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The proportional hazards (PH) model is commonly used to measure the between-group difference under the assumption that the ratio of the two hazard function is constant over time. When this assumption is met, hazard ratio estimate gives useful and easy interpretable estimate to measure the difference between the two survival curves. The question is how to decide if the underlying PH assumption is violated (i.e the hazard ratio is not constant over time) and once the PH assumption is not met, what is the best option beyond proportional hazards? In a recent analysis of PACMEL, a three arm randomised controlled trial with time to event outcomes, we were met with concerns over whether the hazards were proportional. This motivated me to share the experience of our investigation into the methods of assessing proportionality and the options for non-proportional hazards.


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