Centre selection for clinical trials and the generalisability of results: a mixed methods study.

BACKGROUND: The rationale for centre selection in randomised controlled trials (RCTs) is often unclear but may have important implications for the generalisability of trial results. The aims of this study were to evaluate the factors which currently influence centre selection in RCTs and consider how generalisability considerations inform current and optimal practice. METHODS AND FINDINGS: Mixed methods approach consisting of a systematic review and meta-summary of centre selection criteria reported in RCT protocols funded by the UK National Institute of Health Research (NIHR) initiated between January 2005-January 2012; and an online survey on the topic of current and optimal centre selection, distributed to professionals in the 48 UK Clinical Trials Units and 10 NIHR Research Design Services. The survey design was informed by the systematic review and by two focus groups conducted with trialists at the Birmingham Centre for Clinical Trials. 129 trial protocols were included in the systematic review, with a total target sample size in excess of 317,000 participants. The meta-summary identified 53 unique centre selection criteria. 78 protocols (60%) provided at least one criterion for centre selection, but only 31 (24%) protocols explicitly acknowledged generalisability. This is consistent with the survey findings (n = 70), where less than a third of participants reported generalisability as a key driver of centre selection in current practice. This contrasts with trialists' views on optimal practice, where generalisability in terms of clinical practice, population characteristics and economic results were prime considerations for 60% (n = 42), 57% (n = 40) and 46% (n = 32) of respondents, respectively. CONCLUSIONS: Centres are rarely enrolled in RCTs with an explicit view to external validity, although trialists acknowledge that incorporating generalisability in centre selection should ideally be more prominent. There is a need to operationalize 'generalisability' and incorporate it at the design stage of RCTs so that results are readily transferable to 'real world' practice

Simulations of events for the LUX-ZEPLIN (LZ) dark matter experiment

The LUX-ZEPLIN dark matter search aims to achieve a sensitivity to the WIMP-nucleon spin-independent cross-section down to (1–2)×10−12 pb at a WIMP mass of 40 GeV/c2. This paper describes the simulations framework that, along with radioactivity measurements, was used to support this projection, and also to provide mock data for validating reconstruction and analysis software. Of particular note are the event generators, which allow us to model the background radiation, and the detector response physics used in the production of raw signals, which can be converted into digitized waveforms similar to data from the operational detector. Inclusion of the detector response allows us to process simulated data using the same analysis routines as developed to process the experimental data

Screening mammography beliefs and recommendations: a web-based survey of primary care physicians

<p>Abstract</p> <p>Background</p> <p>The appropriateness and cost-effectiveness of screening mammography (SM) for women younger than 50 and older than 74 years is debated in the clinical research community, among health care providers, and by the American public. This study explored primary care physicians' (PCPs) perceptions of the influence of clinical practice guidelines for SM; the recommendations for SM in response to hypothetical case scenarios; and the factors associated with perceived SM effectiveness and recommendations in the US from June to December 2009 before the United States Preventive Services Task Force (USPSTF) recently revised guidelines.</p> <p>Methods</p> <p>A nationally representative sample of 11,922 PCPs was surveyed using a web-based questionnaire. The response rate was 5.7% (684); (41%) 271 family physicians (FP), (36%) 232 general internal medicine physicians (IM), (23%) 150 obstetrician-gynaecologists (OBG), and (0.2%) 31 others. Cross-sectional analysis examined PCPs perceived effectiveness of SM, and recommendation for SM in response to hypothetical case scenarios. PCPs responses were measured using 4-5 point adjectival scales. Differences in perceived effectiveness and recommendations for SM were examined after adjusting for PCPs specialty, race/ethnicity, and the US region.</p> <p>Results</p> <p>Compared to IM and FP, OBG considered SM more effective in reducing breast cancer mortality among women aged 40-49 years (<it>p </it>= 0.003). Physicians consistently recommended mammography to women aged 50-69 years with no differences by specialty (<it>p </it>= 0.11). However, 94% of OBG "always recommended" SM to younger and 86% of older women compared to 81% and 67% for IM and 84% and 59% for FP respectively (<it>p = </it>< .001). In ordinal regression analysis, OBG specialty was a significant predictor for perceived higher SM effectiveness and recommendations for younger and older women. In evaluating hypothetical scenarios, overall PCPs would recommend SM for the 80 year woman with CHF with a significant variation by specialty (38% of OBG, 18% of FP, 17% of IM; <it>p </it>= < .001).</p> <p>Conclusions</p> <p>A majority of physicians, especially OBG, favour aggressive breast cancer screening for women from 40 through 79 years of age, including women with short life expectancy. Policy interventions should focus on educating providers to provide tailored recommendations for mammography based on individualized cancer risk, health status, and preferences.</p

