Background and study aims Endoscopic ultrasoundguided through-The-needle biopsy (TTNB) of pancreatic cystic lesions (PCLs) is associated with a non-negligible risk for adverse events (AEs). We aimed to identify the hierarchic interaction among independent predictors for TTNBrelated AEs and to generate a prognostic model using recursive partitioning analysis (RPA). Patients and methods Multicenter retrospective analysis of 506 patients with PCLs who underwent TTNB. RPA of predictors for AEs was performed and the model was validated by means of bootstrap resampling. Results Mean cysts size was 36.7mm. Most common diagnoses were intraductal papillary mucinous neoplasm (IPMN, 45 %), serous cystadenoma (18.8 %), and mucinous cystadenoma (12.8 %). Fifty-eight (11.5%) AEs were observed. At multivariate analysis, age (odds ratio [OR] 1.32, 1.09 2.14; p = 0.05), number of TTNB passes (OR from 2.17, 1.32 4.34 to OR 3.16, 2.03 6.34 with the increase of the number of passes), complete aspiration of the cyst (OR 0.56, 0.31 0.95; p = 0.02), and diagnosis of IPMN (OR 4.16, 2.27 7.69; p < 0.001) were found to be independent predictors of AEs, as confirmed by logistic regression and random forest analyses. RPA identified three risk classes: high-risk (IPMN sampled with multiple microforceps passes, 28% AEs rate), low-risk (1.4% AE rate, including patients < 64 years with other-Than-IPMN diagnosis sampled with ? 2 microforceps passes and with complete aspiration of the cyst) and middle-risk class (6.1% AEs rate, including the remaining patients). Conclusion TTNB should be selectively used in the evaluation of patients with IPMN. The present model could be applied during patient selection as to optimize the benefit/risk of TTNB.

Predictors of adverse events after endoscopic ultrasound-guided through-The-needle biopsy of pancreatic cysts: A recursive partitioning analysis

Di Matteo F. M.;Pecchia L.;
2022-01-01

Abstract

Background and study aims Endoscopic ultrasoundguided through-The-needle biopsy (TTNB) of pancreatic cystic lesions (PCLs) is associated with a non-negligible risk for adverse events (AEs). We aimed to identify the hierarchic interaction among independent predictors for TTNBrelated AEs and to generate a prognostic model using recursive partitioning analysis (RPA). Patients and methods Multicenter retrospective analysis of 506 patients with PCLs who underwent TTNB. RPA of predictors for AEs was performed and the model was validated by means of bootstrap resampling. Results Mean cysts size was 36.7mm. Most common diagnoses were intraductal papillary mucinous neoplasm (IPMN, 45 %), serous cystadenoma (18.8 %), and mucinous cystadenoma (12.8 %). Fifty-eight (11.5%) AEs were observed. At multivariate analysis, age (odds ratio [OR] 1.32, 1.09 2.14; p = 0.05), number of TTNB passes (OR from 2.17, 1.32 4.34 to OR 3.16, 2.03 6.34 with the increase of the number of passes), complete aspiration of the cyst (OR 0.56, 0.31 0.95; p = 0.02), and diagnosis of IPMN (OR 4.16, 2.27 7.69; p < 0.001) were found to be independent predictors of AEs, as confirmed by logistic regression and random forest analyses. RPA identified three risk classes: high-risk (IPMN sampled with multiple microforceps passes, 28% AEs rate), low-risk (1.4% AE rate, including patients < 64 years with other-Than-IPMN diagnosis sampled with ? 2 microforceps passes and with complete aspiration of the cyst) and middle-risk class (6.1% AEs rate, including the remaining patients). Conclusion TTNB should be selectively used in the evaluation of patients with IPMN. The present model could be applied during patient selection as to optimize the benefit/risk of TTNB.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12610/73390
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