Prevalence and demographics of 331 rare diseases and associated COVID-19-related mortality among 58 million individuals: a nationwide retrospective observational study

IF 23.8 1区 医学 Q1 MEDICAL INFORMATICS Lancet Digital Health Pub Date : 2025-02-01 DOI:10.1016/S2589-7500(24)00253-X
Johan H Thygesen PhD , Huayu Zhang PhD , Hanane Issa MSc , Jinge Wu MSc , Tuankasfee Hama MSc , Ana-Caterina Phiho-Gomes PhD , Tudor Groza PhD , Sara Khalid PhD , Thomas R Lumbers PhD , Mevhibe Hocaoglu PhD , Prof Kamlesh Khunti PhD , Rouven Priedon BA , Prof Amitava Banerjee PhD , Nikolas Pontikos PhD , Chris Tomlinson PhD , Ana Torralbo PhD , Prof Paul Taylor PhD , Prof Cathie Sudlow PhD , Prof Spiros Denaxas PhD , Prof Harry Hemingway PhD , Prof Honghan Wu PhD
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引用次数: 0

Abstract

Background

The Global Burden of Disease Study has provided key evidence to inform clinicians, researchers, and policy makers across common diseases, but no similar effort with a single-study design exists for hundreds of rare diseases. Consequently, for many rare conditions there is little population-level evidence, including prevalence and clinical vulnerability, resulting in an absence of evidence-based care that was prominent during the COVID-19 pandemic. We aimed to inform rare disease care by providing key descriptors from national data and explore the impact of rare diseases during the COVID-19 pandemic.

Methods

In this nationwide retrospective observational cohort study, we used the electronic health records (EHRs) of more than 58 million people in England, linking nine National Health Service datasets spanning health-care settings for people who were alive on Jan 23, 2020. Starting with all rare diseases listed in Orphanet (an extensive online resource for rare diseases), we quality assured and filtered down to analyse 331 conditions mapped to ICD-10 or Systemized Nomenclature of Medicine–Clinical Terms that were clinically validated in our dataset. For all 331 rare diseases, we calculated population prevalences, analysed patients’ clinical and demographic details, and investigated mortality with SARS-CoV-2. We assessed COVID-19-related mortality by comparing cohorts of patients for each rare disease and rare disease category with controls matched for age group, sex, ethnicity, and vaccination status, at a ratio of two controls per individual with a rare disease.

Findings

Of 58 162 316 individuals, we identified 894 396 with at least one rare disease and assessed COVID-19-related mortality between Sept 1, 2020, and Nov 30, 2021. We calculated reproducible estimates, adjusted for age and sex, for all 331 rare diseases, including for 186 (56·2%) conditions without existing prevalence estimates in Orphanet. 49 rare diseases were significantly more frequent in female individuals than in male individuals, and 62 were significantly more frequent in male individuals than in female individuals; 47 were significantly more frequent in Asian or British Asian individuals than in White individuals; and 22 were significantly more frequent in Black or Black British individuals than in White individuals. 37 rare diseases were significantly more frequent in the White population compared with either the Black or Asian population. 7965 (0·9%) of 894 396 patients with a rare disease died from COVID-19, compared with 141 287 (0·2%) of 58 162 316 in the full study population. In fully vaccinated individuals, the risk of COVID-19-related mortality was significantly higher for eight rare diseases, with patients with bullous pemphigoid (hazard ratio 8·07, 95% CI 3·01–21·62) being at highest risk.

Interpretation

Our study highlights that national-scale EHRs provide a unique resource to estimate detailed prevalence, clinical, and demographic data for rare diseases. Using COVID-19-related mortality analysis, we showed the power of large-scale EHRs in providing insights to inform public health decision making for these often neglected patient populations.

Funding

British Heart Foundation Data Science Centre, led by Health Data Research UK.
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5,800 万人中 331 种罕见病的患病率和人口统计学特征以及与 COVID-19 相关的死亡率:一项全国范围的回顾性观察研究。
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来源期刊
CiteScore
41.20
自引率
1.60%
发文量
232
审稿时长
13 weeks
期刊介绍: The Lancet Digital Health publishes important, innovative, and practice-changing research on any topic connected with digital technology in clinical medicine, public health, and global health. The journal’s open access content crosses subject boundaries, building bridges between health professionals and researchers.By bringing together the most important advances in this multidisciplinary field,The Lancet Digital Health is the most prominent publishing venue in digital health. We publish a range of content types including Articles,Review, Comment, and Correspondence, contributing to promoting digital technologies in health practice worldwide.
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