Economic status, location, and healthcare system impact how well treatments work in trials

More consistent reporting of patient characteristics is needed across rheumatology trials.

Rheumatic diseases affect people’s joints, bones, tendons, ligaments and muscles – and often also other organs. Many of these diseases are autoimmune conditions that cause inflammation in the body. There are more than 200 rheumatic diseases, including rheumatoid arthritis, osteoarthritis, psoriatic arthritis, spondyloarthritis, systemic lupus erythematosus, and various other connective tissue diseases. In 2014 an international research network called OMERACT formed a group to develop guidance on how to address contextual factors in studies of treatments in people with rheumatic diseases. A contextual factor is a variable that is not an outcome of the study, but which may influence the outcome. These factors need to be recognised and measured to be able to understand the study results.

The authors wanted to find out whether there are certain features of people or their environments that determine how well different treatments will work for each person. This is important because if we know more about who might do better on particular treatments then we can choose tailored options. Knowing this would help improve the likelihood of people having a good response and would lower the risk of side effects. For example, some treatments might work better depending on a person’s sex or age.

The study looked at 31,274 people with rheumatic and musculoskeletal conditions who had taken part in one of 187 randomised controlled trials. Almost half (49%) of the trials took place in Europe, 19% in Asia, and 19% in North America. The rest were not specified, or took place in more than one continent. Most of the people had osteoarthritis or rheumatoid arthritis, but there were also people with fibromyalgia, osteoporosis and spinal fractures.

This was a meta-epidemiological study. This means the authors looked for links between sets of data in trials that had already taken place. Information from 187 clinical trials was put into a database and analysed to see if there were any association between 20 different population characteristics and the trial results. The population characteristics used were not completely included in the trials. They had previously been suggested as important by members of the OMERACT groups, which included patients and researchers in rheumatology.
The 20 population characteristics included: people’s sex, having other diseases, healthcare system, adherence to treatment, psychological well-being, age, previous drugs used to treat the disease, patient education/health literacy, disease duration, race, smoking, pain sensitisation, (social) support at work or from family and/or friends, socioeconomic status, occupation, religion, economic status, disability, education, and place of residence. In addition, the authors included known factors of social inequity.

Part of the main finding was that information about the 20 chosen population characteristics was poorly reported. On average, only a quarter of the trials included each of the population characteristics. Only age and people’s sex were reported in at least two thirds of the trials. This meant that it was not possible to do most of the planned analyses. However, based on the country where the trials were done, the authors were able to get data from elsewhere for some of the population characteristics. For example, they used a WHO database to find out about the healthcare system used, and data from UNESCO to estimate people’s education or health literacy. Information about religion came from the Pew Research Centre, economic status from the World Bank, and place of residence was assumed to be the same as the location of the first author on the trial publication. Using these other sources of information meant there was enough data to look at 7 of the 20 population characteristics

The analyses showed that economic status, place of residence, and maybe also healthcare system might have an impact on how well treatments worked in the trials. Age, sex, patient education or religion did not influence the treatment effect. For economic status, the authors found that trials in countries with a low- or low-middle income had the highest treatment effect compared with trials in high-income countries. Regarding the place of residence, the different countries were summarised per continent. The study found that trials conducted in Asia
showed larger treatment effects compared with trials in Europe or North America. Finally, it was shown that the treatment effect decreases when the medical health system works better. This might seem strange, but it could be because people taking part in the trials in high-income countries or those with very good healthcare systems are generally better looked after, and so the trial medicine has a smaller overall effect, whereas people who have not received good treatment before might have bigger potential for doing well in a trial.

Yes, no one has investigated these population characteristics across rheumatology trials before.

This study has several limitations, so the findings should be interpreted with caution. First, the lack of data in many of the trials meant that only 7 of the 20 planned population characteristics could be investigated. Second, the trial population may not always fully reflect the population of the country in which the trial was conducted. Using continents as place of residence instead of individual countries may also limit the validity of the study results. Finally, there may be other factors that might explain the associations that were found. It is important to be aware of potential oversimplifications when using grouped data. In this study, only average or grouped data were available, but ideally the analyses should have been done on data from individual people. However, complete access to that information is very limited, and might potentially go against data protection laws.

The results are part of a bigger effort that eventually should ensure that individual patients get the treatment which is most likely to be effective for them. The authors are doing more work to collect information from researchers and people with rheumatic diseases about which population characteristics should always be reported in trials. They hope this will have an impact on trials in the future, as well as on treatment guidelines.
As a next step, the OMERACT working group will develop a set of important contextual factors for rheumatology trials.

If you have a rheumatic disease, researchers are working towards a system to make sure that you always get the best treatment for you and your personal circumstances. However, there is still more work to be done. If you have any questions or concerns about your disease or its treatment, speak to your doctor.

Disclaimer: This is a summary of a scientific article written by a medical professional (“the Original Article”).
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Date prepared: September 2020

Summary based on research article published on: 30 June 2020
From: Nielsen SM, et al. Population characteristics as important contextual factors in rheumatology trials:
an exploratory meta-epidemiological study from an OMERACT Working Group. Ann Rheum Dis 2020;79:
79(10):1269–1276. doi:10.1136/annrheumdis-2020-217237.

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