Safety and Efficacy of Liraglutide, 3.0 mg, Once Daily vs Placebo in Patients With Poor Weight Loss Following Metabolic Surgery: The BARI-OPTIMISE Randomized Clinical Trial

Importance

Metabolic surgery leads to weight loss and improved health, but these outcomes are highly variable. Poor weight loss is associated with lower circulating levels of glucagon-like peptide-1 (GLP-1).

Objective

To assess the efficacy and safety of the GLP-1 receptor agonist, liraglutide, 3.0 mg, on percentage body weight reduction in patients with poor weight loss and suboptimal GLP-1 response after metabolic surgery.

Design, Setting, and Participants

The Evaluation of Liraglutide 3.0 mg in Patients With Poor Weight Loss and a Suboptimal Glucagon-Like Peptide-1 Response (BARI-OPTIMISE) randomized placebo-controlled trial recruited adult patients at least 1 year after metabolic surgery who had experienced 20% or less body weight loss from the day of surgery and a suboptimal nutrient-stimulated GLP-1 response from 2 hospitals in London, United Kingdom, between October 2018 and November 2019. Key exclusion criteria were type 1 diabetes; severe concomitant psychiatric, gastrointestinal, cardiac, kidney or metabolic disease; and use of insulin, GLP-1 receptor analogues, and medication that can affect weight. The study period was 24 weeks followed by a 4-week follow-up period. Last participant follow-up was completed in June 2020. All participants and clinical study personnel were blinded to treatment allocation. Of 154 assessed for eligibility, 70 met trial criteria and were included in the study, and 57 completed follow-up.

Interventions

Liraglutide, 3.0 mg, once daily or placebo as an adjunct to lifestyle intervention with a 500-kcal daily energy deficit for 24 weeks, on a 1:1 allocation by computer-generated randomization sequence, stratified by surgery type (Roux-en-Y gastric bypass [RYGB] or sleeve gastrectomy [SG]) and type 2 diabetes status.

Main Outcome and Measures

The primary outcome was change in percentage body weight from baseline to the end of the 24-week study period based on an intention-to-treat analysis. Participant safety was assessed through monitoring of biochemical parameters, including kidney and liver function, physical examination, and assessment for adverse events.

Results

A total of 70 participants (mean [SD] age, 47.6 [10.7] years; 52 [74%] female) with a poor weight loss response following RYGB or SG were randomized to receive 3.0-mg liraglutide (n = 35) or placebo (n = 35). All participants received at least 1 dose of the trial drug. Eight participants discontinued treatment (4 per group), and 2 in the 3.0-mg liraglutide group and 1 in the placebo group were lost to follow-up. Due to COVID-19 restrictions, 3 participants in the 3.0-mg liraglutide group and 7 in the placebo group were unable to attend their final in-person assessment. Estimated change in mean (SD) percentage body weight from baseline to week 24 was -8.82 (4.94) with liraglutide, 3.0 mg (n = 31), vs -0.54 (3.32) with placebo (n = 26). The mean difference in percentage body weight change for liraglutide, 3.0 mg, vs placebo was -8.03 (95% CI, -10.39 to -5.66; P < .001). Adverse events, predominantly gastrointestinal, were more frequent with liraglutide, 3.0 mg (28 events [80%]), than placebo (20 events [57%]). There were no serious adverse events and no treatment-related deaths.

Conclusion and Relevance

These findings support the use of adjuvant liraglutide, 3.0 mg, for weight management in patients with poor weight loss and suboptimal GLP-1 response after metabolic surgery.

Trial Registration

ClinicalTrials.gov Identifier: NCT03341429.

Outlier identification and monitoring of institutional or clinician performance: an overview of statistical methods and application to national audit data

BACKGROUND

Institutions or clinicians (units) are often compared according to a performance indicator such as in-hospital mortality. Several approaches have been proposed for the detection of outlying units, whose performance deviates from the overall performance.

METHODS

We provide an overview of three approaches commonly used to monitor institutional performances for outlier detection. These are the common-mean model, the 'Normal-Poisson' random effects model and the 'Logistic' random effects model. For the latter we also propose a visualisation technique. The common-mean model assumes that the underlying true performance of all units is equal and that any observed variation between units is due to chance. Even after applying case-mix adjustment, this assumption is often violated due to overdispersion and a post-hoc correction may need to be applied. The random effects models relax this assumption and explicitly allow the true performance to differ between units, thus offering a more flexible approach. We discuss the strengths and weaknesses of each approach and illustrate their application using audit data from England and Wales on Adult Cardiac Surgery (ACS) and Percutaneous Coronary Intervention (PCI).

RESULTS

In general, the overdispersion-corrected common-mean model and the random effects approaches produced similar p-values for the detection of outliers. For the ACS dataset (41 hospitals) three outliers were identified in total but only one was identified by all methods above. For the PCI dataset (88 hospitals), seven outliers were identified in total but only two were identified by all methods. The common-mean model uncorrected for overdispersion produced several more outliers. The reason for observing similar p-values for all three approaches could be attributed to the fact that the between-hospital variance was relatively small in both datasets, resulting only in a mild violation of the common-mean assumption; in this situation, the overdispersion correction worked well.

CONCLUSION

If the common-mean assumption is likely to hold, all three methods are appropriate to use for outlier detection and their results should be similar. Random effect methods may be the preferred approach when the common-mean assumption is likely to be violated.

Relationship Between Maximal Left Ventricular Wall Thickness and Sudden Cardiac Death in Childhood Onset Hypertrophic Cardiomyopathy

BACKGROUND

Maximal left ventricular wall thickness (MLVWT) is a risk factor for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM). In adults, the severity of left ventricular hypertrophy has a nonlinear relationship with SCD, but it is not known whether the same complex relationship is seen in childhood. The aim of this study was to describe the relationship between left ventricular hypertrophy and SCD risk in a large international pediatric HCM cohort.

METHODS

The study cohort comprised 1075 children (mean age, 10.2 years [±4.4]) diagnosed with HCM (1-16 years) from the International Paediatric Hypertrophic Cardiomyopathy Consortium. Anonymized, noninvasive clinical data were collected from baseline evaluation and follow-up, and 5-year estimated SCD risk was calculated (HCM Risk-Kids).

RESULTS

MLVWT Z score was <10 in 598 (58.1%), ≥10 to <20 in 334 (31.1%), and ≥20 in 143 (13.3%). Higher MLVWT Z scores were associated with heart failure symptoms, unexplained syncope, left ventricular outflow tract obstruction, left atrial dilatation, and nonsustained ventricular tachycardia. One hundred twenty-two patients (71.3%) with MLVWT Z score ≥20 had coexisting risk factors for SCD. Over a median follow-up of 4.9 years (interquartile range, 2.3-9.3), 115 (10.7%) had an SCD event. Freedom from SCD event at 5 years for those with MLVWT Z scores <10, ≥10 to <20, and ≥20 was 95.6%, 87.4%, and 86.0, respectively. The estimated SCD risk at 5 years had a nonlinear, inverted U-shaped relationship with MLVWT Z score, peaking at Z score +23. The presence of coexisting risk factors had a summative effect on risk.

CONCLUSIONS

In children with HCM, an inverted U-shaped relationship exists between left ventricular hypertrophy and estimated SCD risk. The presence of additional risk factors has a summative effect on risk. While MLVWT is important for risk stratification, it should not be used either as a binary variable or in isolation to guide implantable cardioverter defibrillator implantation decisions in children with HCM.

The accuracy of clinician predictions of survival in the Prognosis in Palliative care Study II (PiPS2): A prospective observational study

BACKGROUND

Prognostic information is important for patients with cancer, their families, and clinicians. In practice, survival predictions are made by clinicians based on their experience, judgement, and intuition. Previous studies have reported that clinicians' survival predictions are often inaccurate. This study reports a secondary analysis of data from the Prognosis in Palliative care Study II (PiPS2) to assess the accuracy of survival estimates made by doctors and nurses.

METHODS AND FINDINGS

Adult patients (n = 1833) with incurable, locally advanced or metastatic cancer, recently referred to palliative care services (community teams, hospital teams, and inpatient palliative care units) were recruited. Doctors (n = 431) and nurses (n = 777) provided independent prognostic predictions and an agreed multi-professional prediction for each patient. Clinicians provided prognostic estimates in several formats including predictions about length of survival and probability of surviving to certain time points. There was a minimum follow up of three months or until death (whichever was sooner; maximum follow-up 783 days). Agreed multi-professional predictions about whether patients would survive for days, weeks or months+ were accurate on 61.9% of occasions. The positive predictive value of clinicians' predictions about imminent death (within one week) was 77% for doctors and 79% for nurses. The sensitivity of these predictions was low (37% and 35% respectively). Specific predictions about how many weeks patients would survive were not very accurate but showed good discrimination (patients estimated to survive for shorted periods had worse outcomes). The accuracy of clinicians' probabilistic predictions (assessed using Brier's scores) was consistently better than chance, improved with proximity to death and showed good discrimination between groups of patients with different survival outcomes.

CONCLUSIONS

Using a variety of different approaches, this study found that clinicians predictions of survival show good discrimination and accuracy, regardless of whether the predictions are about how long or how likely patients are to survive. Accuracy improves with proximity to death. Although the positive predictive value of estimates of imminent death are relatively high, the sensitivity of such predictions is relatively low. Despite limitations, the clinical prediction of survival should remain the benchmark against which any innovations in prognostication are judged.

STUDY REGISTRATION

ISRCTN13688211. http://www.isrctn.com/ISRCTN13688211.

External validation of the HCM Risk-Kids model for predicting sudden cardiac death in childhood hypertrophic cardiomyopathy

AIMS

Sudden cardiac death (SCD) is the most common mode of death in childhood hypertrophic cardiomyopathy (HCM). The newly developed HCM Risk-Kids model provides clinicians with individualized estimates of risk. The aim of this study was to externally validate the model in a large independent, multi-centre patient cohort.