Competing risk and heterogeneity of treatment effect in clinical trials

It has been demonstrated that patients enrolled in clinical trials frequently have a large degree of variation in their baseline risk for the outcome of interest. Thus, some have suggested that clinical trial results should routinely be stratified by outcome risk using risk models, since the summary results may otherwise be misleading. However, variation in competing risk is another dimension of risk heterogeneity that may also underlie treatment effect heterogeneity. Understanding the effects of competing risk heterogeneity may be especially important for pragmatic comparative effectiveness trials, which seek to include traditionally excluded patients, such as the elderly or complex patients with multiple comorbidities. Indeed, the observed effect of an intervention is dependent on the ratio of outcome risk to competing risk, and these risks – which may or may not be correlated – may vary considerably in patients enrolled in a trial. Further, the effects of competing risk on treatment effect heterogeneity can be amplified by even a small degree of treatment related harm. Stratification of trial results along both the competing and the outcome risk dimensions may be necessary if pragmatic comparative effectiveness trials are to provide the clinically useful information their advocates intend

Perceived difficulty and appropriateness of decision making by General Practitioners: a systematic review of scenario studies

Background: Health-care quality in primary care depends largely on the appropriateness of General Practitioners’ (GPs; Primary Care or Family Physicians) decisions, which may be influenced by how difficult they perceive decisions to be. Patient scenarios (clinical or case vignettes) are widely used to investigate GPs’ decision making. This review aimed to identify the extent to which perceived decision difficulty, decision appropriateness, and their relationship have been assessed in scenario studies of GPs’ decision making; identify possible determinants of difficulty and appropriateness; and investigate the relationship between difficulty and appropriateness. Methods: MEDLINE, EMBASE, PsycINFO, the Cochrane Library and Web of Science were searched for scenario studies of GPs’ decision making. One author completed article screening. Ten percent of titles and abstracts were checked by an independent volunteer, resulting in 91% agreement. Data on decision difficulty and appropriateness were extracted by one author and descriptively synthesised. Chi-squared tests were used to explore associations between decision appropriateness, decision type and decision appropriateness assessment method. Results: Of 152 included studies, 66 assessed decision appropriateness and five assessed perceived difficulty. While no studies assessed the relationship between perceived difficulty and appropriateness, one study objectively varied the difficulty of the scenarios and assessed the relationship between a measure of objective difficulty and appropriateness. Across 38 studies where calculations were possible, 62% of the decisions were appropriate as defined by the appropriateness standard used. Chi-squared tests identified statistically significant associations between decision appropriateness, decision type and decision appropriateness assessment method. Findings suggested a negative relationship between decision difficulty and appropriateness, while interventions may have the potential to reduce perceived difficulty. Conclusions: Scenario-based research into GPs’ decisions rarely considers the relationship between perceived decision difficulty and decision appropriateness. The links between these decisional components require further investigation

Assessing and reporting heterogeneity in treatment effects in clinical trials: a proposal

Mounting evidence suggests that there is frequently considerable variation in the risk of the outcome of interest in clinical trial populations. These differences in risk will often cause clinically important heterogeneity in treatment effects (HTE) across the trial population, such that the balance between treatment risks and benefits may differ substantially between large identifiable patient subgroups; the "average" benefit observed in the summary result may even be non-representative of the treatment effect for a typical patient in the trial. Conventional subgroup analyses, which examine whether specific patient characteristics modify the effects of treatment, are usually unable to detect even large variations in treatment benefit (and harm) across risk groups because they do not account for the fact that patients have multiple characteristics simultaneously that affect the likelihood of treatment benefit. Based upon recent evidence on optimal statistical approaches to assessing HTE, we propose a framework that prioritizes the analysis and reporting of multivariate risk-based HTE and suggests that other subgroup analyses should be explicitly labeled either as primary subgroup analyses (well-motivated by prior evidence and intended to produce clinically actionable results) or secondary (exploratory) subgroup analyses (performed to inform future research). A standardized and transparent approach to HTE assessment and reporting could substantially improve clinical trial utility and interpretability