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The third international consensus definition for sepsis recommended use of a new prognostic tool, the quick Sequential Organ Failure Assessment (qSOFA), based on its ability to predict inhospital mortality and prolonged intensive care unit (ICU) stay in patients with suspected infection. While several studies have compared the prognostic accuracy of qSOFA to the Systemic Inflammatory Response Syndrome (SIRS) criteria in suspected sepsis, few have compared qSOFA and SIRS to the widely used National Early Warning Score (NEWS). This was a retrospective cohort study carried out in a UK tertiary centre. The study population comprised emergency admissions in whom sepsis was suspected and treated. The accuracy for predicting inhospital mortality and ICU admission was calculated and compared for qSOFA, SIRS and NEWS. Among 1818 patients, 53 were admitted to ICU (3%) and 265 died in hospital (15%). For predicting inhospital mortality, the area under the receiver operating characteristics curve for NEWS (0.65, 95% CI 0.61 to 0.68) was similar to qSOFA (0.62, 95% CI 0.59 to 0.66) (test for difference, P=0.18) and superior to SIRS (P<0.001), which was not predictive. The sensitivity of NEWS≥5 (74%, 95% CI 68% to 79%) was similar to SIRS≥2 (80%, 95% CI 74% to 84%) and higher than qSOFA≥2 (37%, 95% CI 31% to 43%). The specificity of NEWS≥5 (43%, 95% CI 41% to 46%) was higher than SIRS≥2 (21%, 95% CI 19% to 23%) and lower than qSOFA≥2 (79%, 95% CI 77% to 81%). The negative predictive value was 88% (86%-90%) for qSOFA, 86% (82%-89%) for SIRS and 91% (88%-93%) for NEWS. Results were similar for the secondary outcome of ICU admission. NEWS has equivalent or superior value for most test characteristics relative to SIRS and qSOFA, calling into question the rationale of adopting qSOFA in institutions where NEWS is already in use.

PurposeThe primary purpose of this study was to evaluate the effect of the fatty acid amide hydrolase (FAAH) inhibitor ASP3652 on efficacy and safety in patients with Interstitial Cystitis/Bladder Pain Syndrome (IC/BPS). The secondary purpose was to evaluate phenotyping based on Hunner’s lesions (HL).MethodsIn this randomized trial, adult female patients with moderate/severe IC/BPS received 12 weeks of treatment with an oral dose of ASP3652 (50, 150, or 300 mg twice daily) or placebo. A Bayesian model was employed using accumulating data to adjust the randomization probability and to analyze the primary efficacy variable (change from baseline to end of treatment in Mean Daily Pain [MDP; range 0–10]). Study outcomes and patient characteristics of patients with and without HL (HL+ and HL−) were compared.ResultsIn total, 287 patients were randomized. The 300 mg dose group (n = 97) showed the largest effect, i.e., a mean change from baseline to end of treatment of −1.73 in MDP. However, the mean difference from placebo was 0.02. The probability that this dose was better than placebo was 13.5%. Adverse event incidence was low and similar between study groups. HL+ patients were older and had more severe symptoms than HL−. An association was suggested in HL+ patients between changes in micturition frequency and MDP (R = 0.41 [95% CI 0.18, 0.63]), which was not observed in HL− (R = 0.04 [95% CI −0.16, 0.29]).ConclusionASP3652 was safe and well tolerated, but did not show efficacy in IC/BPS. The observed differences between HL+ and HL− suggest that IC/BPS diagnosis and treatment may be approached differently in these two phenotypes.Trial registration: EudraCT number 2011-004555-39, date of registration: 2012-05-07.

Background Network Meta-Analysis (NMA) is a key component of submissions to reimbursement agencies world-wide, especially when there is limited direct head-to-head evidence for multiple technologies from randomised controlled trials (RCTs). Many NMAs include only data from RCTs. However, real-world evidence (RWE) is also becoming widely recognised as a valuable source of clinical data. This study aims to investigate methods for the inclusion of RWE in NMA and its impact on the level of uncertainty around the effectiveness estimates, with particular interest in effectiveness of fingolimod. Methods A range of methods for inclusion of RWE in evidence synthesis were investigated by applying them to an illustrative example in relapsing remitting multiple sclerosis (RRMS). A literature search to identify RCTs and RWE evaluating treatments in RRMS was conducted. To assess the impact of inclusion of RWE on the effectiveness estimates, Bayesian hierarchical and adapted power prior models were applied. The effect of the inclusion of RWE was investigated by varying the degree of down weighting of this part of evidence by the use of a power prior. Results Whilst the inclusion of the RWE led to an increase in the level of uncertainty surrounding effect estimates in this example, this depended on the method of inclusion adopted for the RWE. ‘Power prior’ NMA model resulted in stable effect estimates for fingolimod yet increasing the width of the credible intervals with increasing weight given to RWE data. The hierarchical NMA models were effective in allowing for heterogeneity between study designs, however, this also increased the level of uncertainty. Conclusion The ‘power prior’ method for the inclusion of RWE in NMAs indicates that the degree to which RWE is taken into account can have a significant impact on the overall level of uncertainty. The hierarchical modelling approach further allowed for accommodating differences between study types. Consequently, further work investigating both empirical evidence for biases associated with individual RWE studies and methods of elicitation from experts on the extent of such biases is warranted.

