Population-based estimates of age and comorbidity specific life expectancy: a first application in Swedish males

Mieke Van Hemelrijck,Eugenio Ventimiglia,Hans Garmo,Rolf Gedeborg,Lars Holmberg,David Robinson,Pär Stattin

doi:10.1186/s12911-022-01766-0

Abstract

IntroductionFor clinical decision-making, an estimate of remaining lifetime is needed to assess benefit against harm of a treatment during the remaining lifespan. Here, we describe how to predict life expectancy based on age, Charlson Comorbidity Index (CCI) and a Drug Comorbidity Index (DCI), whilst also considering potential future changes in CCI and DCI using population-based data on Swedish men.MethodsSimulations based on annual updates of vital status, CCI and DCI were used to estimate life expectancy at population level. The probabilities of these transitions were determined from generalised linear models using prostate cancer-free comparison men in PCBaSe Sweden. A simulation was performed for each combination of age, CCI, and DCI. Survival curves were created and compared to observed survival. Life expectancy was then calculated as the area under the simulated survival curve.ResultsThere was good agreement between observed and simulated survival curves for most ages and comorbidities, except for younger men. With increasing age and comorbidity, there was a decrease in life expectancy. Cross-validation based on six regions in Sweden also showed that simulated and observed survival was similar.ConclusionOur proposed method provides an alternative statistical approach to estimate life expectancy at population level based on age and comorbidity assessed by routinely collected information on diagnoses and filled prescriptions available in nationwide health care registers.

Highlights

For clinical decision-making, an estimate of remaining lifetime is needed to assess benefit against harm of a treatment during the remaining lifespan
The effect of Charlson Comorbidity Index (CCI) and Drug Comorbidity Index (DCI) on death was decreasing with age and we modelled the interaction between age and CCI/DCI as using a quadratic-constant spline (QCS) with cut-point 100 years
Similar increases in CCI and DCI were observed during increasingly long follow-up (Fig. 1)

Summary

Introduction

For clinical decision-making, an estimate of remaining lifetime is needed to assess benefit against harm of a treatment during the remaining lifespan. For clinical decision-making, an estimate of remaining lifetime is needed to weigh the benefit of a specific treatment against its the potential harm during the remaining lifespan. Some new approaches have been presented to calculate comorbidity-adjusted life expectancy [2, 4, 5] This methodology is usually based on the use of flexible parametric or semi-parametric models or a static baseline assessment of comorbidity levels [4, 6], and may overestimate life expectancy as these models can only be applied to periods for which data is available, without taking into account comorbidity changes during follow-up [1]. We propose to use life tables for each level of age and comorbidity and allow this to change during follow-up by use of a state transition model [7]

Methods

Results

Discussion

Conclusion