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Methods for Specifying the Target Difference in a Randomised Controlled Trial: The Difference ELicitation in TriAls (DELTA) Systematic Review

Author

Listed:
  • Jenni Hislop
  • Temitope E Adewuyi
  • Luke D Vale
  • Kirsten Harrild
  • Cynthia Fraser
  • Tara Gurung
  • Douglas G Altman
  • Andrew H Briggs
  • Peter Fayers
  • Craig R Ramsay
  • John D Norrie
  • Ian M Harvey
  • Brian Buckley
  • Jonathan A Cook
  • for the DELTA group

Abstract

: Jonathan Cook and colleagues systematically reviewed the literature for methods of determining the target difference for use in calculating the necessary sample size for clinical trials, and discuss which methods are best for various types of trials. Background: Randomised controlled trials (RCTs) are widely accepted as the preferred study design for evaluating healthcare interventions. When the sample size is determined, a (target) difference is typically specified that the RCT is designed to detect. This provides reassurance that the study will be informative, i.e., should such a difference exist, it is likely to be detected with the required statistical precision. The aim of this review was to identify potential methods for specifying the target difference in an RCT sample size calculation. Methods and Findings: A comprehensive systematic review of medical and non-medical literature was carried out for methods that could be used to specify the target difference for an RCT sample size calculation. The databases searched were MEDLINE, MEDLINE In-Process, EMBASE, the Cochrane Central Register of Controlled Trials, the Cochrane Methodology Register, PsycINFO, Science Citation Index, EconLit, the Education Resources Information Center (ERIC), and Scopus (for in-press publications); the search period was from 1966 or the earliest date covered, to between November 2010 and January 2011. Additionally, textbooks addressing the methodology of clinical trials and International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) tripartite guidelines for clinical trials were also consulted. A narrative synthesis of methods was produced. Studies that described a method that could be used for specifying an important and/or realistic difference were included. The search identified 11,485 potentially relevant articles from the databases searched. Of these, 1,434 were selected for full-text assessment, and a further nine were identified from other sources. Fifteen clinical trial textbooks and the ICH tripartite guidelines were also reviewed. In total, 777 studies were included, and within them, seven methods were identified—anchor, distribution, health economic, opinion-seeking, pilot study, review of the evidence base, and standardised effect size. Conclusions: A variety of methods are available that researchers can use for specifying the target difference in an RCT sample size calculation. Appropriate methods may vary depending on the aim (e.g., specifying an important difference versus a realistic difference), context (e.g., research question and availability of data), and underlying framework adopted (e.g., Bayesian versus conventional statistical approach). Guidance on the use of each method is given. No single method provides a perfect solution for all contexts. Background: A clinical trial is a research study in which human volunteers are randomized to receive a given intervention or not, and outcomes are measured in both groups to determine the effect of the intervention. Randomized controlled trials (RCTs) are widely accepted as the preferred study design because by randomly assigning participants to groups, any differences between the two groups, other than the intervention under study, are due to chance. To conduct a RCT, investigators calculate how many patients they need to enroll to determine whether the intervention is effective. The number of patients they need to enroll depends on how effective the intervention is expected to be, or would need to be in order to be clinically important. The assumed difference between the two groups is the target difference. A larger target difference generally means that fewer patients need to be enrolled, relative to a smaller target difference. The target difference and number of patients enrolled contribute to the study's statistical precision, and the ability of the study to determine whether the intervention is effective. Selecting an appropriate target difference is important from both a scientific and ethical standpoint. Why Was This Study Done?: There are several ways to determine an appropriate target difference. The authors wanted to determine what methods for specifying the target difference are available and when they can be used. What Did the Researchers Do and Find?: To identify studies that used a method for determining an important and/or realistic difference, the investigators systematically surveyed the research literature. Two reviewers screened each of the abstracts chosen, and a third reviewer was consulted if necessary. The authors identified seven methods to determine target differences. They evaluated the studies to establish similarities and differences of each application. Points about the strengths and limitations of the method and how frequently the method was chosen were also noted. What Do these Findings Mean?: The study draws attention to an understudied but important part of designing a clinical trial. Enrolling the right number of patients is very important—too few patients and the study may not be able to answer the study question; too many and the study will be more expensive and more difficult to conduct, and will unnecessarily expose more patients to any study risks. The target difference may also be helpful in interpreting the results of the trial. The authors discuss the pros and cons of different ways to calculate target differences and which methods are best for which types of studies, to help inform researchers designing such studies. Additional Information: Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001645.

Suggested Citation

  • Jenni Hislop & Temitope E Adewuyi & Luke D Vale & Kirsten Harrild & Cynthia Fraser & Tara Gurung & Douglas G Altman & Andrew H Briggs & Peter Fayers & Craig R Ramsay & John D Norrie & Ian M Harvey & B, 2014. "Methods for Specifying the Target Difference in a Randomised Controlled Trial: The Difference ELicitation in TriAls (DELTA) Systematic Review," PLOS Medicine, Public Library of Science, vol. 11(5), pages 1-16, May.
  • Handle: RePEc:plo:pmed00:1001645
    DOI: 10.1371/journal.pmed.1001645
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    Cited by:

    1. Adam Wagstaff & Ha Thi Hong Nguyen & Huyen Dao & Sarah Bales, 2016. "Encouraging Health Insurance for the Informal Sector: A Cluster Randomized Experiment in Vietnam," Health Economics, John Wiley & Sons, Ltd., vol. 25(6), pages 663-674, June.
    2. Wagstaff, Adam & Nguyen, Ha Thi Hong & Dao, Huyen & Balesd, Sarah, 2014. "Encouraging health insurance for the informal sector : a cluster randomized trial," Policy Research Working Paper Series 6910, The World Bank.

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