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Accuracy of the Narrow-Band Imaging International Colorectal Endoscopic Classification System in Identification of Deep Invasion in Colorectal Polyps

医学 不错 窄带成像 放射科 结直肠癌 粘膜下层 逻辑回归 接收机工作特性 内窥镜检查 内科学 癌症 计算机科学 程序设计语言
作者
Ignasi Puig,María López‐Cerón,Anna Arnau,Òria Rosiñol,Míriam Cuatrecasas,Alberto Herreros de Tejada,Ángel Ferrández,Miquel Serra‐Burriel,Óscar Nogales,Francesc Vida,Luisa de-Castro,Jorge López-Vicente,Pablo Vega,Marco Antonio Álvarez,Jesús Garrido,Marta Hernández‐Conde,Pilar Díez‐Redondo,Liseth Rivero,Antonio Escobar,Aurora Burgos,Javier Tejedor‐Tejada,Marco Bustamante,Eva Martínez‐Bauer,Beatriz Peñas,María Pellisé,Guillermo Muñoz,Isabel Peligros,Antoni Tardío Baiges,Liliam Elbouayadl,Nuria Carames,Mar Iglesias,Sofía del Carmen,Carmen González-Lois,Henar Núñez,Sonia García Hernández,Laura Guerra,Montserrat López Carreira,Àlex Casalots,Alejandra Caminoa,Marina Asunción Pardina Solano,María López-Ibáñez,Jordi Guardiola,Pamela Estévez,Daniel Rodríguez-Alcalde,Santiago Soto,Miguel Pantaleón Sánchez,Alberto Álvarez,Tomás Zamora Martínez,Juan Manuel del Valle Pascual,Julio Ducóns,Javier Garcıa‐Lledo,Francesc Porta,Vicent Hernández,Joaquín Cubiella,Faust Riu,Miguel Ángel Simón,David Martínez,Agustín Seoane,Fernando Gomollón,Lucía Cid,Carlos Sostres,Fulgencio Domínguez,Ramiro Macenlle,Juan de la Revilla,Álvaro Isava,Rafael Campo,Gema de la Poza,Alfonso Martínez,Paola Quintas,Eloy Sánchez,José Ramón Foruny Olcina,Eva Marín,José Luis Martínez,Maria Inés Castro,Juan Ángel González,Elba Llop,Eduardo Martín-Sanz,Rafael Ubaldo Gosálvez Rey,Pau Sort,J. Montesinos,Marta Fornells,Nàdia Ascon
出处
期刊:Gastroenterology [Elsevier BV]
卷期号:156 (1): 75-87 被引量:89
标识
DOI:10.1053/j.gastro.2018.10.004
摘要

Background & AimsT1 colorectal polyps with at least 1 risk factor for metastasis to lymph node should be treated surgically and are considered endoscopically unresectable. Optical analysis, based on the Narrow-Band Imaging International Colorectal Endoscopic (NICE) classification system, is used to identify neoplasias with invasion of the submucosa that require endoscopic treatment. We assessed the accuracy of the NICE classification, along with other morphologic characteristics, in identifying invasive polyps that are endoscopically unresectable (have at least 1 risk factor for metastasis to lymph node).MethodsWe performed a multicenter, prospective study of data collected by 58 endoscopists, from 1634 consecutive patients (examining 2123 lesions) at 17 university and community hospitals in Spain from July 2014 through June 2016. All consecutive lesions >10 mm assessed with narrow-band imaging were included. The primary end point was the accuracy of the NICE classification for identifying lesions with deep invasion, using findings from histology analysis as the reference standard. Conditional inference trees were fitted for the analysis of diagnostic accuracy.ResultsOf the 2123 lesions analyzed, 89 (4.2%) had features of deep invasion and 91 (4.3%) were endoscopically unresectable. The NICE classification system identified lesions with deep invasion with 58.4% sensitivity (95% CI, 47.5–68.8), 96.4% specificity (95% CI, 95.5–97.2), a positive-predictive value of 41.6% (95% CI, 32.9–50.8), and a negative-predictive value of 98.1% (95% CI, 97.5–98.7). A conditional inference tree that included all variables found the NICE classification to most accurately identify lesions with deep invasion (P < .001). However, pedunculated morphology (P < .007), ulceration (P = .026), depressed areas (P < .001), or nodular mixed type (P < .001) affected accuracy of identification. Results were comparable for identifying lesions that were endoscopically unresectable.ConclusionsIn an analysis of 2123 colon lesions >10 mm, we found the NICE classification and morphologic features identify those with deep lesions with >96% specificity—even in non-expert hands and without magnification. ClinicalTrials.gov number NCT02328066. T1 colorectal polyps with at least 1 risk factor for metastasis to lymph node should be treated surgically and are considered endoscopically unresectable. Optical analysis, based on the Narrow-Band Imaging International Colorectal Endoscopic (NICE) classification system, is used to identify neoplasias with invasion of the submucosa that require endoscopic treatment. We assessed the accuracy of the NICE classification, along with other morphologic characteristics, in identifying invasive polyps that are endoscopically unresectable (have at least 1 risk factor for metastasis to lymph node). We performed a multicenter, prospective study of data collected by 58 endoscopists, from 1634 consecutive patients (examining 2123 lesions) at 17 university and community hospitals in Spain from July 2014 through June 2016. All consecutive lesions >10 mm assessed with narrow-band imaging were included. The primary end point was the accuracy of the NICE classification for identifying lesions with deep invasion, using findings from histology analysis as the reference standard. Conditional inference trees were fitted for the analysis of diagnostic accuracy. Of the 2123 lesions analyzed, 89 (4.2%) had features of deep invasion and 91 (4.3%) were endoscopically unresectable. The NICE classification system identified lesions with deep invasion with 58.4% sensitivity (95% CI, 47.5–68.8), 96.4% specificity (95% CI, 95.5–97.2), a positive-predictive value of 41.6% (95% CI, 32.9–50.8), and a negative-predictive value of 98.1% (95% CI, 97.5–98.7). A conditional inference tree that included all variables found the NICE classification to most accurately identify lesions with deep invasion (P < .001). However, pedunculated morphology (P < .007), ulceration (P = .026), depressed areas (P < .001), or nodular mixed type (P < .001) affected accuracy of identification. Results were comparable for identifying lesions that were endoscopically unresectable. In an analysis of 2123 colon lesions >10 mm, we found the NICE classification and morphologic features identify those with deep lesions with >96% specificity—even in non-expert hands and without magnification. ClinicalTrials.gov number NCT02328066.

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