Evidence mapPaperPMID 37535293Full record

ReviewCurrent diabetes reports2023

Team-Based Approach to Reduce Malignancies in People with Diabetes and Obesity.

Ziyue Zhu, Samuel Yeung Shan Wong, Joseph Jao Yiu Sung, Thomas Yuen Tung Lam

Abstract readReview
In one paragraph

Review in Current diabetes reports, 2023. 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

4 authors.

Ziyue ZhuStanley Ho Big Data Analytic and Research Centre, The Chinese University of Hong Kong, Shatin, Hong Kong.ORCID 0000-0002-8797-7492
Samuel Yeung Shan WongThe Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong.ORCID 0000-0003-0934-6385
Joseph Jao Yiu SungLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.ORCID 0000-0003-3125-5199
Thomas Yuen Tung LamStanley Ho Big Data Analytic and Research Centre, The Chinese University of Hong Kong, Shatin, Hong Kong. thomaslam@cuhk.edu.hk.ORCID 0000-0002-4306-4990

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewNumerous observations have indicated an increased risk of developing various types of cancers, as well as cancer-related mortality, among patients with diabetes and obesity. The purpose of this review is to outline multiple-cancer screening among these patients through a team-based approach and to present the findings of a pioneering integrated care program designed for patients with obesity with a specific emphasis on cancer prevention. RECENT

findingsA community-based multi-cancer prevention program, which provides all services in one location and utilizes team-based approaches, is reported to be feasible and has the potential to enhance the uptake rate of multiple cancers screening among patients with diabetes and obesity. The team-based approach is a commonly utilized method for managing patients with diabetes, obesity, and cancer, and has been shown to be efficacious. Nevertheless, research on team-based cancer screening programs for patients with diabetes and obesity remains limited. Providing a comprehensive screening for colorectal, prostate, and breast cancer, as well as metabolic syndrome, during a single clinic visit has been proven effective and well-received by participants.

Indexed as

Diabetes MellitusMetabolic SyndromeNeoplasmsHumansMaleObesityCancer screeningDiabetes mellitusMetabolic syndrome screeningMultidisciplinary careObesityTeam-based approach

Identifiers

PMID37535293
PMCPMC10520129

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.