Stephen Pyke

Fibrinolytic Factors and the Risk of Myocardial Infarction or Sudden Death in Patients With Angina Pectoris

BACKGROUND Disturbances of the fibrinolytic system that lead to decreased removal of fibrin deposits may be important risk factors for coronary thrombosis. There is as yet no consensus on the prognostic value of fibrinolytic parameters, which may be attributed in part to the choice of confounding variables controlled for. METHODS AND RESULTS The ECAT study is a prospective multicenter study of 3043 patients with angina pectoris followed for 2 years. Baseline measurements included 10 fibrinolytic variables. The results were analyzed in relation to the subsequent incidence of myocardial infarction or sudden coronary death. They are presented before and after adjustment for clusters of confounding variables that are markers of different mechanisms: insulin resistance (body mass index, triglyceride, and HDL cholesterol), inflammation (fibrinogen and C-reactive protein), and endothelial cell damage (von Willebrand factor). An increased incidence of events was associated with higher baseline concentrations of tissue plasminogen activator (TPA) antigen (P = .0002), plasminogen activator inhibitor-1 (PAI-1) activity (P = .02), and PAI-1 antigen (P = .001). The associations of PAI-1 activity and PAI-1 antigen with risk of events disappeared after adjustment for parameters reflecting insulin resistance but were not affected by other adjustments. TPA antigen was affected to a similar extent by adjustment for parameters reflecting insulin resistance. Inflammation, or endothelial cell damage, but the risk association disappeared only after combined adjustments. CONCLUSIONS The prognostic role of PAI-1 in predicting coronary events is related principally to insulin resistance, whereas that of TPA antigen could be explained only by its relationship with different mechanisms, including insulin resistance, inflammation and endothelial cell damage.

Meta-analysis of increased dose of inhaled steroid or addition of salmeterol in symptomatic asthma (MIASMA).

Abstract Objective: To examine the benefits of adding salmeterol compared with increasing dose of inhaled corticosteroids. Design: Systematic review of randomised, double blind clinical trials. Independent data extraction and validation with summary data from study reports and manuscripts. Fixed and random effects analyses. Setting: EMBASE, Medline, and GlaxoWellcome internal clinical study registers. Main outcome measures: Efficacy and exacerbations. Results: Among 2055 trials of treatment with salmeterol, there were nine parallel group trials of ≥12 weeks with 3685 symptomatic patients aged ≥12 years taking inhaled steroid in primary or secondary care. Compared with response to increased steroids, in patients receiving salmeterol morning peak expiratory flow was greater at three months (difference 22.4 (95% confidence interval 15.0 to 30.0) litre/min, P<0.001) and six months (27.7 (19.0 to 36.4) litre/min, P<0.001). Forced expiratory volume in one second (FEV1) was also increased at three months (0.10 (0.04 to 0.16) litres, P<0.001) and six months (0.08 (0.02 to 0.14) litres, P<0.01), as were mean percentage of days and nights without symptoms (three months: days—12% (9% to 15%), nights—5% (3% to 7%); six months: days—15% (12% to 18%), nights—5% (3% to 7%); all P<0.001) and mean percentage of days and nights without need for rescue treatment (three months: days—17% (14% to 20%), nights—9% (7% to 11%); six months: days—20% (17 to 23%), nights—8% (6% to 11%); all P<0.001). Fewer patients experienced any exacerbation with salmeterol (difference 2.73% (0.43% to 5.04%), P=0.02), and the proportion of patients with moderate or severe exacerbations was also lower (2.42% (0.24% to 4.60%), P=0.03). Conclusions: Addition of salmeterol in symptomatic patients aged 12 and over on low to moderate doses of inhaled steroid gives improved lung function and increased number of days and nights without symptoms or need for rescue treatment with no increase in exacerbations of any severity.

The design and analysis of paired cluster randomized trials: an application of meta‐analysis techniques

The statistical issues in clinical trials where clusters, communities or groups rather than individuals are randomized are often not fully appreciated. In this paper we discuss the design and analysis of trials in which pairs of clusters are randomized in the context of one recent trial, the British Family Heart Study. Both sample size calculations and the analysis strategy need to take account of the between-cluster component of variance. The analysis can be considered as a random effects meta-analysis across cluster pairs, and can usefully be presented as such. Techniques developed in the context of meta-analysis can then be used in the analysis, for example using a profile likelihood method to derive a confidence interval for the overall treatment effect which takes into account the variability in the estimate of the between-cluster variance. The methods presented here are contrasted with previously published methods for cluster randomized trials.