METHODS AND RESULTS

A retrospective, longitudinal cohort of 421 patients diagnosed with HCM aged 1-16 years independent of the HCM Risk-Kids development and internal validation cohort was studied. Data on HCM Risk-Kids predictor variables (unexplained syncope, non-sustained ventricular tachycardia, maximal left ventricular wall thickness, left atrial diameter, and left ventricular outflow tract gradient) were collected from the time of baseline clinical evaluation. The performance of the HCM Risk-Kids model in predicting risk at 5 years was assessed. Twenty-three patients (5.4%) met the SCD end-point within 5 years, with an overall incidence rate of 2.03 per 100 patient-years [95% confidence interval (CI) 1.48-2.78]. Model validation showed a Harrell's C-index of 0.745 (95% CI 0.52-0.97) and Uno's C-index 0.714 (95% 0.58-0.85) with a calibration slope of 1.15 (95% 0.51-1.80). A 5-year predicted risk threshold of ≥6% identified 17 (73.9%) SCD events with a corresponding C-statistic of 0.702 (95% CI 0.60-0.81).

CONCLUSIONS

This study reports the first external validation of the HCM Risk-Kids model in a large and geographically diverse patient population. A 5-year predicted risk of ≥6% identified over 70% of events, confirming that HCM Risk-Kids provides a method for individualized risk predictions and shared decision-making in children with HCM.

Risk prediction in multicentre studies when there is confounding by cluster or informative cluster size

Background

Clustered data arise in research when patients are clustered within larger units. Generalised Estimating Equations (GEE) and Generalised Linear Models (GLMM) can be used to provide marginal and cluster-specific inference and predictions, respectively.

Methods

Confounding by Cluster (CBC) and Informative cluster size (ICS) are two complications that may arise when modelling clustered data. CBC can arise when the distribution of a predictor variable (termed ‘exposure’), varies between clusters causing confounding of the exposure-outcome relationship. ICS means that the cluster size conditional on covariates is not independent of the outcome. In both situations, standard GEE and GLMM may provide biased or misleading inference, and modifications have been proposed. However, both CBC and ICS are routinely overlooked in the context of risk prediction, and their impact on the predictive ability of the models has been little explored. We study the effect of CBC and ICS on the predictive ability of risk models for binary outcomes when GEE and GLMM are used. We examine whether two simple approaches to handle CBC and ICS, which involve adjusting for the cluster mean of the exposure and the cluster size, respectively, can improve the accuracy of predictions.

Results

Both CBC and ICS can be viewed as violations of the assumptions in the standard GLMM; the random effects are correlated with exposure for CBC and cluster size for ICS. Based on these principles, we simulated data subject to CBC/ICS. The simulation studies suggested that the predictive ability of models derived from using standard GLMM and GEE ignoring CBC/ICS was affected. Marginal predictions were found to be mis-calibrated. Adjusting for the cluster-mean of the exposure or the cluster size improved calibration, discrimination and the overall predictive accuracy of marginal predictions, by explaining part of the between cluster variability. The presence of CBC/ICS did not affect the accuracy of conditional predictions. We illustrate these concepts using real data from a multicentre study with potential CBC.

Conclusion

Ignoring CBC and ICS when developing prediction models for clustered data can affect the accuracy of marginal predictions. Adjusting for the cluster mean of the exposure or the cluster size can improve the predictive accuracy of marginal predictions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01321-x.

Study recruitment factors in advanced cancer: the Prognosis in Palliative care Study II (PiPS2) - a multicentre, prospective, observational cohort project

OBJECTIVES

The Prognosis in Palliative care Study II (PiPS2) was a large multicentre observational study validating prognostic tools in patients with advanced cancer. Many palliative care studies fail to reach their recruitment target. To inform future studies, PiPS2 rigorously monitored and identified any potential recruitment barriers.

METHODS

Key recruitment stages (ie, whether patients were eligible for the study, approached by the researchers and whether consent was obtained for enrolment) were monitored via comprehensive screening logs at participating sites (inpatient hospices, hospitals and community palliative care teams). The reasons for patients' ineligibility, inaccessibility or decision not to consent were documented.

RESULTS

17 014 patients were screened across 27 participating sites over a 20-month recruitment period. Of those, 4642 (27%) were ineligible for participation in the study primarily due to non-cancer diagnoses. Of 12 372 eligible patients, 9073 (73%) were not approached, the most common reason being a clinical decision not to do so. Other reasons included patients' death or discharge before they were approached by the researchers. Of the 3299 approached patients, 1458 (44%) declined participation mainly because of feeling too unwell, experiencing severe distress or having other competing priorities. 11% (n=1841/17 014) of patients screened were enrolled in the study, representing 15% (n=1841/12 372) of eligible patients. Different recruitment patterns were observed across inpatient hospice, hospital and community palliative care teams.

CONCLUSIONS

The main barrier to recruitment was 'accessing' potentially eligible patients. Monitoring key recruitment stages may help to identify barriers and facilitators to enrolment and allow results to be put into better context.

TRIAL REGISTRATION NUMBER

ISRCTN13688211.

Prognostic models of survival in patients with advanced incurable cancer: the PiPS2 observational study

BACKGROUND

The Prognosis in Palliative care Study (PiPS) prognostic survival models predict survival in patients with incurable cancer. PiPS-A (Prognosis in Palliative care Study - All), which involved clinical observations only, and PiPS-B (Prognosis in Palliative care Study - Blood), which additionally required blood test results, consist of 14- and 56-day models that combine to create survival risk categories: 'days', 'weeks' and 'months+'.

OBJECTIVES

The primary objectives were to compare PIPS-B risk categories against agreed multiprofessional estimates of survival and to validate PiPS-A and PiPS-B. The secondary objectives were to validate other prognostic models, to assess the acceptability of the models to patients, carers and health-care professionals and to identify barriers to and facilitators of clinical use.

DESIGN

This was a national, multicentre, prospective, observational, cohort study with a nested qualitative substudy using interviews with patients, carers and health-care professionals.

SETTING

Community, hospital and hospice palliative care services across England and Wales.

PARTICIPANTS

For the validation study, the participants were adults with incurable cancer, with or without capacity to consent, who had been recently referred to palliative care services and had sufficient English language. For the qualitative substudy, a subset of participants in the validation study took part, along with informal carers, patients who declined to participate in the main study and health-care professionals.

MAIN OUTCOME MEASURES

For the validation study, the primary outcomes were survival, clinical prediction of survival and PiPS-B risk category predictions. The secondary outcomes were predictions of PiPS-A and other prognostic models. For the qualitative substudy, the main outcomes were participants' views about prognostication and the use of prognostic models.

RESULTS

For the validation study, 1833 participants were recruited. PiPS-B risk categories were as accurate as agreed multiprofessional estimates of survival (61%; p = 0.851). Discrimination of the PiPS-B 14-day model (c-statistic 0.837, 95% confidence interval 0.810 to 0.863) and the PiPS-B 56-day model (c-statistic 0.810, 95% confidence interval 0.788 to 0.832) was excellent. The PiPS-B 14-day model showed some overfitting (calibration in the large -0.202, 95% confidence interval -0.364 to -0.039; calibration slope 0.840, 95% confidence interval 0.730 to 0.950). The PiPS-B 56-day model was well-calibrated (calibration in the large 0.152, 95% confidence interval 0.030 to 0.273; calibration slope 0.914, 95% confidence interval 0.808 to 1.02). PiPS-A risk categories were less accurate than agreed multiprofessional estimates of survival (p < 0.001). The PiPS-A 14-day model (c-statistic 0.825, 95% confidence interval 0.803 to 0.848; calibration in the large -0.037, 95% confidence interval -0.168 to 0.095; calibration slope 0.981, 95% confidence interval 0.872 to 1.09) and the PiPS-A 56-day model (c-statistic 0.776, 95% confidence interval 0.755 to 0.797; calibration in the large 0.109, 95% confidence interval 0.002 to 0.215; calibration slope 0.946, 95% confidence interval 0.842 to 1.05) had excellent or reasonably good discrimination and calibration. Other prognostic models were also validated. Where comparisons were possible, the other prognostic models performed less well than PiPS-B. For the qualitative substudy, 32 health-care professionals, 29 patients and 20 carers were interviewed. The majority of patients and carers expressed a desire for prognostic information and said that PiPS could be helpful. Health-care professionals said that PiPS was user friendly and may be helpful for decision-making and care-planning. The need for a blood test for PiPS-B was considered a limitation.

LIMITATIONS

The results may not be generalisable to other populations.

CONCLUSIONS

PiPS-B risk categories are as accurate as agreed multiprofessional estimates of survival. PiPS-A categories are less accurate. Patients, carers and health-care professionals regard PiPS as potentially helpful in clinical practice.

FUTURE WORK

A study to evaluate the impact of introducing PiPS into routine clinical practice is needed.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN13688211.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 28. See the NIHR Journals Library website for further project information.

Estimation of required sample size for external validation of risk models for binary outcomes

Risk-prediction models for health outcomes are used in practice as part of clinical decision-making, and it is essential that their performance be externally validated. An important aspect in the design of a validation study is choosing an adequate sample size. In this paper, we investigate the sample size requirements for validation studies with binary outcomes to estimate measures of predictive performance (C-statistic for discrimination and calibration slope and calibration in the large). We aim for sufficient precision in the estimated measures. In addition, we investigate the sample size to achieve sufficient power to detect a difference from a target value. Under normality assumptions on the distribution of the linear predictor, we obtain simple estimators for sample size calculations based on the measures above. Simulation studies show that the estimators perform well for common values of the C-statistic and outcome prevalence when the linear predictor is marginally Normal. Their performance deteriorates only slightly when the normality assumptions are violated. We also propose estimators which do not require normality assumptions but require specification of the marginal distribution of the linear predictor and require the use of numerical integration. These estimators were also seen to perform very well under marginal normality. Our sample size equations require a specified standard error (SE) and the anticipated C-statistic and outcome prevalence. The sample size requirement varies according to the prognostic strength of the model, outcome prevalence, choice of the performance measure and study objective. For example, to achieve an SE < 0.025 for the C-statistic, 60–170 events are required if the true C-statistic and outcome prevalence are between 0.64–0.85 and 0.05–0.3, respectively. For the calibration slope and calibration in the large, achieving SE < 0.15 would require 40–280 and 50–100 events, respectively. Our estimators may also be used for survival outcomes when the proportion of censored observations is high.