Background Vitiligo is reported to affect 2% of the world’s population and has a significant impact on health related quality of life (HRQoL). The relationship between HRQoL and clinical outcomes used in vitiligo require further examination. Mapping condition specific measures of HRQoL: vitiligo specific quality of life instrument (VitiQoL), vitiligo noticeability scale (VNS) and vitiligo re-pigmentation scores (RPS) to the EQ-5D have not yet been reported. Methods Data collected from a randomised clinical trial (HI-Light) in vitiligo was used to develop mapping algorithms for the EQ-5D-5 L and the relationship between HRQoL, clinical outcomes and EQ-5D were investigated. Two EQ-5D-5 L value sets (Van Hout and Alava) using linear and non-linear models were considered. Logistic regression models were used to model the probability of vitiligo noticeability (VNS) in terms of RPS, EQ-5D and VitiQoL scores. Results Mapping from RPS appeared to perform better followed by VNS for the Alava crosswalks using polynomial models: Mean observed vs. predicted utilities of 0.9008 (0.005) vs. 0.8984 (0.0004) were observed for RPS. For VNS, mean observed vs. predicted utilities of 0.9008 (0.005) vs. 0.8939 (0.0003) were observed. For VitiQoL, mean observed vs. predicted utilities of 0.9008 (0.005) vs. 0.8912 (0.0002) were observed. For patients with the least re-pigmentation (RPS < 25%), a Total VitiQoL score of about 20 points gives around an 18% chance of vitiligo being no longer or a lot less noticeable. Conclusion The algorithm based on RPS followed by VNS performed best. The relationship between effects from vitiligo specific HRQoL instruments and clinical RPS was established allowing for plausible clinically relevant differences to be identified, although further work is required in this area.

Background When designing studies it is common to search the literature to investigate variability estimates to use in sample size calculations. Proprietary data of previously designed trials in a particular indication are also used to obtain estimates of variability. Estimates of treatment effects are typically obtained from randomised controlled clinical trials (RCTs). Based on the observed estimates of treatment effect, variability and the minimum clinical relevant difference to detect, the sample size for a subsequent trial is estimated. However, data from real world evidence (RWE) studies, such as observational studies and other interventional studies in patients in routine clinical practice, are not widely used in a systematic manner when designing studies. In this paper, we propose a framework for inclusion of RWE in planning of a clinical development programme. Methods In our proposed approach, all evidence, from both RCTs and RWE (i.e. from studies in routine clinical practice), available at the time of designing of a new clinical trial is combined in a Bayesian network meta-analysis (NMA). The results can be used to inform the design of the next clinical trial in the programme. The NMA was performed at key milestones, such as at the end of the phase II trial and prior to the design of key phase III studies. To illustrate the methods, we designed an alternative clinical development programme in multiple sclerosis using RWE through clinical trial simulations. Results Inclusion of RWE in the NMA and the resulting trial simulations demonstrated that 284 patients per arm were needed to achieve 90% power to detect effects of predetermined size in the TRANSFORMS study. For the FREEDOMS and FREEDOMS II clinical trials, 189 patients per arm were required. Overall there was a reduction in sample size of at least 40% across the three phase III studies, which translated to a time savings of at least 6 months for the undertaking of the fingolimod phase III programme. Conclusion The use of RWE resulted in a reduced sample size of the pivotal phase III studies, which led to substantial time savings compared to the approach of sample size calculations without RWE.

We aim to use real-world data in evidence synthesis to optimize an evidence base for the effectiveness of biologic therapies in rheumatoid arthritis to allow for evidence on first-line therapies to inform second-line effectiveness estimates. We use data from the British Society for Rheumatology Biologics Register for Rheumatoid Arthritis to supplement randomized controlled trials evidence obtained from the literature, by emulating target trials of treatment sequences to estimate treatment effects in each line of therapy. Treatment effects estimates from the target trials inform a bivariate network meta-analysis (NMA) of first-line and second-line treatments. Summary data were obtained from 21 trials of biologic therapies including two for second-line treatment and results from six emulated target trials of both treatment lines. Bivariate NMA resulted in a decrease in uncertainty around the effectiveness estimates of the second-line therapies, when compared to the results of univariate NMA, and allowed for predictions of treatment effects not evaluated in second-line randomized controlled trials. Bivariate NMA provides effectiveness estimates for all treatments in first and second line, including predicted effects in second line where these estimates did not exist in the data. This novel methodology may have further applications; for example, for bridging networks of trials in children and adults.

