Sample size re-estimation in crossover trials: application to the AIM HY-INFORM study

Abstract Background Crossover designs are commonly utilised in randomised controlled trials investigating treatments for long-term chronic illnesses. One problem with this design is its inherent repeated measures necessitate the availability of an estimate of the within-person standard deviation (SD) to perform a sample size calculation, which may be rarely available at the design stage of a trial. Interim sample size re-estimation designs can be used to help alleviate this issue by adapting the sample size mid-way through the trial, using accrued information in a statistically robust way. Methods The AIM HY-INFORM study is part of the Informative Markers in Hypertension (AIM HY) Programme and comprises two crossover trials, each with a planned recruitment of 600 participants. The objective of the study is to test whether blood pressure response to first line antihypertensive treatment depends on ethnicity. An interim analysis is planned to reassess the assumptions of the planned sample size for the study. The aims of this paper are: (1) to provide a formula for sample size re-estimation in both crossover trials; and (2) to present a simulation study of the planned interim analysis to investigate alternative within-person SDs to that assumed. Results The AIM HY-INFORM protocol sample size calculation fixes the within-person SD to be 8 mmHg, giving > 90% power for a primary treatment effect of 4 mmHg. Using the method developed here and simulating the interim sample size reassessment, if we were to see a larger within-person SD of 9 mmHg at interim, 640 participants for 90% power 90% of the time in the three-period three-treatment design would be required. Similarly, in the four-period four-treatment crossover design, 602 participants would be required. Conclusions The formulas presented here provide a method for re-estimating the sample size in crossover trials. In the context of the AIM HY-INFORM study, simulating the interim analysis allows us to explore the results of a possible increase in the within-person SD from that assumed. Simulations show that without increasing the planned sample size of 600 participants, we can reasonably still expect to achieve 80% power with a small increase in the within-person SD from that assumed. Trial registration ClinicalTrials.gov, NCT02847338. Registered on 28 July 2016.

Download Full-text

Impact of repeated measures of joint space width on the sample size calculation: An application to hip osteoarthritis

Joint Bone Spine ◽

10.1016/j.jbspin.2014.10.006 ◽

2015 ◽

Vol 82 (3) ◽

pp. 172-176 ◽

Cited By ~ 3

Author(s):

Paul Ornetti ◽

Laure Gossec ◽

Davy Laroche ◽

Christophe Combescure ◽

Maxime Dougados ◽

...

Keyword(s):

Sample Size ◽

Repeated Measures ◽

Sample Size Calculation ◽

Joint Space Width ◽

Hip Osteoarthritis ◽

Joint Space ◽

Space Width

Download Full-text

DELTA2 guidance on choosing the target difference and undertaking and reporting the sample size calculation for a randomised controlled trial

Trials ◽

10.1186/s13063-018-2884-0 ◽

2018 ◽

Vol 19 (1) ◽

Cited By ~ 17

Author(s):

Jonathan A. Cook ◽

Steven A. Julious ◽

William Sones ◽

Lisa V. Hampson ◽

Catherine Hewitt ◽

...

Keyword(s):

Randomised Controlled Trial ◽

Sample Size ◽

Controlled Trial ◽

Sample Size Calculation ◽

Target Difference ◽

Randomised Controlled

Download Full-text

P062 A SYSTEMATIC REVIEW ON POWER ESTIMATION TO SUPPORT SAMPLE SIZE CALCULATION FOR RANDOMISED TRIALS IN INFLAMMATORY BOWEL DISEASE

Inflammatory Bowel Diseases ◽

10.1093/ibd/zaa010.021 ◽

2020 ◽

Vol 26 (Supplement_1) ◽

pp. S9-S9

Author(s):

Svetlana Lakunina ◽

Zipporah Iheozor-Ejiofor ◽

Morris Gordon ◽

Daniel Akintelure ◽

Vassiliki Sinopoulou

Keyword(s):