The role of the electrocardiographic phenotype in risk stratification for sudden cardiac death in childhood hypertrophic cardiomyopathy

AIMS

The 12-lead electrocardiogram (ECG) is routinely performed in children with hypertrophic cardiomyopathy (HCM). An ECG risk score has been suggested as a useful tool for risk stratification, but this has not been independently validated. This aim of this study was to describe the ECG phenotype of childhood HCM in a large, international, multi-centre cohort and investigate its role in risk prediction for arrhythmic events.

METHODS AND RESULTS

Data from 356 childhood HCM patients with a mean age of 10.1 years (±4.5) were collected from a retrospective, multi-centre international cohort. Three hundred and forty-seven (97.5%) patients had ECG abnormalities at baseline, most commonly repolarization abnormalities (n = 277, 77.8%); left ventricular hypertrophy (n = 240, 67.7%); abnormal QRS axis (n = 126, 35.4%); or QT prolongation (n = 131, 36.8%). Over a median follow-up of 3.9 years (interquartile range 2.0-7.7), 25 (7%) had an arrhythmic event, with an overall annual event rate of 1.38 (95% CI 0.93-2.04). No ECG variables were associated with 5-year arrhythmic event on univariable or multivariable analysis. The ECG risk score threshold of >5 had modest discriminatory ability [C-index 0.60 (95% CI 0.484-0.715)], with corresponding negative and positive predictive values of 96.7% and 6.7.

CONCLUSION

In a large, international, multi-centre cohort of childhood HCM, ECG abnormalities were common and varied. No ECG characteristic, either in isolation or combined in the previously described ECG risk score, was associated with 5-year sudden cardiac death risk. This suggests that the role of baseline ECG phenotype in improving risk stratification in childhood HCM is limited.

Community Occupational Therapy for people with dementia and family carers (COTiD-UK) versus treatment as usual (Valuing Active Life in Dementia [VALID]) study: A single-blind, randomised controlled trial

BACKGROUND

We aimed to estimate the clinical effectiveness of Community Occupational Therapy for people with dementia and family carers-UK version (Community Occupational Therapy in Dementia-UK version [COTiD-UK]) relative to treatment as usual (TAU). We hypothesised that COTiD-UK would improve the ability of people with dementia to perform activities of daily living (ADL), and family carers' sense of competence, compared with TAU.

METHODS AND FINDINGS

The study design was a multicentre, 2-arm, parallel-group, assessor-masked, individually randomised controlled trial (RCT) with internal pilot. It was conducted in 15 sites across England from September 2014 to January 2018. People with a diagnosis of mild to moderate dementia living in their own home were recruited in pairs with a family carer who provided domestic or personal support for at least 4 hours per week. Pairs were randomised to either receive COTiD-UK, which comprised 10 hours of occupational therapy delivered over 10 weeks in the person with dementia's home or TAU, which comprised the usual local service provision that may or may not include standard occupational therapy. The primary outcome was the Bristol Activities of Daily Living Scale (BADLS) score at 26 weeks. Secondary outcomes for the person with dementia included the following: the BADLS scores at 52 and 78 weeks, cognition, quality of life, and mood; and for the family carer: sense of competence and mood; plus the number of social contacts and leisure activities for both partners. Participants were analysed by treatment allocated. A total of 468 pairs were recruited: people with dementia ranged from 55 to 97 years with a mean age of 78.6 and family carers ranged from 29 to 94 with a mean of 69.1 years. Of the people with dementia, 74.8% were married and 19.2% lived alone. Of the family carers, 72.6% were spouses, and 22.2% were adult children. On randomisation, 249 pairs were assigned to COTiD-UK (62% people with dementia and 23% carers were male) and 219 to TAU (52% people with dementia and 32% carers were male). At the 26 weeks follow-up, data were available for 364 pairs (77.8%). The BADLS score at 26 weeks did not differ significantly between groups (adjusted mean difference estimate 0.35, 95% CI -0.81 to 1.51; p = 0.55). Secondary outcomes did not differ between the groups. In total, 91% of the activity-based goals set by the pairs taking part in the COTiD-UK intervention were fully or partially achieved by the final COTiD-UK session. Study limitations include the following: Intervention fidelity was moderate but varied across and within sites, and the reliance on primarily proxy data focused on measuring the level of functional or cognitive impairment which may not truly reflect the actual performance and views of the person living with dementia.

CONCLUSIONS

Providing community occupational therapy as delivered in this study did not improve ADL performance, cognition, quality of life, or mood in people with dementia nor sense of competence or mood in family carers. Future research should consider measuring person-centred outcomes that are more meaningful and closely aligned to participants' priorities, such as goal achievement or the quantity and quality of activity engagement and participation.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN10748953.

A comparison of methods for analysing multiple outcome measures in randomised controlled trials using a simulation study

Multiple primary outcomes are sometimes collected and analysed in randomised controlled trials (RCTs), and are used in favour of a single outcome. By collecting multiple primary outcomes, it is possible to fully evaluate the effect that an intervention has for a given disease process. A simple approach to analysing multiple outcomes is to consider each outcome separately, however, this approach does not account for any pairwise correlations between the outcomes. Any cases with missing values must be ignored, unless an additional imputation step is performed. Alternatively, multivariate methods that explicitly model the pairwise correlations between the outcomes may be more efficient when some of the outcomes have missing values. In this paper, we present an overview of relevant methods that can be used to analyse multiple outcome measures in RCTs, including methods based on multivariate multilevel (MM) models. We perform simulation studies to evaluate the bias in the estimates of the intervention effects and the power of detecting true intervention effects observed when using selected methods. Different simulation scenarios were constructed by varying the number of outcomes, the type of outcomes, the degree of correlations between the outcomes and the proportions and mechanisms of missing data. We compare multivariate methods to univariate methods with and without multiple imputation. When there are strong correlations between the outcome measures (ρ > .4), our simulation studies suggest that there are small power gains when using the MM model when compared to analysing the outcome measures separately. In contrast, when there are weak correlations (ρ < .4), the power is reduced when using univariate methods with multiple imputation when compared to analysing the outcome measures separately.

A validation study of the European Society of Cardiology guidelines for risk stratification of sudden cardiac death in childhood hypertrophic cardiomyopathy

AIMS

Sudden cardiac death (SCD) is the most common cause of death in children with hypertrophic cardiomyopathy (HCM). The European Society of Cardiology (ESC) recommends consideration of an implantable cardioverter-defibrillator (ICD) if two or more clinical risk factors (RFs) are present, but this approach to risk stratification has not been formally validated.

METHODS AND RESULTS

Four hundred and eleven paediatric HCM patients were assessed for four clinical RFs in accordance with current ESC recommendations: severe left ventricular hypertrophy, unexplained syncope, non-sustained ventricular tachycardia, and family history of SCD. The primary endpoint was a composite outcome of SCD or an equivalent event (aborted cardiac arrest, appropriate ICD therapy, or sustained ventricular tachycardia), defined as a major arrhythmic cardiac event (MACE). Over a follow-up period of 2890 patient years (median 5.5 years), MACE occurred in 21 patients (7.5%) with 0 RFs, 19 (16.8%) with 1 RFs, and 3 (18.8%) with 2 or more RFs. Corresponding incidence rates were 1.13 [95% confidence interval (CI) 0.7-1.73], 2.07 (95% CI 1.25-3.23), and 2.52 (95% CI 0.53-7.35) per 100 patient years at risk. Patients with two or more RFs did not have a higher incidence of MACE (log-rank test P = 0.34), with a positive and negative predictive value of 19% and 90%, respectively. The C-statistic was 0.62 (95% CI 0.52-0.72) at 5 years.

CONCLUSIONS

The incidence of MACE is higher for patients with increasing numbers of clinical RFs. However, the current ESC guidelines have a low ability to discriminate between high- and low-risk individuals.

A contingency management intervention to reduce cannabis use and time to relapse in early psychosis: the CIRCLE RCT

BACKGROUND

Cannabis is the most prevalent illicit substance among people with psychosis, and its use is associated with poorer clinical and social outcomes. However, so far, there has been limited evidence that any treatment is effective for reducing use. Contingency management (CM) is an incentive-based intervention for substance misuse that has a substantial evidence base across a range of substances and cohorts. However, to date there have been no randomised controlled trials (RCTs) of CM as a treatment for cannabis use specifically in psychosis.

OBJECTIVE

To conduct a RCT investigating the clinical effectiveness and cost-effectiveness of CM in reducing cannabis use among Early Intervention in Psychosis (EIP) service users.

DESIGN

The CIRCLE (Contingency Intervention for Reduction of Cannabis in Early Psychosis) trial was a rater-blinded, multicentre RCT with two arms. Participants were randomised 1 : 1 to either an CM arm, in which participants received CM for cannabis use alongside an optimised treatment-as-usual programme including structured psychoeducation, or a control arm in which participants received the treatment as usual only.

SETTING

EIP services across the Midlands and the south-east of England.

PARTICIPANTS

The main eligibility criteria were EIP service users with a history of psychosis, aged 18-36 years, and having used cannabis at least once per week during 12 of the previous 24 weeks.

INTERVENTION

The CM intervention offered financial incentives (i.e. shopping vouchers) for cannabis abstinence over 12 once-weekly sessions, confirmed using urinalysis. The maximum value in vouchers that participants could receive was £240.

