Development and Validation of a Risk Prediction Model for Mortality Using Nomogram Among the Chinese Older Adults

Abstract

Background: Rapid population ageing is a worldwide trend, highlighting an urgent need to have a reliable prediction tool for estimating a general older adult mortality risk. Previous predictive models have limited by the cause mortality, clinical indexes, participants as young as 50 years old, and western countries. We aimed to develop and validate a all-cause mortality prediction model based on multidimensional risk factors in Chinese older adults. Methods: In three prospective cohorts, we used the Chinese Longitudinal Healthy Longevity Survey (CLHLS) (mean age 88.08, n=37074) as the derivation cohort and the Healthy Ageing and Biomarkers Cohort Study (HABCS) (mean age 86.74, n=2552) and the China Health and Retirement Longitudinal Study (CHARLS) (mean age 72.48, n=4794) as validation cohorts. 42 risk factors were filtered by Lasso regression. The predictive factors of final models were decided by both improved net reclassification improvement (NRI) and public health significance. Cox proportional hazards models were established the mortality risk prediction equations. Model fit was evaluated by discrimination C-statistic. We conducted the 10x10 cross-validation technique to evaluate the internal consistency of the discrimination and calibration performance. Calibration plots were shown the results by comparing the predicted probabilities with the observed probabilities. The prediction ability of the equation was illustrated by using Nomogram. Findings: During 20-year follow-up, 28158 older adults (76%) died, leading to a total of 101429 person-years of observation in the CLHLS. The final model for all-cause mortality included age, sex, cognitive status, ADL status, current spouse status, past smoke status, frequency of doing housework, frequency of reading and watching TV, and frequency of doing garden work. The C statistic of derivation Cohort was 0.728 (96%CI, 0.724,0.732), and external validation were 0.761 (96%CI, 0.749,0.773) in HABCS and 0.713 (96%CI, 0.697,0.729) in CHARS. Interpretation: This study provides an objective, validated, and acceptable predictive factors to predict mortality risk in Chinese older adults. Our finding suggest that these predictive factors could be useful for policy, epidemiological and clinical applications. Funding Information: This work was supported by the fund of “San-ming” Project of Medicine in Shenzhen (NO.SZSM201812088) for data collection and analysis. Declaration of Interests: None. Ethics Approval Statement: The Protection of Human Subjects for the CLHLS, HACBS and CHARLS were approved by the biomedical ethics committee of Peking university. The written informed consent was provided by survey respondents before investigation.