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Background Available methods for the joint modelling of longitudinal and time-to-event outcomes have typically only allowed for a single longitudinal outcome and a solitary event time. In practice, clinical studies are likely to record multiple longitudinal outcomes. Incorporating all sources of data will improve the predictive capability of any model and lead to more informative inferences for the purpose of medical decision-making. Methods We reviewed current methodologies of joint modelling for time-to-event data and multivariate longitudinal data including the distributional and modelling assumptions, the association structures, estimation approaches, software tools for implementation and clinical applications of the methodologies. Results We found that a large number of different models have recently been proposed. Most considered jointly modelling linear mixed models with proportional hazard models, with correlation between multiple longitudinal outcomes accounted for through multivariate normally distributed random effects. So-called current value and random effects parameterisations are commonly used to link the models. Despite developments, software is still lacking, which has translated into limited uptake by medical researchers. Conclusion Although, in an era of personalized medicine, the value of multivariate joint modelling has been established, researchers are currently limited in their ability to fit these models routinely. We make a series of recommendations for future research needs.

Background Joint modelling of longitudinal and time-to-event outcomes has received considerable attention over recent years. Commensurate with this has been a rise in statistical software options for fitting these models. However, these tools have generally been limited to a single longitudinal outcome. Here, we describe the classical joint model to the case of multiple longitudinal outcomes, propose a practical algorithm for fitting the models, and demonstrate how to fit the models using a new package for the statistical software platform R, joineRML . Results A multivariate linear mixed sub-model is specified for the longitudinal outcomes, and a Cox proportional hazards regression model with time-varying covariates is specified for the event time sub-model. The association between models is captured through a zero-mean multivariate latent Gaussian process. The models are fitted using a Monte Carlo Expectation-Maximisation algorithm, and inferences are based on approximate standard errors from the empirical profile information matrix, which are contrasted to an alternative bootstrap estimation approach. We illustrate the model and software on a real data example for patients with primary biliary cirrhosis with three repeatedly measured biomarkers. Conclusions An open-source software package capable of fitting multivariate joint models is available. The underlying algorithm and source code makes use of several methods to increase computational speed.

Salinity is a key abiotic property of inland waters; it has a major influence on biotic communities and is affected by many natural and anthropogenic processes. Salinity of inland waters tends to increase with aridity, and biota of inland waters may have evolved greater salt tolerance in more arid regions. Here we compare the sensitivity of stream macroinvertebrate species to salinity from a relatively wet region in France (Lorraine and Brittany) to that in three relatively arid regions eastern Australia (Victoria, Queensland and Tasmania), South Africa (south-east of the Eastern Cape Province) and Israel using the identical experimental method in all locations. The species whose salinity tolerance was tested, were somewhat more salt tolerant in eastern Australia and South Africa than France, with those in Israel being intermediate. However, by far the greatest source of variation in species sensitivity was between taxonomic groups (Order and Class) and not between the regions. We used a bayesian statistical model to estimate the species sensitivity distributions (SSDs) for salinity in eastern Australia and France adjusting for the assemblages of species in these regions. The assemblage in France was slightly more salinity sensitive than that in eastern Australia. We therefore suggest that regional salinity sensitivity is therefore likely to depend most on the taxonomic composition of respective macroinvertebrate assemblages. On this basis it would be possible to screen rivers globally for risk from salinisation.

ObjectiveThe objective of this multicentre study was to compare short-term and midterm outcomes between sternotomy and minimally invasive approaches for mitral valve surgery.MethodsData for all mitral valve procedures with or without concomitant tricuspid atrial fibrillation surgery were analysed from three UK hospitals between January 2008 and December 2016. To account for selection bias between minimally invasive approach and sternotomy, one-to-one propensity score calliper matching without replacement was performed. The main outcome measure was midterm reintervention free survival that was summarised by the Kaplan-Meier estimator and compared between treatment arms using the stratified log-rank test.ResultsA total of 2404 procedures (1757 sternotomy and 647 minimally invasive) were performed during the study period. Propensity score matching resulted in 639 matched pairs with improved balance postmatching in all 31 covariates (absolute standardised mean differences <10%). Despite longer procedural times patients who underwent minimally invasive surgery had a lower need for transfusion (20.5%vs14.4%, p=0.005) and reduced median postoperative length of stay (7 vs 6 days, p<0.001). There were no statistically significant differences in the rates of in-hospital mortality or postoperative stroke. Reintervention-free survival at 8 years was estimated as 86.1% in the minimally invasive group and 84.1% in the sternotomy group (p=0.40).ConclusionsMinimally invasive surgery is associated with excellent short-term outcomes and comparable midterm outcomes for patients undergoing mitral valve surgery. A minimally invasive approach should be considered for all patients who require mitral valve intervention and should be the standard against which transcatheter mitral techniques are compared.