MAIN OUTCOME MEASURES

The main outcome was time to relapse, operationalised as admission to an acute mental health service or hospital. The primary outcome was assessed at 18 months post inclusion using electronic patient records. Secondary outcomes assessed the clinical effectiveness and cost-effectiveness of the intervention, for which data were collected at 3 and 18 months.

RESULTS

A total of 278 participants were randomised to the CM arm and 273 were randomised to the control arm. In total, 530 (96%) participants were followed up for the primary outcome. There was no significant difference in time to admission between trial arms by 18 months following consent (hazard ratio 1.03, 95% confidence interval 0.76 to 1.40). There were no statistically significant differences in most secondary outcomes, including cannabis use, at either follow-up assessment. There were 58 serious adverse events, comprising 52 inpatient episodes, five deaths and one arrest.

LIMITATIONS

Participant retention was low at 18 months, limiting the assessment of secondary outcomes. A different CM intervention design or reward level may have been effective.

CONCLUSIONS

The CM intervention did not appear to be effective in reducing cannabis use and acute relapse among people with early psychosis and problematic cannabis use.

FUTURE WORK

Cannabis use is still a significant clinical concern in this population. A pressing need remains to identify suitable treatments. A wider perspective on the social circumstances of young people with psychosis may be needed for a successful intervention to be found.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN33576045.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 23, No. 45. See the NIHR Journals Library website for further project information.

Seroprevalence of SARS-CoV-2 antibodies in people with an acute loss in their sense of smell and/or taste in a community-based population in London, UK: An observational cohort study

BACKGROUND

Loss of smell and taste are commonly reported symptoms associated with coronavirus disease 2019 (COVID-19); however, the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in people with acute loss of smell and/or taste is unknown. The study aimed to determine the seroprevalence of SARS-CoV-2 antibodies in a community-based population with acute loss of smell and/or taste and to compare the frequency of COVID-19 associated symptoms in participants with and without SARS-CoV-2 antibodies. It also evaluated whether smell or taste loss are indicative of COVID-19 infection.

METHODS AND FINDINGS

Text messages, sent via primary care centers in London, United Kingdom, invited people with loss of smell and/or taste in the preceding month, to participate. Recruitment took place between 23 April 2020 and 14 May 2020. A total of 590 participants enrolled via a web-based platform and responded to questions about loss of smell and taste and other COVID-19-related symptoms. Mean age was 39.4 years (SD ± 12.0) and 69.1% (n = 392) of participants were female. A total of 567 (96.1%) had a telemedicine consultation during which their COVID-19-related symptoms were verified and a lateral flow immunoassay test that detected SARS-CoV-2 immunoglobulin G (IgG) and immunoglobulin M (IgM) antibodies was undertaken under medical supervision. A total of 77.6% of 567 participants with acute smell and/or taste loss had SARS-CoV-2 antibodies; of these, 39.8% (n = 175) had neither cough nor fever. New loss of smell was more prevalent in participants with SARS-CoV-2 antibodies, compared with those without antibodies (93.4% versus 78.7%, p < 0.001), whereas taste loss was equally prevalent (90.2% versus 89.0%, p = 0.738). Seropositivity for SARS-CoV-2 was 3 times more likely in participants with smell loss (OR 2.86; 95% CI 1.27-6.36; p < 0.001) compared with those with taste loss. The limitations of this study are the lack of a general population control group, the self-reported nature of the smell and taste changes, and the fact our methodology does not take into account the possibility that a population subset may not seroconvert to develop SARS-CoV-2 antibodies post-COVID-19.

CONCLUSIONS

Our findings suggest that recent loss of smell is a highly specific COVID-19 symptom and should be considered more generally in guiding case isolation, testing, and treatment of COVID-19.

TRIALS REGISTRATION

ClinicalTrials.gov NCT04377815.

Empowering Better End-of-Life Dementia Care (EMBED-Care): A mixed methods protocol to achieve integrated person-centred care across settings

OBJECTIVES

Globally, the number of people with dementia who have palliative care needs will increase fourfold over the next 40 years. The Empowering Better End-of-Life Dementia Care (EMBED-Care) Programme aims to deliver a step change in care through a large sequential study, spanning multiple work streams.

METHODS

We will use mixed methods across settings where people with dementia live and die: their own homes, care homes, and hospitals. Beginning with policy syntheses and reviews of interventions, we will develop a conceptual framework and underpinning theory of change. We will use linked data sets to explore current service use, care transitions, and inequalities and predict future need for end-of-life dementia care. Longitudinal cohort studies of people with dementia (including young onset and prion dementias) and their carers will describe care transitions, quality of life, symptoms, formal and informal care provision, and costs. Data will be synthesised, underpinned by the Knowledge-to-Action Implementation Framework, to design a novel complex intervention to support assessment, decision making, and communication between patients, carers, and inter-professional teams. This will be feasibility and pilot tested in UK settings. Patient and public involvement and engagement, innovative work with artists, policymakers, and third sector organisations are embedded to drive impact. We will build research capacity and develop an international network for excellence in dementia palliative care.

CONCLUSIONS

EMBED-Care will help us understand current and future need, develop novel cost-effective care innovations, build research capacity, and promote international collaborations in research and practice to ensure people live and die well with dementia.

227A novel risk prediction model for sudden cardiac death in childhood hypertrophic cardiomyopathy (HCM Risk-Kids)

Background

Sudden cardiac death (SCD) is the most common mode of death in childhood hypertrophic cardiomyopathy (HCM) but there is no validated algorithm to identify those at highest risk. This study sought to develop and validate a SCD risk prediction model that provides individualized risk estimates.

Methods

A prognostic model was derived from an international, retrospective, multi-center longitudinal cohort study of 1024 consecutively evaluated patients aged ≤16 years. The model was developed using pre-selected predictor variables [unexplained syncope, maximal left ventricular (LV) wall thickness (MWT), left atrial diameter (LAD), LV outflow tract (LVOT) gradient and non-sustained ventricular tachycardia (NSVT)] identified from the literature and internally validated using bootstrapping.

Results

Over a median follow up of 5.3 years (IQR 2.6, 8.2, total patient years 5984), 89 (8.7%) patients died suddenly or had an equivalent event [annual event rate 1.49 (95% CI 1.15–1.92)]. The pediatric model was developed using pre-selected variables to predict the risk of SCD. The model's ability to predict risk at 5 years was validated; C-statistic was 0.69 (95% CI 0.66–0.72) and the calibration slope was 0.98 (95% CI 0.58–1.38). For every 10 ICDs implanted in patients with ≥6% 5-year SCD risk, potentially 1 patient will be saved from SCD at 5 years.

Conclusions

This new validated risk stratification model for SCD in childhood HCM provides accurate individualized estimates of risk at 5 years using readily obtained clinical risk factors.

Acknowledgement/Funding

British Heart Foundation

Development of a Novel Risk Prediction Model for Sudden Cardiac Death in Childhood Hypertrophic Cardiomyopathy (HCM Risk-Kids)

Importance

Sudden cardiac death (SCD) is the most common mode of death in childhood hypertrophic cardiomyopathy (HCM), but there is no validated algorithm to identify those at highest risk.

Objective

To develop and validate an SCD risk prediction model that provides individualized risk estimates.

Design, Setting, and Participants

A prognostic model was developed from a retrospective, multicenter, longitudinal cohort study of 1024 consecutively evaluated patients aged 16 years or younger with HCM. The study was conducted from January 1, 1970, to December 31, 2017.

Exposures

The model was developed using preselected predictor variables (unexplained syncope, maximal left-ventricular wall thickness, left atrial diameter, left-ventricular outflow tract gradient, and nonsustained ventricular tachycardia) identified from the literature and internally validated using bootstrapping.

Main Outcomes and Measures

A composite outcome of SCD or an equivalent event (aborted cardiac arrest, appropriate implantable cardioverter defibrillator therapy, or sustained ventricular tachycardia associated with hemodynamic compromise).

Results

Of the 1024 patients included in the study, 699 were boys (68.3%); mean (interquartile range [IQR]) age was 11 (7-14) years. Over a median follow-up of 5.3 years (IQR, 2.6-8.3; total patient years, 5984), 89 patients (8.7%) died suddenly or had an equivalent event (annual event rate, 1.49; 95% CI, 1.15-1.92). The pediatric model was developed using preselected variables to predict the risk of SCD. The model's ability to predict risk at 5 years was validated; the C statistic was 0.69 (95% CI, 0.66-0.72), and the calibration slope was 0.98 (95% CI, 0.59-1.38). For every 10 implantable cardioverter defibrillators implanted in patients with 6% or more of a 5-year SCD risk, 1 patient may potentially be saved from SCD at 5 years.

Conclusions and Relevance

This new, validated risk stratification model for SCD in childhood HCM may provide individualized estimates of risk at 5 years using readily obtained clinical risk factors. External validation studies are required to demonstrate the accuracy of this model's predictions in diverse patient populations.

Clinical and cost-effectiveness of contingency management for cannabis use in early psychosis: the CIRCLE randomised clinical trial

BACKGROUND

Cannabis is the most commonly used illicit substance amongst people with psychosis. Continued cannabis use following the onset of psychosis is associated with poorer functional and clinical outcomes. However, finding effective ways of intervening has been very challenging. We examined the clinical and cost-effectiveness of adjunctive contingency management (CM), which involves incentives for abstinence from cannabis use, in people with a recent diagnosis of psychosis.

METHODS

CIRCLE was a pragmatic multi-centre randomised controlled trial. Participants were recruited via Early Intervention in Psychosis (EIP) services across the Midlands and South East of England. They had had at least one episode of clinically diagnosed psychosis (affective or non-affective); were aged 18 to 36; reported cannabis use in at least 12 out of the previous 24 weeks; and were not currently receiving treatment for cannabis misuse, or subject to a legal requirement for cannabis testing. Participants were randomised via a secure web-based service 1:1 to either an experimental arm, involving 12 weeks of CM plus a six-session psychoeducation package, or a control arm receiving the psychoeducation package only. The total potential voucher reward in the CM intervention was £240. The primary outcome was time to acute psychiatric care, operationalised as admission to an acute mental health service (including community alternatives to admission). Primary outcome data were collected from patient records at 18 months post-consent by assessors masked to allocation. The trial was registered with the ISRCTN registry, number ISRCTN33576045.

