Cluster randomised trials in the medical literature: two bibliometric surveys

Background: Several reviews of published cluster randomised trials have reported that about half did not take clustering into account in the analysis, which was thus incorrect and potentially misleading. In this paper I ask whether cluster randomised trials are increasing in both number and quality of reporting. Methods: Computer search for papers on cluster randomised trials since 1980, hand search of trial reports published in selected volumes of the British Medical Journal over 20 years. Results: There has been a large increase in the numbers of methodological papers and of trial reports using the term 'cluster random' in recent years, with about equal numbers of each type of paper. The British Medical Journal contained more such reports than any other journal. In this journal there was a corresponding increase over time in the number of trials where subjects were randomised in clusters. In 2003 all reports showed awareness of the need to allow for clustering in the analysis. In 1993 and before clustering was ignored in most such trials. Conclusion: Cluster trials are becoming more frequent and reporting is of higher quality. Perhaps statistician pressure works

Assessment of GFR by four methods in adults in Ashanti, Ghana: the need for an eGFR equation for lean African populations

Background. Equations for estimating glomerular filtration rate (GFR) have not been validated in Sub-Saharan African populations, and data on GFR are few. Methods. GFR by creatinine clearance (Ccr) using 24-hour urine collections and estimated GFR (eGFR) using the four-variable Modification of Diet in Renal Disease (MDRD-4)[creatinine calibrated to isotope dilution mass spectrometry (IDMS) standard], Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Cockcroft–Gault equations were obtained in Ghanaians aged 40–75. The population comprised 1013 inhabitants in 12 villages; 944 provided a serum creatinine and two 24-hour urines. The mean weight was 54.4 kg; mean body mass index was 21.1 kg/m2. Results. Mean GFR by Ccr was 84.1 ml/min/1.73m2; 86.8% of participants had a GFR of 60 ml/min/1.73m2. Mean MDRD-4 eGFR was 102.3 ml/min/1.73m2 (difference vs. Ccr, 18.2: 95% CI: 16.8–19.5); when the factor for black race was omitted, the value (mean 84.6 ml/min/1.73m2) was close to Ccr. Mean CKD-EPI eGFR was 103.1 ml/min/1.73m2, and 89.4 ml/min/1.73m2 when the factor for race was omitted. The Cockcroft–Gault equation underestimated GFR compared with Ccr by 9.4 ml/min/1.73m2 (CI: 8.3–10.6); particularly in older age groups. GFR by Ccr, and eGFR by MDRD-4, CKD-EPI and Cockcroft–Gault showed falls with age: MDRD-4 5.5, Ccr 7.7, CKD-EPI 8.8 and Cockcroft–Gault 11.0 ml/min/1.73m2/10 years. The percentage of individuals identified with CKD stages 3–5 depended on the method used: MDRD-4 1.6% (7.2 % without factor for black race; CKD-EPI 1.7% (4.7% without factor for black race), Ccr 13.2% and Cockcroft–Gault 21.0%. Conclusions. Mean eGFR by both MDRD-4 and CKD-EPI was considerably higher than GFR by Ccr and Cockcroft–Gault, a difference that may be attributable to leanness. MDRD-4 appeared to underestimate the fall in GFR with age compared with the three other measurements; the fall with CKD-EPI without the adjustment for race was the closest to that of Ccr. An equation tailored specifically to the needs of the lean populations of Africa is urgently needed. For the present, the CKD-EPI equation without the adjustment for black race appears to be the most useful

Sample size calculations for cluster randomised controlled trials with a fixed number of clusters

Background\ud Cluster randomised controlled trials (CRCTs) are frequently used in health service evaluation. Assuming an average cluster size, required sample sizes are readily computed for both binary and continuous outcomes, by estimating a design effect or inflation factor. However, where the number of clusters are fixed in advance, but where it is possible to increase the number of individuals within each cluster, as is frequently the case in health service evaluation, sample size formulae have been less well studied. \ud \ud Methods\ud We systematically outline sample size formulae (including required number of randomisation units, detectable difference and power) for CRCTs with a fixed number of clusters, to provide a concise summary for both binary and continuous outcomes. Extensions to the case of unequal cluster sizes are provided. \ud \ud Results\ud For trials with a fixed number of equal sized clusters (k), the trial will be feasible provided the number of clusters is greater than the product of the number of individuals required under individual randomisation ($n_i$) and the estimated intra-cluster correlation ($\rho$). So, a simple rule is that the number of clusters ($\kappa$) will be sufficient provided: \ud \ud $\kappa$ > $n_i$ x $\rho$\ud \ud Where this is not the case, investigators can determine the maximum available power to detect the pre-specified difference, or the minimum detectable difference under the pre-specified value for power. \ud \ud Conclusions\ud Designing a CRCT with a fixed number of clusters might mean that the study will not be feasible, leading to the notion of a minimum detectable difference (or a maximum achievable power), irrespective of how many individuals are included within each cluster. \ud \u

Blood Pressure and Haematological Indices in Twelve Communities in Ashanti, Ghana

