163 research outputs found

    Unbiased estimation in seamless phase II/III trials with unequal treatment effect variances and hypothesis-driven selection rules.

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    Seamless phase II/III clinical trials offer an efficient way to select an experimental treatment and perform confirmatory analysis within a single trial. However, combining the data from both stages in the final analysis can induce bias into the estimates of treatment effects. Methods for bias adjustment developed thus far have made restrictive assumptions about the design and selection rules followed. In order to address these shortcomings, we apply recent methodological advances to derive the uniformly minimum variance conditionally unbiased estimator for two-stage seamless phase II/III trials. Our framework allows for the precision of the treatment arm estimates to take arbitrary values, can be utilised for all treatments that are taken forward to phase III and is applicable when the decision to select or drop treatment arms is driven by a multiplicity-adjusted hypothesis testing procedure. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd

    Correcting for bias in the selection and validation of informative diagnostic tests.

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    When developing a new diagnostic test for a disease, there are often multiple candidate classifiers to choose from, and it is unclear if any will offer an improvement in performance compared with current technology. A two-stage design can be used to select a promising classifier (if one exists) in stage one for definitive validation in stage two. However, estimating the true properties of the chosen classifier is complicated by the first stage selection rules. In particular, the usual maximum likelihood estimator (MLE) that combines data from both stages will be biased high. Consequently, confidence intervals and p-values flowing from the MLE will also be incorrect. Building on the results of Pepe et al. (SIM 28:762-779), we derive the most efficient conditionally unbiased estimator and exact confidence intervals for a classifier's sensitivity in a two-stage design with arbitrary selection rules; the condition being that the trial proceeds to the validation stage. We apply our estimation strategy to data from a recent family history screening tool validation study by Walter et al. (BJGP 63:393-400) and are able to identify and successfully adjust for bias in the tool's estimated sensitivity to detect those at higher risk of breast cancer

    Accounting for selection and correlation in the analysis of two-stage genome-wide association studies.

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    The problem of selection bias has long been recognized in the analysis of two-stage trials, where promising candidates are selected in stage 1 for confirmatory analysis in stage 2. To efficiently correct for bias, uniformly minimum variance conditionally unbiased estimators (UMVCUEs) have been proposed for a wide variety of trial settings, but where the population parameter estimates are assumed to be independent. We relax this assumption and derive the UMVCUE in the multivariate normal setting with an arbitrary known covariance structure. One area of application is the estimation of odds ratios (ORs) when combining a genome-wide scan with a replication study. Our framework explicitly accounts for correlated single nucleotide polymorphisms, as might occur due to linkage disequilibrium. We illustrate our approach on the measurement of the association between 11 genetic variants and the risk of Crohn's disease, as reported in Parkes and others (2007. Sequence variants in the autophagy gene IRGM and multiple other replicating loci contribute to Crohn's disease susceptibility. Nat. Gen. 39: (7), 830-832.), and show that the estimated ORs can vary substantially if both selection and correlation are taken into account

    Sleep duration and cardiometabolic risk factors among individuals with type 2 diabetes.

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    OBJECTIVE: To examine the association between sleep duration and cardiometabolic risk factors among individuals with recently diagnosed type 2 diabetes (n = 391). METHODS: Sleep duration was derived using a combination of questionnaire and objective heart rate and movement sensing in the UK ADDITION-Plus study (2002-2007). Adjusted means were estimated for individual cardiometabolic risk factors and clustered cardiometabolic risk (CCMR) by five categories of sleep duration. RESULTS: We observed a J-shaped association between sleep duration and CCMR - individuals sleeping 7 to <8 h had a significantly better CCMR profile than those sleeping ≥9 h. Independent of physical activity and sedentary time, individuals sleeping 7 to <8 h had lower triacylglycerol (0.62 mmol/l (0.29, 1.06)) and higher high-density lipoprotein (HDL)-cholesterol levels (0.23 mmol/l (0.16, 0.30)) compared with those sleeping ≥9 h, and a lower waist circumference (7.87 cm (6.06, 9.68)) and body mass index (BMI) (3.47 kg/m(2) (2.69, 4.25)) than those sleeping <6 h. Although sleeping 7 to <8 h was associated with lower levels of systolic and diastolic blood pressure, HbA1c, total cholesterol, and low-density lipoprotein (LDL)-cholesterol, these associations were not statistically significant. CONCLUSIONS: Sleep duration has a J-shaped association with CCMR in individuals with diabetes, independent of potential confounding. Health promotion interventions might highlight the importance of adequate sleep in this high-risk population.The trial is supported by the Wellcome Trust, the Medical Research Council, Diabetes UK and National Health Service R&D support funding. SJG was a member of the National Institute for Health Research (NIHR) School for Primary Care Research. The General Practice and Primary Care Research Unit was supported by NIHR Research funds. SJG received support from the Department of Health NIHR Programme Grant funding scheme [RP-PG-0606-1259]. ATP is supported by the NIHR Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.sleep.2014.10.00