Inflammatory Bowel Disease ◽

Sample Size ◽

Bowel Disease ◽

Sample Size Calculation ◽

Sample Size Estimation ◽

Power Calculation ◽

Size Estimation ◽

Target Sample ◽

Inflammatory Bowel ◽

Randomised Controlled

Abstract Inflammatory bowel disease is a collection of disorders of the gastrointestinal tract, characterised by relapsing and remitting inflammation. Studies have reported several pharmacological or non-pharmacological interventions being effective in the management of the disease. Sample size estimation with power calculation is necessary for a trial to detect the effect of an intervention. This project critically evaluates the sample size estimation and power calculation reported by randomised controlled studies of inflammatory bowel disease management to effectively conclude appropriateness of the studies results. We conducted a literature search in the Cochrane database to identify systematic literature reviews. Their reference lists were screened, and studies were selected if they met the inclusion criteria. The data was extracted based on power calculation parameters and outcomes, results were analysed and summarised in percentages, means and graphs. We screened almost all trials about the management of inflammatory bowel disease published in the past 25 years. 232 studies were analysed, of which 167 reported power calculation. Less than half (48%) of these studies achieved their target sample size, needed for them to accurately conclude that the interventions were effective. Moreover, the average minimal difference those studies were aimed to detect was 30%, which could be not enough to prove the effect of an intervention. To conclude inaccurate power calculations and failure to achieve the target sample sizes can lead to errors in the results on how effective an intervention is in the management of inflammatory bowel disease.

Download Full-text

Correction to: Choosing the target difference and undertaking and reporting the sample size calculation for a randomised controlled trial – the development of the DELTA2 guidance

Trials ◽

10.1186/s13063-019-3809-2 ◽

2019 ◽

Vol 20 (1) ◽

Author(s):

William Sones ◽

Steven A. Julious ◽

Joanne C. Rothwell ◽

Craig Robert Ramsay ◽

Lisa V. Hampson ◽

...

Keyword(s):

Randomised Controlled Trial ◽

Sample Size ◽

Controlled Trial ◽

Sample Size Calculation ◽

Target Difference ◽

Randomised Controlled

Following publication of the original article [1], we have been notified of a few mistakes:

Download Full-text

Reporting of sample size calculation in randomised controlled trials: review

BMJ ◽

10.1136/bmj.b1732 ◽

2009 ◽

Vol 338 (may12 1) ◽

pp. b1732-b1732 ◽

Cited By ~ 138

Author(s):

P. Charles ◽

B. Giraudeau ◽

A. Dechartres ◽

G. Baron ◽

P. Ravaud

Keyword(s):

Sample Size ◽

Randomised Controlled Trials ◽

Sample Size Calculation ◽

Controlled Trials ◽

Randomised Controlled

Download Full-text

Choosing the Target Difference (“effect size”) for a Randomised Controlled Trial - DELTA2 Guidance

10.20944/preprints201808.0521.v1 ◽

2018 ◽

Author(s):

Jonathan A. Cook ◽

Steven A. Julious ◽

William Sones ◽

Lisa V. Hampson ◽

Catherine Hewitt ◽

...

Keyword(s):

Randomised Controlled Trial ◽

Sample Size ◽

Controlled Trial ◽

Sample Size Calculation ◽

Main Body ◽

Target Difference ◽

Superiority Trial ◽

The Difference ◽

The One ◽

Randomised Controlled

The aim of this document is to provide practical guidance on the choice of target difference used in the sample size calculation of a randomised controlled trial (RCT). Guidance is provided with a definitive trial, one that seeks to provide a useful answer, in mind and not those of a more exploratory nature. The term “target difference” is taken throughout to refer to the difference that is used in the sample size calculation (the one that the study formally “targets”). Please see the glossary for definitions and clarification with regards other relevant concepts. In order to address the specification of the target difference, it is appropriate, and to some degree necessary, to touch on related statistical aspects of conducting a sample size calculation. Generally the discussion of other aspects and more technical details is kept to a minimum, with more technical aspects covered in the appendices and referencing of relevant sources provided for further reading.The main body of this guidance assumes a standard RCT design is used; formally, this can be described as a two-arm parallel-group superiority trial. Most RCTs test for superiority of the interventions, that is, whether or not one of the interventions is superior to the other (See Box 1 for a formal definition of superiority, and of the two most common alternative approaches). Some common alternative trial designs are considered in Appendix 3. Additionally, it is assumed in the main body of the text that the conventional (Neyman-Pearson) approach to the sample size calculation of an RCT is being used. Other approaches (Bayesian, precision and value of information) are briefly considered in Appendix 2 with reference to the specification of the target difference.

Download Full-text