Value of External Data in the Extrapolation of Survival Data: A Study Using the NJR Data Set.

BACKGROUND: Extrapolation of time-to-event data can be a critical component of cost-effectiveness analysis. OBJECTIVES: To contrast the value of external data on treatment effects as a selection aid in model fitting to the clinical data or for the direct extrapolation of survival. METHODS: We assume the existence of external summary data on both treatment and control and consider two scenarios: availability of external individual patient data (IPD) on the control only and an absence of external IPD. We describe how the summary data can be used to extrapolate survival or to assess the plausibility of extrapolations of the clinical data. We assess the merit of either approach using a comparison of cemented and cementless total hip replacement as a case study. Merit is judged by comparing incremental net benefit (INB) obtained in scenarios with incomplete IPD with that derived from modeling external IPD on both treatment and control. RESULTS: Measures of fit with the external summary data did not identify survival model specifications that best estimated INB. Addition of external IPD for the control only did not improve estimates of INB. Extrapolation of survival using the external summary data comparing treatment and control improved estimates of INB. CONCLUSIONS: Our case study indicates that summary data comparing treatment and control are more valuable than IPD limited to the control when extrapolating event rates for cost-effectiveness analysis. These data are best exploited in direct extrapolation of event rates rather than as an aid to select extrapolations on the basis of the clinical data.