    Study protocol: Phase III single-blinded fast-track pragmatic randomised controlled trial of a complex intervention for breathlessness in advanced disease.

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    BACKGROUND: Breathlessness in advanced disease causes significant distress to patients and carers and presents management challenges to health care professionals. The Breathlessness Intervention Service (BIS) seeks to improve the care of breathless patients with advanced disease (regardless of cause) through the use of evidence-based practice and working with other healthcare providers. BIS delivers a complex intervention (of non-pharmacological and pharmacological treatments) via a multi-professional team. BIS is being continuously developed and its impact evaluated using the MRC's framework for complex interventions (PreClinical, Phase I and Phase II completed). This paper presents the protocol for Phase III. METHODS/DESIGN: Phase III comprises a pragmatic, fast-track, single-blind randomised controlled trial of BIS versus standard care. Due to differing disease trajectories, the service uses two broad service models: one for patients with malignant disease (intervention delivered over two weeks) and one for patients with non-malignant disease (intervention delivered over four weeks). The Phase III trial therefore consists of two sub-protocols: one for patients with malignant conditions (four week protocol) and one for patients with non-malignant conditions (eight week protocol). Mixed method interviews are conducted with patients and their lay carers at three to five measurement points depending on randomisation and sub-protocol. Qualitative interviews are conducted with referring and non-referring health care professionals (malignant disease protocol only). The primary outcome measure is 'patient distress due to breathlessness' measured on a numerical rating scale (0-10). The trial includes economic evaluation. Analysis will be on an intention to treat basis. DISCUSSION: This is the first evaluation of a breathlessness intervention for advanced disease to have followed the MRC framework and one of the first palliative care trials to use fast track methodology and single-blinding. The results will provide evidence of the clinical and cost-effectiveness of the service, informing its longer term development and implementation of the model in other centres nationally and internationally. It adds to methodological developments in palliative care research where complex interventions are common but evidence sparse. TRIAL REGISTRATION: ClinicalTrials.gov: NCT00678405ISRCTN: ISRCTN04119516.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

    Changing Epidemiology of Bariatric Surgery in the UK: Cohort Study Using Primary Care Electronic Health Records

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    Background: This study aimed to use primary care electronic health records to evaluate the epidemiology of bariatric surgery in the UK. Methods: A cohort comprising all obese patients with a bariatric surgical procedure was drawn from the Clinical Practice Research Datalink (CPRD). Rates of bariatric surgery were estimated using the registered CPRD population as denominator. Results: There were 3039 adult obese patients with first bariatric surgery procedures between 2002 and 2014, including laparoscopic adjustable gastric banding (LAGB), 1297; gastric bypass (GBP), 1265; and sleeve gastrectomy (SG), 477. Annual procedures increased from one in 2002 to a maximum of 525 in 2010. Intervention rates were greatest among those aged 35–54, with a peak of 37 procedures per 100,000 population per year in women and 10 per 100,000 per year in men. The mean age and body mass index of participants increased, as did the proportion of men and proportion with diabetes. Between 2002 and 2006, LAGB accounted for >90 % of procedures; in 2014, GBP accounted for 52 % and SG 26 %. Among patients initially receiving LAGB, the rate of band removal was 1.6 (95 % confidence interval 1.3–2.0) per 100 patient years; the rate of a second procedure of a different type was 1.2 (0.9–1.5) per 100 patient years. Conclusions: Numbers of bariatric surgical procedures have increased with increasing use of GBP and SG. Rates of bariatric surgery per 100,000 population remain low and provide evidence of limited access to bariatric surgical procedures in relation to need

