SynthesisOrphanet journal of rare diseases2024
A systematic review of studies that estimated the burden of chronic non-communicable rare diseases using disability-adjusted life years.
Synthesis in Orphanet journal of rare diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Citywide implementation of a rapid whole-genome sequencing program for critically ill pediatric patients.Nature medicine · 2026Article
- Reframing disease burden: validation of DALY-per-case as a per-diagnosis severity metric.Population health metrics · 2026Article
- Article
- Article
- Reevaluating health metrics: Unraveling the limitations of disability-adjusted life years as an indicator in disease burden assessment.World journal of methodology · 2025Review
- Predictors for readmission risk in schizophrenia: insights from a Saudi Arabian cohort.Frontiers in psychiatry · 2025Article
- Disability-Adjusted Life Years (DALYs) due to Breast, Cervical, Colorectal and Oral Cancers in Taiwan Regions.Cancer medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInitiatives aiming to assess the impact of rare diseases on population health might be hampered due to the complexity of disability-adjusted life years (DALYs) estimation. This study aimed to give insight into the epidemiological data sources and methodological approaches used in studies that estimated DALYs for chronic non-communicable rare diseases (CNCRD), and compare its results.
methodsA literature strategy was developed for peer-review search in Embase and Medline, and also performed on grey literature databases and population health and/or rare disease-focused websites. We included studies that determined the burden of CNCRD listed on the Orphanet's and/or the Genetic and Rare Diseases information center (GARD) websites. We excluded communicable and occupational diseases, rare cancers, and cost-effectiveness/benefit studies. Two researchers independently screened the identified records and extracted data from the final included studies. We used the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) statement to assess the quality of reporting of the included studies. The data synthesis depicted the studies' characteristics, their distribution by geographic coverage and the group of disease(s) they focused on, the methods and data input sources used and estimated DALY per case.
resultsIn total, 533 titles were screened, and 18 studies were included. These studies covered 19 different CNCRDs, of which most fell in the disease category "Diseases of the nervous system". Diverse methodological approaches and data input sources were observed among burden of CNCRD studies. A wide range of DALY per case was observed across the different studies and diseases included.
conclusionsA low number of burden of CNCRD studies was observed and most estimates resulted from multi-country studies, underlining the importance of international cooperation to further CNCRD research. This study revealed a lack of epidemiological data and harmonization of methods which hampers comparisons across burden of CNCRD studies.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.