Why rare kidney diseases must be part of the CKD conversation – and how epidemiological insights can help

Approximately 750 million people worldwide live with chronic kidney disease (CKD), impacting nearly 10% of the global population. Healthcare strategies to prevent and manage CKD frequently recognise diabetes and hypertension as both leading causes and common comorbidities of the disease.¹ However, there has recently been growing recognition that a crucial component of the CKD burden has been overlooked.

Rare kidney diseases, of which around 80% are believed to have a genetic origin,² are an important, yet often under-recognised, contributor to the overall CKD patient population – despite being individually uncommon, collectively these conditions may account for 5% –10% of all CKD cases.³ This represents a patient population of tens of millions of people whose diagnosis and care could look very different if the underlying cause of their CKD was better understood and identified earlier.

The diagnostic gap: Why rare kidney diseases go undetected in CKD

Rare kidney diseases can be challenging to diagnose in CKD, as their symptoms may be non-specific - which can result in patients being misclassified as having CKD of unknown aetiology, or in misdiagnosis as more common conditions. Routine genetic testing – critical for identifying rare kidney diseases of genetic origin – has also not traditionally been part of standard nephrology practice.

However, recent studies suggest that 17.1% of CKD cases with unknown aetiology could be reclassified with genetic testing.⁴ This means many people may be living with undiagnosed, and potentially treatable, rare conditions – highlighting an avoidable gap in our current understanding of CKD populations.

“Routine genetic testing enables earlier, more accurate diagnoses and gives patients access to the right interventions sooner — that would represent a fundamental shift in CKD care.” – Dr Laura Webber, COO at HealthLumen.

Recent large-scale genetic sequencing studies have suggested that pathogenic variants associated with several rare kidney diseases – including Alport syndrome⁵ and autosomal dominant polycystic kidney disease (ADPKD)⁶ – may be more common and more genetically complex than previously thought. Better understanding the genetic basis of these conditions and the true size of their patient populations could be an important step towards improving fundamental understanding of CKD populations and helping patients get diagnosed quicker.

What’s at stake: The consequences of missed rare kidney disease diagnoses

Diagnosing CKD in the early stages is important, as the longer CKD goes undetected, the more complex and costly the disease becomes to treat – leading to significant health and economic consequences on patients, healthcare systems, and society at large.

Early diagnosis is particularly important where CKD is caused by underlying rare kidney diseases, as they disproportionately increase the risk of kidney failure among CKD patients. Individuals with these rare conditions are 28 times more likely to experience kidney failure compared to other CKD patients² and, although patients with rare kidney diseases represent a minority of CKD cases, they account for over 25% of those needing costly and invasive renal replacement therapy.³

This trend is particularly evident in children, with rare kidney diseases accounting for most paediatric CKD cases requiring kidney replacement therapies.⁷ This suggests that focusing diagnostic efforts within younger CKD patient groups may be a particularly efficient way of discovering patients who may benefit from receiving relevant rare kidney disease therapies. 

Data to shape strategy: Bridging the diagnostic gap in rare kidney disease with epidemiological insights

Advances in genetic data and data modelling techniques are offering new ways to establish strong epidemiological data that can provide a better understanding of the size and characteristics of rare kidney disease populations to drive better diagnostic strategies.

To address uncertainties around the number of patients with rare genetic kidney diseases, large-scale genetic databases containing genetic data from hundreds of thousands of individuals can be analysed to accurately estimate how many people carry disease-causing variants linked to these conditions.

“When we interrogate these large-scale datasets, we start to uncover the true picture of rare kidney diseases – often finding that their genetic variants are often more prevalent within populations than previously thought. These insights into the genetic basis and distribution of these conditions are essential for guiding more efficient diagnostic strategies.” – Dr James Cook, Senior Genetic Epidemiologist at HealthLumen.

This kind of data is not only valuable evidence when raising awareness of these rare conditions and advocating for policy change – such as introducing standard genetic testing for rare kidney diseases in CKD populations – but is also vital for pharmaceutical and biotech companies developing strategies to identify and correctly size patient populations for novel rare kidney disease treatments.

