients switch to the alternate randomized treatment upon disease progression, progression-free survival (PFS) is an increasingly important endpoint in oncologic drug development. However, several concerns exist regarding the use of PFS as a basis to compare treatments. Unlike survival, the exact time of progression is unknown, so progression times might be over-estimated and, consequently, bias may be introduced when comparing treatments. Further, it is not uncommon for randomized therapy to be stopped prior to progression being documented due to toxicity or the initiation of additional anti-cancer therapy; in such cases patients are frequently not followed further for progression and, consequently, are right-censored in the analysis. This article reviews these issues and concludes that concerns relating to the exact timing of progression are generally overstated, with analysis techniques and simple alternative endpoints available to either remove bias entirely or at least provide reassurance via supportive analyses that bias is not present. Further, it is concluded that the regularly recommended manoeuvre to censor PFS time at dropout due to toxicity or upon the initiation of additional anti-cancer therapy is likely to favour the more toxic, less efficacious treatment and so should be avoided whenever possible.
Carroll
Kevin J
KJ
AstraZeneca Pharmaceuticals, Global Clinical Information Science, Alderley Park, Macclesfield, UK. kevin.carroll2@astrazeneca.com
D000970:Antineoplastic Agents / Q000009:adverse effects / Q000627:therapeutic use; D018572:Disease-Free Survival; D006801:Humans; D009369:Neoplasms / Q000188:drug therapy*; D016032:Randomized Controlled Trials as Topic
D000970:Antineoplastic Agents