Abstract
Introduction (with objective): Ultra-rare diseases (URDs) represent a challenge for health systems due to their low prevalence, clinical heterogeneity, delayed diagnosis, and limited availability of specific therapies. Although there are published studies on URDs, the heterogeneity and dispersion of evidence hinder its use in clinical, regulatory, and health technology adoption decisions. Mapping scientific production can identify gaps, research trends, and geographical inequalities. The objective of this study was to analyze the scientific evidence related to URDs, characterizing the volume of publications, geographical distribution, and association with the Human Development Index (HDI). Material and Method: A cross-sectional study of publications indexed in PubMed was conducted. Initially, articles were identified using a search strategy based on descriptors related to URDs. The Medical Subject Headings (MeSH) and Supplementary Concepts (NM) terms referring to the health conditions of the retrieved articles were exported to a Microsoft Excel 2019 spreadsheet for screening and identification of terms related to URDs. To this end, the prevalence of each condition was consulted in the Orphanet, Genetic and Rare Diseases Information Center, National Organization for Rare Disorders, and Online Mendelian Inheritance in Man databases. Rare disease-related conditions (DRUs) were considered those with a prevalence of up to 1 case per 50,000 inhabitants. Subsequently, the terms referring to the identified DRUs were combined with the name of each country, using the affiliation identification (AD) field. The total number of articles retrieved using MeSH and NM was normalized by the number of inhabitants of each country, through the calculation of articles per million inhabitants. Scatter plots, simple linear regression, and Spearman correlation analyses were performed between the number of articles (MeSH, NM, total, and articles per million) and the HDI. The analyses were conducted using R/Rstudio software (dplyr, ggplot2, tidyr, and corrplot). Results: 390,986 publications related to DURs were identified, of which 383,423 (98.1%) were from MeSH terms and 7,563 (1.9%) from NM. The countries with the highest number of publications were the United States (n=79,043; 20.2%), Japan (n=34,757; 8.9%), China (n=34,438; 8.8%), the United Kingdom (n=26,959; 6.9%), and Italy (n=24,658; 6.3%). Publications were concentrated in Europe (n=160,722; 41.1%), Asia (n=116,801; 29.9%), and North America (n=90,446; 23.1%). A positive non-linear trend was observed between articles per million inhabitants and HDI, with an inflection point around HDI ≥0.75–0.80, from which further increases were reflected in greater scientific production. In countries with HDI <0.70, the relationship was less evident and with low publication density, while above 0.80 there was a more pronounced growth in articles per million inhabitants. In the Spearman correlation, a strong positive association was identified between HDI and articles per million inhabitants (ρ=0.83) and a moderate association with the number of articles indexed by MeSH terms (ρ=0.59), articles related to NM (ρ=0.63) and total publications (ρ=0.59). Conclusions: Scientific production on DURs was concentrated in countries with higher HDI. The findings reinforce the need to encourage research, international cooperation, and funding in underrepresented regions, aiming to expand knowledge and support public policies focused on urban development.
