Pai, R K

Objective Effective medical therapy and validated trial outcomes are lacking for small bowel Crohn’s disease (CD) strictures. Histopathology of surgically resected specimens is the gold standard for correlation with imaging techniques. However, no validated histopathological scoring systems are currently available for small bowel stricturing disease. We convened an expert panel to evaluate the appropriateness of histopathology scoring systems and items generated based on panel opinion. Design Modified RAND/University of California Los Angeles methodology was used to determine the appropriateness of 313 candidate items related to assessment of CD small bowel strictures. Results In this exercise, diagnosis of naïve and anastomotic strictures required increased bowel wall thickness, decreased luminal diameter or internal circumference, and fibrosis of the submucosa. Specific definitions for stricture features and technical sampling parameters were also identified. Histopathologically, a stricture was defined as increased thickness of all layers of the bowel wall, fibrosis of the submucosa and bowel wall, and muscularisation of the submucosa. Active mucosal inflammatory disease was defined as neutrophilic inflammation in the lamina propria and any crypt or intact surface epithelium, erosion, ulcer and fistula. Chronic mucosal inflammatory disease was defined as crypt architectural distortion and loss, pyloric gland metaplasia, Paneth cell hyperplasia, basal lymphoplasmacytosis, plasmacytosis and fibrosis, or prominent lymphoid aggregates at the mucosa/submucosa interface. None of the scoring systems used to assess CD strictures were considered appropriate for clinical trials. Conclusion Standardised assessment of gross pathology and histopathology of CD small bowel strictures will improve clinical trial efficiency and aid drug development.

Abstract Background Incidence of early-onset (younger than 50 years of age) colorectal cancer (CRC) is increasing in many countries. Thus, elucidating the role of traditional CRC risk factors in early-onset CRC is a high priority. We sought to determine whether risk factors associated with late-onset CRC were also linked to early-onset CRC and whether association patterns differed by anatomic subsite. Methods Using data pooled from 13 population-based studies, we studied 3767 CRC cases and 4049 controls aged younger than 50 years and 23 437 CRC cases and 35 311 controls aged 50 years and older. Using multivariable and multinomial logistic regression, we estimated odds ratios (ORs) and 95% confidence intervals (CIs) to assess the association between risk factors and early-onset CRC and by anatomic subsite. Results Early-onset CRC was associated with not regularly using nonsteroidal anti-inflammatory drugs (OR = 1.43, 95% CI = 1.21 to 1.68), greater red meat intake (OR = 1.10, 95% CI = 1.04 to 1.16), lower educational attainment (OR = 1.10, 95% CI = 1.04 to 1.16), alcohol abstinence (OR = 1.23, 95% CI = 1.08 to 1.39), and heavier alcohol use (OR = 1.25, 95% CI = 1.04 to 1.50). No factors exhibited a greater excess in early-onset compared with late-onset CRC. Evaluating risks by anatomic subsite, we found that lower total fiber intake was linked more strongly to rectal (OR = 1.30, 95% CI = 1.14 to 1.48) than colon cancer (OR = 1.14, 95% CI = 1.02 to 1.27; P = .04). Conclusion In this large study, we identified several nongenetic risk factors associated with early-onset CRC, providing a basis for targeted identification of those most at risk, which is imperative in mitigating the rising burden of this disease.

Abstract Background: Inherited susceptibility is an important contributor to colorectal cancer risk, and rare variants in key genes or pathways could account in part for the missing proportion of colorectal cancer heritability. Methods: We conducted an exome-wide association study including 2,327 cases and 2,966 controls of European ancestry from three large epidemiologic studies. Single variant associations were tested using logistic regression models, adjusting for appropriate study-specific covariates. In addition, we examined the aggregate effects of rare coding variation at the gene and pathway levels using Bayesian model uncertainty techniques. Results: In an exome-wide gene-level analysis, we identified ST6GALNAC2 as the top associated gene based on the Bayesian risk index (BRI) method [summary Bayes factor (BF)BRI = 2604.23]. A rare coding variant in this gene, rs139401613, was the top associated variant (P = 1.01 × 10–6) in an exome-wide single variant analysis. Pathway-level association analyses based on the integrative BRI (iBRI) method found extreme evidence of association with the DNA repair pathway (BFiBRI = 17852.4), specifically with the nonhomologous end joining (BFiBRI = 437.95) and nucleotide excision repair (BFiBRI = 36.96) subpathways. The iBRI method also identified RPA2, PRKDC, ERCC5, and ERCC8 as the top associated DNA repair genes (summary BFiBRI ≥ 10), with rs28988897, rs8178232, rs141369732, and rs201642761 being the most likely associated variants in these genes, respectively. Conclusions: We identified novel variants and genes associated with colorectal cancer risk and provided additional evidence for a role of DNA repair in colorectal cancer tumorigenesis. Impact: This study provides new insights into the genetic predisposition to colorectal cancer, which has potential for translation into improved risk prediction.

