Evidence map›Paper›PMID 38644549›Full record

ArticleJournal of cachexia, sarcopenia and muscle2024

Exploring the optimal indicator of short-term peridiagnosis weight dynamics to predict cancer survival: A multicentre cohort study.

Liangyu Yin, Ling Zhang, Long Li, Ming Liu, Jin Zheng, Aiguo Xu, Quanjun Lyu, Yongdong Feng, Zengqing Guo, Hu Ma and 12 more

Abstract readMulticenter Study
In one paragraph

Article in Journal of cachexia, sarcopenia and muscle, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

22 authors.

Liangyu YinDepartment of Clinical Nutrition, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, China.ORCID 0000-0001-8876-2680
Ling ZhangDepartment of Clinical Nutrition, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Long LiDepartment of Clinical Nutrition, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Ming LiuDepartment of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Jin ZhengDepartment of Traditional Chinese Medicine, Tangdu Hospital, Air Force Medical University (The Fourth Military Medical University), Xi'an, China.
Aiguo XuDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Quanjun LyuDepartment of Nutrition, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yongdong FengDepartment of GI Cancer Research Institute, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zengqing GuoDepartment of Medical Oncology, Fujian Cancer Hospital, Fujian Medical University Cancer Hospital, Fuzhou, China.
Hu MaDepartment of Oncology, The Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Jipeng LiDepartment of Experimental Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Zhikang ChenDepartment of Colorectal and Anus Surgery, Xiangya Hospital of Central South University, Changsha, China.
Hui WangDepartment of Oncology, The People's Hospital of Dujiangyan, Dujiangyan, China.
Zengning LiDepartment of Clinical Nutrition, The First Hospital of Hebei Medical University, Shijiazhuang, China.
Chunling ZhouDepartment of Clinical Nutrition, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Xi GaoDepartment of Oncology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Min WengDepartment of Clinical Nutrition, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Qinghua YaoDepartment of Integrated Chinese and Western Medicine, Cancer Hospital of the University of Chinese Academy of Science (Zhejiang Cancer Hospital), Hangzhou, China.
Wei LiCancer Center, The First Hospital of Jilin University, Changchun, China.
Tao LiDepartment of Radiation Oncology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Hanping ShiDepartment of Gastrointestinal Surgery and Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Hongxia XuDepartment of Clinical Nutrition, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, China.ORCID 0000-0001-5215-734X

Funding

National Key Research and Development Program 2017YFC1309200National Natural Science Foundation of China 81673167Talent Innovation Capacity Development Program of Army Medical Center of PLA 2019CXJSC003
6 · The paper itself

Abstract

backgroundBody weight and its changes have been associated with cancer outcomes. However, the associations of short-term peridiagnosis weight dynamics in standardized, clinically operational time frames with cancer survival remain largely unknown. This study aimed to screen for and evaluate the optimal indicator of short-term peridiagnosis weight dynamics to predict overall survival (OS) in patients with cancer.

methodsThis multicentre cohort study prospectively collected data from 7460 patients pathologically diagnosed with cancer between 2013 and 2019. Body weight data were recorded 1 month before, at the time of and 1 month following diagnosis. By permuting different types (point value in kg, point height-adjusted value in kg/m

resultsThe study enrolled 5012 males and 2448 females, with a median age of 59 years. During a median follow-up of 37 months, 1026 deaths occurred. Peridiagnosis (1 month before diagnosis to 1 month following diagnosis) RWC showed higher prognostic performance (Harrell's C-index = 0.601, 95% confidence interval [CI] = [0.583, 0.619]) than other types of indicators including body mass index (BMI), absolute weight change, absolute BMI change, prediagnosis RWC and postdiagnosis RWC in the study population (all P < 0.05). Time-dependent C-index analysis also indicated that peridiagnosis RWC was optimal for predicting OS. The multivariable-adjusted RCS analysis revealed an N-shaped non-linear association between peridiagnosis RWC and OS (P

conclusionsThe prognostic performance of peridiagnosis RWC is superior to other weight-related indicators in patients with cancer. The findings underscore the importance of expanding the surveillance of body weight from at diagnosis to both past and future, and conducting it within clinically operational time frames, in order to identify and intervene with patients who are at risk of weight change-related premature deaths.

Indexed as

Body WeightNeoplasmsAdultAgedCohort StudiesFemaleHumansMaleMiddle AgedPrognosiscancerperidiagnosissurvivalweight changeweight gainweight loss

Identifiers

PMID38644549
PMCPMC11154758

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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.