Clinical Activity and Quality of Life Indices Are Valid Across Ulcerative Colitis But Not Crohn’s Disease Phenotypes

Background Clinical activity and quality of life (QOL) indices assess disease activity in Crohn’s disease (CD) and ulcerative colitis (UC). However, a paucity of data exists on the validity of these indices according to disease characteristics. Aims To examine the correlation between QOL and clinical activity indices and endoscopic disease activity according to disease characteristics. Methods We used a prospective registry to identify CD and UC patients ≥18 years old with available information on Short Inflammatory Bowel Disease Questionnaire scores (SIBDQ), Harvey–Bradshaw Index (HBI) and simple endoscopic scores for CD (SES-CD), and Simple Clinical Colitis Activity Index (SCCAI) and Mayo endoscopic score for UC. We used Spearman rank correlations to calculate correlations between indices and Fisher transformation to compare correlations across disease characteristics. Results Among 282 CD patients, we observed poor correlation between clinical activity and QOL indices to SES-CD with no differences in correlation according to disease characteristics. Conversely, among 226 UC patients, clinical activity and QOL had good correlation to Mayo endoscopic score (r = 0.55 and −0.56, respectively) with better correlations observed with left-sided versus extensive colitis (r = 0.73 vs. 0.45, p = 0.005) and shorter duration of disease (r = 0.61 vs. 0.37, p = 0.04). Conclusions Our data suggest good correlation between SCCAI and endoscopic disease activity in UC, particularly in left-sided disease. Poor correlations between HBI or SIBDQ and SES-CD appear to be consistent across different disease phenotypes.American Gastroenterological Associatio

Early life environment and natural history of inflammatory bowel diseases

Background: Early life exposures may modify risk of inflammatory bowel diseases (IBD; Crohn’s disease (CD), ulcerative colitis (UC)). However, the relationship between early life exposures and natural history of IBD has not been previously examined. Methods: This single center study included patients with CD or UC recruited in a prospective IBD registry. Enrolled patients completed a detailed environmental questionnaire that assessed various early life environmental exposures. Our primary outcome was requirement for disease-related surgery in CD and UC. Logistic regression models defined independent effect of early life exposures, adjusting for potential confounders. Results: Our study included 333 CD and 270 UC patients. Just over half were female with a median age at diagnosis of 25 years. One-third of the cohort had history of bowel surgery (31%) and nearly half had used at least one biologic agent (47%). Among those with CD, being breastfed was associated with reduced risk of CD-related surgery (34% vs. 55%), while childhood cigarette smoke exposure was associated with increased risk. On multivariate analysis, history of being breastfed (odds ratio (OR) 0.21, 95% confidence interval [CI] 0.09–0.46) and cigarette smoke exposure as a child (OR 2.17, 95% CI 1.10–4.29) remained independently associated with surgery. None of the early life variables influenced disease phenotype or outcome in UC. Conclusion: A history of being breastfed was associated with a decreased risk while childhood cigarette smoke exposure was associated with an increased risk of surgery in patients with CD. Further investigation to examine biological mechanisms is warranted. Electronic supplementary material The online version of this article (doi:10.1186/s12876-014-0216-8) contains supplementary material, which is available to authorized users

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]