Hypertension is the most important risk factor for cardiovascular mortality and morbidity in Sub-Saharan Africa. In western populations, high haemoglobin levels are associated with raised BP unlike in Sub-Saharan Africa where there is a paucity of data. Our study examines the association between haematological indices with BP variables. Weight, height, BP, and whole blood indices of viscosity (Hb, haematocrit, RBC count, and MCV) were measured in 921 adults (340 men, 581 women; aged 40–75) in 12 communities in Ghana. Mean values for Hb (12.3 g/dl ± 1.7 SD), haematocrit (36.7% ± 5.2), RBC (4.10 million/μL ± 0.64), and MCV were lower than reference values used in Sub-Saharan Africa. Mean BMI was 21.1 ± 4.1 indicating a lean population. Systolic BP increased by 1.0 mmHg (95% CI 0.5–1.5), p < 0.001, for women and 0.5 (0.1–1.0), p = 0.027, for men per unit increase in haematocrit. Similar relationships were found for Hb and RBC but not for MCV or platelets. The relationships were weaker when adjusted for BMI, 0.7 mmHg (0.2–1.2) in women and 0.5 (0.0–1.0) in men. Findings for diastolic BP were similar. Overall haematological indices were low. We have found a significant, positive relationship between BP, Hb, Haematocrit, and RBC count in our population

A Primary Care Nurse-Delivered Walking Intervention in Older Adults: PACE (Pedometer Accelerometer Consultation Evaluation)-Lift Cluster Randomised Controlled Trial.

Background: Brisk walking in older people can increase step-counts and moderate to vigorous intensity physical activity (MVPA) in ≥10-minute bouts, as advised in World Health Organization guidelines. Previous interventions have reported step-count increases, but not change in objectively measured MVPA in older people. We assessed whether a primary care nurse-delivered complex intervention increased objectively measured step-counts and MVPA. Methods and Findings: A total of 988 60–75 year olds, able to increase walking and randomly selected from three UK family practices, were invited to participate in a parallel two-arm cluster randomised trial; randomisation was by household. Two-hundred-ninety-eight people from 250 households were randomised between 2011 and 2012; 150 individuals to the intervention group, 148 to the usual care control group. Intervention participants received four primary care nurse physical activity (PA) consultations over 3 months, incorporating behaviour change techniques, pedometer step-count and accelerometer PA intensity feedback, and an individual PA diary and plan. Assessors were not blinded to group status, but statistical analyses were conducted blind. The primary outcome was change in accelerometry assessed average daily step-counts between baseline and 3 months, with change at 12 months a secondary outcome. Other secondary outcomes were change from baseline in time in MVPA weekly in ≥10-minute bouts, accelerometer counts, and counts/minute at 3 months and 12 months. Other outcomes were adverse events, anthropometric measures, mood, and pain. Qualitative evaluations of intervention participants and practice nurses assessed the intervention’s acceptability. At 3 months, eight participants had withdrawn or were lost to follow-up, 280 (94%) individuals provided primary outcome data. At 3 months changes in both average daily step-counts and weekly MVPA in ≥10-minute bouts were significantly higher in the intervention than control group: by 1,037 (95% CI 513–1,560) steps/day and 63 (95% CI 40–87) minutes/week, respectively. At 12 months corresponding differences were 609 (95% CI 104–1,115) steps/day and 40 (95% CI 17–63) minutes/week. Counts and counts/minute showed similar effects to steps and MVPA. Adverse events, anthropometry, mood, and pain were similar in the two groups. Participants and practice nurses found the intervention acceptable and enjoyable. Conclusions : The PACE-Lift trial increased both step-counts and objectively measured MVPA in ≥10-minute bouts in 60–75 year olds at 3 and 12 months, with no effect on adverse events. To our knowledge, this is the first trial in this age group to demonstrate objective MVPA increases and highlights the value of individualised support incorporating objective PA assessment in a primary care setting. Trial Registration: Controlled-Trials.com ISRCTN4212256

Design effect in multicenter studies: gain or loss of power?

<p>Abstract</p> <p>Background</p> <p>In a multicenter trial, responses for subjects belonging to a common center are correlated. Such a clustering is usually assessed through the design effect, defined as a ratio of two variances. The aim of this work was to describe and understand situations where the design effect involves a gain or a loss of power.</p> <p>Methods</p> <p>We developed a design effect formula for a multicenter study aimed at testing the effect of a binary factor (which thus defines two groups) on a continuous outcome, and explored this design effect for several designs (from individually stratified randomized trials to cluster randomized trials, and for other designs such as matched pair designs or observational multicenter studies).</p> <p>Results</p> <p>The design effect depends on the intraclass correlation coefficient (ICC) (which assesses the correlation between data for two subjects from the same center) but also on a statistic <it>S</it>, which quantifies the heterogeneity of the group distributions among centers (thus the level of association between the binary factor and the center) and on the degree of global imbalance (the number of subjects are then different) between the two groups. This design effect may induce either a loss or a gain in power, depending on whether the <it>S </it>statistic is respectively higher or lower than 1.</p> <p>Conclusion</p> <p>We provided a global design effect formula applying for any multicenter study and allowing identifying factors – the ICC and the distribution of the group proportions among centers – that are associated with a gain or a loss of power in such studies.</p

Using the theory of planned behaviour as a process evaluation tool in randomised trials of knowledge translation strategies : A case study from UK primary care

Peer reviewedPublisher PD

PACE-UP (Pedometer and consultation evaluation--UP)--a pedometer-based walking intervention with and without practice nurse support in primary care patients aged 45-75 years: study protocol for a randomised controlled trial.