RESULTS

Five hundred fifty-one participants were recruited between June 2012 and April 2016. Primary outcome data were obtained for 272 (98%) in the CM (experimental) group and 259 (95%) in the control group. There was no statistically significant difference in time to acute psychiatric care (the primary outcome) (HR 1.03, 95% CI 0.76, 1.40) between groups. By 18 months, 90 (33%) of participants in the CM group, and 85 (30%) of the control groups had been admitted at least once to an acute psychiatric service. Amongst those who had experienced an acute psychiatric admission, the median time to admission was 196 days (IQR 82, 364) in the CM group and 245 days (IQR 99, 382) in the control group. Cost-effectiveness analyses suggest that there is an 81% likelihood that the intervention was cost-effective, mainly resulting from higher mean inpatient costs for the control group compared with the CM group; however, the cost difference between groups was not statistically significant. There were 58 adverse events, 27 in the CM group and 31 in the control group.

CONCLUSIONS

Overall, these results suggest that CM is not an effective intervention for improving the time to acute psychiatric admission or reducing cannabis use in psychosis, at least at the level of voucher reward offered.

Methods to adjust for multiple comparisons in the analysis and sample size calculation of randomised controlled trials with multiple primary outcomes

BACKGROUND

Multiple primary outcomes may be specified in randomised controlled trials (RCTs). When analysing multiple outcomes it's important to control the family wise error rate (FWER). A popular approach to do this is to adjust the p-values corresponding to each statistical test used to investigate the intervention effects by using the Bonferroni correction. It's also important to consider the power of the trial to detect true intervention effects. In the context of multiple outcomes, depending on the clinical objective, the power can be defined as: 'disjunctive power', the probability of detecting at least one true intervention effect across all the outcomes or 'marginal power' the probability of finding a true intervention effect on a nominated outcome. We provide practical recommendations on which method may be used to adjust for multiple comparisons in the sample size calculation and the analysis of RCTs with multiple primary outcomes. We also discuss the implications on the sample size for obtaining 90% disjunctive power and 90% marginal power.

METHODS

We use simulation studies to investigate the disjunctive power, marginal power and FWER obtained after applying Bonferroni, Holm, Hochberg, Dubey/Armitage-Parmar and Stepdown-minP adjustment methods. Different simulation scenarios were constructed by varying the number of outcomes, degree of correlation between the outcomes, intervention effect sizes and proportion of missing data.

RESULTS

The Bonferroni and Holm methods provide the same disjunctive power. The Hochberg and Hommel methods provide power gains for the analysis, albeit small, in comparison to the Bonferroni method. The Stepdown-minP procedure performs well for complete data. However, it removes participants with missing values prior to the analysis resulting in a loss of power when there are missing data. The sample size requirement to achieve the desired disjunctive power may be smaller than that required to achieve the desired marginal power. The choice between whether to specify a disjunctive or marginal power should depend on the clincial objective.

Effectiveness of the 2014 European Society of Cardiology guideline on sudden cardiac death in hypertrophic cardiomyopathy: a systematic review and meta-analysis

OBJECTIVE

In 2014, the European Society of Cardiology (ESC) recommended the use of a novel risk prediction model (HCM Risk-SCD) to guide use of implantable cardioverter defibrillators (ICD) for the primary prevention of sudden cardiac death (SCD) in patients with hypertrophic cardiomyopathy (HCM). We sought to determine the performance of HCM Risk-SCD by conducting a systematic review and meta-analysis of articles reporting on the prevalence of SCD within 5 years of evaluation in low, intermediate and high-risk patients as defined by the 2014 guidelines (predicted risk <4%, 4%-<6% and ≥6%, respectively).

METHODS

The protocol was registered with PROSPERO (registration number: CRD42017064203). MEDLINE and manual searches for papers published from October 2014 to December 2017 were performed. Longitudinal, observational cohorts of unselected adult patients, without history of cardiac arrest were considered. The original HCM Risk-SCD development study was included a priori. Data were pooled using a random effects model.

RESULTS

Six (0.9%) out of 653 independent publications identified by the initial search were included. The calculated 5-year risk of SCD was reported in 7291 individuals (70% low, 15% intermediate; 15% high risk) with 184 (2.5%) SCD endpoints within 5 years of baseline evaluation. Most SCD endpoints (68%) occurred in patients with an estimated 5-year risk of ≥4% who formed 30% of the total study cohort. Using the random effects method, the pooled prevalence of SCD endpoints was 1.01% (95% CI 0.52 to 1.61) in low-risk patients, 2.43% (95% CI 1.23 to 3.92) in intermediate and 8.4% (95% CI 6.68 to 10.25) in high-risk patients.

CONCLUSIONS

This meta-analysis demonstrates that HCM Risk-SCD provides accurate risk estimations that can be used to guide ICD therapy in accordance with the 2014 ESC guidelines.

REGISTRATION NUMBER

PROSPERO CRD42017064203;Pre-results.

The Prognosis in Palliative care Study II (PiPS2): study protocol for a multi-centre, prospective, observational, cohort study

BACKGROUND

More accurate methods of prognostication are likely to lead to improvements in the quality of care of patients approaching the ends of their lives. The Prognosis in Palliative care Scales (PiPS) are prognostic models of survival. The scores are calculated using simple clinical data and observations. There are two separate PiPS models; PiPS-A for patients without blood test results and PiPS-B for patients with blood test results. Both models predict whether a patient is likely to live for "days", "weeks" or "months" and have been shown to perform as well as clinicians' estimates of survival. PiPS-B has also been found to be significantly better than doctors' estimates of survival. We report here a protocol for the validation of PiPS and for the evaluation of the accuracy of other prognostic tools in a new, larger cohort of patients with advanced cancer.

METHODS

This is a national, multi-centre, prospective, observational cohort study, aiming to recruit 1778 patients via palliative care services across England and Wales. Eligible patients have advanced, incurable cancer and have recently been referred to palliative care services. Patients with or without capacity are included in the study. The primary outcome is the accuracy of PiPS predictions and the difference in accuracy between these predictions and the clinicians' estimates of survival; with PiPS-B being the main model of interest. The secondary outcomes include the accuracy of predictions by the Palliative Prognostic Index (PPI), Palliative Performance Scale (PPS), Palliative Prognostic score (PaP) and the Feliu Prognostic Nomogram (FPN) compared with actual patient survival and clinicians' estimates of survival. A nested qualitative sub-study using face-to-face interviews with patients, carers and clinicians is also being undertaken to assess the acceptability of the prognostic models and to identify barriers and facilitators to clinical use.

DISCUSSION

The study closed to recruitment at the end of April 2018 having exceeded the required sample size of 1778 patients. The qualitative sub-study is nearing completion. This demonstrates the feasibility of recruiting large numbers of participants to a prospective palliative care study.

TRIAL REGISTRATION

ISRCTN13688211 (registration date: 28/06/2016).

Cost-effectiveness of habit-based advice for weight control versus usual care in general practice in the Ten Top Tips (10TT) trial: economic evaluation based on a randomised controlled trial

OBJECTIVE

Ten Top Tips (10TT) is a primary care-led behavioural intervention which aims to help adults reduce and manage their weight by following 10 weight loss tips. The intervention promotes habit formation to encourage long-term behavioural changes. The aim of this study was to estimate the cost-effectiveness of 10TT in general practice from the perspective of the UK National Health Service.

DESIGN

An economic evaluation was conducted alongside an individually randomised controlled trial.

SETTING

14 general practitioner practices in England.

PARTICIPANTS

All patients were aged ≥18 years, with body mass index ≥30 kg/m². A total of 537 patients were recruited; 270 received the usual care offered by their practices and 267 received the 10TT intervention.

OUTCOMES MEASURES

Health service use and quality-adjusted life years (QALYs) were measured over 2 years. Analysis was conducted in terms of incremental net monetary benefits (NMBs), using non-parametric bootstrapping and multiple imputation.

RESULTS

Over a 2-year time horizon, the mean costs and QALYs per patient in the 10TT group were £1889 (95% CI £1522 to £2566) and 1.51 (95% CI 1.44 to 1.58). The mean costs and QALYs for usual care were £1925 (95% CI £1599 to £2251) and 1.51 (95% CI 1.45 to 1.57), respectively. This generated a mean cost difference of -£36 (95% CI -£512 to £441) and a mean QALY difference of 0.001 (95% CI -0.080 to 0.082). The incremental NMB for 10TT versus usual care was £49 (95% CI -£1709 to £1800) at a maximum willingness to pay for a QALY of £20 000. 10TT had a 52% probability of being cost-effective at this threshold.

CONCLUSIONS

Costs and QALYs for 10TT were not significantly different from usual care and therefore 10TT is as cost-effective as usual care. There was no evidence to recommend nor advice against offering 10TT to obese patients in general practices based on cost-effectiveness considerations.

TRIAL REGISTRATION NUMBER

ISRCTN16347068; Post-results.

International External Validation Study of the 2014 European Society of Cardiology Guidelines on Sudden Cardiac Death Prevention in Hypertrophic Cardiomyopathy (EVIDENCE-HCM)

Background:

Identification of people with hypertrophic cardiomyopathy (HCM) who are at risk of sudden cardiac death (SCD) and require a prophylactic implantable cardioverter defibrillator is challenging. In 2014, the European Society of Cardiology proposed a new risk stratification method based on a risk prediction model (HCM Risk-SCD) that estimates the 5-year risk of SCD. The aim was to externally validate the 2014 European Society of Cardiology recommendations in a geographically diverse cohort of patients recruited from the United States, Europe, the Middle East, and Asia.

