Development of an algorithm combining blood-based biomarkers, fecal immunochemical test, and age for population-based colorectal cancer screening.

BACKGROUND AND AIMS: Implementation of screening modalities have reduced the burden of colorectal cancer (CRC), but high false positive rates pose a major problem for colonoscopy capacity. We aimed to create a tailored screening algorithm that expands the fecal immunochemical test (FIT) with a blood specimen and current age to improve selection of individuals for diagnostic colonoscopy. METHODS: In this prospective multicenter study, 8 blood-based biomarkers (carcinoembryonic antigen, ferritin, high-sensitivity C-reactive protein, human epididymis protein 4, Cyfra21-1, hepsin, interleukin 8, and osteoprotegerin) were investigated in 1977 FIT-positive individuals from the Danish national CRC screening program undergoing follow-up colonoscopy. Specimens were analyzed on Architect i2000, Architect c8000 (both from Abbott, Chicago, IL, USA), or Luminex xMAP machines (MilliporeSigma, St. Louis, Mo, USA). FIT analyses and blood-based biomarker data were combined with clinical data (ie, age and colonoscopy findings) in a cross-validated logistic regression model (algorithm) benchmarked against a model solely using the FIT result (FIT model) applying different cutoffs for FIT positivity. RESULTS: The cohort included individuals with CRC (n = 240), adenomas (n = 938), or no neoplastic lesions (n = 799). The cross-validated algorithm combining the 8 biomarkers, quantitative FIT result, and age performed superior to the FIT model in discriminating CRC versus non-CRC individuals (area under the receiver operating characteristic curve, 0.77 vs 0.67, respectively; P < .001). When discriminating individuals with either CRC or high- or medium-risk adenomas versus low-risk adenomas or clean colorectum, the areas under the receiver operating characteristic curve were 0.68 versus 0.64 for the algorithm and FIT model, respectively. CONCLUSIONS: The algorithm presented here can improve patient allocation to colonoscopy, reducing colonoscopy burden without compromising cancer and adenoma detection rates or vice versa.

Evaluation of a fully automated high-throughput serology assay for detection of Hepatitis D virus antibodies.

BACKGROUND: HDV antibody testing is recommended for universal screening and as the first line in an HDV double reflex testing strategy for effectively identifying patients with active infection for therapeutic treatments. OBJECTIVE: The aim of this study is to evaluate the performance of a newly developed ARCHITECT HDV Total Ig (ARCHITECT HDV Ig) prototype assay. STUDY DESIGN: Performance characteristics were determined for the ARCHITECT HDV Ig and a reference test, LIAISON XL Anti-HDV using a well-characterized specimen panel, comprising HDV RNA positive (n = 62) and negative (n = 70) samples, and healthy US blood donors. RESULTS: Healthy US blood donors (n=200) showed 99.5% (199/200, 95%CI=97.65-99.98) specificity with ARCHITECT HDV Ig and 98.5 % (197/200, 95 %CI = 96.10-99.64) with LIAISON Anti-HDV. Among known HDV RNA positive samples, ARCHITECT HDV Ig detected 59/62 demonstrating 95.2 % sensitivity while LIAISON Anti-HDV sensitivity was 90.3 % (56/62). Among 101 HBV positive samples, 70 were reactive in the ARCHITECT test, 59 of which tested positive for HDV RNA for a positive predictive value (PPV) for the presence of HDV RNA was 84.3 %. For LIAISON Anti-HDV, 79 specimens were reactive and 56 contained HDV RNA: PPV for HDV RNA was 70.9 %. Among 70 HDV RNA negative samples, 39 were HBV positive. ARCHITECT HDV Ig negative predictive value (NPV) was 71.8 % and LIAISON Anti-HDV NPV was 41 % for the HBV positive group, respectively. CONCLUSION: When compared to the LIASON Anti-HDV test, the ARCHITECT HDV Ig assay demonstrated enhanced sensitivity and specificity and better NPV and PPV values for HDV RNA status. The ARCHITECT HDV Ig assay represents a promising tool for universal screening of all HBsAg-positive persons.