MAICing a Decision
Do methods that compare newly approved drugs with those already on the market help cut healthcare costs?
James Strachan |
Regulatory approval is seen as a major milestone in drug development, but it’s far from being the final hurdle. After approval, companies must demonstrate the clinical and economic value of their product relative to other existing drugs on the market – so healthcare payers know which drugs to pay for, and how much. A lack of direct comparisons forces analysts to compare results across different studies – often with different study designs and different patient characteristics. And the problem can be especially tricky given that access to the complete patient-level data is usually only available for one study.
With these difficulties in mind, researchers came up with a new method in 2010: matching adjusted indirect comparison (1). MAIC allows researchers to reweight observations or adjust final analyses so that the patient characteristics match the summaries of another trial. In the UK, MAIC has been used in over 20 successful drug reimbursement evaluations and included in methodological guidance for indirect comparisons issued by the National Institute of Clinical Excellence (NICE).
David Cheng, postdoctoral researcher at Harvard’s T.H. Chan School of Public Health is co-author of a new study that looks at the statistical performance of MAIC (2). Here, we speak with him to find out more.
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