Methods:

This was an observational, retrospective, longitudinal cohort study.

Results:

The cohort consisted of 3703 patients. Seventy three (2%) patients reached the SCD end point within 5 years of follow-up (5-year incidence, 2.4% [95% confidence interval {CI}, 1.9–3.0]). The validation study revealed a calibration slope of 1.02 (95% CI, 0.93–1.12), C-index of 0.70 (95% CI, 0.68–0.72), and D-statistic of 1.17 (95% CI, 1.05–1.29). In a complete case analysis (n= 2147; 44 SCD end points at 5 years), patients with a predicted 5-year risk of <4% (n=1524; 71%) had an observed 5-year SCD incidence of 1.4% (95% CI, 0.8–2.2); patients with a predicted risk of ≥6% (n=297; 14%) had an observed SCD incidence of 8.9% (95% CI, 5.96–13.1) at 5 years. For every 13 (297/23) implantable cardioverter defibrillator implantations in patients with an estimated 5-year SCD risk ≥6%, 1 patient can potentially be saved from SCD.

Conclusions:

This study confirms that the HCM Risk-SCD model provides accurate prognostic information that can be used to target implantable cardioverter defibrillator therapy in patients at the highest risk of SCD.

Living and dying with advanced dementia: A prospective cohort study of symptoms, service use and care at the end of life

BACKGROUND

Increasing number of people are dying with advanced dementia. Comfort and quality of life are key goals of care.

AIMS

To describe (1) physical and psychological symptoms, (2) health and social care service utilisation and (3) care at end of life in people with advanced dementia.

DESIGN

9-month prospective cohort study.

SETTING AND PARTICIPANTS

Greater London, England, people with advanced dementia (Functional Assessment Staging Scale 6e and above) from 14 nursing homes or their own homes.

MAIN OUTCOME MEASURES

At study entry and monthly: prescriptions, Charlson Comorbidity Index, pressure sore risk/severity (Waterlow Scale/Stirling Scale, respectively), acute medical events, pain (Pain Assessment in Advanced Dementia), neuropsychiatric symptoms (Neuropsychiatric Inventory), quality of life (Quality of Life in Late-Stage Dementia Scale), resource use (Resource Utilization in Dementia Questionnaire and Client Services Receipt Inventory), presence/type of advance care plans, interventions, mortality, place of death and comfort (Symptom Management at End of Life in Dementia Scale).

RESULTS

Of 159 potential participants, 85 were recruited (62% alive at end of follow-up). Pain (11% at rest, 61% on movement) and significant agitation (54%) were common and persistent. Aspiration, dyspnoea, septicaemia and pneumonia were more frequent in those who died. In total, 76% had 'do not resuscitate' statements, less than 40% advance care plans. Most received primary care visits, there was little input from geriatrics or mental health but contact with emergency paramedics was common.

CONCLUSION

People with advanced dementia lived with distressing symptoms. Service provision was not tailored to their needs. Longitudinal multidisciplinary input could optimise symptom control and quality of life.

Clinical outcomes of staff training in positive behaviour support to reduce challenging behaviour in adults with intellectual disability: cluster randomised controlled trial

BACKGROUND

Staff training in positive behaviour support (PBS) is a widespread treatment approach for challenging behaviour in adults with intellectual disability. Aims To evaluate whether such training is clinically effective in reducing challenging behaviour during routine care (trial registration: NCT01680276).

METHOD

We carried out a multicentre, cluster randomised controlled trial involving 23 community intellectual disability services in England, randomly allocated to manual-assisted staff training in PBS (n = 11) or treatment as usual (TAU, n = 12). Data were collected from 246 adult participants.

RESULTS

No treatment effects were found for the primary outcome (challenging behaviour over 12 months, adjusted mean difference = -2.14, 95% CI: -8.79, 4.51) or secondary outcomes.

CONCLUSIONS

Staff training in PBS, as applied in this study, did not reduce challenging behaviour. Further research should tackle implementation issues and endeavour to identify other interventions that can reduce challenging behaviour. Declaration of interest None.

Association of Age, Sex and Deprivation with Quality Indicators for Diabetes: Population-Based Cross Sectional Survey in Primary Care

Objectives

To determine the quality of diabetes management in primary care after the publication of the National Service Framework and examine the impact of age, gender and deprivation on the achievement of established quality indicators.

Design

Population-based cross sectional survey using electronic general practice records carried out between June–October 2003.

Setting

Thirty-four practices in Wandsworth, South-West London, UK.

Participants

6035 adult patients (≥18 years) with diabetes from a total registered population of 201 572 patients.

Interventions

None.

Main Outcome Measures

Success rates for the diabetes quality indicators within the General Medical Services contract for general practitioners.

Results

We identified large variations in diabetes management between general practitioner practices with poorer recording of quality care in younger patients (18–44 years). In addition, younger patients had a worse cholesterol and glycaemia profile, although hypertension was more common in older patients. Gender and deprivation did not appear to be important determinants of the quality of care received.

Conclusions

There are large variations in diabetes management between general practitioner practices, with care seemingly worse for younger adults. Longitudinal studies are required to determine whether current UK quality improvement initiatives have been successful in attenuating existing variations in care and treatment outcomes.

Implementing the compassion intervention, a model for integrated care for people with advanced dementia towards the end of life in nursing homes: a naturalistic feasibility study

BACKGROUND

Many people with dementia die in nursing homes, but quality of care may be suboptimal. We developed the theory-driven 'Compassion Intervention' to enhance end-of-life care in advanced dementia.

OBJECTIVES

To (1) understand how the Intervention operated in nursing homes in different health economies; (2) collect preliminary outcome data and costs of an interdisciplinary care leader (ICL) to facilitate the Intervention; (3) check the Intervention caused no harm.

DESIGN

A naturalistic feasibility study of Intervention implementation for 6 months.

SETTINGS

Two nursing homes in northern London, UK.

PARTICIPANTS

Thirty residents with advanced dementia were assessed of whom nine were recruited for data collection; four of these residents' family members were interviewed. Twenty-eight nursing home and external healthcare professionals participated in interviews at 7 (n=19), 11 (n=19) and 15 months (n=10).

INTERVENTION

An ICL led two core Intervention components: (1) integrated, interdisciplinary assessment and care; (2) education and support for paid and family carers.

DATA COLLECTED

Process and outcome data were collected. Symptoms were recorded monthly for recruited residents. Semistructured interviews were conducted at 7, 11 and 15 months with nursing home staff and external healthcare professionals and at 7 months with family carers. ICL hours were costed using Department of Health and Health Education England tariffs.

RESULTS

Contextual differences were identified between sites: nursing home 2 had lower involvement with external healthcare services. Core components were implemented at both sites but multidisciplinary meetings were only established in nursing home 1. The Intervention prompted improvements in advance care planning, pain management and person-centred care; we observed no harm. Six-month ICL costs were £18 255.

CONCLUSIONS

Implementation was feasible to differing degrees across sites, dependent on context. Our data inform future testing to identify the Intervention's effectiveness in improving end-of-life care in advanced dementia.

TRIAL REGISTRATION

ClinicalTrials.gov:NCT02840318: Results.

Review and evaluation of performance measures for survival prediction models in external validation settings

Background

When developing a prediction model for survival data it is essential to validate its performance in external validation settings using appropriate performance measures. Although a number of such measures have been proposed, there is only limited guidance regarding their use in the context of model validation. This paper reviewed and evaluated a wide range of performance measures to provide some guidelines for their use in practice.

Methods

An extensive simulation study based on two clinical datasets was conducted to investigate the performance of the measures in external validation settings. Measures were selected from categories that assess the overall performance, discrimination and calibration of a survival prediction model. Some of these have been modified to allow their use with validation data, and a case study is provided to describe how these measures can be estimated in practice. The measures were evaluated with respect to their robustness to censoring and ease of interpretation. All measures are implemented, or are straightforward to implement, in statistical software.

Results

Most of the performance measures were reasonably robust to moderate levels of censoring. One exception was Harrell’s concordance measure which tended to increase as censoring increased.

Conclusions

We recommend that Uno’s concordance measure is used to quantify concordance when there are moderate levels of censoring. Alternatively, Gönen and Heller’s measure could be considered, especially if censoring is very high, but we suggest that the prediction model is re-calibrated first. We also recommend that Royston’s D is routinely reported to assess discrimination since it has an appealing interpretation. The calibration slope is useful for both internal and external validation settings and recommended to report routinely. Our recommendation would be to use any of the predictive accuracy measures and provide the corresponding predictive accuracy curves. In addition, we recommend to investigate the characteristics of the validation data such as the level of censoring and the distribution of the prognostic index derived in the validation setting before choosing the performance measures.

A randomised controlled trial of the clinical and cost-effectiveness of a contingency management intervention compared to treatment as usual for reduction of cannabis use and of relapse in early psychosis (CIRCLE): a study protocol for a randomised controlled trial

Background

Around 35–45 % of people in contact with services for a first episode of psychosis are using cannabis. Cannabis use is associated with delays in remission, poorer clinical outcomes, significant increases in the risk of relapse, and lower engagement in work or education. While there is a clear need for effective interventions, so far only very limited benefits have been achieved from psychological interventions. Contingency management (CM) is a behavioural intervention in which specified desired behavioural change is reinforced through financial rewards. CM is now recognised to have a substantial evidence base in some contexts and its adoption in the UK is advocated by the National Institute for Health and Care Excellence (NICE) guidance as a treatment for substance or alcohol misuse. However, there is currently little published data testing its effectiveness for reducing cannabis use in early psychosis.

