Multiple treatments comparisons

Posted on by A Nabhan

Health care is a rapidly growing field and this is a challenge to policy makers, caregivers as well as patients. Secondary research methodology responds to this challenge by a systematic approach to synthesizing research-based evidence and presenting it in an accessible format known as a systematic review. The systematic approach to evidence synthesis is  a self fulfilling prophecy.

Sometimes, an overview is needed to compile evidence from multiple systematic reviews of interventions into one accessible and usable document. Reasons for developing an overview of reviews include

  1. Different populations: DHEA for IVF cycles in women with normal ovarian reserve or in women with DOR
  2. Different interventions
  3. Different outcomes: HRT for menopause, bone density & fractures, menopausal symptoms, cardiovascular events, cognitive function

A special method of meta-analysis known as multiple treatments meta-analysis (MTM) is suited to the practical issues addressed by overviews of reviews. However, MTM (also known as ‘network meta-analysis’, or ‘multiple treatments comparisons’ (‘MTC’) meta-analysis) relies on a strong assumption that studies of different comparisons are similar in all ways other than the interventions being compared.

The simplest example of a multiple-treatments meta-analysis is the indirect comparison. With three interventions, any two can be compared indirectly through comparisons with the third. For example, treatment A and treatment B can be compared indirectly by contrasting trials of ‘A versus C’ with trials of ‘B versus C’. This analysis may be extended in various ways. For example, if there are also trials of the direct comparison ‘A versus B’, then these might be combined with the results of the indirect comparison. If there are more than three interventions, then there will be several direct and indirect comparisons, and it will be more convenient to analyse them simultaneously. Furthermore, using a particular framework, all interventions in the analysis can be ranked, using probabilistic, rather than crude, methods.

NMA graph osteoporosis
Evidence network of randomised trials comparing the effects of drugs to prevent osteoporotic hip fractures. The size of the circle is proportional to the number of participants randomised to that treatment. Width of the lines is proportional to the number of trials for that comparison. Coloured dashed lines refer to loops for indirect evidence
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