    Researchers' experiences of the design and conduct challenges associated with parallel-group cluster-randomised trials and views on a novel open-cohort design

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    BACKGROUND: Two accepted designs exist for parallel-group cluster-randomised trials (CRTs). Closed-cohort designs follow the same individuals over time with a single recruitment period before randomisation, but face challenges in settings with high attrition. (Repeated) cross-sectional designs recruit at one or more timepoints before and/or after randomisation, collecting data from different individuals present in the cluster at these timepoints, but are unsuitable for assessment of individual change over time. An 'open-cohort' design allows individual follow-up with recruitment before and after cluster-randomisation, but little literature exists on acceptability to inform their use in CRTs. AIM: To document the views and experiences of expert trialists to identify: a) Design and conduct challenges with established parallel-group CRT designs,b) Perceptions of potential benefits and barriers to implementation of open-cohort CRTs,c) Methods for minimising, and investigating the impact of, bias in open-cohort CRTs. METHODS: Qualitative consultation via two expert workshops including triallists (n = 24) who had worked on CRTs over a range of settings. Workshop transcripts were analysed using Descriptive Thematic Analysis utilising inductive and deductive coding. RESULTS: Two central organising concepts were developed. Design and conduct challenges with established CRT designs confirmed that current CRT designs are unable to deal with many of the complex research and intervention circumstances found in some trial settings (e.g. care homes). Perceptions of potential benefits and barriers of open cohort designs included themes on: approaches to recruitment; data collection; analysis; minimising/investigating the impact of bias; and how open-cohort designs might address or present CRT design challenges. Open-cohort designs were felt to provide a solution for some of the challenges current CRT designs present in some settings. CONCLUSIONS: Open-cohort CRT designs hold promise for addressing the challenges associated with standard CRT designs. Research is needed to provide clarity around definition and guidance on application.</p

    The impact of communicating genetic risks of disease on risk-reducing health behaviour: systematic review with meta-analysis.

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    OBJECTIVE: To assess the impact of communicating DNA based disease risk estimates on risk-reducing health behaviours and motivation to engage in such behaviours. DESIGN: Systematic review with meta-analysis, using Cochrane methods. DATA SOURCES: Medline, Embase, PsycINFO, CINAHL, and the Cochrane Central Register of Controlled Trials up to 25 February 2015. Backward and forward citation searches were also conducted. STUDY SELECTION: Randomised and quasi-randomised controlled trials involving adults in which one group received personalised DNA based estimates of disease risk for conditions where risk could be reduced by behaviour change. Eligible studies included a measure of risk-reducing behaviour. RESULTS: We examined 10,515 abstracts and included 18 studies that reported on seven behavioural outcomes, including smoking cessation (six studies; n=2663), diet (seven studies; n=1784), and physical activity (six studies; n=1704). Meta-analysis revealed no significant effects of communicating DNA based risk estimates on smoking cessation (odds ratio 0.92, 95% confidence interval 0.63 to 1.35, P=0.67), diet (standardised mean difference 0.12, 95% confidence interval -0.00 to 0.24, P=0.05), or physical activity (standardised mean difference -0.03, 95% confidence interval -0.13 to 0.08, P=0.62). There were also no effects on any other behaviours (alcohol use, medication use, sun protection behaviours, and attendance at screening or behavioural support programmes) or on motivation to change behaviour, and no adverse effects, such as depression and anxiety. Subgroup analyses provided no clear evidence that communication of a risk-conferring genotype affected behaviour more than communication of the absence of such a genotype. However, studies were predominantly at high or unclear risk of bias, and evidence was typically of low quality. CONCLUSIONS: Expectations that communicating DNA based risk estimates changes behaviour is not supported by existing evidence. These results do not support use of genetic testing or the search for risk-conferring gene variants for common complex diseases on the basis that they motivate risk-reducing behaviour. SYSTEMATIC REVIEW REGISTRATION: This is a revised and updated version of a Cochrane review from 2010, adding 11 studies to the seven previously identified.A previous version of this review was funded as part of a grant from the Medical Research Council, UK (Risk communication in preventive medicine: optimising the impact of DNA risk information; G0500274). Updating this review was funded by an NIHR Senior Investigator award to TMM. The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.This is the final version of the article. It first appeared from the BMJ Publishing Group via http://dx.doi.org/10.1136/bmj.i110
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