A Validation Study of the Rank-Preserving Structural Failure Time Model: Confidence Intervals and Unique, Multiple, and Erroneous Solutions

Med Decis Making. 2018 May;38(4):509-519. doi: 10.1177/0272989X18765175. Epub 2018 Apr 1.

Abstract

Background: The rank-preserving structural failure time model (RPSFTM) is used for health technology assessment submissions to adjust for switching patients from reference to investigational treatment in cancer trials. It uses counterfactual survival (survival when only reference treatment would have been used) and assumes that, at randomization, the counterfactual survival distribution for the investigational and reference arms is identical. Previous validation reports have assumed that patients in the investigational treatment arm stay on therapy throughout the study period.

Objectives: To evaluate the validity of the RPSFTM at various levels of crossover in situations in which patients are taken off the investigational drug in the investigational arm.

Methods: The RPSFTM was applied to simulated datasets differing in percentage of patients switching, time of switching, underlying acceleration factor, and number of patients, using exponential distributions for the time on investigational and reference treatment.

Results: There were multiple scenarios in which two solutions were found: one corresponding to identical counterfactual distributions, and the other to two different crossing counterfactual distributions. The same was found for the hazard ratio (HR). Unique solutions were observed only when switching patients were on investigational treatment for <40% of the time that patients in the investigational arm were on treatment.

Limitations: Distributions other than exponential could have been used for time on treatment.

Conclusions: An HR equal to 1 is a necessary but not always sufficient condition to indicate acceleration factors associated with equal counterfactual survival. Further assessment to distinguish crossing counterfactual curves from equal counterfactual curves is especially needed when the time that switchers stay on investigational treatment is relatively long compared to the time direct starters stay on investigational treatment.

Keywords: G-estimation method; RPSFTM; hazard ratio; health technology assessment; rank-preserving structural failure time model; treatment switching.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antineoplastic Agents / therapeutic use
  • Confidence Intervals
  • Cross-Over Studies
  • Data Interpretation, Statistical
  • Humans
  • Models, Statistical
  • Neoplasms / drug therapy
  • Proportional Hazards Models*
  • Research Design*
  • Survival Analysis
  • Technology Assessment, Biomedical / methods*

Substances

  • Antineoplastic Agents