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Please use this identifier to cite or link to this item:
http://ir.nhri.org.tw/handle/3990099045/15676
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| Title: | Develop and validate a prognostic index with laboratory tests to predict mortality in middle-aged and older adults using machine learning models: A prospective cohort study |
| Authors: | Huang, CH;Fang, YH;Zhang, S;Wu, IC;Chuang, SC;Chang, HY;Tsai, YF;Tseng, WT;Wu, RC;Liu, YT;Lien, LM;Juan, CC;Tange, C;Otsuka, R;Arai, H;Hsu, CC;Hsiung, CA |
| Contributors: | Institute of Population Health Sciences |
| Abstract: | BACKGROUND: Prognostic indices can enhance personalized predictions of health burdens. However, a simple, practical and reproducible tool is lacking for clinical use. This study aimed to develop a machine learning-based prognostic index for predicting all-cause mortality in community-dwelling elderly individuals. METHODS: We utilized the Healthy Aging Longitudinal Study in Taiwan (HALST) cohort, encompassing data from 5,663 participants. Over the 5-year follow-up, 447 deaths were confirmed. A machine learning-based routine blood examination prognostic index (MARBE-PI) was developed using common laboratory tests based on machine learning techniques. Participants were grouped into multiple risk categories by stratum-specific likelihood ratios analysis based on their MARBE-PI scores. The MARBE-PI was subsequently externally validated with an independent population-based cohort from Japan. RESULTS: Beyond age, sex, education level and BMI, six laboratory tests (LDL, albumin, AST, lymphocyte count, hsCRP, and creatinine) emerged as pivotal predictors via stepwise logistic regression for 5-year mortality. The AUCs of MARBE-PI constructed by logistic regression were 0.799 (95% CI: 0.778-0.819) and 0.756 (95% CI: 0.694-0.814) for the internal and external validation datasets, and were 0.801 (95% CI: 0.790-0.811) and 0.809 (95% CI: 0.774-0.845) for the extended 10-year mortality in both datasets, respectively. Risk categories stratified by MARBE-PI showed a consistent dose-response association with mortality. The MARBE-PI also performed comparably with indices constructed with clinical health deficits and/or laboratory results. CONCLUSIONS: The MARBE-PI is considered the most applicable measure for risk stratification in busy clinical settings. It holds potential to pinpoint elderly individuals at elevated mortality risk, thereby aiding clinical decision-making. |
| Date: | 2024-05 |
| Relation: | Journals of Gerontology. Series A, Biological Sciences and Medical Sciences. 2024 May;79(5):Article number glae041. |
| Link to: | http://dx.doi.org/10.1093/gerona/glae041 |
| JIF/Ranking 2023: | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1079-5006&DestApp=IC2JCR |
| Cited Times(WOS): | https://www.webofscience.com/wos/woscc/full-record/WOS:001197826500001 |
| Cited Times(Scopus): | https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85190175941 |
| Appears in Collections: | [熊昭] 期刊論文
[許志成] 期刊論文
[張新儀] 期刊論文
[莊淑鈞] 期刊論文
[吳易謙] 期刊論文
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