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Does multimorbidity impact chronic disease treatment?


Anastasia Tsirtsakis


13/06/2023 1:40:12 PM

New international research has looked into a range of chronic diseases and their potential impact on effectiveness of common medications.

A man placing a tablet in a pill organiser.
It is estimated that one in five Australians have two or more chronic diseases.

Chronic disease in Australia is on the rise, having increased by 38% over the past three decades.
 
In 2020–21, it was estimated that 47% of Australians had at least one of 10 common chronic conditions – and 20% were estimated to have two or more.
 
With most care for chronic conditions provided in primary care, this poses a unique challenge for GPs when it comes to treating patients, as clinical guidelines often have a single condition focus.
 
Recognising this, a team of international researchers, led by Professor David McAllister from the University of Glasgow, have set out to address the knowledge gap in a new analysis.
 
Published in PLOS Medicine, they analysed data from 120 Phase 3 and 4 randomised controlled clinical trials for 23 common chronic conditions, including asthma, diabetes, hypertension, migraine, and osteoporosis.
 
The dataset included 128,331 participants from trials carried out between 1990 and 2017.
 
For each trial and treatment type, the team modelled whether there were any interactions between treatment efficacy and comorbidities, and found no evidence that treatment efficacy differs depending on comorbidities for any of the chronic conditions studied.
 
‘The standard assumption used in evidence syntheses is that efficacy is constant across subgroups, although this is often criticised. Our findings suggest that for modest levels of comorbidities, this assumption is reasonable,’ the authors concluded.
 
‘Thus, trial efficacy findings can be combined with data on natural history and competing risks to assess the likely overall benefit of treatments in the context of comorbidity.’
 
However, the authors did note that while treatment efficacy was not found to differ by comorbidity count, ‘net overall treatment benefits may nonetheless differ in people with differing degrees of comorbidity’.
 
‘For example, while there is strong evidence that the benefits of dual antiplatelet therapy [DAPT] following myocardial infarction [versus a single antiplatelet] outweigh the risks, this may not be true for patients with coexisting COPD,’ the authors wrote.
 
‘Cardiovascular mortality is commoner in COPD than the general population, favouring DAPT. However, non-cardiovascular mortality is also higher, favouring single-antiplatelet therapy because of competing risks.
 
‘Intensive control of blood glucose and other risk factors in diabetes and anticoagulant use in atrial fibrillation provide similar examples where the net overall treatment benefits are uncertain for people with comorbidity.’
 
Among the 23 conditions included in the analysis were four of the most common chronic diseases GPs see in Australia – asthma, COPD, diabetes, and osteoporosis.
 
In 2020, an Australian systemic review of 33 studies from 14 countries, published in BMC Primary Care, found that when it comes to managing patients with multimorbidity, GPs cite practising without supportive evidence as one of three main challenges.
 
‘GPs described an ongoing tension between applying single condition guidelines to patients with multimorbidity as security against uncertainty or penalty, and potentially causing patients harm,’ the authors had found.
 
Study co-author, Dr Peter Hanlon, who is a GP and Clinical Research Fellow at the University of Glasgow, said the research findings should prove useful in clinical practice.
 
‘Many people live with multiple long-term conditions; however, deciding on the most appropriate treatment for these people is often challenging because clinical trials rarely report whether treatments work as well in people with multiple conditions and clinical guidelines rarely address the specific needs of these people,’ he said.
 
‘We found that treatments had similar effects in people with multiple conditions, which is important as this information can be used to help experts decide which treatments they should recommend in clinical guidelines.’
 
To come to their conclusion, the team analysed the outcome most frequently reported in the trials for each condition and estimated modification of treatment effect by comorbidity. They did this by modelling the interaction between the comorbidity and treatment adjusted for age and sex.
 
The team then analysed the comorbidity–treatment interaction from each trial.
 
The estimated effect of each comorbidity was measured in three ways:

  1. The number of comorbidities (in addition to the index condition)
  2. Presence or absence of the six commonest comorbid diseases for each index condition
  3. Using continuous markers of underlying conditions
While the findings are promising, the authors did highlight that a limitation of the analysis is that the trials included ‘were not designed or powered to assess variation in treatment effect by comorbidity’, and that ‘relatively few trial participants had more than three comorbidities’.
 
Across the 120 trials, the percentage of participants with three or more comorbidities ranged from 2.3–57%.
 
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