Serum total cholesterol is one of the major targets for cardiovascular disease prevention. Statins are effective for cholesterol control in individual patients. At the population level, however, their contribution to total cholesterol decline remains unclear. The aim of this study was to quantify the contribution of statins to the observed fall in population mean cholesterol levels in England over the past two decades, and explore any differences between socioeconomic groups. This is a modelling study based on data from the Health Survey for England. We analysed changes in observed mean total cholesterol levels in the adult England population between 1991-92 (baseline) and 2011-12. We then compared the observed changes with a counterfactual 'no statins' scenario, where the impact of statins on population total cholesterol was estimated and removed. We estimated uncertainty intervals (UI) using Monte Carlo simulation, where confidence intervals (CI) were impractical. In 2011-12, 13.2% (95% CI: 12.5-14.0%) of the English adult population used statins at least once per week, compared with 1991-92 when the proportion was just 0.5% (95% CI: 0.3-1.0%). Between 1991-92 and 2011-12, mean total cholesterol declined from 5.86 mmol/L (95% CI: 5.82-5.90) to 5.17 mmol/L (95% CI: 5.14-5.20). For 2011-12, mean total cholesterol was lower in more deprived groups. In our 'no statins' scenario we predicted a mean total cholesterol of 5.36 mmol/L (95% CI: 5.33-5.40) for 2011-12. Statins were responsible for approximately 33.7% (95% UI: 28.9-38.8%) of the total cholesterol reduction since 1991-92. The statin contribution to cholesterol reduction was greater among the more deprived groups of women, while showing little socio-economic gradient among men. Our model suggests that statins explained around a third of the substantial falls in total cholesterol observed in England since 1991. Approximately two thirds of the cholesterol decrease can reasonably be attributed non-pharmacological determinants.

Objectives To estimate the potential impact of universal screening for primary prevention of cardiovascular disease (National Health Service Health Checks) on disease burden and socioeconomic inequalities in health in England, and to compare universal screening with alternative feasible strategies.Design Microsimulation study of a close-to-reality synthetic population. Five scenarios were considered: baseline scenario, assuming that current trends in risk factors will continue in the future; universal screening; screening concentrated only in the most deprived areas; structural population-wide intervention; and combination of population-wide intervention and concentrated screening.Setting Synthetic population with similar characteristics to the community dwelling population of England.Participants Synthetic people with traits informed by the health survey for England.Main outcome measure Cardiovascular disease cases and deaths prevented or postponed by 2030, stratified by fifths of socioeconomic status using the index of multiple deprivation.Results Compared with the baseline scenario, universal screening may prevent or postpone approximately 19 000 cases (interquartile range 11 000-28 000) and 3000 deaths (−1000-6000); concentrated screening 17 000 cases (9000-26 000) and 2000 deaths (−1000-5000); population-wide intervention 67 000 cases (57 000-77 000) and 8000 deaths (4000-11 000); and the combination of the population-wide intervention and concentrated screening 82 000 cases (73 000-93 000) and 9000 deaths (6000-13 000). The most equitable strategy would be the combination of the population-wide intervention and concentrated screening, followed by concentrated screening alone and the population-wide intervention. Universal screening had the least apparent impact on socioeconomic inequalities in health.Conclusions When primary prevention strategies for reducing cardiovascular disease burden and inequalities are compared, universal screening seems less effective than alternative strategies, which incorporate population-wide approaches. Further research is needed to identify the best mix of population-wide and risk targeted CVD strategies to maximise cost effectiveness and minimise inequalities.

Joint modelling of longitudinal data and competing risks has grown over the past decade. Despite the recent methodological developments, there are still limited options for fitting these models in standard statistical software programs, which prohibits their adoption by applied biostatisticians. We summarize four published models, each of which has software available for model estimation. Each model features a different hazard function, latent association structure between the submodels, estimation approach and software implementation. Of the four models considered here, the model specifications and association structures are substantially different, thus complicating model-to-model comparison. The models are applied to the ‘Standard and new anti-epileptic drugs’ trial of anti-epileptic drugs to investigate the effect of drug titration on the treatment effects of lamotrigine and carbamazepine on the mode of treatment failure. Notwithstanding the vastly different association structures, we show that the inference from each model is consistent, namely, that there is a beneficial effect of lamotrigine on unacceptable adverse events over carbamazepine and a non-significant effect on the hazard of inadequate seizure control. The association between anti-epileptic drug titration and treatment failure was significant in most models. To allow for the routine adoption of joint modelling of competing risks and longitudinal data in the analysis of clinical data sets, further work is required on the development of model diagnostics to aid model choice.

