18 research outputs found

    Variation in Treatment of Patients With Inflammatory Bowel Diseases at Major Referral Centers in the United States

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    We performed a prospective study of patients with inflammatory bowel diseases to examine variations in treatment among medical centers. In a prospective cohort study of 1659 patients with CD and 946 patients with UC seen at 7 high-volume referral centers, we collected data on demographics, disease characteristic, and medical and surgical treatments. We used logistic regression to determine differences in treatment among centers, controlling for potential confounders. We found significant variations among centers in treatment of CD with immunomodulators (odds ratio [OR], 3.34; 95% confidence interval [CI], 2.09 – 5.32) but not anti-tumor necrosis factor agents (OR, 1.64; 95% CI, 0.97 – 2.77). There was less variation in treatment of UC; we found no difference in use of immunomodulators (OR,1.83 95% CI, 1.00 – 3.36) or anti-TNF therapy (OR, 0.81; 95% CI, 0.40 – 1.65). Development and implementation of evidence-based standards of care for IBD may help reduce variation and improve outcomes

    Optimistic Planning for Markov Decision Processes

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    International audienceThe reinforcement learning community has recently intensified its interest in online planning methods, due to their relative independence on the state space size. However, tight near-optimality guarantees are not yet available for the general case of stochastic Markov decision processes and closed-loop, state-dependent planning policies. We therefore consider an algorithm related to AO* that optimistically explores a tree representation of the space of closed-loop policies, and we analyze the near-optimality of the action it returns after n tree node expansions. While this optimistic planning requires a finite number of actions and possible next states for each transition, its asymptotic performance does not depend directly on these numbers, but only on the subset of nodes that significantly impact near-optimal policies. We characterize this set by introducing a novel measure of problem complexity, called the near-optimality exponent. Specializing the exponent and performance bound for some interesting classes of MDPs illustrates the algorithm works better when there are fewer near-optimal policies and less uniform transition probabilities

    Multi-omic approach identifies hypoxic tumor-associated myeloid cells that drive immunobiology of high-risk pediatric ependymoma.

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    Ependymoma (EPN) is a devastating childhood brain tumor. Single-cell analyses have illustrated the cellular heterogeneity of EPN tumors, identifying multiple neoplastic cell states including a mesenchymal-differentiated subpopulation which characterizes the PFA1 subtype. Here, we characterize the EPN immune environment, in the context of both tumor subtypes and tumor cell subpopulations using single-cell sequencing (scRNAseq, n = 27), deconvolution of bulk tumor gene expression (n = 299), spatial proteomics (n = 54), and single-cell cytokine release assays (n = 12). We identify eight distinct myeloid-derived subpopulations from which a group of cells, termed hypoxia myeloid cells, demonstrate features of myeloid-derived suppressor cells, including IL6/STAT3 pathway activation and wound healing ontologies. In PFA tumors, hypoxia myeloid cells colocalize with mesenchymal-differentiated cells in necrotic and perivascular niches and secrete IL-8, which we hypothesize amplifies the EPN immunosuppressive microenvironment. This myeloid cell-driven immunosuppression will need to be targeted for immunotherapy to be effective in this difficult-to-cure childhood brain tumor. [Abstract copyright: © 2023 The Author(s).

    Variation in Treatment of Patients With Inflammatory Bowel Diseases at Major Referral Centers in the United States

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    We performed a prospective study of patients with inflammatory bowel diseases to examine variations in treatment among medical centers. In a prospective cohort study of 1659 patients with CD and 946 patients with UC seen at 7 high-volume referral centers, we collected data on demographics, disease characteristic, and medical and surgical treatments. We used logistic regression to determine differences in treatment among centers, controlling for potential confounders. We found significant variations among centers in treatment of CD with immunomodulators (odds ratio [OR], 3.34; 95% confidence interval [CI], 2.09 – 5.32) but not anti-tumor necrosis factor agents (OR, 1.64; 95% CI, 0.97 – 2.77). There was less variation in treatment of UC; we found no difference in use of immunomodulators (OR,1.83 95% CI, 1.00 – 3.36) or anti-TNF therapy (OR, 0.81; 95% CI, 0.40 – 1.65). Development and implementation of evidence-based standards of care for IBD may help reduce variation and improve outcomes
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