Preventive effects of 13 different drugs on colorectal cancer: a network meta-analysis.

chemical prevention colorectal cancer drug intervention network meta-analysis

Journal

Archives of medical science : AMS
ISSN: 1734-1922
Titre abrégé: Arch Med Sci
Pays: Poland
ID NLM: 101258257

Informations de publication

Date de publication:
2023
Historique:
received: 08 03 2023
accepted: 06 06 2023
medline: 21 9 2023
pubmed: 21 9 2023
entrez: 21 9 2023
Statut: epublish

Résumé

The aim of the study was to evaluate the preventive effect of 13 drugs on colorectal cancer (CRC) and guide the clinical application of these drugs. PubMed, Web of Science, Embase, Cochrane Library, and China National Knowledge Infrastructure were searched for randomized controlled trials (RCTs) and cohort studies. The Cochrane bias risk assessment tool and the Newcastle-Ottawa Scale quality evaluation tool were used to evaluate the quality of the included RCTs and cohort studies. The funnel plot was used to analyze publication bias. A network meta-analysis of the extracted data was conducted using Stata16.0 software. A total of 57 studies (34 RCTs and 23 cohort studies) involving 82719 participants were included. The network meta-analysis revealed that the quality of the included studies was good; the funnel plot showed no obvious publication bias. The network meta-analysis showed that the preventive effect of 13 drugs on CRC was better than that of the placebo. Allopurinol (SUCRA: 97.2%) was found to have the best effect, followed by berberine (SUCRA: 89.9%), non-aspirin NSAIDs (SUCRA: 84.5%), statins (SUCRA: 66.5%), metformin (SUCRA: 66.3%), calcium (SUCRA: 48.9%), mesalazine (SUCRA: 44.5%), ursodeoxycholic acid (SUCRA: 42.6%), vitamin D (SUCRA: 41.4%), mercaptopurine (SUCRA: 39.4%), aspirin (SUCRA: 30.4%), folic acid (SUCRA: 24.9%), and eicosapentaenoic acid (SUCRA: 16.3%). The preventive effect of allopurinol on CRC was better than that of the other 13 drugs. These results can help doctors and patients understand the preventative effects of these drugs more intuitively and provide an evidence-based basis for the clinical application of these drugs.

Identifiants

pubmed: 37732038
doi: 10.5114/aoms/167480
pii: 167480
pmc: PMC10507769
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

1428-1445

Informations de copyright

Copyright: © 2023 Termedia & Banach.

Déclaration de conflit d'intérêts

The authors declare no conflict of interest.

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Auteurs

Qi Fu (Q)

Affiliated Hospital of Qinghai University (The Clinical Medical School), Qinghai University, Xining, China.

Huini Liao (H)

Department of Oncology, Affiliated Hospital of Qinghai University, Xining, China.

Zhihao Li (Z)

Department of Oncology, Affiliated Hospital of Qinghai University, Xining, China.

Xing Chen (X)

Department of Oncology, Affiliated Hospital of Qinghai University, Xining, China.

Xuan Zhang (X)

The First Clinical Medical School, Gansu University of Chinese Medicine, Lanzhou, China.

Ji Di (J)

Department of Oncology, Affiliated Hospital of Qinghai University, Xining, China.

Classifications MeSH