Species sensitivity distributions (SSDs) may accurately predict the proportion of species in a community that are at hazard from environmental contaminants only if they contain sensitivity data from a large sample of species representative of the mix of species present in the locality or habitat of interest. With current widely accepted ecotoxicological methods, however, this rarely occurs. Two recent suggestions address this problem. First, use rapid toxicity tests, which are less rigorous than conventional tests, to approximate experimentally the sensitivity of many species quickly and in approximate proportion to naturally occurring communities. Second, use expert judgements regarding the sensitivity of higher taxonomic groups (e.g., orders) and Bayesian statistical methods to construct SSDs that reflect the richness (or perceived importance) of these groups. Here, we describe and analyze several models from a Bayesian perspective to construct SSDs from data derived using rapid toxicity testing, combining both rapid test data and expert opinion. We compare these new models with two frequentist approaches, Kaplan-Meier and a log-normal distribution, using a large data set on the salinity sensitivity of freshwater macroinvertebrates from Victoria (Australia). The frequentist log-normal analysis produced a SSD that overestimated the hazard to species relative to the Kaplan-Meier and Bayesian analyses. Of the Bayesian analyses investigated, the introduction of a weighting factor to account for the richness (or importance) of taxonomic groups influenced the calculated hazard to species. Furthermore, Bayesian methods allowed us to determine credible intervals representing SSD uncertainty. We recommend that rapid tests, expert judgements, and novel Bayesian statistical methods be used so that SSDs reflect communities of organisms found in nature.

ObjectivesSocial deprivation impacts on healthcare outcomes but is not included in the majority of cardiac surgery risk prediction models. The objective was to investigate geographical variations in social deprivation of patients undergoing cardiac surgery and identify whether social deprivation is an independent predictor of outcomes.MethodsNational Adult Cardiac Surgery Audit data for coronary artery bypass graft (CABG), or valve surgery performed in England between April 2003 and March 2013, were analysed. Base hospitals in England were divided into geographical regions. Social deprivation was measured by quintile groups of the index of multiple deprivation (IMD) score with the first quintile group (Q1) being the least, and the last quintile group (Q5) the most deprived group. In-hospital mortality and midterm survival were analysed using mixed effects logistic, and stratified Cox proportional hazards regression models respectively.Results240 221 operations were analysed. There was substantial regional variation in social deprivation with the proportion of patients in IMD Q5 ranging from 34.5% in the North East to 6.5% in the East of England. Following adjustment for preoperative risk factors, patients undergoing all cardiac surgery in IMD Q5 were found to have an increased risk of in-hospital mortality relative to IMD Q1 (OR=1.13; 95%CI 1.03 to 1.24), as were patients undergoing isolated CABG (OR=1.19; 95%CI 1.03 to 1.37). For midterm survival, patients in IMD Q5 had an increased hazard in all groups (HRs ranged between 1.10 (valve+CABG) and 1.26 (isolated CABG)). For isolated CABG, the median postoperative length of stay was 6 and 7 days, respectively, for IMD Q1–Q4 and Q5.ConclusionsSignificant regional variation exists in the social deprivation of patients undergoing cardiac surgery in England. Social deprivation is associated with an increased risk of in-hospital mortality and reduced midterm survival. These findings have implications for health service provision, risk prediction models and analyses of surgical outcomes.

BackgroundThe SPYRAL HTN clinical trial program was initiated with two 80-patient pilot studies, SPYRAL HTN-OFF MED and SPYRAL HTN-ON MED, which provided biological proof of principle that renal denervation has a blood pressure-lowering effect versus sham controls for subjects with uncontrolled hypertension in the absence or presence of antihypertensive medications, respectively.Trial designTwo multicenter, prospective, randomized, sham-controlled trials have been designed to evaluate the safety and efficacy of catheter-based renal denervation for the reduction of blood pressure in subjects with hypertension in the absence (SPYRAL HTN-OFF MED Pivotal) or presence (SPYRAL HTN-ON MED Expansion) of antihypertensive medications. The primary efficacy endpoint is baseline-adjusted change from baseline in 24-h ambulatory systolic blood pressure. The primary safety endpoint is incidence of major adverse events at 1 month after randomization (or 6 months in cases of new renal artery stenosis). Both trials utilize a Bayesian design to allow for prespecified interim analyses to take place, and thus, the final sample sizes are dependent on whether enrollment is stopped at the first or second interim analysis. SPYRAL HTN-OFF MED Pivotal will enroll up to 300 subjects and SPYRAL HTN-ON MED Expansion will enroll up to 221 subjects. A novel Bayesian power prior approach will leverage historical information from the pilot studies, with a degree of discounting determined by the level of agreement with data from the prospectively powered studies.ConclusionsThe Bayesian paradigm represents a novel and promising approach in device-based hypertension trials.Clinical trial registrationURL: https://www.clinicaltrials.gov. Unique identifier: NCT02439749 (SPYRAL HTN-OFF MED Pivotal) and NCT02439775 (SPYRAL HTN-ON MED Expansion).