Symptom-based stratification of patients with primary Sjögren's syndrome: multi-dimensional characterisation of international observational cohorts and reanalyses of randomised clinical trials

Background Heterogeneity is a major obstacle to developing effective treatments for patients with primary Sjögren's syndrome. We aimed to develop a robust method for stratification, exploiting heterogeneity in patient-reported symptoms, and to relate these differences to pathobiology and therapeutic response. Methods We did hierarchical cluster analysis using five common symptoms associated with primary Sjögren's syndrome (pain, fatigue, dryness, anxiety, and depression), followed by multinomial logistic regression to identify subgroups in the UK Primary Sjögren's Syndrome Registry (UKPSSR). We assessed clinical and biological differences between these subgroups, including transcriptional differences in peripheral blood. Patients from two independent validation cohorts in Norway and France were used to confirm patient stratification. Data from two phase 3 clinical trials were similarly stratified to assess the differences between subgroups in treatment response to hydroxychloroquine and rituximab. Findings In the UKPSSR cohort (n=608), we identified four subgroups: Low symptom burden (LSB), high symptom burden (HSB), dryness dominant with fatigue (DDF), and pain dominant with fatigue (PDF). Significant differences in peripheral blood lymphocyte counts, anti-SSA and anti-SSB antibody positivity, as well as serum IgG, κ-free light chain, β2-microglobulin, and CXCL13 concentrations were observed between these subgroups, along with differentially expressed transcriptomic modules in peripheral blood. Similar findings were observed in the independent validation cohorts (n=396). Reanalysis of trial data stratifying patients into these subgroups suggested a treatment effect with hydroxychloroquine in the HSB subgroup and with rituximab in the DDF subgroup compared with placebo. Interpretation Stratification on the basis of patient-reported symptoms of patients with primary Sjögren's syndrome revealed distinct pathobiological endotypes with distinct responses to immunomodulatory treatments. Our data have important implications for clinical management, trial design, and therapeutic development. Similar stratification approaches might be useful for patients with other chronic immune-mediated diseases. Funding UK Medical Research Council, British Sjogren's Syndrome Association, French Ministry of Health, Arthritis Research UK, Foundation for Research in Rheumatology

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

Measurements of Higgs boson production cross sections and couplings in the diphoton decay channel at root s=13 TeV

Measurements of Higgs boson production cross sections and couplings in events where the Higgs boson decays into a pair of photons are reported. Events are selected from a sample of proton-proton collisions at root s = 13TeV collected by the CMS detector at the LHC from 2016 to 2018, corresponding to an integrated luminosity of 137 fb(-1). Analysis categories enriched in Higgs boson events produced via gluon fusion, vector boson fusion, vector boson associated production, and production associated with top quarks are constructed. The total Higgs boson signal strength, relative to the standard model (SM) prediction, is measured to be 1.12 +/- 0.09. Other properties of the Higgs boson are measured, including SM signal strength modifiers, production cross sections, and its couplings to other particles. These include the most precise measurements of gluon fusion and vector boson fusion Higgs boson production in several different kinematic regions, the first measurement of Higgs boson production in association with a top quark pair in five regions of the Higgs boson transverse momentum, and an upper limit on the rate of Higgs boson production in association with a single top quark. All results are found to be in agreement with the SM expectations.Peer reviewe

Bayesian Model Building from a large Medical Dataset: A Practical Study

An experiment in Bayesian model building from a large medical dataset for Mental Retardation is discussed in this paper. We give a step by step approach to the practical aspects of building a Bayesian Network from a dataset. We enumerate the tools required, address the problem of missing values in big datasets resulting from surveys and elaborate on our solution to the problem. We advance some reasons why imputation is a more desirable approach for model building than some other ad hoc methods suggested in literature. We use the CHDS dataset, HUGIN software, CB algorithm, IMP algorithm and CondProb program for generating our model. The network structure and the conditional probabilities are modified under the guidance of the domain expert. We also present validation results and give some suggestions for improvement of the model. 1.1 Introduction Some decades back we reached a situation when we could not analyze data collected from a Census before the next Census. And again a stage has..

Genome and phylogenetic analyses of Trypanosoma evansi reveal extensive similarity to T. brucei and multiple independent origins for dyskinetoplasty.

Two key biological features distinguish Trypanosoma evansi from the T. brucei group: independence from the tsetse fly as obligatory vector, and independence from the need for functional mitochondrial DNA (kinetoplast or kDNA). In an effort to better understand the molecular causes and consequences of these differences, we sequenced the genome of an akinetoplastic T. evansi strain from China and compared it to the T. b. brucei reference strain. The annotated T. evansi genome shows extensive similarity to the reference, with 94.9% of the predicted T. b. brucei coding sequences (CDS) having an ortholog in T. evansi, and 94.6% of the non-repetitive orthologs having a nucleotide identity of 95% or greater. Interestingly, several procyclin-associated genes (PAGs) were disrupted or not found in this T. evansi strain, suggesting a selective loss of function in the absence of the insect life-cycle stage. Surprisingly, orthologous sequences were found in T. evansi for all 978 nuclear CDS predicted to represent the mitochondrial proteome in T. brucei, although a small number of these may have lost functionality. Consistent with previous results, the F1FO-ATP synthase γ subunit was found to have an A281 deletion, which is involved in generation of a mitochondrial membrane potential in the absence of kDNA. Candidates for CDS that are absent from the reference genome were identified in supplementary de novo assemblies of T. evansi reads. Phylogenetic analyses show that the sequenced strain belongs to a dominant group of clonal T. evansi strains with worldwide distribution that also includes isolates classified as T. equiperdum. At least three other types of T. evansi or T. equiperdum have emerged independently. Overall, the elucidation of the T. evansi genome sequence reveals extensive similarity of T. brucei and supports the contention that T. evansi should be classified as a subspecies of T. brucei