Aging & Longevity

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

TL;DR

PhenoAge outperformed chronological age and KDM-BA in predicting all-cause mortality in COPD, and PhenoAge-based models provided modest but consistent improvements in risk prediction over models based on chronological age.

Key Findings

PhenoAge consistently outperformed chronological age, PhenoAge acceleration, and KDM-BA in predicting all-cause mortality at all time points evaluated.

  • Time-dependent ROC analyses were performed at 5-, 10-, and 15-year follow-up intervals
  • PhenoAge demonstrated higher AUCs than chronological age, PhenoAge acceleration, and KDM-BA at each time point
  • The study included 19,882 patients with COPD who had complete survival data extending beyond 10 years
  • Patients were recruited between 2006 and 2010 from a large biobank cohort

The mean biological ages measured by PhenoAge and KDM-BA differed substantially from mean chronological age in the COPD cohort.

  • Mean chronological age was 59.9 ± 7.1 years
  • Mean PhenoAge was 53.4 ± 9.4 years
  • Mean KDM-BA (Klemera-Doubal Method biological age) was 58.9 ± 12.8 years
  • PhenoAge showed a mean value approximately 6.5 years lower than chronological age, while KDM-BA was approximately 1 year lower

Cox regression models incorporating PhenoAge demonstrated improved discriminatory performance compared to chronological age-based models.

  • PhenoAge-based models showed higher AUCs compared with chronological age-based models
  • Net Reclassification Index (NRI) values were positive for PhenoAge-incorporating models versus chronological age-based models
  • Integrated Discrimination Improvement (IDI) values were also positive, indicating improved risk discrimination
  • Two Cox models were constructed based on univariate analyses and assessment of collinearity among pulmonary function variables

Decision curve analysis indicated that PhenoAge-derived models provided greater net clinical benefit compared to chronological age-based models.

  • DCA curves showed PhenoAge-derived models provided greater net clinical benefit across most threshold probabilities
  • Decision curve analysis was used to evaluate the clinical benefit of each model
  • The improvement was described as 'modest but consistent'

Biological aging in COPD patients was quantified using two distinct established biomarkers, PhenoAge and KDM-BA, enabling direct comparison of their prognostic utility.

  • PhenoAge (phenotypic age) and Klemera-Doubal Method biological age (KDM-BA) were both assessed
  • PhenoAge acceleration was also calculated and included in comparative analyses
  • The study population of 19,882 COPD patients was drawn from a large biobank cohort
  • All patients had complete survival data extending beyond 10 years

What This Means

This research suggests that a measure called 'PhenoAge' — which estimates how biologically old a person is based on blood test results and other clinical markers — is better at predicting the risk of death in people with COPD (chronic obstructive pulmonary disease) than simply using a person's actual age. The study analyzed data from nearly 20,000 COPD patients tracked for up to 15 years, comparing PhenoAge against another biological age measure (KDM-BA) and standard chronological age. PhenoAge consistently came out on top at predicting who was most likely to die over 5-, 10-, and 15-year periods. The researchers built statistical models to predict mortality risk and found that models using PhenoAge performed better than those using chronological age alone — they were more accurate and provided clearer clinical benefit across a range of risk thresholds. Interestingly, the average PhenoAge in this COPD group was about 53 years, roughly 6–7 years younger than the patients' actual average age of nearly 60, suggesting that biological and chronological age can diverge meaningfully in this population. This research suggests that incorporating biological age measurements like PhenoAge into clinical assessments for COPD patients could help doctors better identify who is at highest risk of dying and tailor care more precisely. While the improvements over using chronological age were described as 'modest but consistent,' the findings support the potential value of biological aging metrics as complementary tools for individualized risk stratification in COPD management.

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Citation

Cheng W, Hou Y, Zhou A, Liu C, Huang S, Zhao Y, et al.. (2026). Predictive Value of Biological Age for All-Cause Mortality in Patients with COPD.. International journal of chronic obstructive pulmonary disease. https://doi.org/10.2147/COPD.S617907