Evidence map›Paper›PMID 34522458›Full record

ArticleAmerican journal of cancer research2021

Body mass index and type 2 diabetes and breast cancer survival: a Mendelian randomization study.

Yi-Shian Liu, Pei-Ei Wu, Wen-Cheng Chou, Rajeev Vikram, Wei-Ting Chen, Show-Ling Yang, Manjeet K Bolla, Qin Wang, Joe Dennis, Tsun L Chan and 13 more

Open access · greenAbstract read
In one paragraph

Article in American journal of cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 4 pooled it
2.1field-weighted citation impact, top 12% of its field
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

10 citing papers in PubMed, 4 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
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  6. Review
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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

23 authors at 10 institutions in 7 countries.

Yi-Shian LiuInstitute of Biomedical Sciences, Academia Sinica Taipei, Taiwan.
Pei-Ei WuInstitute of Biomedical Sciences, Academia Sinica Taipei, Taiwan.
Wen-Cheng ChouInstitute of Biomedical Sciences, Academia Sinica Taipei, Taiwan.
Rajeev VikramInstitute of Biomedical Sciences, Academia Sinica Taipei, Taiwan.
Wei-Ting ChenInstitute of Biomedical Sciences, Academia Sinica Taipei, Taiwan.
Show-Ling YangInstitute of Biomedical Sciences, Academia Sinica Taipei, Taiwan.
Manjeet K BollaCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge Cambridge, United Kingdom.
Qin WangCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge Cambridge, United Kingdom.
Joe DennisCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge Cambridge, United Kingdom.
Tsun L ChanHong Kong Hereditary Breast Cancer Family Registry, Cancer Genetics Centre Happy Valley, Hong Kong, China.
Ji-Yeob ChoiDepartment of Biomedical Sciences, Seoul National University Graduate School Seoul, Korea.
Ming-Feng HouDepartment of Surgery, Kaohsiung Municipal Hsiao-Kang Hospital Kaohsiung, Taiwan.
Hidemi ItoDivision of Cancer Information and Control, Aichi Cancer Center Research Institute Nagoya, Japan.
Daehee KangCancer Research Institute, Seoul National University Seoul, Korea.
Sung-Won KimDepartment of Surgery, Daerim Saint Mary's Hospital Seoul, Korea.
Ava KwongHong Kong Hereditary Breast Cancer Family Registry, Cancer Genetics Centre Happy Valley, Hong Kong, China.
Keitaro MatsuoDivision of Cancer Epidemiology, Nagoya University Graduate School of Medicine Nagoya, Japan.
Sue K ParkDepartment of Biomedical Sciences, Seoul National University Graduate School Seoul, Korea.
Xiao-Ou ShuDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine Nashville, TN, USA.
Wei ZhengDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine Nashville, TN, USA.
Alison M DunningCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge Cambridge, United Kingdom.
Douglas F EastonCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge Cambridge, United Kingdom.
Chen-Yang ShenInstitute of Biomedical Sciences, Academia Sinica Taipei, Taiwan.
Institute of Biomedical Sciences, Academia Sinica · TWCancer Research UK Cambridge Center · GBAichi Cancer Center · JPBreast Cancer Research Foundation · USSeoul National University · KRVanderbilt University · USCancer Research Institute · USChina Medical University · TWKaohsiung Municipal Hsiao-Kang Hospital · TWUniversity of Saint Mary · US

Funding

Cancer Research UK 16563
6 · The paper itself

Abstract

The causal relationship between body mass index (BMI) and type 2 diabetes (T2D) and breast cancer prognosis is still ambiguous. The aim of this study was to investigate the prognostic effect of BMI and T2D on breast cancer disease-free survival (DFS) among Asian individuals. In this two-sample Mendelian randomization (MR) study, the instrumental variables (IVs) were identified using a genome-wide association study (GWAS) among 24,000 participants in the Taiwan Biobank. Importantly, the validity of these IVs was confirmed with a previous large-scale GWAS (Biobank Japan Project, BBJ). In this study, we found that a genetic predisposition toward higher BMI (as indicated by BMI IVs, F = 86.88) was associated with poor breast cancer DFS (hazard ratio [HR] = 6.11; P < 0.001). Furthermore, higher level of genetically predicted T2D (as indicated by T2D IVs) was associated with an increased risk of recurrence of and mortality from breast cancer (HR = 1.43; P < 0.001). Sensitivity analyses, including the weighted-median approach, MR-Egger regression, Radial regression and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) supported the consistency of our findings. Finally, the causal relationship between BMI and poor breast cancer prognosis was confirmed in a prospective cohort study. Our MR analyses demonstrated the causal relationship between the genetic prediction of elevated BMI and a greater risk of T2D with poor breast cancer prognosis. BMI and T2D have important clinical implications and may be used as prognostic indicators of breast cancer.

Indexed as

body mass indexbreast cancer progressionbreast cancer survival analysisMendelian randomizationtype 2 diabetes

Identifiers

PMID34522458
PMCPMC8414374
OpenAlexW3199828678

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.