MétaCan
Menu
Back to cohort
Record W4402958951 · doi:10.15403/jgld-5527

Long-Term Risk of Colorectal Cancer in Patients With Prediabetes: A Comprehensive Systematic Review and Meta-Analysis

2024· review· en· W4402958951 on OpenAlexaboutno aff
Praneeth Reddy Keesari, Akhil Jain, Yashwitha Sai Pulakurthi, Rewanth R. Katamreddy, Ali Tariq Alvi, Rupak Desai

Bibliographic record

VenueJournal of Gastrointestinal and Liver Diseases · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePrediabetesMeta-analysisOdds ratioColorectal cancerSubgroup analysisIncidence (geometry)Internal medicineMEDLINEProspective cohort studyCancerType 2 diabetesDiabetes mellitusEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: Prediabetes is often underdiagnosed and underreported due to its asymptomatic state in over 80% of individuals. Considering its role in promoting cancer incidence and limited evidence linking prediabetes and colorectal cancer (CRC), we conducted a systematic review and meta-analysis to evaluate the incidence of colorectal cancer in people with prediabetes. METHODS: A comprehensive search through PubMed/Medline, Embase, Scopus, and Google Scholar was performed until June 1, 2022, to screen for studies reporting CRC incidence/risk in prediabetics. Binary random-effects models were used to perform meta-analysis and subgroup analyses. Sensitivity analysis was done using leave-one-out method. The quality of the studies was assessed by the Newcastle Ottawa Scale for observational studies. RESULTS: Seven prospective and one retrospective study comprising 15 cohorts and a pooled number of 854,876 cases and 219,0511 controls were included in the analysis (2 Japan, 2 Korea, 1 Sweden, 1 UK, 1 China, and 1 USA). After combining all the studies, the forest plots for adjusted analysis shows a statistically significant increase in odds of having CRC with prediabetes (OR=1.16; 1.08-1.25, p< 0.01; I2=56.06%) and unadjusted analysis also shows a statistically significant increase in odds of having CRC with prediabetes (OR=1.62; 1.35-1.95, p< 0.01; I2=85.72% ). Sensitivity analysis using the Leave-one-out method did confirm equivalent results. Subgroup analysis based on type of study, the odds of developing CRC was higher in prospective studies (OR=1.175; 1.065-1.298) (p=0.001) than retrospective studies (OR=1.162; 1.033- 1.306) (p=0.012). The odds of developing CRC were not significantly higher in ages >60 (OR=1.446; 0.887-2.356) (p=0.139) compared to less than 60 years. The strongest association b/w prediabetes and CRC was found on a median 5-10 years (aOR=1.257; 1.029-1.534) (p=0.025) follow-up compared to < 5 years and 10 years and higher. CONCLUSIONS: This study showed that the odds of developing CRC is 16% higher in patients with prediabetes than those with normal blood glucose. Lifestyle modifications such as weight loss, proper diet, and exercise are essential to control prediabetes. This study further warrants a specific prediabetes screening for patients already at high risk of colorectal cancer with other risk factors.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.035
Bibliometrics0.0060.007
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.281
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Gastrointestinal and Liver DiseasesSame topicMetabolism, Diabetes, and CancerFrench-language works237,207