Evidence map›Paper›PMID 42389436›Full record

ArticleJournal of translational internal medicine2026

Joint association of the frailty index and phenotypic age with all-cause and cause-specific mortality: A prospective cohort study.

Zilun Shao, Yuxuan Zhao, Haiming Yang, Meng Xiao, Mingyu Song, Chunxiao Liao, Yuanjie Pang, Wenjing Gao, Tao Huang, Canqing Yu and 5 more

Abstract read
In one paragraph

Article in Journal of translational internal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Zilun ShaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Yuxuan ZhaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Haiming YangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Meng XiaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Mingyu SongDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Chunxiao LiaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Yuanjie PangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Wenjing GaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Tao HuangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Shengxu LiChildren's Minnesota Research Institute, Children's Minnesota Hospital, Minneapolis, MN, USA.
Lu QiDepartment of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA.
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Dianjianyi SunDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.ORCID https://orcid.org/0000-0003-3651-6693

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: Little is known about whether frailty index (FI) and phenotypic age (PhenoAge), two independent indicators of biological age, may jointly or interactively predict death risk. Methods: This prospective study was conducted using National Health and Nutrition Examination Survey (NHANES) data of four survey cycles (2003 to 2010) and mortality records until December 31, 2019. FI was calculated for each participant based on his/her responses to 34 questions, and PhenoAge was derived from algorithms using data of nine biomarkers and chronological age. We used Cox proportional hazards (PH) models and competing risk models to estimate the associations of FI, PhenoAge, and their interactions with all-cause mortality and cause-specific mortality. The C-statistic, continuous net reclassification index (NRI), and integrated discrimination improvement (IDI) were used to evaluate model performance. Results: After an updated median follow-up of 11.8 years among 20, 089 adults, a total of 3778 deaths were documented. Each 1 standard deviation (SD) increment in FI and PhenoAgeAccel was associated with 47% (42%-51%) and 41% (38%-45%) higher risk of all-cause mortality, respectively. However, their multiplicative interaction on death risk was not found ( Conclusions: Individual death risk could be better predicted by a joint inclusion of both FI and PhenoAge, indicating that targeting their components may reduce death risk and prolong health span.

Indexed as

frailty indexmortality riskphenotypic age

Identifiers

PMID42389436
PMCPMC13320525

What Socratic holds

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LicenceCC BY
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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.