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Systematic bias found in cost-effectiveness studies sponsored by industry

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Systematic bias found in cost-effectiveness studies sponsored by industry

Study prompts calls for more transparency, and increased funding for independent analyses of new medicines 

Industry-sponsored studies on a new drug or health technology are more likely to be found ‘cost-effective’ than independent studies, across a range of diseases, suggests a study in The BMJ

In a linked editorial, experts call for improved reporting of results, increased transparency, open-source cost-effectiveness models, and more independent studies, to reduce decision makers’ reliance on potentially biased cost-effectiveness analyses.

In many countries, manufacturers of a new medicine are required to submit a cost-effectiveness analysis (CEA) to weigh up its costs and effects.

This cost analysis evidence can be used to set the price for a drug or health technology or decide whether they will be covered by insurance policies. New drugs covered by insurance plans can be much more profitable than those not covered, which could lead to bias in CEAs funded by the drug and technology manufacturing industry.

While previous studies have consistently shown sponsorship bias in CEAs, most studies were limited to specific diseases, and are out of date. To fill in the gaps,Feng Xie and Ting Zhou from McMaster University, Canada, analysed data from all eligible CEAs published between 1976 and March 2021. 

Eligible CEAs were those that reported an incremental cost-effectiveness ratio (ICER) using quality-adjusted life years or QALYs – a ‘value for money’ measure of years lived in good health.

The authors used data from the Tufts Cost-Effectiveness Analysis Registry. Of around 10,000 analyses, those that didn’t provide sufficient information were omitted.  In total, 8,192 CEAs were included in the study, almost 30% of which were sponsored by industry. 

CEA industry sponsorship was defined in the study as an analysis wholly or partially funded by drug, medical device, or biotechnology companies. 

The results show that the industry-sponsored CEAs were significantly more likely to conclude that the new medicine or health technology was cost-effective than those not sponsored by industry.

For example, industry-sponsored studies were more likely to report the intervention being studied as cost-effective below the commonly used threshold of $50,000 per QALY gained than non-industry sponsored studies.

Among 5,877 CEAs that reported the intervention was more effective but more expensive than the comparator, the ICERs from industry sponsored studies were one third (33%) lower than those from non-industry sponsored studies.

The authors point out that their analyses are limited to the available information recorded in the registry. However, they say their analysis offers a systematic and comprehensive assessment on the sponsorship bias that allows for comparison with previous investigations.

As such, they suggest that “sponsorship bias in CEAs is significant, systemic, and present across a range of diseases and study designs.”

And they warn that industry sponsorship bias may lead to higher drug prices in lower and middle-income countries, where fewer resources mean decision-makers often need to rely on published, rather than independent CEAs. 

In a linked editorial, Adam Raymakers and Aaron Kesselheim from, respectively, Cancer Control Research, Canada, and Brigham and Women’s Hospital, Boston, USA, argue that decision-makers “should exercise caution when using published cost-effectiveness analysis in coverage decisions.”

They say finding solutions to tackle bias is more important than ever, and make the case for open-source analysis models, increased transparency, and increased funding for independent analyses, to help minimise reliance on industry-sponsored cost analyses.


Notes for editors
Research: Industry sponsorship bias in cost effectiveness analysis: registry

based analysis doi: 10.1136/bmj-2021-069573

Editorial: Promoting confidence in cost-effectiveness analyses 10.1136/bmj.o1452 

Journal: The BMJ

Link to Academy of Medical Sciences press release labelling system:

Externally peer reviewed? Yes (Analysis); No (linked editorial)
Evidence type: Observational data analysis; Opinion
Subjects: People