ArticleJournal of the Chinese Medical Association : JCMA2025
Predictors of metachronous advanced colorectal adenoma after polypectomy.
Article in Journal of the Chinese Medical Association : JCMA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAdenoma recurrence following polypectomy remains a major clinical concern, necessitating the optimization of risk assessment strategies. This study explored key risk factors for metachronous advanced adenomas, focusing on metabolic factors and initial colonoscopic findings, to offer recommendations regarding risk stratification and surveillance.
methodsThis retrospective study included individuals who had undergone two colonoscopies between January 2014 and February 2020, with adenomas detected during the initial examination. The associations of various factors-such as age, sex, metabolic disorders, and baseline colonoscopic findings-with metachronous advanced adenomas were investigated.
resultsOf 33 073 individuals who underwent baseline colonoscopy, 2013 met the eligibility criteria. Multivariate analysis indicated that age of ≥45 years, male sex, and baseline colonoscopic findings were key predictors of metachronous advanced adenomas. The adjusted odds ratio (OR; 95% CI) values for metachronous advanced adenomas in patients with multiple (≥3) diminutive adenomas, those with multiple (≥3) small adenomas, and those with advanced adenomas were 1.56 (95% CI, 0.87-2.80), 3.27 (95% CI, 2.02-5.29), and 5.41 (95% CI, 3.73-7.83), respectively, compared with the results in patients with one or two nonadvanced adenomas.
conclusionThis study highlights the importance of baseline colonoscopy in identifying patients at elevated risk of developing metachronous advanced adenomas, particularly advanced adenomas. On the basis of our findings, we recommend integrating risk stratification by adenoma size, number, and histology into postpolypectomy surveillance guidelines. Personalized surveillance intervals informed by baseline findings and patient-specific risk factors may help clinicians optimize follow-up strategies and improve clinical outcomes.
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