Tissue Biomarkers are information written in the tissue and used in Pathology to recognize specific subsets of patients with diagnostic, prognostic or predictive purposes, thus representing the key elements of Personalized Medicine. The advent of Artificial Intelligence (AI) promises to further reinforce the role of Pathology in the scenario of Personalized Medicine: AI-based devices are expected to standardize the evaluation of tissue biomarkers and also to discover novel information, which would otherwise be ignored by human review, and use them to make specific predictions. In this review we will present how AI has been used to support Tissue Biomarkers evaluation in the specific field of Pathology, give an insight to the intriguing field of AI-based biomarkers and discuss possible advantages, risk and perspectives for Pathology.
Background and aims The association between smoking and inflammatory bowel disease (IBD) relies on old meta-analyses including exclusively non-Jewish White populations. Uncertainty persists regarding the role of smoking in other ethnicities. Methods We systematically searched Medline/PubMed, Embase and Scopus for studies examining tobacco smoking and the risk of developing IBD, i.e., Crohn’s disease (CD) or ulcerative colitis (UC). Two authors independently extracted study data and assessed each study’s risk-of-bias. We examined heterogeneity and small-study effect, and calculated summary estimates using random-effects models. Stratified analyses and meta-regression were employed to study the association between study-level characteristics and effect estimates. The strength of epidemiological evidence was assessed through prespecified criteria. Results We synthesized 57 studies examining the smoking-related risk of developing CD and UC. Non-Jewish White smokers were at increased risk of CD (29 studies; RR: 1.95, 95% CI: 1.69‒2.24; moderate evidence). No association was observed in Asian, Jewish and Latin-American populations (11 studies; RR: 0.97; 95% CI: 0.83–1.13), with no evidence of heterogeneity across these ethnicities. Smokers were at reduced risk of UC (51 studies; RR: 0.55, 95% CI: 0.48–0.64; weak evidence) irrespectively of ethnicity; however, cohort studies, large studies and those recently published showed attenuated associations. Conclusions This meta-analysis did not identify any increased risk of CD in smokers in ethnicities other than non-Jewish Whites, and confirmed the protective effect of smoking on UC occurrence. Future research should characterize the genetic background of CD patients across different ethnicities to improve our understanding on the role of smoking in CD pathogenesis.
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