Development and external validation of a faecal immunochemical test-based prediction model for colorectal cancer detection in symptomatic patients

BMC Medicine

Research Article

Marta Díaz-Ondina¹  Daniel Rodríguez-Alcalde²  Luis Bujanda³  Victoria Álvarez-Sánchez⁴  Pablo Vega⁵  María Salve⁵  Javier Fernández-Seara⁶  Joaquín Cubiella⁶  Jaume Boadas⁷  Leyanira Torrealba⁸  Virginia Piñol⁸  Fernando Fernández-Bañares⁹  Enrique Quintero^1,10  Rafel Campo^1,11  Joan Clofent^1,12  Vicent Hernández^1,13  Maria Teresa Alves^1,14  Ángel Ferrandez^1,15 

[1] Clinical Analysis Department, Complexo Hospitalario Universitario de Ourense, Rua Ramón Puga 52-54, 32003, Ourense, Spain;Digestive Disease Section, Hospital Universitario de Móstoles Río Júcar, s/n, 28935, Mostoles, Madrid, Spain;Donostia Hospital, Biodonostia Institute, University of the Basque Country UPV/EHU, (CIBERehd), Paseo del Doctor Begiristain 117, 20080, San Sebastian, Guipuzcoa, Spain;Gastroenterology Department, Complejo Hospitalario de Pontevedra, Av. Montecelo, 36164 Casas Novas, Pontevedra, Spain;Gastroenterology Department, Complexo Hospitalario Universitario de Ourense, Rua Ramón Puga 52-54, 32005, Ourense, Spain;Gastroenterology Department, Complexo Hospitalario Universitario de Ourense, Rua Ramón Puga 52-54, 32005, Ourense, Spain;Instituto de Investigación Biomedica (IBI) Ourense, Pontevedra y Vigo, Vigo, Rua Ramón Puga 52-54, 32003, Ourense, Spain;Gastroenterology Department, Consorci Sanitari de Terrassa, Carr. Torrebonica, S/N, 08227, Terrassa, Barcelona, Spain;Gastroenterology Department, Hospital Dr. Josep Trueta, Avenida de Francia, s/n, 17007, Girona, Spain;Gastroenterology Department, Hospital Universitari Mútua de Terrassa, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Plaça del Doctor Robert, 5, 08221, Terrassa, Barcelona, Spain;Gastroenterology Department, Hospital Universitario de Canarias, Instituto Universitario de Tecnologías Biomédicas (ITB) & Centro de Investigación Biomédica de Canarias (CIBICAN), Universidad de La Laguna, Carretera de Ofra, s/n, 38320, San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain;Gastroenterology Department, Hospital de Sabadell, Corporació Sanitària i Universitària Parc Taulí, Parc Taulí, 1, 08208, Sabadell, Barcelona, Spain;Gastroenterology Department, Hospital de Sagunto, Avenida Ramón y Cajal, S/N, 46520, Sagunto, Valencia, Spain;Instituto de Investigación Biomedica (IBI) Ourense, Pontevedra y Vigo, Vigo, Rua Ramón Puga 52-54, 32003, Ourense, Spain;Gastroenterology Department, Vigo, Pontevedra, Spain;NECOM Group, University of Vigo, Campus Universitario As Lagoas, Marcosende, 36310, Vigo, Spain;Servicio de Aparato Digestivo, Hospital Clínico Universitario, IIS Aragón, University of Zaragoza, (CIBERehd), Avda. San Juan Bosco, 15, 50009, Zaragoza, Spain;

关键词: Colorectal cancer;    Faecal immunochemical test;    Colonoscopy;    Diagnostic accuracy;    Risk stratification;    Prompt diagnosis;   

DOI  :  10.1186/s12916-016-0668-5

 received in 2016-05-12, accepted in 2016-08-04,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundRisk prediction models for colorectal cancer (CRC) detection in symptomatic patients based on available biomarkers may improve CRC diagnosis. Our aim was to develop, compare with the NICE referral criteria and externally validate a CRC prediction model, COLONPREDICT, based on clinical and laboratory variables.MethodsThis prospective cross-sectional study included consecutive patients with gastrointestinal symptoms referred for colonoscopy between March 2012 and September 2013 in a derivation cohort and between March 2014 and March 2015 in a validation cohort. In the derivation cohort, we assessed symptoms and the NICE referral criteria, and determined levels of faecal haemoglobin and calprotectin, blood haemoglobin, and serum carcinoembryonic antigen before performing an anorectal examination and a colonoscopy. A multivariate logistic regression analysis was used to develop the model with diagnostic accuracy with CRC detection as the main outcome.ResultsWe included 1572 patients in the derivation cohort and 1481 in the validation cohorts, with a 13.6 % and 9.1 % CRC prevalence respectively. The final prediction model included 11 variables: age (years) (odds ratio [OR] 1.04, 95 % confidence interval [CI] 1.02–1.06), male gender (OR 2.2, 95 % CI 1.5–3.4), faecal haemoglobin ≥20 μg/g (OR 17.0, 95 % CI 10.0–28.6), blood haemoglobin <10 g/dL (OR 4.8, 95 % CI 2.2–10.3), blood haemoglobin 10–12 g/dL (OR 1.8, 95 % CI 1.1–3.0), carcinoembryonic antigen ≥3 ng/mL (OR 4.5, 95 % CI 3.0–6.8), acetylsalicylic acid treatment (OR 0.4, 95 % CI 0.2–0.7), previous colonoscopy (OR 0.1, 95 % CI 0.06–0.2), rectal mass (OR 14.8, 95 % CI 5.3–41.0), benign anorectal lesion (OR 0.3, 95 % CI 0.2–0.4), rectal bleeding (OR 2.2, 95 % CI 1.4–3.4) and change in bowel habit (OR 1.7, 95 % CI 1.1–2.5). The area under the curve (AUC) was 0.92 (95 % CI 0.91–0.94), higher than the NICE referral criteria (AUC 0.59, 95 % CI 0.55–0.63; p < 0.001). On the basis of the thresholds with 90 % (5.6) and 99 % (3.5) sensitivity, we divided the derivation cohort into three risk groups for CRC detection: high (30.9 % of the cohort, positive predictive value [PPV] 40.7 %, 95 % CI 36.7–45.9 %), intermediate (29.5 %, PPV 4.4 %, 95 % CI 2.8–6.8 %) and low (39.5 %, PPV 0.2 %, 95 % CI 0.0–1.1 %). The discriminatory ability was equivalent in the validation cohort (AUC 0.92, 95 % CI 0.90–0.94; p = 0.7).ConclusionsCOLONPREDICT is a highly accurate prediction model for CRC detection.

【 授权许可】

CC BY   
© The Author(s). 2016