Evidence map›Paper›PMID 36353671›Full record

ArticleInnovation (Cambridge (Mass.))2022

Body mass index and survival after cancer diagnosis: A pan-cancer cohort study of 114 430 patients with cancer.

Huakang Tu, Jennifer L McQuade, Michael A Davies, Maosheng Huang, Kunlin Xie, Yuanqing Ye, Wong-Ho Chow, Alma Rodriguez, Xifeng Wu

Abstract read
In one paragraph

Article in Innovation (Cambridge (Mass.)), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
–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

25 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Observational
  5. Racial/ethnic and sex disparities in mortality among US cancer survivors.Journal of cancer research and clinical oncology · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. The role of adipogenic niche resident cells in colorectal cancer progression in relation to obesity.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2025
    Review
  12. Article
  13. Article
  14. Article
  15. Observational
  16. Article
  17. Article
  18. Article
  19. Review
  20. Prediction of 90-day mortality risk after unplanned emergency department visits of advanced stage cancer patients.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
    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

9 authors.

Huakang TuDepartment of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China.
Jennifer L McQuadeDepartment of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Michael A DaviesDepartment of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Maosheng HuangDepartment of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Kunlin XieDepartment of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Yuanqing YeDepartment of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Wong-Ho ChowDepartment of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Alma RodriguezDepartment of Lymphoma/Myeloma, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Xifeng WuDepartment of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China.

Funding

The University of Texas MD Anderson Cancer Center SPORE in MelanomaP50CA221703 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DAVIES, MICHAEL · 2019 to 2023
$10.3M
NCI NIH HHS P50 CA221703
6 · The paper itself

Abstract

The recommendation encouraging patients with cancer to keep a normal body mass index (BMI) is largely extrapolated from data on risk of developing cancer. We tested the prospective association between peri-diagnostic (within 1 year post-diagnosis) BMI and all-cause mortality in patients with incident cancers. During 7.2 years of follow-up, 42% (48,340) of the 114 430 patients with cancer died. Spline analysis revealed that compared with a BMI of 22.5, a BMI lower than 22.5 was associated with increased risk of all-cause mortality across 24 cancer types. A BMI higher than 22.5 was associated with reduced all-cause mortality, while a non-linear association was observed; the lowest risk was found at a BMI of 29.6-34.2, and the risk started to return to and above unity at very high BMI values. The reduced mortality risk of high BMI was observed in 23 of 24 cancer types and maintained after attempts to remove potential selection bias, confounding by smoking and comorbidities, and reserve causality. Compared with a normal BMI of 18.5-24.9, the hazard ratios were 0.85 (95% confidence interval [CI], 0.83-0.87) for an overweight BMI (25-29.9) and 0.82 (0.80-0.85) for an obese BMI (≥30), and the associations were generally consistent across cancer types and various subgroups. Obese BMI was associated with increased life expectancy, up to 6 years among men and 3 years among women. In conclusion, while overweight/obese BMI increases the risk of developing cancer in the general population, overweight/obese peri-diagnostic BMI was associated with longer survival in cancer patients.

Identifiers

PMID36353671
PMCPMC9638833

What OpenQuestion holds

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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 OpenQuestion graph.