Randomised controlled trials and clinical maternity care: moving on from intention-to-treat and other simplistic analyses of efficacy

This review questions the ubiquitous adherence to the ITT approach, and gives examples of where this may have misled the maternity care professions. It gives an overview of techniques to overcome potential deficiencies in result presentation, using method effectiveness models such as ‘Per Protocol’ (PP) or ‘As-Treated’ (AT) that may give more accurate clinical meaning to the presentation of obstetrical results. It then proceeds to cover the added benefits, considerations and potential pitfalls of the use of Instrumental Variable (IV) models in order to better reflect the clinical context.While ITT may achieve statistical purity, it frequently fails to address the true clinical or patient’s perspective. Though more complex and potentially beset by problems of their own, alternative methods of result presentation may better serve the latter aim. Each of the other methods may rely on untestable assumptions and therefore it is wisest that study results are presented in multiple formats to allow for informed reader evaluation.In the hierarchy of statistical trials, the RCT has been on the throne for over half a century [1]. Bradford-Hill is credited with provision of ‘criteria’ inferring causation [2], that have guided RCT design since 1965, though it is unclear whether this was his intention [3,4]. The universally favoured method for data analysis from RCTs is ITT [5,6], proposed for two reasons: ensuring comparable treatment groups due to randomisation, and preventing bias in analyses resulting from post randomisation exclusions. With ITT a solid statistical basis is said to exist for determining the significance of any observed difference in outcome between treatment groups [7], though all patients must be followed according to a prespecified schedule of outcome measurements regardless of compliance, adverse effects or other post randomisation observations [8].Randomisation and adherence/compliance are critical for ITT to produce a good estimate of efficacy. Randomisa