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Updated: Sep 5, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Within trial comparison of survival time projections from short-term follow-up with long-term follow-up findings
João Pedro Ferreira1,2, Brian L Claggett3, Kieran F Docherty2
1INSERM, Centre d'Investigations Cliniques-1433, INI CRCT, INSERM U1116, CHRU Nancy, Université de Lorraine, Nancy, France.
Aims:
Data on long-term treatment effects are scarce, despite the intent to use new therapies for many years and the need of patients, physicians and payers to have a better understanding of the lifetime benefits of treatments. The restricted mean or median survival time (RMST) calculated using age instead of time, hypothetically enables estimation of long-term gain in event-free or overall survival from the short-term (within-trial) effects of an intervention, compared with its control. Tha aim of the study is to use trials with long-term follow-up available through extension studies to compare the long-term projections estimated using RMST from within-trial follow-up data with the actual long-term outcomes in the extension studies.
Methods And Results:
We estimated the median long-term survival time using age instead of follow-up time and compared these model-based projections with the actual long-term estimates in the (i) SCD-HeFT trial vs. SCD-HeFT long-term outcomes; (ii) SOLVD trial vs. SOLVD 12 year follow-up; (iii) STICH trial vs. STICHES; and (iv) ACCORD study vs. ACCORDION. In the long-term follow-up of SCD-HeFT, gain in survival with ICD vs. placebo over a median of 11.0 years was +1.4 years of life. The RMST model-derived survival projection from the within-trial data (median follow-up of 3.4 years) gave an estimated survival gain of +1.2 years. In STICHES, over a median follow-up of 9.8 years, coronary artery bypass grafting (CABG) vs. medical care led to a survival extension of +1.4 years in favour of CABG. RMST projections using within-trial data from STICH (median follow-up of 4.9 years), gave an extended survival of +2.4 years in favour of CABG in younger patients. In the long-term follow-up of SOLVD, enalapril vs. placebo led to a survival gain of +0.8 years over a median follow-up of 12.1 years. The RMST projections from the within-trial data (median follow-up of 2.8 years) gave a survival extension of +0.3 years in favour of enalapril. In the long-term follow-up ACCORDION study, with a median follow-up of 8.8 years, intensive vs. a standard anti-hyperglycaemic treatment did not influence long-term survival, which was concordant with the RMST projections from the short-term ACCORD study with median follow-up of 4.9 years.
Conclusions:
Age-based survival projections using within-trial data generally provided concordant results with the actual survival measured in long-term follow-up extension studies. Our findings suggest that age-based lifetime projections may be used as means to assess the long-term treatment effects.
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