Methods

CIRCLE is a two-arm, rater-blinded randomised controlled trial (RCT) investigating the clinical and cost-effectiveness of a CM intervention for reducing cannabis use among young people receiving treatment from UK Early Intervention in Psychosis (EIP) services. EIP service users (n = 544) with a recent history of cannabis use will be recruited. The experimental group will receive 12 once-weekly CM sessions, and a voucher reward if urinalysis shows that they have not used cannabis in the previous week. Both the experimental and the control groups will be offered an Optimised Treatment as Usual (OTAU) psychoeducational package targeting cannabis use. Assessment interviews will be performed at consent, at 3 months, and at 18 months. The primary outcome is time to relapse, defined as admission to an acute mental health service. Secondary outcomes include proportion of cannabis-free urine samples during the intervention period, severity of positive psychotic symptoms, quality-adjusted life years, and engagement in work or education.

Discussion

CIRCLE is a RCT of CM for cannabis use in young people with a recent history of psychosis (EIP service users) and recent cannabis use. It is designed to investigate whether the intervention is a clinically and cost-effective treatment for cannabis use. It is intended to inform future treatment delivery, particularly in EIP settings.

Trial registration

ISRCTN33576045: doi 10.1186/ISRCTN33576045, registered on 28 November 2011.

Inverted U-Shaped Relation Between the Risk of Sudden Cardiac Death and Maximal Left Ventricular Wall Thickness in Hypertrophic Cardiomyopathy

Background—

Hypertrophic cardiomyopathy is associated with sudden cardiac death (SCD). Some studies have shown an association between risk of sudden death and left ventricular maximal wall thickness (MWT), but there are few data in patients with extreme hypertrophy. The aim of this study was to determine the relation between MWT and the risk of SCD.

Methods and Results—

This is a multicenter, retrospective, longitudinal cohort study of 3673 adult (≥16 years) patients, previously used to develop and validate a risk prediction model for SCD (HCM Risk-SCD [hypertrophic cardiomyopathy risk-SCD]). There was an inverted U-shaped relation between MWT and the estimated 5-year risk of SCD. In patients with MWT≥35 mm (n=47; mean age, 33 years; 81% men), there was a single SCD end point (annual rate, 0.2%; 95% confidence interval, 0.03–1.60) and 3 additional cardiovascular events during a median follow-up of 9.5 years. Compared with patients with MWT≤14 mm, those with MWT≥35 mm did not have a higher risk for SCD (hazard ratio, 0.22; 95% confidence interval, 0.03–1.65), cardiovascular death (hazard ratio, 0.66; 95% confidence interval, 0.26–1.67), or all-cause mortality (hazard ratio, 0.73; 95% confidence interval, 0.32–1.69).

Conclusions—

The risk of SCD has a complex, nonlinear relationship to MWT. The pathophysiological mechanisms behind this observation require further study but implantable cardioverter defibrillator implantation should not be guided solely on the severity of left ventricular hypertrophy.

Clinical outcomes and costs for people with complex psychosis; a naturalistic prospective cohort study of mental health rehabilitation service users in England

BACKGROUND

Mental health rehabilitation services in England focus on people with complex psychosis. This group tend to have lengthy hospital admissions due to the severity of their problems and, despite representing only 10-20 % of all those with psychosis, they absorb 25-50 % of the total mental health budget. Few studies have investigated the effectiveness of these services and there is little evidence available to guide clinicians working in this area. As part of a programme of research into inpatient mental health rehabilitation services, we carried out a prospective study to investigate longitudinal outcomes and costs for patients of these services and the predictors of better outcome.

METHOD

Inpatient mental health rehabilitation services across England that scored above average (median) on a standardised quality assessment tool used in a previous national survey were eligible for the study. Unit quality was reassessed and costs of care and patient characteristics rated using standardised tools at recruitment. Multivariable regression modelling was used to investigate the relationship between service quality, patient characteristics and the following clinical outcomes at 12 month follow-up: social function; length of admission in the rehabiliation unit; successful community discharge (without readmission or community placement breakdown) and costs of care.

RESULTS

Across England, 50 units participated and 329 patients were followed over 12 months (94 % of those recruited). Service quality was not associated with patients' social function or length of admission (median 16 months) at 12 months but most patients were successfully discharged (56 %) or ready for discharge (14 %), with associated reductions in the costs of care. Factors associated with successful discharge were the recovery orientation of the service (OR 1.04, 95 % CI 1.00-1.08), and patients' activity (OR 1.03, 95 % CI 1.01-1.05) and social skills (OR 1.13, 95 % CI 1.04-1.24) at recruitment.

CONCLUSION

Inpatient mental health rehabilitation services in England are able to successfully discharge over half their patients within 18 months, reducing the costs of care for this complex group. Provision of recovery orientated practice that promotes patients' social skills and activities may further enhance the effectiveness of these services.

Review and evaluation of penalised regression methods for risk prediction in low-dimensional data with few events

Risk prediction models are used to predict a clinical outcome for patients using a set of predictors. We focus on predicting low-dimensional binary outcomes typically arising in epidemiology, health services and public health research where logistic regression is commonly used. When the number of events is small compared with the number of regression coefficients, model overfitting can be a serious problem. An overfitted model tends to demonstrate poor predictive accuracy when applied to new data. We review frequentist and Bayesian shrinkage methods that may alleviate overfitting by shrinking the regression coefficients towards zero (some methods can also provide more parsimonious models by omitting some predictors). We evaluated their predictive performance in comparison with maximum likelihood estimation using real and simulated data. The simulation study showed that maximum likelihood estimation tends to produce overfitted models with poor predictive performance in scenarios with few events, and penalised methods can offer improvement. Ridge regression performed well, except in scenarios with many noise predictors. Lasso performed better than ridge in scenarios with many noise predictors and worse in the presence of correlated predictors. Elastic net, a hybrid of the two, performed well in all scenarios. Adaptive lasso and smoothly clipped absolute deviation performed best in scenarios with many noise predictors; in other scenarios, their performance was inferior to that of ridge and lasso. Bayesian approaches performed well when the hyperparameters for the priors were chosen carefully. Their use may aid variable selection, and they can be easily extended to clustered-data settings and to incorporate external information.

Development of a model for integrated care at the end of life in advanced dementia: A whole systems UK-wide approach

BACKGROUND

The prevalence of dementia is rising worldwide and many people will die with the disease. Symptoms towards the end of life may be inadequately managed and informal and professional carers poorly supported. There are few evidence-based interventions to improve end-of-life care in advanced dementia.

AIM

To develop an integrated, whole systems, evidence-based intervention that is pragmatic and feasible to improve end-of-life care for people with advanced dementia and support those close to them.

DESIGN

A realist-based approach in which qualitative and quantitative data assisted the development of statements. These were incorporated into the RAND/UCLA appropriateness method to achieve consensus on intervention components. Components were mapped to underlying theory of whole systems change and the intervention described in a detailed manual.

SETTING/PARTICIPANTS

Data were collected from people with dementia, carers and health and social care professionals in England, from expert opinion and existing literature. Professional stakeholders in all four countries of the United Kingdom contributed to the RAND/UCLA appropriateness method process.

RESULTS

A total of 29 statements were agreed and mapped to individual, group, organisational and economic/political levels of healthcare systems. The resulting main intervention components are as follows: (1) influencing local service organisation through facilitation of integrated multi-disciplinary care, (2) providing training and support for formal and informal carers and (3) influencing local healthcare commissioning and priorities of service providers.

CONCLUSION

Use of in-depth data, consensus methods and theoretical understanding of the intervention components produced an evidence-based intervention for further testing in end-of-life care in advanced dementia.

Predicting dementia risk in primary care: development and validation of the Dementia Risk Score using routinely collected data

BACKGROUND

Existing dementia risk scores require collection of additional data from patients, limiting their use in practice. Routinely collected healthcare data have the potential to assess dementia risk without the need to collect further information. Our objective was to develop and validate a 5-year dementia risk score derived from primary healthcare data.

METHODS

We used data from general practices in The Health Improvement Network (THIN) database from across the UK, randomly selecting 377 practices for a development cohort and identifying 930,395 patients aged 60-95 years without a recording of dementia, cognitive impairment or memory symptoms at baseline. We developed risk algorithm models for two age groups (60-79 and 80-95 years). An external validation was conducted by validating the model on a separate cohort of 264,224 patients from 95 randomly chosen THIN practices that did not contribute to the development cohort. Our main outcome was 5-year risk of first recorded dementia diagnosis. Potential predictors included sociodemographic, cardiovascular, lifestyle and mental health variables.

RESULTS

Dementia incidence was 1.88 (95% CI, 1.83-1.93) and 16.53 (95% CI, 16.15-16.92) per 1000 PYAR for those aged 60-79 (n = 6017) and 80-95 years (n = 7104), respectively. Predictors for those aged 60-79 included age, sex, social deprivation, smoking, BMI, heavy alcohol use, anti-hypertensive drugs, diabetes, stroke/TIA, atrial fibrillation, aspirin, depression. The discrimination and calibration of the risk algorithm were good for the 60-79 years model; D statistic 2.03 (95% CI, 1.95-2.11), C index 0.84 (95% CI, 0.81-0.87), and calibration slope 0.98 (95% CI, 0.93-1.02). The algorithm had a high negative predictive value, but lower positive predictive value at most risk thresholds. Discrimination and calibration were poor for the 80-95 years model.

CONCLUSIONS

Routinely collected data predicts 5-year risk of recorded diagnosis of dementia for those aged 60-79, but not those aged 80+. This algorithm can identify higher risk populations for dementia in primary care. The risk score has a high negative predictive value and may be most helpful in 'ruling out' those at very low risk from further testing or intensive preventative activities.

Stepped wedge randomised controlled trials: systematic review of studies published between 2010 and 2014

BACKGROUND

In a stepped wedge, cluster randomised trial, clusters receive the intervention at different time points, and the order in which they received it is randomised. Previous systematic reviews of stepped wedge trials have documented a steady rise in their use between 1987 and 2010, which was attributed to the design's perceived logistical and analytical advantages. However, the interventions included in these systematic reviews were often poorly reported and did not adequately describe the analysis and/or methodology used. Since 2010, a number of additional stepped wedge trials have been published. This article aims to update previous systematic reviews, and consider what interventions were tested and the rationale given for using a stepped wedge design.