BACKGROUND: Most adults do not achieve the 150 minutes weekly of at least moderate intensity activity recommended for health. Adults' most common physical activity (PA) is walking, light intensity if strolling, moderate if brisker. Pedometers can increase walking; however, most trials have been short-term, have combined pedometer and support effects, and have not reported PA intensity. This trial will investigate whether pedometers, with or without nurse support, can help less active 45-75 year olds to increase their PA over 12 months. METHODS/DESIGN: DESIGN: Primary care-based 3-arm randomized controlled trial with 12-month follow-up and health economic and qualitative evaluations. PARTICIPANTS: Less active 45-75 year olds (n = 993) will be recruited by post from six South West London general practices, maximum of two per household and households randomised into three groups. Step-count and time spent at different PA intensities will be assessed for 7 days at baseline, 3 and 12 months by accelerometer. Questionnaires and anthropometric assessments will be completed. INTERVENTION: The pedometer-alone group will be posted a pedometer (Yamax Digi-Walker SW-200), handbook and diary detailing a 12-week pedometer-based walking programme, using targets from their baseline assessment. The pedometer-plus-support group will additionally receive three practice nurse PA consultations. The handbook, diary and consultations include behaviour change techniques (e.g., self-monitoring, goal-setting, relapse prevention planning). The control group will receive usual care. OUTCOMES: Changes in average daily step-count (primary outcome), time spent sedentary and in at least moderate intensity PA weekly at 12 months, measured by accelerometry. Other outcomes include change in body mass index, body fat, self-reported PA, quality of life, mood and adverse events. Cost-effectiveness will be assessed by the incremental cost of the intervention to the National Health Service and incremental cost per change in step-count and per quality adjusted life year. Qualitative evaluations will explore reasons for trial non-participation and the interventions' acceptability. DISCUSSION: The PACE-UP trial will determine the effectiveness and cost-effectiveness of a pedometer-based walking intervention delivered by post or practice nurse to less active primary care patients aged 45-75 years old. Approaches to minimise bias and challenges anticipated in delivery will be discussed

A priori postulated and real power in cluster randomized trials: mind the gap

BACKGROUND: Cluster randomization design is increasingly used for the evaluation of health-care, screening or educational interventions. The intraclass correlation coefficient (ICC) defines the clustering effect and be specified during planning. The aim of this work is to study the influence of the ICC on power in cluster randomized trials. METHODS: Power contour graphs were drawn to illustrate the loss in power induced by an underestimation of the ICC when planning trials. We also derived the maximum achievable power given a specified ICC. RESULTS: The magnitude of the ICC can have a major impact on power, and with low numbers of clusters, 80% power may not be achievable. CONCLUSION: Underestimating the ICC during planning cluster randomized trials can lead to a seriously underpowered trial. Publication of a priori postulated and a posteriori estimated ICCs is necessary for a more objective reading: negative trial results may be the consequence of a loss of power due to a mis-specification of the ICC

Interpreting population reach of a large, successful physical activity trial delivered through primary care.

Abstract Background Failure to include socio-economically deprived or ethnic minority groups in physical activity (PA) trials may limit representativeness and could lead to implementation of interventions that then increase health inequalities. Randomised intervention trials often have low recruitment rates and rarely assess recruitment bias. A previous trial by the same team using similar methods recruited 30% of the eligible population but was in an affluent setting with few non-white residents and was limited to those over 60 years of age. Methods PACE-UP is a large, effective, population-based walking trial in inactive 45-75 year-olds that recruited through seven London general practices. Anonymised practice demographic data were available for all those invited, enabling investigation of inequalities in trial recruitment. Non-participants were invited to complete a questionnaire. Results From 10,927 postal invitations, 1150 (10.5%) completed baseline assessment. Participation rate ratios (95% CI), adjusted for age and gender as appropriate, were lower in men 0.59 (0.52, 0.67) than women, in those under 55 compared with those ≥65, 0.60 (0.51, 0.71), in the most deprived quintile compared with the least deprived 0.52 (0.39, 0.70) and in Asian individuals compared with whites 0.62 (0.50, 0.76). Black individuals were equally likely to participate as white individuals. Participation was also associated with having a co-morbidity or some degree of health limitation. The most common reasons for non-participation were considering themselves as being too active or lack of time. Conclusions Conducting the trial in this diverse setting reduced overall response, with lower response in socio-economically deprived and Asian sub-groups. Trials with greater reach are likely to be more expensive in terms of recruitment and gains in generalizability need to be balanced with greater costs. Differential uptake of successful trial interventions may increase inequalities in PA levels and should be monitored