Elsevier

Annals of Oncology

Volume 30, Issue 9, September 2019, Pages 1507-1513
Annals of Oncology

Original articles
Statistics and trial methodology
Are we assuming too much with our statistical assumptions? Lessons learned from the ALTTO trial

https://doi.org/10.1093/annonc/mdz195Get rights and content
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Abstract

Background

Design, conduct, and analysis of randomized clinical trials (RCTs) with time to event end points rely on a variety of assumptions regarding event rates (hazard rates), proportionality of treatment effects (proportional hazards), and differences in intensity and type of events over time and between subgroups.

Design and methods

In this article, we use the experience of the recently reported Adjuvant Lapatinib and/or Trastuzumab Treatment Optimization (ALTTO) RCT, which enrolled 8381 patients with human epidermal growth factor 2-positive early breast cancer between June 2007 and July 2011, to highlight how routinely applied statistical assumptions can impact RCT result reporting.

Results and conclusions

We conclude that (i) futility stopping rules are important to protect patient safety, but stopping early for efficacy can be misleading as short-term results may not imply long-term efficacy, (ii) biologically important differences between subgroups may drive clinically different treatment effects and should be taken into account, e.g. by pre-specifying primary subgroup analyses and restricting end points to events which are known to be affected by the targeted therapies, (iii) the usual focus on the Cox model may be misleading if we do not carefully consider non-proportionality of the hazards. The results of the accelerated failure time model illustrate that giving more weight to later events (as in the log rank test) can affect conclusions, (iv) the assumption that accruing additional events will always ensure gain in power needs to be challenged. Changes in hazard rates and hazard ratios over time should be considered, and (v) required family-wise control of type 1 error ≤ 5% in clinical trials with multiple experimental arms discourages investigations designed to answer more than one question.

Trial Registration

clinicaltrials.gov Identifier NCT00490139.

Key words

proportional hazards
stopping boundaries
accelerated failure time models
power
family-wise type 1 error
early breast cancer

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