On the Use of the Accelerated Failure Time Model as an Alternative to the Proportional Hazards Model in the Treatment of Time to Event Data: A Case Study in Influenza

Abstract

The accelerated failure time model is presented as an alternative to the proportional hazards model in the analysis of time to event data. A case study in influenza looking at the time to resolution of influenza symptoms is used to illustrate these considerations. The proportional hazards model displays significant lack of fit while the accelerated failure time model describes the data well. From a clinical perspective the accelerated failure time model in this and other applications is seen to be a more appropriate modeling framework and has the added advantage of being easier to interpret. It is concluded that the accelerated failure time model should be considered as an alternative to the proportional hazards model in the analysis of time to event data, especially in applications where the effects of treatment are to accelerate (or delay) the event of interest with no permanent effect in the context of the follow-up period.