Diagnostic Accuracy of Point-of-Care Fecal Calprotectin and Immunochemical Occult Blood Tests for Diagnosis of Organic Bowel Disease in Primary Care: The Cost-Effectiveness of a Decision Rule for Abdominal Complaints in Primary Care (CEDAR) Study

BACKGROUND: Fecal biomarker tests that differentiate between organic bowel disease (OBD) and non-OBD in primary care patients with persistent lower-abdomen complaints could reduce the number of unnecessary referrals for endoscopy. We quantified the accuracy of fecal calprotectin and immunochemical occult blood (iFOBT) point-of-care (POC) tests and a calprotectin ELISA in primary care patients with suspected OBD. METHODS: We performed biomarker tests on fecal samples from 386 patients with lower-abdomen complaints suggestive for OBD. Endoscopic and histological diagnosis served as reference. RESULTS: OBD was diagnosed in 99 patients (prevalence 25.9%); 19 had adenocarcinoma, 53 adenoma, and 27 inflammatory bowel disease. Sensitivity for OBD was 0.64 (95% CI 0.54-0.72) for calprotectin POC, 0.56 (0.46-0.66) for iFOBT POC, and 0.74 (0.65-0.82) for calprotectin ELISA; specificities were 0.53 (0.48-0.59), 0.83 (0.78-0.87), and 0.47 (0.41-0.53), respectively. Negative predictive values (NPVs) were 0.81 (0.74-0.86), 0.85 (0.80-0.88), and 0.84 (0.78-0.89); positive predictive values (PPVs) varied from 0.32 (0.26-0.39) and 0.33 (0.27-0.39) (calprotectin tests) to 0.53 (0.44-0.63) (iFOBT POC). Combining the 2 POC tests improved sensitivity [0.79 (0.69-0.86)] and NPV [0.87 (0.81-0.91)] but lowered specificity [0.49 (0.44-0.55)] and PPV [0.35 (0.29-0.42)]. When adenomas 0.90 [combined POC tests, 0.97 (0.93-0.99)]. CONCLUSIONS: Diagnostic accuracy of the tests alone or combined was insufficient when all adenomas were considered OBD. When only adenomas >1 cm were considered OBD, all tests could rule out OBD to a reasonable extent, particularly the combined POC tests. The tests were less useful for inclusion of OBD

Is there an added value of faecal calprotectin and haemoglobin in the diagnostic work-up for primary care patients suspected of significant colorectal disease? A cross-sectional diagnostic study

Background The majority of primary care patients referred for bowel endoscopy do not have significant colorectal disease (SCD), and are – in hindsight – unnecessarily exposed to a small but realistic risk of severe endoscopy-associated complications. We developed a diagnostic strategy to better exclude SCD in these patients and evaluated the value of adding a faecal calprotectin point-of-care (POC) and/or a POC faecal immunochemical test for haemoglobin (FIT) to routine clinical information. Methods We used data from a prospective diagnostic study in SCD-suspected patients from 266 Dutch primary care practices referred for endoscopy to develop a diagnostic model for SCD with routine clinical information, which we extended with faecal calprotectin POC (quantitatively in μg/g faeces) and/or POC FIT results (qualitatively with a 6 μg/g faeces detection limit). We defined SCD as colorectal cancer (CRC), inflammatory bowel disease, diverticulitis, or advanced adenoma (>1 cm). Results Of 810 patients, 141 (17.4 %) had SCD. A diagnostic model with routine clinical data discriminated between patients with and without SCD with an area under the receiver operating characteristic curve (AUC) of 0.741 (95 % CI, 0.694–0.789). This AUC increased to 0.763 (95 % CI, 0.718–0.809; P = 0.078) when adding the calprotectin POC test, to 0.831 (95 % CI, 0.791–0.872; P < 0.001) when adding the POC FIT, and to 0.837 (95 % CI, 0.798–0.876; P < 0.001) upon combined extension. At a ≥ 5.0 % SCD probability threshold for endoscopy referral, 30.4 % of the patients tested negative based on this combined POC-tests extended model (95 % CI, 25.7–35.3 %), with 96.4 % negative predictive value (95 % CI, 93.1–98.2 %) and 93.7 % sensitivity (95 % CI, 88.2–96.8 %). Excluding the calprotectin POC test from this model still yielded 30.1 % test negatives (95 % CI, 24.7–35.6 %) and 96.0 % negative predictive value (95 % CI, 92.6–97.9 %), with 93.0 % sensitivity (95 % CI, 87.4–96.4 %). Conclusions FIT – and to a much lesser extent calprotectin – POC testing showed incremental value for SCD diagnosis beyond standard clinical information. A diagnostic strategy with routine clinical data and a POC FIT test may safely rule out SCD and prevent unnecessary endoscopy referral in approximately one third of SCD-suspected primary care patients

Published diagnostic models safely excluded colorectal cancer in an independent primary care validation study

