Evidence map›Paper›PMID 37969022›Full record

ArticleJournal of cachexia, sarcopenia and muscle2023

Predicted lean body mass trajectories, and cancer risk and cancer-specific and all-cause mortality: A prospective cohort study.

Chenan Liu, Qingsong Zhang, Tong Liu, Qi Zhang, Mengmeng Song, Guotian Ruan, Shiqi Lin, Ziwen Wang, Xin Zheng, Yue Chen and 7 more

Abstract read
In one paragraph

Article in Journal of cachexia, sarcopenia and muscle, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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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

8 citing papers in PubMed.

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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

17 authors.

Chenan LiuDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Qingsong ZhangDepartment of General Surgery, Kailuan General Hospital, Tangshan, China.
Tong LiuDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Qi ZhangDepartment of Genetics, Yale University School of Medicine, New Haven, Connecticut, USA.
Mengmeng SongCardiovascular Research Institute, University of California, San Francisco, California, USA.
Guotian RuanDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Shiqi LinDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Ziwen WangDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Xin ZhengDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Yue ChenDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Heyang ZhangDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Yizhong GeDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Hailun XieDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Jinyu ShiDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Li DengKey Laboratory of Cancer FSMP for State Market Regulation, Beijing, China.
Shouling WuDepartment of Cardiology, Kailuan General Hospital, Tangshan, China.
Hanping ShiDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0003-4514-8693

Funding

National Key Research and Development Program 2022YFC2009600
6 · The paper itself

Abstract

backgroundAlthough many studies have investigated the association between body composition, cancer risk and mortality, predicting these risks through a single body composition measurement undoubtedly increases the limitations of the study. Few studies have explored the association between the trajectory of changes in body composition and the risk of cancer and death. We aimed to explore the association of predicted lean mass trajectories with cancer risk, cancer-specific mortality and all-cause mortality.

methodsThe participants in this study were all from the Kailuan cohort, a prospective, periodic, resurvey cohort study initiated in 2006. Latent mixture modelling was used to identify predicted lean mass trajectories for 2006-2010. The hazard ratios (HRs) and 95% confidence intervals (95% CIs) of the Cox proportional hazard models were used to describe the association between predicted lean mass trajectories and cancer risk and cancer-specific and all-cause mortality during follow-up (2010-2021).

resultsA total of 44 374 participants (average age, 53.01 ± 11.41 years, 78.99% men and 21.01% women) were enrolled in this study. Five distinct trajectories were identified: low-stable (n = 12 060), low-increasing (n = 8027), moderately stable-decreasing (n = 4725), moderately stable-increasing (n = 8053) and high-stable (n = 11 509). During the 11-year follow-up period, 2183 cancer events were recorded. After adjusting for age, predicted fat mass in 2010, sex, BMI, sedentary, physical activity, smoke, alcohol use, salt consumption, high-fat diet, high-sensitivity C-reactive protein, serum creatinine, family history of tumour, hypertension, diabetes mellitus, compared with the low-stable group, participants in the low-increasing group (HR = 0.851, 95% CI, 0.748-0.969), moderately stable-increasing group (HR = 0.803, 95% CI, 0.697-0.925) and high-stable group (HR = 0.770, 95% CI, 0.659-0.901) had a lower cancer risk, but not in the moderately stable-decreasing group (HR = 0.864, 95% CI, 0.735-1.015). Compared with the low-stable group, the risk of cancer-specific mortality was reduced by 25.4% (8.8-38.9%), 36.5% (20.3-49.4%) and 35.4% (17.9-49.2%), and the risk of all-cause mortality was reduced by 24.2% (16.9-30.8%), 37.0% (30.0-43.2%) and 47.4% (41.0-53.1%) in the low-increasing, moderately stable-increasing group and high-stable groups, respectively.

conclusionsPredicted lean mass trajectories may be closely associated with cancer risk and cancer-specific and all-cause mortality. Regular monitoring of body composition is necessary.

Indexed as

Body CompositionNeoplasmsAdultCohort StudiesFemaleHumansMaleMiddle AgedProspective StudiesRisk FactorsBody compositionCancer riskMortalityPredicted lean massTrajectory

Identifiers

PMID37969022
PMCPMC10751432

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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 OpenQuestion graph.