Evidence map›Paper›PMID 42634650›Full record

ArticleInternational journal of chronic obstructive pulmonary disease2026

Predictive Value of Biological Age for All-Cause Mortality in Patients with COPD.

Wei Cheng, Yanqun Hou, Aiyuan Zhou, Cong Liu, Shuwan Huang, Yiyang Zhao, Ji Li, Zhili Deng, Tongtong Zhang, Rui Mao and 2 more

Abstract readComparative Study
In one paragraph

Article in International journal of chronic obstructive pulmonary disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

12 authors.

Wei ChengDepartment of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.ORCID 0000-0003-1025-0591
Yanqun HouDepartment of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.
Aiyuan ZhouDepartment of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.
Cong LiuDepartment of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.
Shuwan HuangDepartment of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.
Yiyang ZhaoNational Clinical Research Center for Geriatric Diseases (Xiangya Hospital), Changsha, Hunan, People's Republic of China.ORCID 0000-0001-5975-8025
Ji LiNational Clinical Research Center for Geriatric Diseases (Xiangya Hospital), Changsha, Hunan, People's Republic of China.
Zhili DengNational Clinical Research Center for Geriatric Diseases (Xiangya Hospital), Changsha, Hunan, People's Republic of China.
Tongtong ZhangThe Center of Gastrointestinal and Minimally Invasive Surgery, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.
Rui Mao *National Clinical Research Center for Geriatric Diseases (Xiangya Hospital), Changsha, Hunan, People's Republic of China.ORCID 0000-0002-0135-8579
Yan TangNational Clinical Research Center for Geriatric Diseases (Xiangya Hospital), Changsha, Hunan, People's Republic of China.
Pinhua Pan *Department of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.ORCID 0000-0001-5883-0531

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Although biological age has emerged as a robust predictor of mortality across multiple chronic diseases, its prognostic value in patients with COPD remains insufficiently defined. This study aimed to compare the predictive performance of major biological age biomarkers and to develop a mortality risk prediction model for COPD based on the optimal biomarker. Patients and Methods: We included 19,882 patients with COPD who had complete survival data extending beyond 10 years, recruited between 2006 and 2010 from a large biobank cohort. Biological aging was quantified using phenotypic age (PhenoAge) and Klemera-Doubal Method biological age (KDM-BA). Time-dependent ROC analyses were performed to compare the discriminatory ability of these biomarkers for predicting all-cause mortality. Cox regression was subsequently developed to construct mortality prediction models, with time-dependent ROC, net reclassification index (NRI) and integrated discrimination improvement (IDI) analyses evaluating model performance. Decision curve analysis(DCA) was then performed to evaluate the clinical benefit of each model. Results: Among 19,882 patients with COPD, the mean chronological age was 59.9 ± 7.1 years, with a mean PhenoAge of 53.4 ± 9.4 years and a mean KDM-BA of 58.9 ± 12.8 years. Time-dependent ROC analyses showed that PhenoAge consistently outperformed chronological age, PhenoAge acceleration, and KDM-BA in predicting all-cause mortality at 5-, 10-, and 15-year follow-up. Based on univariate analyses and assessment of collinearity among pulmonary function variables, two Cox models were constructed. Models incorporating PhenoAge demonstrated higher AUCs, as well as positive NRI and IDI values, compared with chronological age-based models. DCA curves further indicated that PhenoAge-derived models provided greater net clinical benefit across most threshold probabilities. Conclusion: PhenoAge outperformed chronological age and KDM-BA in predicting all-cause mortality in COPD. PhenoAge-based models provided modest but consistent improvements in risk prediction over models based on chronological age and may complement individualized risk stratification.

Indexed as

AgingLungPulmonary Disease, Chronic ObstructiveAgedAge FactorsBiomarkersCause of DeathDecision Support TechniquesFemaleHumansMaleMiddle AgedPhenotypePredictive Value of TestsPrognosisRisk AssessmentBiomarkersbiological ageCOPDKDM-BAmortalityPhenoAgeprediction model

Identifiers

PMID42634650
PMCPMC13500022

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.