Endoscopy 2018; 50(04): S54-S55
DOI: 10.1055/s-0038-1637189
ESGE Days 2018 oral presentations
20.04.2018 – Best abstract awards
Georg Thieme Verlag KG Stuttgart · New York

IN VIVO DIAGNOSTIC ACCURACY OF THE NICE CLASSIFICATION FOR PREDICTING DEEP INVASION IN COLONIC LESIONS

Autor*innen

    , EndoCAR group

  • I Puig

    1   Althaia. Xarxa Assistencial Universitària de Manresa, Endoscopy, Manresa, Spain

  • M López-Cerón

    2   Hospital Clínic i Provincial de Barcelona, Barcelona, Spain

  • A Arnau

    3   Althaia. Xarxa Assistencial Universitària de Manresa, Manresa, Spain

  • O Rosiñol

    3   Althaia. Xarxa Assistencial Universitària de Manresa, Manresa, Spain

  • M Cuatrecasas

    2   Hospital Clínic i Provincial de Barcelona, Barcelona, Spain

  • A Herreros-de-Tejada

    4   Hospital Universitario Puerta de Hierro, Majadahonda, Spain

  • A Fernández

    5   Hospital Clínico Universitario Lozano Blesa, Zaragoza, Spain

  • F Vida

    3   Althaia. Xarxa Assistencial Universitària de Manresa, Manresa, Spain

  • O Nogales Rincón

    6   Hospital General Universitario Gregorio Marañón, Madrid, Spain

  • L De Castro

    7   Complexo Hospitalario Universitario de Vigo, Vigo, Spain

  • J López-Vicente

    8   Hospital Universitario de Móstoles, Móstoles, Spain

  • P Vega

    9   Complexo Hospitalario Universitario de Ourense, Ourense, Spain

  • M Álvarez-González

    10   Hospital del Mar, Barcelona, Spain

  • J González Santiago

    11   Complejo Asistencial Universitario de Salamanca. IBSAL, Salamanca, Spain

  • M Hernández-Conde

    4   Hospital Universitario Puerta de Hierro, Majadahonda, Spain

  • P Díez-Redondo

    12   Hospital Universitario Río Hortega, Valladolid, Spain

  • L Rivero Sánchez

    2   Hospital Clínic i Provincial de Barcelona, Barcelona, Spain

  • A Gimeno-García

    13   Hospital Universitario de Canarias, Universidad de La Laguna, Santa Cruz de Tenerife, Spain

  • A Burgos

    14   Hospital Universitario La Paz, Madrid, Spain

  • J García-Alonso

    15   Hospital Universitario de Fuenlabrada, Fuenlabrada, Spain

  • E Martínez-Bauer

    16   Corporació Sanitària Parc Taulí, Sabadell, Spain

  • B Peñas

    17   Hospital Universitario Ramón y Cajal, Madrid, Spain

  • G Muñoz

    5   Hospital Clínico Universitario Lozano Blesa, Zaragoza, Spain

  • I Peligros

    6   Hospital General Universitario Gregorio Marañón, Madrid, Spain

  • A Tardio Baiges

    7   Complexo Hospitalario Universitario de Vigo, Vigo, Spain

  • C González Lois

    18   Hospital Universitario Puerta de Hierro, Madrid, Spain

  • L Guerra Pastrian

    14   Hospital Universitario La Paz, Madrid, Spain

  • S García Hernández

    13   Hospital Universitario de Canarias, Universidad de La Laguna, Santa Cruz de Tenerife, Spain

  • A Caminoa

    17   Hospital Universitario Ramón y Cajal, Madrid, Spain

  • T Zamora Martínez

    12   Hospital Universitario Río Hortega, Valladolid, Spain

  • L Elbouayadl

    8   Hospital Universitario de Móstoles, Móstoles, Spain

  • M López Carreira

    15   Hospital Universitario de Fuenlabrada, Fuenlabrada, Spain

  • A Casalots Casado

    16   Corporació Sanitària Parc Taulí, Sabadell, Spain

  • N Carames Díaz

    9   Complexo Hospitalario Universitario de Ourense, Ourense, Spain

  • M Iglesias

    10   Hospital del Mar, Barcelona, Spain

  • S del Carmen

    11   Complejo Asistencial Universitario de Salamanca. IBSAL, Salamanca, Spain

  • M López-Ibáñez

    6   Hospital General Universitario Gregorio Marañón, Madrid, Spain

  • M Pantaleón

    10   Hospital del Mar, Barcelona, Spain

  • M Solano

    5   Hospital Clínico Universitario Lozano Blesa, Zaragoza, Spain

  • A Álvarez

    11   Complejo Asistencial Universitario de Salamanca. IBSAL, Salamanca, Spain

  • S Soto

    9   Complexo Hospitalario Universitario de Ourense, Ourense, Spain

  • P Estévez

    7   Complexo Hospitalario Universitario de Vigo, Vigo, Spain

  • M Serra-Burriel

    19   Center for the Prevention and Diagnosis of CoeliCenter for Research in Health and Economics, Universitat Pompeu Fabra, Barcelona, Spain

  • M Bustamante

    20   Hospital Universitario y Politécnico de La Fe, Valencia, Spain

  • D Rodríguez Alcalde

    8   Hospital Universitario de Móstoles, Móstoles, Spain

  • M Pellisé

    2   Hospital Clínic i Provincial de Barcelona, Barcelona, Spain
Weitere Informationen

Publikationsverlauf

Publikationsdatum:
27. März 2018 (online)

Auch verfügbar auf
 

Aims:

  • The NICE 3 category in the NBI International Colorectal Endoscopic classification was designed to predict deep submucosal invasion in colorectal lesions for which surgery is indicated.

  • The primary aim of this study was to assess the diagnostic accuracy of the NICE classification for predicting deep submucosal invasion in routine clinical practice.

  • The secondary aim was to determine its accuracy combined with the appreciation of other lesion characteristics.

Methods:

  • Multicenter, prospective, observational diagnostic accuracy study conducted by 58 endoscopists at 17 university and community hospitals in their routine clinical practice.

  • All consecutive lesions > 1 cm assessed with NBI were included.

  • The primary outcome was deep invasion according to the index test (NICE classification) and the gold standard (histology).

  • Conditional inference trees were fitted for the analysis of diagnostic accuracy.

Results:

  • Of 2123 lesions analysed, 89 (4.2%) showed deep invasion.

  • Diagnostic accuracy of NICE 3 for predicting deep invasion was: Se = 58.4% (95% CI 47.5 – 68.8), Sp = 96.4% (95% CI 95.5 – 97.2), PPV = 41.6% (95% CI 32.9 – 50.8), and NPV = 98.1% (95% CI 97.5 – 98.7).

  • A conditional inference tree including all the variables showed that the NICE classification was the best predictor of deep invasion (p < 0.001). Further, statistically significant changes in the probability of deep invasion were found in NICE 3 pedunculated polyps (13%, p = 0.007) and NICE 3 non-pedunculated and ulcerated lesions (93%, p = 0.026). By contrast, deep invasion were more frequent in lesions NICE 1/2 if depressed areas (9.7%, p < 0.001) or nodular mixed type morphology (8.6% p < 0.001) was present, but exceptional in the remaining NICE 1/2 lesions (1.1% p < 0.001).

Conclusions:

  • The diagnostic accuracy of optical diagnosis is limited.

  • However, the NICE classification is the best known tool for predicting deep invasion, even without magnification and when used by non-expert endoscopists.

  • This classification could be improved by including certain morphologies and groß morphological malignant features.