Objective To investigate the clinical characteristics of colorectal polyps in patients with melanosis coli (MC), analyze the recurrence risk after polypectomy, and construct a prediction model for polyp recurrence.
Methods A total of 1, 763 patients who underwent colorectal polypectomy at the First Hospital of Handan from January 2017 to June 2023 were divided into MC group (n=149) and non-MC group (n=1, 614). Among them, 122 patients in the MC group underwent colonoscopic re-examination one year later and were further divided into recurrence group (n=52) and non-recurrence group (n=70) based on polyp recurrence. The characteristics of colorectal polyps and recurrence risk after polypectomy in MC patients were analyzed. A multivariable Logistic regression analysis was used to construct a polyp recurrence risk model, and the nomogram model was plotted using R studio software. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis were employed to evaluate the discrimination, calibration, and clinical practicality of the model.
Results The detection rates of large polyps (≥1.0 cm), right-sided colon polyps, multiple polyps (≥3 polyps), and Yamada type Ⅰ polyps in the MC group were significantly higher than those in the non-MC group, while the detection rates of left-sided colon polyps and Yamada type Ⅳ polyps were significantly lower (P < 0.05). The detection rates of adenomatous polyps and polyps with mild dysplasia in the MC group were significantly higher than those in the non-MC group, whereas the detection rate of polyps with moderate dysplasia in the MC group was significantly lower (P < 0.05). Significant differences were observed between the recurrence and non-recurrence groups in terms of a history of cholecystectomy, Helicobacter pylori (Hp) infection, and family history of colorectal cancer (P < 0.05). There were also significant differences in the distribution, size, and the number of initial polyps between the two groups (P < 0.05). Multivariable Logistic regression analysis identified cholecystectomy, Hp infection, first-degree relatives with colorectal cancer, polyp size (≥1 cm), and multiple polyps (≥3 polyps) as independent risk factors for polyp recurrence after polypectomy (P < 0.05). Based on these factors, a recurrence prediction model was constructed. The area under the curve (AUC) of this model was 0.824 (95%CI, 0.753 to 0.895), indicating good discrimination. The calibration curve showed a good fit. Decision curve analysis demonstrated a high net benefit within the threshold range of 0.1 to 0.8, suggesting that the model had a wide range of beneficial thresholds and clinical practical value.
Conclusion Compared with the non-MC group, the MC group has higher detection rates of large polyps, right-sided colon polyps, multiple polyps, Yamada type Ⅰ polyps, adenomatous polyps, and polyps with low-grade dysplasia, but lower detection rates of left-sided colon polyps, Yamada type Ⅳ polyps, and polyps with moderate dysplasia. Cholecystectomy, Hp infection, first-degree relatives with colorectal cancer, large polyps (≥1 cm), and multiple polyps (≥3 polyps) are independent risk factors for polyp recurrence after colorectal polypectomy in MC patients. The recurrence prediction model constructed based on these factors has high practical value.
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