Head-to-head comparison of prostate cancer risk calculators predicting biopsy outcome

Background: Multivariable risk calculators (RCs) predicting prostate cancer (PCa) aim to reduce unnecessary workup (e.g., MRI and biopsy) by selectively identifying those men at risk for PCa or clinically significant PCa (csPCa) (Gleason ≥7). The lack of an adequate comparison makes choosing between RCs difficult for patients, clinicians and guideline developers. We aim to perform a head-to-head comparison of seven well known RCs predicting biopsy outcome. Methods: Our study comprised 7,119 men from ten independent contemporary cohorts in Europe and Australia, who underwent prostate biopsy between 2007 and 2015. We evaluated the performance of the ERSPC RPCRC, Finne, Chun, ProstataClass, Karakiewicz, Sunnybrook, and PCPT 2.0 (HG) RCs in predicting the presence of any PCa and csPCa. Performance was assessed by discrimination, calibration and net benefit analyses. Results: A total of 3,458 (48%) PCa were detected; 1,784 (25%) men had csPCa. No particular RC stood out predicting any PCa: pooled area under the ROC-curve (AUC) ranged between 0.64 and 0.72. The ERSPC RPCRC had the highest pooled AUC 0.77 (95% CI: 0.73-0.80) when predicting csPCa. Decision curve analysis (DCA) showed limited net benefit in the detection of csPCa, but that can be improved by a simple calibration step. The main limitation is the retrospective design of the study. Conclusions: No particular RC stands out when predicting biopsy outcome on the presence of any PCa. The ERSPC RPCRC is superior in identifying those men at risk for csPCa. Net benefit analyses show that a multivariate approach before further workup is advisable.info:eu-repo/semantics/publishedVersio

Polygenetic risk scores do not add predictive power to clinical models for response to anti-TNFα therapy in inflammatory bowel disease

BACKGROUND: Anti-tumour necrosis factor alpha (TNFα) therapy is widely used in the management of Crohn’s disease (CD) and ulcerative colitis (UC). However, up to a third of patients do not respond to induction therapy and another third of patients lose response over time. To aid patient stratification, polygenetic risk scores have been identified as predictors of response to anti-TNFα therapy. We aimed to replicate the association between polygenetic risk scores and response to anti-TNFα therapy in an independent cohort of patients, to establish its clinical validity. MATERIALS AND METHODS: Primary non-response, primary response, durable response and loss of response to anti-TNFα therapy was retrospectively assessed for each patient using stringent definitions. Genome wide genotyping was performed and previously described polygenetic risk scores for primary non-response and durable response were calculated. We compared polygenetic risk scores between patients with primary response and primary non-response, and between patients with durable response and loss of response, using separate analyses for CD and UC. RESULTS: Out of 334 patients with CD, 15 (4%) patients met criteria for primary non-response, 221 (66%) for primary response, 115 (34%) for durable response and 35 (10%) for loss of response. Out of 112 patients with UC, 12 (11%) met criteria for primary non-response, 68 (61%) for primary response, 19 (17%) for durable response and 20 (18%) for loss of response. No significant differences in polygenetic risk scores were found between primary non-responders and primary responders, and between durable responders and loss of responders. CONCLUSIONS: We could not replicate the previously reported association between polygenetic risk scores and response to anti-TNFα therapy in an independent cohort of patients with CD or UC. Currently, there is insufficient evidence to use polygenetic risk scores to predict response to anti-TNFα therapy in patients with IBD

Considerations and challenges in support of science and communication of fish consumption advisories for per- and polyfluoroalkyl substances

