A prediction model and nomogram for technical difficulty of peroral endoscopic myotomy.

Background And Aims: Peroral endoscopic myotomy (POEM) is a promising endoscopic technique for achalasia. We aimed to establish a regression model and develop a simple nomogram to predict the technical difficulty of POEM in a single center with large volume cases.

Methods: 3385 achalasia patients treated with POEM were included, and the technical difficulty was systemically evaluated. All of them were randomized into the training cohort (n = 1693) or internal validation cohort (n = 1692). Then, the prediction model and nomogram were proposed based on multivariate logistic regression analysis in the training cohort and assessed in the validation cohort.

Results: Of 3385 patients, technical difficulty happened in 417 (12.32%) cases. In the training stage, six factors were weighted based on the β coefficient from the regression model, including age, disease duration, sigmoid esophagus, mucosal edema, submucosal fibrosis, and tunnel length. The patients were categorized into low-risk (< 0.1), medium-risk (0.1-0.25), and high-risk (> = 0.25) groups. Our score model performed satisfying discrimination with the areas under the receiver-operating characteristic curve (AUC) of 0.743 (95% confidence interval (CI), 0.701-0.785) and calibration with goodness of fit in the Hosmer-Lemeshow test (P = 0.088) in internal validation.

Conclusions: The prediction model and nomogram demonstrated good performance in predicting the technical difficulty of POEM.