Battat, Robert

SummaryBackgroundThe optimal ulcerative colitis biopsy protocol is unclear.AimTo evaluate the number of biopsies required to accurately assess microscopic disease activity in ulcerative colitisMethodsBiopsies from patients with ≥4 rectosigmoid samples, and clinical and endoscopic data, were retrospectively obtained from a prospective biobank. Histology and endoscopic videos were read blindly. A 4‐biopsy Robarts Histopathology Index (RHI) reference score, consisting of the worst item‐level ratings from four biopsies, was compared to 1‐, 2‐ and 3‐biopsy estimates. Agreement was determined using bivariate errors‐in‐variable regression analysis (acceptance interval: ±8.25). Endoscopic activity and disease location subgroup analyses were also performed.ResultsForty‐six patients had ≥4 rectosigmoid biopsies available (N = 287). The 2‐biopsy (tolerance interval: −7.66, 4.79) and 3‐biopsy (tolerance interval: −4.86, 3.46) RHI scores demonstrated acceptable agreement with 4‐biopsy scores. One‐biopsy scores demonstrated unacceptable agreement (tolerance interval: −13.99, 7.78). Mean RHI scores using the 2‐, 3‐ and 4‐biopsy approaches were similar (6.1 ± 9.6 P = 0.36; 6.8 ± 10.5, P = 0.7; 7.5 ± 11.2), whereas the 1‐biopsy estimate was lower (4.4 ± 8.1, P = 0.06). Histological remission rates were identical for the 2‐, 3‐ and 4‐biopsy methods (65.2%, P = 1.0). Subgroup analysis demonstrated that three biopsies were required in patients with endoscopically active disease. Sampling additional colonic locations yielded lower histological remission rates compared to rectosigmoid sampling alone (33.3% vs 61.9%, P = 0.1).ConclusionsA minimum of two — conservatively, three — biopsies are required to reliably assess disease activity in a single colonic segment using the RHI. Further studies are needed of endoscopically active patients and sampling locations. These results have implications for biopsy strategies in clinical trials and practice.

Abstract Background and Aim Data are lacking on predicting inpatient mortality (IM) in patients admitted for inflammatory bowel disease (IBD). IM is a critical outcome; however, difficulty in its prediction exists due to infrequent occurrence. We assessed IM predictors and developed a predictive model for IM using machine‐learning (ML). Methods Using the National Inpatient Sample (NIS) database (2005–2017), we extracted adults admitted for IBD. After ML‐guided predictor selection, we trained and internally validated multiple algorithms, targeting minimum sensitivity and positive likelihood ratio (+LR) ≥ 80% and ≥ 3, respectively. Diagnostic odds ratio (DOR) compared algorithm performance. The best performing algorithm was additionally trained and validated for an IBD‐related surgery sub‐cohort. External validation was done using NIS 2018. Results In 398 426 adult IBD admissions, IM was 0.32% overall, and 0.87% among the surgical cohort ( n = 40 784). Increasing age, ulcerative colitis, IBD‐related surgery, pneumonia, chronic lung disease, acute kidney injury, malnutrition, frailty, heart failure, blood transfusion, sepsis/septic shock and thromboembolism were associated with increased IM. The QLattice algorithm, provided the highest performance model (+LR: 3.2, 95% CI 3.0–3.3; area‐under‐curve [AUC]:0.87, 85% sensitivity, 73% specificity), distinguishing IM patients by 15.6‐fold when comparing high to low‐risk patients. The surgical cohort model (+LR: 8.5, AUC: 0.94, 85% sensitivity, 90% specificity), distinguished IM patients by 49‐fold. Both models performed excellently in external validation. An online calculator ( https://clinicalc.ai/im‐ibd/ ) was developed allowing bedside model predictions. Conclusions An online prediction‐model calculator captured > 80% IM cases during IBD‐related admissions, with high discriminatory effectiveness. This allows for risk stratification and provides a basis for assessing interventions to reduce mortality in high‐risk patients.

INTRODUCTION: We applied the Grading of Recommendations, Assessment, Development, and Evaluation framework to evaluate the performance of fecal calprotectin (FC) as an alternative to endoscopy in patients with moderate-to-severe ulcerative colitis (UC) treated with a biologic agent or tofacitinib. METHODS: Individual participant data from the trials of infliximab, golimumab, vedolizumab, and tofacitinib for UC were pooled to generate prevalence of endoscopic activity (Mayo endoscopy score) across different combinations of the rectal bleeding score (RBS) and stool frequency score (SFS). These estimates were then combined with the data from an updated systematic review of the operating properties of FC to generate clinical scenario–specific assessments of the performance of FC as a predictor of endoscopic disease activity. A prespecified threshold of acceptability for false-negative (FN) and false-positive (FP) test results was set at 5%. RESULTS: For patients with UC achieving RBS 0 + SFS 0/1, FC ≤ 50 μg/g may avoid endoscopy in 50% patients with a FN rate <5%. Similarly, for patients with RBS 2/3 + SFS 2/3, FC ≥ 250 μg/g potentially avoids endoscopy in approximately 50% patients with an FP rate <5%. The greatest uncertainty in the diagnostic performance for FC was observed in patients with UC achieving RBS 0 but having SFS 2/3, where FN and FP rates were consistently >10%, and endoscopic evaluation may be warranted. DISCUSSION: Two clinical scenarios were identified where FC can be used with confidence for monitoring treatment response to biologics or tofacitinib in patients with UC without the requirement for endoscopy.

OBJECTIVES: Histologic remission is a potentially valuable means of assessing disease activity and treatment response in ulcerative colitis (UC). However, the efficacy of existing therapies to achieve this outcome is unclear. We performed a systematic review and meta-analysis of histologic outcomes in UC randomized controlled trials and examined the relationship between histologic and endoscopic outcomes. METHODS: MEDLINE, EMBASE, CENTRAL, and the Cochrane IBD Register were searched for randomized controlled trials of aminosalicylates, corticosteroids, immunosuppressives, biologics, and small molecules. Histologic and endoscopic remission and response data were independently extracted and pooled using binomial–normal random-effect or fixed-effect models. Pooled efficacy estimates were calculated as risk ratios (RRs) using the Mantel–Haenszel method. Univariable and multivariable random-effect meta-regression models examined factors associated with histologic remission. RESULTS: Seventy-four studies (68 induction and 7 maintenance) were identified. Topical aminosalicylate enemas [37.2%, 95% confidence interval (CI), 29.0–46.3] and suppositories (44.9%, 95% CI, 28.9–62.3) had the highest induction of histologic remission rates. Aminosalicylate enemas (RR = 4.14, 95% CI, 2.35–7.31), aminosalicylate suppositories (RR = 3.94, 95% CI, 1.26–12.32), and budesonide multimatrix (RR = 1.47, 95% CI 1.08–1.99) had higher histologic remission rates than placebo. Data were lacking for biologics and immunosuppressives. The pooled histologic remission rate for placebo in induction studies was 10.4% (95% CI, 7.1–15.2). Histologic and endoscopic remission correlated strongly ( r = 0.66; 95% CI, 0.50–0.78). In multivariate analysis of placebo-arm data, less severe clinical disease activity and corticosteroid use were associated with higher histologic remission rates. Similarly, mild clinical disease activity was associated with higher histologic remission rates when active-arm data were analyzed. CONCLUSIONS: Histologic remission rates for current UC treatments ranged from 15.0% to 44.9% according to drug class and patient population with the highest rates observed for topical aminosalicylates. Placebo remission rates were low with relatively narrow CIs. These data provide benchmarks to inform future trial design. Histologic remission is a potential treatment target in clinical practice.