Federal, state, tribal, or local entities in the United States issue fish consumption advisories (FCAs) as guidance for safer consumption of locally caught fish containing contaminants. Fish consumption advisories have been developed for commonly detected compounds such as mercury and polychlorinated biphenyls. The existing national guidance does not specifically address the unique challenges associated with bioaccumulation and consumption risk related to per- and polyfluoroalkyl substances (PFAS). As a result, several states have derived their own PFAS-related consumption guidelines, many of which focus on one frequently detected PFAS, known as perfluorooctane sulfonic acid (PFOS). However, there can be significant variation between tissue concentrations or trigger concentrations (TCs) of PFOS that support the individual state-issued FCAs. This variation in TCs can create challenges for risk assessors and risk communicators in their efforts to protect public health. The objective of this article is to review existing challenges, knowledge gaps, and needs related to issuing PFAS-related FCAs and to provide key considerations for the development of protective fish consumption guidance. The current state of the science and variability in FCA derivation, considerations for sampling and analytical methodologies, risk management, risk communication, and policy challenges are discussed. How to best address PFAS mixtures in the development of FCAs, in risk assessment, and establishment of effect thresholds remains a major challenge, as well as a source of uncertainty and scrutiny. This includes developments better elucidating toxicity factors, exposures to PFAS mixtures, community fish consumption behaviors, and evolving technology and analytical instrumentation, methods, and the associated detection limits. Given the evolving science and public interests informing PFAS-related FCAs, continued review and revision of FCA approaches and best practices are vital. Nonetheless, consistent, widely applicable, PFAS-specific approaches informing methods, critical concentration thresholds, and priority compounds may assist practitioners in PFAS-related FCA development and possibly reduce variability between states and jurisdictions

Mucosal microbiota modulate host intestinal immune signatures in Inflammatory Bowel Disease

BackgroundHost intestinal immune gene signatures and microbial dysregulations expose potential mechanisms in the pathogenesis of inflammatory bowel diseases (IBD). Profiling of mucosa-attached microbiota allows the understanding of locally present microbial communities and their immediate impact on the host. This study evaluated interactions between host mucosal gene expression and intestinal mucosa-attached microbiota in IBD.MethodsIntestinal mucosal bulk RNA-sequencing data was combined with mucosal 16S rRNA gene sequencing data from 696 intestinal biopsies derived from 337 patients with IBD (181 with Crohn’s disease [CD] and 156 with ulcerative colitis [UC]) and 16 non-IBD controls. Hierarchical all-against-all associations testing (HAllA) was used to assess factors affecting host gene expressions and microbiota. Mucosal cell enrichments were predicted by deconvolution. Linear mixed interaction models were used to investigate host-microbiota interactions, adjusting for age, sex, BMI and batch effects. Variation explanation analysis was performed by Lasso regression.ResultsIn total, 15,934 intestinal genes and 113 microbial taxa were identified and included in subsequent analyses. Host intestinal gene expressions were characterized by tissue- and inflammation-specificity, whereas intraindividual variability of the mucosal microbiota dominated over disease location and inflammation effects. We observed forty associations between the mucosal expression of genes and the abundance of specific microbes independent of dysbiosis (FDR<0.05). Examples include a positive association between aryl hydrocarbon receptor (AHR) and Bifidobacterium, and a negative association between interleukin 18 receptor 1 (IL18R1) and Lachnoclostridium. Furthermore, 112 gene-microbiota interactions changed in patients with microbial dysbiosis compared to non-dysbiosis (FDR<0.05). These interactions were enriched in immune-related and extracellular matrix organization pathways. For example, the IL1R1 gene was positively associated with Collinsella abundance in non-dysbiotic patients, whereas an inverse association was observed in high dysbiosis. Finally, the presence of mucosal microbial taxa explained up to 10% of the variation in cell type enrichment, affecting epithelial cells, macrophages and regulatory T-cells.ConclusionInteractions between host intestinal gene expressions and mucosa-attached microbiota are disrupted in patients with IBD. Furthermore, mucosal microbiota are highly personalized and potentially contribute to intestinal cell type alterations. Our study unravels key immune-mediated molecular pathways and relevant bacteria in intestinal tissue, which may guide drug development and precision medicine in IBD