作者
Eduardo Albéniz,Antonio Escobar,María Fraile,Berta Ibáñez,Carlos Guarner‐Argente,Pedro Alonso-Aguirre,Marco Antonio Álvarez,Carla J. Gargallo-Puyuelo,María Pellisé,Felipe Ramos Zabala,Alberto Herreros de Tejada,Óscar Nogales,David Martı́nez-Ares,Fernándo Múgica,Joaquín de la Peña,Jorge C. Espinós,Alaín Huerta,Alberto Álvarez,Jesús Garrido,Francisco Navajas,Juan Gabriel Martínez‐Cara,Eduardo Redondo‐Cerezo,Josep Merlo Mas,Fernando Sábado,Liseth Rivero,Esteban Saperas,Santiago Soto,Joaquín Rodríguez‐Sánchez,Leopoldo López-Rosés,Manuel Rodríguez-Téllez,María Rullán,Alfonso Elosúa González,Remedios Pardeiro,Eduardo Valdivielso Cortázar,Mar Concepción-Martín,Patricia Huelin Álvarez,Juan Colán‐Hernández,Julyssa Cobián,José Santiago,Alejandro Jiménez,David Remedios,Bartolomé López-Viedma,Orlando García,Felipe Martínez-Alcalá,Francisco Pérez-Roldán,Jorge Carbó,Mónica Enguita
摘要
Background and Aims The Endoscopic Resection Group of the Spanish Society of Endoscopy (GSEED-RE) model and the Australian Colonic Endoscopic Resection (ACER) model were proposed to predict delayed bleeding (DB) after EMR of large superficial colorectal lesions, but neither has been validated. We validated and updated these models. Methods A multicenter cohort study was performed in patients with nonpedunculated lesions ≥20 mm removed by EMR. We assessed the discrimination and calibration of the GSEED-RE and ACER models. Difficulty performing EMR was subjectively categorized as low, medium, or high. We created a new model, including factors associated with DB in 3 cohort studies. Results DB occurred in 45 of 1034 EMRs (4.5%); it was associated with proximal location (odds ratio [OR], 2.84; 95% confidence interval [CI], 1.31-6.16), antiplatelet agents (OR, 2.51; 95% CI, .99-6.34) or anticoagulants (OR, 4.54; 95% CI, 2.14-9.63), difficulty of EMR (OR, 3.23; 95% CI, 1.41-7.40), and comorbidity (OR, 2.11; 95% CI, .99-4.47). The GSEED-RE and ACER models did not accurately predict DB. Re-estimation and recalibration yielded acceptable results (GSEED-RE area under the curve [AUC], .64 [95% CI, .54-.74]; ACER AUC, .65 [95% CI, .57-.73]). We used lesion size, proximal location, comorbidity, and antiplatelet or anticoagulant therapy to generate a new model, the GSEED-RE2, which achieved higher AUC values (.69-.73; 95% CI, .59-.80) and exhibited lower susceptibility to changes among datasets. Conclusions The updated GSEED-RE and ACER models achieved acceptable prediction levels of DB. The GSEED-RE2 model may achieve better prediction results and could be used to guide the management of patients after validation by other external groups. (Clinical trial registration number: NCT 03050333.) The Endoscopic Resection Group of the Spanish Society of Endoscopy (GSEED-RE) model and the Australian Colonic Endoscopic Resection (ACER) model were proposed to predict delayed bleeding (DB) after EMR of large superficial colorectal lesions, but neither has been validated. We validated and updated these models. A multicenter cohort study was performed in patients with nonpedunculated lesions ≥20 mm removed by EMR. We assessed the discrimination and calibration of the GSEED-RE and ACER models. Difficulty performing EMR was subjectively categorized as low, medium, or high. We created a new model, including factors associated with DB in 3 cohort studies. DB occurred in 45 of 1034 EMRs (4.5%); it was associated with proximal location (odds ratio [OR], 2.84; 95% confidence interval [CI], 1.31-6.16), antiplatelet agents (OR, 2.51; 95% CI, .99-6.34) or anticoagulants (OR, 4.54; 95% CI, 2.14-9.63), difficulty of EMR (OR, 3.23; 95% CI, 1.41-7.40), and comorbidity (OR, 2.11; 95% CI, .99-4.47). The GSEED-RE and ACER models did not accurately predict DB. Re-estimation and recalibration yielded acceptable results (GSEED-RE area under the curve [AUC], .64 [95% CI, .54-.74]; ACER AUC, .65 [95% CI, .57-.73]). We used lesion size, proximal location, comorbidity, and antiplatelet or anticoagulant therapy to generate a new model, the GSEED-RE2, which achieved higher AUC values (.69-.73; 95% CI, .59-.80) and exhibited lower susceptibility to changes among datasets. The updated GSEED-RE and ACER models achieved acceptable prediction levels of DB. The GSEED-RE2 model may achieve better prediction results and could be used to guide the management of patients after validation by other external groups. (Clinical trial registration number: NCT 03050333.)