ArticleScientific reports2025
The association between phenotypic age acceleration and the risk of all-cause and cancer mortality among cancer survivors: NHANES 1999-2018.
Article in Scientific reports, 2025. 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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Abstract
Phenotypic age (PhenoAge) is a biological aging clock that estimates an individual's biological age. However, the effect of PhenoAge acceleration (PhenoAgeAccel) on cancer is unclear. This study investigates the relationship between PhenoAgeAccel and cancer survivors. Data for this cohort study were sourced from the U.S. National Health and Nutrition Examination Survey (NHANES) spanning 1999-2018. The relationship between PhenoAgeAccel and cancer prevalence was evaluated using weighted multivariate logistic regression. Kaplan-Meier analyses and weighted multivariate-adjusted Cox analyses were conducted to examine the association between PhenoAgeAccel and all-cause as well as cancer-specific mortality in cancer survivors. Restricted cubic spline (RCS) analysis was utilized to assess nonlinear associations. Subgroup and sensitivity analyses were also performed to confirm the robustness of the findings. A total of 34,246 participants were included in our study, of which 3067 were cancer survivors (8.95% prevalence). With a median follow-up of 117 months (interquartile range: 50-155 months), there were 1161 deaths, including 351 from cancer. Weighted multivariate regression analysis revealed a significant positive association between higher PhenoAgeAccel and cancer prevalence (P for trend < 0.001). Multivariable-adjusted Cox regression analyses showed that elevated PhenoAgeAccel was significantly associated with increased all-cause and cancer-specific mortality among cancer survivors (P for trend < 0.001). RCS regression indicated no nonlinear relationship between PhenoAgeAccel and mortality outcomes (P for nonlinear relationship > 0.05). Kaplan-Meier analyses indicated a poorer prognosis with higher PhenoAgeAccel. Subgroup analyses based on tumor classification highlighted the differential prognostic impact of PhenoAgeAccel across various tumor types. Our findings reveal a significant linear correlation between PhenoAgeAccel and both all-cause and cancer-specific mortality in cancer survivors.
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