Background/AimsStress hyperglycemia is common in critical illness but it has not been clearly studied in patients with acute pancreatitis (AP). This study aimed to investigate the specific blood glucose (BG) level that defines stress hyperglycemia and to determine the impact of stress hyperglycemia on clinical outcomes in AP patients.MethodsAP patients admitted ≤ 48 h after abdominal pain onset were retrospectively analyzed. Patients were stratified by pre-existing diabetes and stress hyperglycemia was defined using stratified BG levels for non-diabetes and diabetes with clinical outcomes compared.ResultsThere were 967 non-diabetic and 114 diabetic (10.5%) patients met the inclusion criteria and the clinical outcomes between these two groups were not significantly different. In non-diabetes, the cut-off BG level of ≥ 180 mg/dl was selected to define stress hyperglycemia with an 8.8-fold higher odds ratio for persistent organ failure (POF) (95% CI 5.4–14.3; P < 0.001). For diabetes, ≥ 300 mg/dl was selected with a 7.5-fold higher odds ratio for POF (95% CI 1.7–34.3; P = 0.009). In multivariable logistic regression, stress hyperglycemia was independently associated with POF, acute necrotic collection, major infection and mortality. The combination of BG and systemic inflammatory response syndrome (SIRS) score in predicting POF was better than SIRS or Glasgow score alone.ConclusionsThis study identifies a cut-off BG level of ≥ 180 mg/dl and ≥ 300 mg/dl was optimal to define stress hyperglycemia for non-diabetic and diabetic AP patients, respectively. There was a significant relationship between stress hyperglycemia and adverse clinical outcomes.

Background: Network Meta-Analysis (NMA) is a key component of submissions to reimbursement agencies world-wide, especially when there is limited direct head-to-head evidence for multiple technologies from randomised controlled trials (RCTs). Many NMAs include only data from RCTs. However, real-world evidence (RWE) is also becoming widely recognised as a valuable source of clinical data. We investigate methods for the inclusion of RWE in NMA and its impact on the uncertainty around the effectiveness estimates. Methods: A range of methods for inclusion of RWE in evidence synthesis, including Bayesian hierarchical and power prior models, were investigated by applying them to an example in relapsing remitting multiple sclerosis. The effect of the inclusion of RWE was investigated by varying the degree of down weighting of this part of evidence by the use of a power prior. Results: Whilst the inclusion of the RWE led to an increase in the level of uncertainty surrounding effect estimates in this example, this depended on the method of inclusion adopted for the RWE. Power prior NMA model resulted in stable effect estimates for fingolimod yet increasing the width of the credible intervals with increasing weight given to RWE data. The hierarchical NMA models were effective in allowing for heterogeneity between study designs; however, this also increased the level of uncertainty. Conclusion: The power prior approach for the inclusion of RWE in NMAs indicates that the degree to which RWE is taken into account can have a significant impact on the overall level of uncertainty. The hierarchical modelling approach further allowed for accommodating differences between study types. Consequently, further work investigating both empirical evidence for biases associated with individual RWE studies and methods of elicitation from experts on the extent of such biases is warranted.

Background: Pre-marketing authorisation estimates of survival are generally restricted to those observed directly in randomised controlled trials (RCTs). However, for regulatory and Health Technology Assessment (HTA) decision-making a longer time horizon is often required than is studied in RCTs. Therefore, extrapolation is required to estimate long-term treatment effect. Registry data can provide evidence to support extrapolation of treatment effects from RCTs, which are considered the main sources of evidence of effect for new drug applications. A number of methods are available to extrapolate survival data, such as Exponential, Weibull, Gompertz, log-logistic or log-normal parametric models. The different methods have varying functional forms and can result in different survival estimates. Methods: The aim of this paper was to use registry data to supplement the relatively short term RCT data to obtain long term estimates of effect. No formal hypotheses were tested. We explore the above parametric regression models as well as a nonparametric regression model based on local linear (parametric) regression. We also explore a Bayesian model constrained to the long term estimate of survival reported in literature, a Bayesian power prior approach on the variability observed from published literature, and a Bayesian Model Averaging (BMA) approach. The methods were applied to extrapolate overall survival of a RCT in metastatic melanoma. Results: The results showed that the BMA approach was able to fit the RCT data well, with the lowest variability of the area under the curve up to 72 months with or without the SEER Medicare registry. Conclusion: the BMA approach is a viable approach to extrapolate overall survival in the absence of long term data.

It is estimated that there are 390 million cases of dengue virus infection each year. In this double-blind, placebo-controlled trial, a tetravalent dengue vaccine was evaluated in 20,071 children. The vaccine was found to be 80% effective in preventing dengue infection.