Evidence map›Paper›PMID 39403338›Full record

ArticleFrontiers in oncology2024

Predicting the risk of colorectal cancer among diabetes patients using a random survival forest-guided approach.

Sarah Tsz Yui Yau, Chi Tim Hung, Eman Yee Man Leung, Ka Chun Chong, Albert Lee, Eng Kiong Yeoh

Abstract read
In one paragraph

Article in Frontiers in oncology, 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

6 authors.

Sarah Tsz Yui YauJC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Chi Tim HungJC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Eman Yee Man LeungJC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Ka Chun ChongJC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Albert LeeJC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Eng Kiong YeohJC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Colorectal cancer (CRC) is the third most frequently diagnosed cancer worldwide. Diabetes and CRC share many overlapping lifestyle risk factors such as obesity, heavy alcohol use, and diet. This study aims to develop a risk scoring system for CRC prediction among diabetes patients using routine medical records. Methods: A retrospective cohort study was conducted using electronic health records of Hong Kong. Patients who received diabetes care in public general outpatient clinics between 2010 and 2019 and had no cancer history were identified, and followed up until December 2019. The outcome was diagnosis of CRC during follow-up. For model building, predictors were first selected using random survival forest, and weights were subsequently assigned to selected predictors using Cox regression. Results: Of the 386,325 patients identified, 4,199 patients developed CRC during a median follow-up of 6.2 years. The overall incidence rate of CRC was 1.93 per 1000 person-years. In the final scoring system, age, waist-to-hip ratio, and serum creatinine were included as predictors. The C-index on test set was 0.651 (95%CI: 0.631-0.669). Elevated serum creatinine (≥127 µmol/L) could be a potential important predictor of increased CRC risk. Conclusion: While obesity is a well-known risk factor for CRC, renal dysfunction could be potentially linked to an elevated risk of CRC among diabetes patients. Further studies are warranted to explore whether renal function could be a potential parameter to guide screening recommendation for diabetes patients.

Indexed as

colorectal cancerdiabetesrandom forestrisk predictionsurvival analysis

Identifiers

PMID39403338
PMCPMC11471444

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.