Costs and cost effectiveness of cardiovascular screening and intervention: the British family heart study

Abstract Objective: To measure costs and cost effectiveness of the British family heart study cardiovascular screening and intervention programme. Design: Cost effectiveness analysis of randomised controlled trial. Clinical and resource use data taken from trial and unit cost data from external estimates. Setting: 13 general practices across Britain. Subjects: 4185 men aged 40-59 and their 2827 partners. Intervention: Nurse led programme using a family centred approach, with follow up according to degree of risk. Main outcome measures: Cost of the programme itself; overall short term cost to NHS; cost per 1% reduction in coronary risk at one year. Results: Estimated cost of putting the programme into practice for one year was £63 per person (95% confidence interval £60 to £65). The overall short term cost to the health service was £77 per man (£29 to £124) but only £13 per woman (-£48 to £74), owing to differences in utilisation of other health service resources. The cost per 1% reduction in risk was £5.08 per man (£5.92 including broader health service costs) and £5.78 per woman (£1.28 taking into account wider health service savings). Conclusions: The direct cost of the programme to a four partner practice of 7500 patients would be approximately £58 000. Annually, £8300 would currently be paid to a practice of this size working to the maximum target on the health promotion bands, plus any additional reimbursement of practice staff salaries for which the practice qualified. The broader short term costs to the NHS may augment these costs for men but offset them considerably for women. Key messages Patient specific data from the British family heart study are used in this detailed cost effectiveness analysis The costs of the programme to general practitioners was estimated with reasonable precision: an average four partner practice of 7500 patients will require 1.75 nurse years to implement this programme, costing £58 000 The direct costs of the programme may not be fully reimbursed under the current health promotion banding scheme The broader impact on drug costs and use of other health care resources is uncertain, and larger trials will be needed to estimate these important effects

Effect of non-attenders on the potential of a primary care programme to reduce cardiovascular risk in the population. Family Heart Study Group.

Abstract Objectives: To determine the feasibility of enrolling non-attenders of a population based cardiovascular risk reduction programme (the British family heart study) into a further, similar programme and to assess the effect of non-attendance on the effectiveness of the programme. Design: Follow up of non-attenders by practice nurses, including home visits if necessary, to administer questionnaires and obtain physiological measurements. Setting: Eight general practices across England, Scotland, and Wales. Subjects—Non-attenders in a cardiovascular risk factor screening and intervention programme compared with attenders. Main outcome measures: Number of nonattenders enrolled; sociodemographic characteristics; personal and family history of coronary heart disease; cardiovascular risk factors; and total coronary risk score. Results: Data were collected from 106 (17%) of the 608 non-attending families (99 men and 42 women). Of the 543 non-attending families from five practices that attempted complete follow up, 256 had moved away or died. Only 76 were eventually enrolled into the study. The prevalence of coronary heart disease and a family history of coronary heart disease were similar among non-attenders and attenders as were the individual coronary risk factors studied except smoking. Women non-attenders were more likely to be current cigarette smokers than attenders (15/42 (upsilon) 202/948, P = 0.02). Conclusions: The intensive follow up of nonattenders resulted in real intervention opportunities in only a small number. Since the effect of any intervention in a population is reduced by nonattendance audit of preventive medical programmes aimed at the population should allow for the effect of non-attenders on the overall results.

Proposed best practice for statisticians in the reporting and publication of pharmaceutical industry‐sponsored clinical trials

In this paper we set out what we consider to be a set of best practices for statisticians in the reporting of pharmaceutical industry-sponsored clinical trials. We make eight recommendations covering: author responsibilities and recognition; publication timing; conflicts of interest; freedom to act; full author access to data; trial registration and independent review. These recommendations are made in the context of the prominent role played by statisticians in the design, conduct, analysis and reporting of pharmaceutical sponsored trials and the perception of the reporting of these trials in the wider community.

The potential for bias in reporting of industry‐sponsored clinical trials

Concerns about potentially misleading reporting of pharmaceutical industry research have surfaced many times. The potential for duality (and thereby conflict) of interest is only too clear when you consider the sums of money required for the discovery, development and commercialization of new medicines. As the ability of major, mid-size and small pharmaceutical companies to innovate has waned, as evidenced by the seemingly relentless decline in the numbers of new medicines approved by Food and Drug Administration and European Medicines Agency year-on-year, not only has the cost per new approved medicine risen: so too has the public and media concern about the extent to which the pharmaceutical industry is open and honest about the efficacy, safety and quality of the drugs we manufacture and sell. In 2005 an Editorial in Journal of the American Medical Association made clear that, so great was their concern about misleading reporting of industry-sponsored studies, henceforth no article would be published that was not also guaranteed by independent statistical analysis. We examine the precursors to this Editorial, as well as its immediate and lasting effects for statisticians, for the manner in which statistical analysis is carried out, and for the industry more generally.

Making available information from studies sponsored by the pharmaceutical industry: some current practices.

Since the web-based registry ClinicalTrials.gov was launched on 29 February 2000, the pharmaceutical industry has made available an increasing amount of information about the clinical trials that it sponsors. The process has been spurred on by a number of factors including a wish by the industry to provide greater transparency regarding clinical trial data; and has been both aided and complicated by the number of institutions that have a legitimate interest in guiding and defining what should be made available. This article reviews the history of this process of making information about clinical trials publicly available. It provides a readers guide to the study registries and the databases of results; and looks at some indicators of consistency in the posting of study information.

Best practice for statisticians in industry sponsored trials

In light of CONSORT 2010,1 the recently proposed best practice for statisticians in reporting industry sponsored trials should be highlighted.2 The eight recommendations below were explained in two accompanying articles.3 4 A forum for editors, industry, and academia to discuss the issues raised would be beneficial.