To quantify the future health and economic impacts of earlier diagnosis or interventions – including new therapies – within rare kidney disease populations, or CKD populations more widely, burden of disease modelling is a powerful tool. Microsimulation modelling is a particularly applicable modelling methodology, as it uses country-specific data to model populations at a highly granular individual-level – projecting disease emergence, progression, and outcomes, and accounting for changes in behaviour over time at a patient-level.

These models serve as vital tools for illustrating the potential value of widespread screening for rare kidney diseases in patients with CKD. By generating robust health economic projections, they can support payer submissions and health technology assessment (HTA) dossiers. This evidence, in turn, can guide regulatory bodies, policymakers, and payers in making informed decisions about how best to allocate resources and shape CKD screening and treatment strategies.

Looking ahead: A more proactive future for CKD care

Although rare kidney diseases remain a significantly overlooked contributor to the global burden of CKD, things have begun to shift in recent years – in 2023, for example, an international panel published a roadmap recommending integrating genetic testing into routine nephrology practice.⁸

Strong epidemiological evidence will be key to accelerating further change – making the case to prioritise rare kidney diseases within broader CKD strategies, helping guide resource allocation, and supporting policy and reimbursement decisions that enable earlier and more effective care. With the right data and tools, we can move towards a more proactive and equitable future for CKD care.

HealthLumen supports this shift by working with industry, advocates, and researchers to turn data into meaningful action – using our robust genetic database mining methodology to help to uncover the true size of rare disease patient populations and better understand their characteristics, and using our microsimulation-based modelling platform to project the future impact of interventions, quantify unmet needs, and guide strategic decision-making across the healthcare ecosystem.

“By combining deep insights on the genetic characteristics and real size of rare kidney disease populations with data-driven evidence of the benefit of future interventions, we can work with CKD and rare disease stakeholders to drive earlier, more effective intervention and care for patients” - Dr James Cook, Senior Genetic Epidemiologist at HealthLumen.

To find out more about our work at HealthLumen, please visit www.healthlumen.com. Email the HealthLumen team at info@healthlumen.com.

About the authors

Dr Laura Webber is co-founder and Chief Operating Officer of HealthLumen. She leads a multi-disciplinary team working on global, European, and national health projects for the public and private sector. Major clients she has worked with include AstraZeneca, Cancer Research UK, British Heart Foundation, Pfizer, Amgen, the World Health Organization, and the World Bank. Before co-founding HealthLumen, Dr Webber was Director of Public Health Modelling at the UK Health Forum, where she coordinated the development of chronic disease policy models to answer a range of policy and clinical questions related to the prevention and earlier management of chronic diseases such as cardiovascular disease, COPD, and diabetes. Dr Webber holds an MA in social and political sciences from Cambridge University and a PhD from the Department of Epidemiology and Public Health, University College London. She holds an honorary research position at Imperial College, London, and has co-authored many high-impact peer-reviewed publications (h-index of 29) and major reports.

Olivia Seifert is Content Strategist at HealthLumen, where she develops and manages content that translates the company’s advanced epidemiological modelling into accessible insights for stakeholders across pharma, biotech, and healthcare. She has extensive experience in academic and scientific publishing, having previously held content management roles with leading publishers. Seifert holds a BSc in Human Sciences from University College London and an MPhil in Human Evolutionary Studies from the University of Cambridge.

About HealthLumen

HealthLumen specialises in precision epidemiological modelling, quantifying the health and economic burden of chronic and rare diseases, and the impact of proposed interventions. The evidence we generate supports clients across pharma, biotech, and public health in making informed decisions throughout the product lifecycle and in helping to shape policy decisions. Our work on CKD, supported by AstraZeneca, projected the future prevalence, disease burden, healthcare use and costs, and the benefits of screening, in over 35 countries, and made a strong case for earlier detection and intervention at a policy level.