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As the global population ages, healthcare providers are under pressure to identify the most effective and best-value treatments to counteract disease and disability. For the first time, a new policy model, developed by NDPH researchers, has enabled the cost-benefit ratio to be quantified for a range of treatment options for patients with impaired kidney function.

Chronic kidney disease (CKD) affects over 250 million people worldwide, and is becoming increasingly prevalent. Yet even mildly reduced kidney function significantly increases the risk of death, particularly from cardiovascular disease. A key target therefore, is to reduce the risk of cardiovascular disease in patients with reduced kidney function, through the use of cardioprotective treatments.

To support this, a team from NDPH’s Health Economics Research Centre (HERC) have developed a disease forecasting model to assess the net benefits and cost-effectiveness of different management regimes. The study was published today in PLOS Medicine.

The researchers used a UK primary healthcare database, the Clinical Practice Research Datalink, to identify an open cohort of 1.1 million individuals with reduced kidney function. This ranged from slightly impaired kidney function to severely restricted, based on the rate at which blood passed through their kidneys each minute. These were followed up for a median period of 4.8 years to measure outcomes that included stroke, myocardial infarction, kidney disease progression and death.

Two-thirds of the cohort were used to estimate risk equations for outcomes and develop a chronic kidney - cardiovascular disease health outcomes model. The aim was that this would simulate an individual’s long-term outcomes, healthcare costs and quality of life based on their sociodemographic and clinical characteristics at the time they entered the study.

Dr Iryna Schlackow, a study author and model developer at HERC, explains ‘The model simulates well the complex interactions between kidney function decline and increased cardiovascular disease risk. When we validated the model on the remaining third of the cohort, we found that it accurately predicted risks of cardiovascular events in patient categories by kidney function impairment, overall and by ten geographic regions in England’.

To demonstrate the model’s utility, the research team estimated the population gains in life expectancy resulting from three common cardiovascular prevention treatments (statins, antihypertensives and antiplatelets). They report that even partial adherence to these treatments would increase the life expectancy of CKD patients by 0.07 to 1.5 extra years per person, depending on their age and clinical condition. Further gains of an additional 0.12 to 0.61 years per person could be achieved if the treatments were fully optimised.

Associate Professor Borislava Mihaylova, who led the study, says ‘This policy model is a novel resource for health economists, health data scientists and policy makers to compare the clinical benefits and cost effectiveness of treatments for people with reduced kidney function.’

Ultimately, this framework can help healthcare providers identify the most cost-effective treatments, and allow patients to make informed decisions about their treatment. Hopefully, this will lead to more patients with reduced kidney function being offered and taking up treatments that can improve their life.

A key advantage of the model is that it can be adapted to incorporate different treatments, for instance to slow kidney function decline and CKD progression. ‘We have demonstrated the ability to study cardioprotective treatments, but we intend to also perform cost-effectiveness analysis of treatments that help protect against CKD’ continues Professor Mihaylova.

This study is part of the research team’s ongoing work to advise the NHS on the optimal frequency to monitor kidney function in patients at risk of CKD.