OBJECTIVE: To validate published diagnostic models for their ability to safely reduce unnecessary endoscopy referrals in primary care patients suspected of significant colorectal disease. STUDY DESIGN AND SETTING: Following a systematic literature search, we independently validated the identified diagnostic models in a cross-sectional study of 810 Dutch primary care patients with persistent lower abdominal complaints referred for endoscopy. We estimated diagnostic accuracy measures for colorectal cancer (N=37) and significant colorectal disease (N=141; including colorectal cancer, inflammatory bowel disease, diverticulitis, or >1cm adenomas). RESULTS: We evaluated 18 models - 12 specific for colorectal cancer -, of which most were able to safely rule out colorectal cancer: the best model (NICE-1) prevented 59% of referrals (95% confidence interval (CI): 56-63%), with 96% sensitivity (95%CI: 83-100%), 100% negative predictive value (NPV; 95%CI: 99-100%), and an area under the receiver operating characteristics curve (AUC) of 0.86 (95%CI: 0.80-0.92). The models performed less for significant colorectal disease: the best model (Brazer) prevented 23% of referrals (95%CI: 20-26%), with 95% sensitivity (95%CI: 90-98%), 96% NPV (95%CI: 92-98%), and an AUC of 0.73 (95%CI: 0.69-0.78). CONCLUSION: Most models safely excluded colorectal cancer in many primary care patients with lower gastrointestinal complaints referred for endoscopy. Models performed less well for significant colorectal disease

Published diagnostic models safely excluded colorectal cancer in an independent primary care validation study

OBJECTIVE: To validate published diagnostic models for their ability to safely reduce unnecessary endoscopy referrals in primary care patients suspected of significant colorectal disease. STUDY DESIGN AND SETTING: Following a systematic literature search, we independently validated the identified diagnostic models in a cross-sectional study of 810 Dutch primary care patients with persistent lower abdominal complaints referred for endoscopy. We estimated diagnostic accuracy measures for colorectal cancer (N=37) and significant colorectal disease (N=141; including colorectal cancer, inflammatory bowel disease, diverticulitis, or >1cm adenomas). RESULTS: We evaluated 18 models - 12 specific for colorectal cancer -, of which most were able to safely rule out colorectal cancer: the best model (NICE-1) prevented 59% of referrals (95% confidence interval (CI): 56-63%), with 96% sensitivity (95%CI: 83-100%), 100% negative predictive value (NPV; 95%CI: 99-100%), and an area under the receiver operating characteristics curve (AUC) of 0.86 (95%CI: 0.80-0.92). The models performed less for significant colorectal disease: the best model (Brazer) prevented 23% of referrals (95%CI: 20-26%), with 95% sensitivity (95%CI: 90-98%), 96% NPV (95%CI: 92-98%), and an AUC of 0.73 (95%CI: 0.69-0.78). CONCLUSION: Most models safely excluded colorectal cancer in many primary care patients with lower gastrointestinal complaints referred for endoscopy. Models performed less well for significant colorectal disease

Published diagnostic models safely excluded colorectal cancer in an independent primary care validation study

OBJECTIVE: To validate published diagnostic models for their ability to safely reduce unnecessary endoscopy referrals in primary care patients suspected of significant colorectal disease. STUDY DESIGN AND SETTING: Following a systematic literature search, we independently validated the identified diagnostic models in a cross-sectional study of 810 Dutch primary care patients with persistent lower abdominal complaints referred for endoscopy. We estimated diagnostic accuracy measures for colorectal cancer (N=37) and significant colorectal disease (N=141; including colorectal cancer, inflammatory bowel disease, diverticulitis, or >1cm adenomas). RESULTS: We evaluated 18 models - 12 specific for colorectal cancer -, of which most were able to safely rule out colorectal cancer: the best model (NICE-1) prevented 59% of referrals (95% confidence interval (CI): 56-63%), with 96% sensitivity (95%CI: 83-100%), 100% negative predictive value (NPV; 95%CI: 99-100%), and an area under the receiver operating characteristics curve (AUC) of 0.86 (95%CI: 0.80-0.92). The models performed less for significant colorectal disease: the best model (Brazer) prevented 23% of referrals (95%CI: 20-26%), with 95% sensitivity (95%CI: 90-98%), 96% NPV (95%CI: 92-98%), and an AUC of 0.73 (95%CI: 0.69-0.78). CONCLUSION: Most models safely excluded colorectal cancer in many primary care patients with lower gastrointestinal complaints referred for endoscopy. Models performed less well for significant colorectal disease

Additional file 1: of Is there an added value of faecal calprotectin and haemoglobin in the diagnostic work-up for primary care patients suspected of significant colorectal disease? A cross-sectional diagnostic study

Supplementary appendix. Contents: interaction between POC FIT and overt rectal bleeding; Table S1: model development strategy and specification; Table S2: reclassification table combined POC extended model versus basic diagnostic model; Table S3: reclassification table POC FIT extended model versus basic diagnostic model; Table S4: optimism corrected parameters for the basic model, the calprotectin POC extended model, the calprotectin ELISA extended model, and the calprotectin ELISA and POC FIT extended model; Figure S1: calibration curves; Figure S2: decision curve analysis; Figure S3: ROC curves subsitituting calprotectin POC with ELISA; Figure S4: nomogram of the combined POC extended model; Figure S5: nomogram of the POC FIT extended model. (DOCX 2031 kb