AimsTo develop and validate a deep learning algorithm to quantify a broad spectrum of histological features in colorectal carcinoma.Methods and resultsA deep learning algorithm was trained on haematoxylin and eosin‐stained slides from tissue microarrays of colorectal carcinomas (N = 230) to segment colorectal carcinoma digitised images into 13 regions and one object. The segmentation algorithm demonstrated moderate to almost perfect agreement with interpretations by gastrointestinal pathologists, and was applied to an independent test cohort of digitised whole slides of colorectal carcinoma (N = 136). The algorithm correctly classified mucinous and high‐grade tumours, and identified significant differences between mismatch repair‐proficient and mismatch repair‐deficient (MMRD) tumours with regard to mucin, inflammatory stroma, and tumour‐infiltrating lymphocytes (TILs). A cutoff of >44.4 TILs per mm2 carcinoma gave a sensitivity of 88% and a specificity of 73% in classifying MMRD carcinomas. Algorithm measures of tumour budding (TB) and poorly differentiated clusters (PDCs) outperformed TB grade derived from routine sign‐out, and compared favourably with manual counts of TB/PDCs with regard to lymphatic, venous and perineural invasion. Comparable associations were seen between algorithm measures of TB/PDCs and manual counts of TB/PDCs for lymph node metastasis (all P < 0.001); however, stronger correlations were seen between the proportion of positive lymph nodes and algorithm measures of TB/PDCs. Stronger associations were also seen between distant metastasis and algorithm measures of TB/PDCs (P = 0.004) than between distant metastasis and TB (P = 0.04) and TB/PDC counts (P = 0.06).ConclusionsOur results highlight the potential of deep learning to identify and quantify a broad spectrum of histological features in colorectal carcinoma.

Summary Background Regulatory requirements for claims of mucosal healing in ulcerative colitis ( UC ) will require demonstration of both endoscopic and histologic healing. Quantifying these rates is essential for future drug development. Aims To meta‐analyse endoscopic and histologic placebo response and remission rates in UC randomised controlled trials ( RCT s) and identify factors influencing these rates. Methods MEDLINE , EMBASE and the Cochrane Library were searched from inception to March 2017 for placebo‐controlled trials of pharmacological interventions for UC . Endoscopic and histologic placebo rates were pooled by random effects. Mixed effects univariable and multivariable meta‐regression was used to evaluate the influence of patient, intervention and trial‐related study‐level covariates on these rates. Results Fifty‐six induction (placebo n = 4171) and 8 maintenance trials (placebo n = 1011) were included. Pooled placebo endoscopic remission and response rates for induction trials were 23% [95 confidence interval ( CI ) 19‐28%] and 35% [95% CI 27‐42%] respectively, and 20% [95% CI 16‐24%] for maintenance of remission. The pooled histologic placebo remission rate was 14% [95% CI 8‐22%] for induction trials. High heterogeneity was observed for all outcomes ( I 2 56.2%‐88.3%). On multivariable meta‐regression, central endoscopy reading was associated with significantly lower endoscopic placebo remission rates (16% vs 25%; OR = 0.52, [95% CI 0.29‐0.92], P = 0.03). On univariable meta‐regression, higher histologic placebo remission was associated with concomitant corticosteroids ( OR = 1.17 [95% CI 1.08‐1.26], P < 0.0001, per 10% increase in corticosteroid use). Conclusions Placebo endoscopic and histologic rates range from 14% to 35% in UC RCT s but are highly heterogeneous. Outcome standardisation may reduce heterogeneity and is needed in this field.