Symptom or faecal immunochemical test based referral criteria for colorectal cancer detection in symptomatic patients: a diagnostic tests study.

BACKGROUND: Symptom based referral criteria for colorectal cancer (CRC) detection are the cornerstone of the strategy to improve prognosis in CRC. In 2017, the National Institute for Health and Care Excellence (NICE) updated their referral criteria (2017 NG12). Recently, several studies have evaluated the faecal haemoglobin (f-Hb) concentration in this setting. The aim of this study is to evaluate the diagnostic accuracy of the 2017 NG12 referral criteria and to compare them with the CG27 referral criteria, the f-Hb concentration and two f-Hb based prediction model: COLONPREDICT and FAST Score. METHODS: This is a post-hoc diagnostic test study performed within the COLONPREDICT study database (1572 patients, CRC prevalence 13.6%). We assessed symptoms, the 2017 NG12 and CG27 referral criteria and determined the f-Hb before performing a colonoscopy. We compared the discriminatory ability using the area under the curve (AUC) and the sensitivity and specificity at pre-stablished thresholds with the McNemar's test. RESULTS: The 2017 NG12 referral criteria discriminatory ability (AUC 0.53; 95% confidence interval- CI 0.49-0.57) was inferior to the CG27 version (AUC 0.59; 95% CI 0.55-0.63; p = 0.01), the f-Hb concentration (AUC 0.86; 95% CI 0.84-0-89; p < 0.001), the COLONPREDICT Score (AUC 0.92; 95% CI 0.91-0.94; p < 0.001) or the FAST Score (AUC 0.87; 95% CI 0.85-0.89; p < 0.001). The number of patients meeting each criteria were as follows: 2017 NG12 and CG27 = 94.1% and 52.2%; f-Hb ≥20 and ≥ 10 µg/g faeces = 38.6 and 44.3%; COLONPREDICT Score ≥ 5.6 and ≥ 3.2 = 29.4 and 63.2% and FAST Score ≥ 4.50 and ≥ 2.12 = 37.1 and 87.0%. The 2017 NG12 criteria were more sensitive (100%) than the CG27 criteria (68.2%), the f-Hb (≥20 µg/g) (91.2%), the f-Hb (≥10 µg/g) (93.5%), the COLONPREDICT Score (≥5.6) (90.1%) and the FAST Score (≥4.50) (89.8%) (p ≤ 0.001) and equivalent to the COLONPREDICT Score (≥3.5) (99.5%) or the FAST Score (≥2.12) (100.0%) (p = 1). However, their specificity (6.8%) was significantly lower than any of the evaluated criteria (50.3%, 69.6%, 63.4%, 78.7%, 45.8%, 71.3%, 13.9%; p < 0.001). CONCLUSION: Referral criteria based on f-Hb measurement, either as a single test or within prediction models, are more accurate than symptom-based referral criteria for CRC detection in symptomatic patients.

Effect of aspirin on the diagnostic accuracy of the faecal immunochemical test for colorectal advanced neoplasia.

BACKGROUND: Aspirin (ASA) is a drug that can cause gastrointestinal lesions and symptoms. Colorectal cancer (CRC) is the most prevalent type of cancer in Western countries. We assessed the effect of aspirin on the diagnostic accuracy of the faecal immunochemical test (FIT) for CRC and/or advanced neoplasia (AN) in patients undergoing colonoscopy for gastrointestinal symptoms. METHODS: We conducted a prospective multicentre observational study of diagnostic tests that included patients with gastrointestinal symptoms undergoing colonoscopy between March 2012 and 2014 (the COLONPREDICT study). Symptoms were assessed and a FIT and blood tests assessing haemoglobin and carcinoembryonic antigen (CEA) levels were performed. RESULTS: The study included 3052 patients: A total of 2567 did not take aspirin (non-user group) and 485 (16%) took aspirin (user group). Continuous treatment with ASA did not change the AUC (0.88, 0.82; p = 0.06), sensitivity (92%, 88%; p = 0.5) or specificity (71%, 67%; p = 0.2) of the FIT for CRC detection. Similarly, we found no differences in the AUC (0.81, 0.79; p = 0.6), sensitivity (74%, 75.5%; p = 0.3) or specificity (76%, 73.6%; p = 0.3) for AN detection. Patients with an aspirin use of ≥ 300 mg/day had a lower prevalence of AN and the sensitivity, specificity and AUC for AN for these patients were 54%, 68% and 0.66, significantly lower than for the non-user group (p = 0.03). CONCLUSIONS: Aspirin does not modify the diagnostic accuracy of FIT for CRC and/or AN in patients with gastrointestinal symptoms. Aspirin use of ≥ 300 mg/day decreases the accuracy of the test.

The fecal hemoglobin concentration, age and sex test score: Development and external validation of a simple prediction tool for colorectal cancer detection in symptomatic patients.

Prediction models for colorectal cancer (CRC) detection in symptomatic patients, based on easily obtainable variables such as fecal haemoglobin concentration (f-Hb), age and sex, may simplify CRC diagnosis. We developed, and then externally validated, a multivariable prediction model, the FAST Score, with data from five diagnostic test accuracy studies that evaluated quantitative fecal immunochemical tests in symptomatic patients referred for colonoscopy. The diagnostic accuracy of the Score in derivation and validation cohorts was compared statistically with the area under the curve (AUC) and the Chi-square test. 1,572 and 3,976 patients were examined in these cohorts, respectively. For CRC, the odds ratio (OR) of the variables included in the Score were: age (years): 1.03 (95% confidence intervals (CI): 1.02-1.05), male sex: 1.6 (95% CI: 1.1-2.3) and f-Hb (0-<20 µg Hb/g feces): 2.0 (95% CI: 0.7-5.5), (20-<200 µg Hb/g): 16.8 (95% CI: 6.6-42.0), ≥200 µg Hb/g: 65.7 (95% CI: 26.3-164.1). The AUC for CRC detection was 0.88 (95% CI: 0.85-0.90) in the derivation and 0.91 (95% CI: 0.90-093; p = 0.005) in the validation cohort. At the two Score thresholds with 90% (4.50) and 99% (2.12) sensitivity for CRC, the Score had equivalent sensitivity, although the specificity was higher in the validation cohort (p < 0.001). Accordingly, the validation cohort was divided into three groups: high (21.4% of the cohort, positive predictive value-PPV: 21.7%), intermediate (59.8%, PPV: 0.9%) and low (18.8%, PPV: 0.0%) risk for CRC. The FAST Score is an easy to calculate prediction tool, highly accurate for CRC detection in symptomatic patients.

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

BACKGROUND: Risk 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. METHODS: This 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. RESULTS: We 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). CONCLUSIONS: COLONPREDICT is a highly accurate prediction model for CRC detection.