METHODS

We searched PubMed, PsychINFO, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Web of Science, the Cochrane Library and the Current Controlled Trials Register for articles published between January 2010 and May 2014. We considered stepped wedge randomised controlled trials in all fields of research. We independently extracted data from retrieved articles and reviewed them. Interventions were then coded using the functions specified by the Behaviour Change Wheel, and for behaviour change techniques using a validated taxonomy.

RESULTS

Our review identified 37 stepped wedge trials, reported in 10 articles presenting trial results, one conference abstract, 21 protocol or study design articles and five trial registrations. These were mostly conducted in developed countries (n = 30), and within healthcare organisations (n = 28). A total of 33 of the interventions were educationally based, with the most commonly used behaviour change techniques being 'instruction on how to perform a behaviour' (n = 32) and 'persuasive source' (n = 25). Authors gave a wide range of reasons for the use of the stepped wedge trial design, including ethical considerations, logistical, financial and methodological. The adequacy of reporting varied across studies: many did not provide sufficient detail regarding the methodology or calculation of the required sample size.

CONCLUSIONS

The popularity of stepped wedge trials has increased since 2010, predominantly in high-income countries. However, there is a need for further guidance on their reporting and analysis.

Sample size calculation for a stepped wedge trial

BACKGROUND

Stepped wedge trials (SWTs) can be considered as a variant of a clustered randomised trial, although in many ways they embed additional complications from the point of view of statistical design and analysis. While the literature is rich for standard parallel or clustered randomised clinical trials (CRTs), it is much less so for SWTs. The specific features of SWTs need to be addressed properly in the sample size calculations to ensure valid estimates of the intervention effect.

METHODS

We critically review the available literature on analytical methods to perform sample size and power calculations in a SWT. In particular, we highlight the specific assumptions underlying currently used methods and comment on their validity and potential for extensions. Finally, we propose the use of simulation-based methods to overcome some of the limitations of analytical formulae. We performed a simulation exercise in which we compared simulation-based sample size computations with analytical methods and assessed the impact of varying the basic parameters to the resulting sample size/power, in the case of continuous and binary outcomes and assuming both cross-sectional data and the closed cohort design.

RESULTS

We compared the sample size requirements for a SWT in comparison to CRTs based on comparable number of measurements in each cluster. In line with the existing literature, we found that when the level of correlation within the clusters is relatively high (for example, greater than 0.1), the SWT requires a smaller number of clusters. For low values of the intracluster correlation, the two designs produce more similar requirements in terms of total number of clusters. We validated our simulation-based approach and compared the results of sample size calculations to analytical methods; the simulation-based procedures perform well, producing results that are extremely similar to the analytical methods. We found that usually the SWT is relatively insensitive to variations in the intracluster correlation, and that failure to account for a potential time effect will artificially and grossly overestimate the power of a study.

CONCLUSIONS

We provide a framework for handling the sample size and power calculations of a SWT and suggest that simulation-based procedures may be more effective, especially in dealing with the specific features of the study at hand. In selected situations and depending on the level of intracluster correlation and the cluster size, SWTs may be more efficient than comparable CRTs. However, the decision about the design to be implemented will be based on a wide range of considerations, including the cost associated with the number of clusters, number of measurements and the trial duration.

How to develop a more accurate risk prediction model when there are few events

When the number of events is low relative to the number of predictors, standard regression could produce overfitted risk models that make inaccurate predictions. Use of penalised regression may improve the accuracy of risk prediction

A note on obtaining correct marginal predictions from a random intercepts model for binary outcomes

Background

Clustered data with binary outcomes are often analysed using random intercepts models or generalised estimating equations (GEE) resulting in cluster-specific or ‘population-average’ inference, respectively.

Methods

When a random effects model is fitted to clustered data, predictions may be produced for a member of an existing cluster by using estimates of the fixed effects (regression coefficients) and the random effect for the cluster (conditional risk calculation), or for a member of a new cluster (marginal risk calculation). We focus on the second. Marginal risk calculation from a random effects model is obtained by integrating over the distribution of random effects. However, in practice marginal risks are often obtained, incorrectly, using only estimates of the fixed effects (i.e. by effectively setting the random effects to zero). We compare these two approaches to marginal risk calculation in terms of model calibration.

Results

In simulation studies, it has been seen that use of the incorrect marginal risk calculation from random effects models results in poorly calibrated overall marginal predictions (calibration slope <1 and calibration in the large ≠ 0) with mis-calibration becoming worse with higher degrees of clustering. We clarify that this was due to the incorrect calculation of marginal predictions from a random intercepts model and explain intuitively why this approach is incorrect. We show via simulation that the correct calculation of marginal risks from a random intercepts model results in predictions with excellent calibration.

Conclusion

The logistic random intercepts model can be used to obtain valid marginal predictions by integrating over the distribution of random effects.

Electronic supplementary material

The online version of this article (doi:10.1186/s12874-015-0046-6) contains supplementary material, which is available to authorized users.

Are multiple primary outcomes analysed appropriately in randomised controlled trials? A review

OBJECTIVES

To review how multiple primary outcomes are currently considered in the analysis of randomised controlled trials. We briefly describe the methods available to safeguard the inferences and to raise awareness of the potential problems caused by multiple outcomes.

METHODS/DESIGN

We reviewed randomised controlled trials (RCTs) in neurology and psychiatry disease areas, as these frequently analyse multiple outcomes. We reviewed all published RCTs from July 2011 to June 2014 inclusive in the following high impact journals: The New England Journal of Medicine, The Lancet, The American Journal of Psychiatry, JAMA Psychiatry, The Lancet Neurology and Neurology. We examined the information presented in the abstract and the methods used for sample size calculation and statistical analysis. We recorded the number of primary outcomes, the methods used to account for multiple primary outcomes, the number of outcomes discussed in the abstract and the number of outcomes used in the sample size calculation.

RESULTS

Of the 209 RCTs that we identified, 60 (29%) analysed multiple primary outcomes. Of these, 45 (75%) did not adjust for multiplicity in their analyses. Had multiplicity been addressed, some of the trial conclusions would have changed. Of the 15 (25%) trials which accounted for multiplicity, Bonferroni's correction was the most commonly used method.

CONCLUSIONS

Our review shows that trials with multiple primary outcomes are common. However, appropriate steps are not usually taken in most of the analyses to safeguard the inferences against multiplicity. Authors should state their chosen primary outcomes clearly and justify their methods of analysis.

Prediction of thrombo-embolic risk in patients with hypertrophic cardiomyopathy (HCM Risk-CVA)

Aims

Atrial fibrillation (AF) and thrombo‐embolism (TE) are associated with reduced survival in hypertrophic cardiomyopathy (HCM), but the absolute risk of TE in patients with and without AF is unclear. The primary aim of this study was to derive and validate a model for estimating the risk of TE in HCM. Exploratory analyses were performed to determine predictors of TE, the performance of the CHA₂DS₂‐VASc score, and outcome with vitamin K antagonists (VKAs).

Methods and results

A retrospective, longitudinal cohort of seven institutions was used to develop multivariable Cox regression models fitted with pre‐selected predictors. Bootstrapping was used for validation. Of 4821 HCM patients recruited between 1986 and 2008, 172 (3.6%) reached the primary endpoint of cerebrovascular accident (CVA), transient ischaemic attack (TIA), or systemic peripheral embolus within 10 years. A total of 27.5% of patients had a CHA₂DS₂‐VASc score of 0, of whom 9.8% developed TE during follow‐up. Cox regression revealed an association between TE and age, AF, the interaction between age and AF, TE prior to first evaluation, NYHA class, left atrial (LA) diameter, vascular disease, and maximal LV wall thickness. There was a curvilinear relationship between LA size and TE risk. The model predicted TE with a C‐index of 0.75 [95% confidence interval (CI) 0.70–0.80] and the D‐statistic was 1.30 (95% CI 1.05–1.56). VKA treatment was associated with a 54.8% (95% CI 31–97%, P = 0.037) relative risk reduction in HCM patients with AF.

Conclusions

The study shows that the risk of TE in HCM patients can be identified using a small number of simple clinical features. LA size, in particular, should be monitored closely, and the assessment and treatment of conventional vascular risk factors should be routine practice in older patients. Exploratory analyses show for the first time evidence for a reduction of TE with VKA treatment. The CHA₂DS₂‐VASc score does not appear to correlate well with the clinical outcome in patients with HCM and should not be used to assess TE risk in this population.

Monetary costs of agitation in older adults with Alzheimer's disease in the UK: prospective cohort study

OBJECTIVE

While nearly half of all people with Alzheimer's disease (AD) have agitation symptoms every month, little is known about the costs of agitation in AD. We calculated the monetary costs associated with agitation in older adults with AD in the UK from a National Health Service and personal social services perspective.

DESIGN

Prospective cohort study.

SETTING

London and the South East Region of the UK (LASER-AD study).

PARTICIPANTS

224 people with AD recruited between July 2002 and January 2003 and followed up for 54 months.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome was health and social care costs, including accommodation costs and costs of contacts with health and social care services. Agitation was assessed using the Neuropsychiatric Inventory (NPI) agitation score.

RESULTS

After adjustment, health and social care costs varied significantly by agitation, from £29,000 over a 1 year period with no agitation symptoms (NPI agitation score=0) to £57,000 at the most severe levels of agitation (NPI agitation score=12; p=0.01). The mean excess cost associated with agitation per person with AD was £4091 a year, accounting for 12% of the health and social care costs of AD in our data, and equating to £2 billion a year across all people with AD in the UK.

CONCLUSIONS

Agitation in people with AD represents a substantial monetary burden over and above the costs associated with cognitive impairment.