topic JMP > Proportional Hazard with Continuous parameter > Cutoff Optimization in Discussions

JMP > Proportional Hazard with Continuous parameter > Cutoff Optimization

Thierry_S — Thu, 08 Jun 2023 16:27:32 GMT

Hi JMP Community,

JMP 16.1 Standard

Windows

This might be a naive question. I am exploring the impact of a continuous baseline variable on the survival of subjects using the Proportional Hazard platform. I identified some factors with strong associations (see one example below), but I am still determining how to visualize this relationship.

For example, I can create a survival plot if I create arbitrary sub-groups using the median as cutoff point (see below). However, this approach does not take into account the actual optimal cutoff point of the continuous variable.

Hence, I am looking for an approach to estimate this cutoff point for all identified parameters. Beside a brute-force bootstrap approach (cycling through likely cutoffs), I could not find a more elegant approach to this apparent simple problem (Yes, I read the documentation for the platform).

Any input would be greatly appreciated.

Please, feel free to let me know if my question is misguided.

Thank you.

Best,

Re: JMP > Proportional Hazard with Continuous parameter > Cutoff Optimization

Mark_Bailey — Mon, 20 Mar 2023 14:29:12 GMT

Have you considered a profiler on the fitted model? I see that the Proportional Hazard platform cannot save a prediction formula, and it does not provide a profiler either. Can you use the Parametric Survival platform? If so, it provides both features.

Re: JMP > Proportional Hazard with Continuous parameter > Cutoff Optimization

winfriedkoch0 — Mon, 20 Mar 2023 17:33:13 GMT

I support the proposal by Mark as I use this proceding very often by myself. At this occasion I would appreciate if the Parametric Survival Platform of JMP would provide risk ratios in addition as the majority of parametric survival functions implemented fulfil the proportional hazards assumption.

Winfried

Re: JMP > Proportional Hazard with Continuous parameter > Cutoff Optimization

Thierry_S — Tue, 21 Mar 2023 13:50:01 GMT

Hi JMP Team,

I decided to adopt the brute-force approach by developing a short script that iterates in 50 steps through a range of cutoffs between the 25th and 75th percentiles of the variable on interest. For each cutoff, I run the Proportional Hazard platform on the dichotomized variable of interest, recording the test performance. The optimized cutoff is then set to the value that maximizes the test performance.

Best,