Validation of diagnostic codes and epidemiologic trends of Huntington disease: a population-based study in Navarre, Spain

Abstract

Background There is great heterogeneity on geographic and temporary Huntington disease (HD) epidemiological estimates. Most research studies of rare diseases, including HD, use health information systems (HIS) as data sources. This study investigates the validity and accuracy of national and international diagnostic codes for HD in multiple HIS and analyses the epidemiologic trends of HD in the Autonomous Community of Navarre (Spain). Methods HD cases were ascertained by the Rare Diseases Registry and the reference Medical Genetics Centre of Navarre. Positive predictive values (PPV) and sensitivity with 95% confidence intervals (95% CI) were estimated. Overall and 9-year periods (1991–2017) HD prevalence, incidence and mortality rates were calculated, and trends were assessed by Joinpoint regression. Results Overall PPV and sensitivity of combined HIS were 71.8% (95% CI: 59.7, 81.6) and 82.2% (95% CI: 70.1, 90.4), respectively. Primary care data was a more valuable resource for HD ascertainment than hospital discharge records, with 66% versus 50% sensitivity, respectively. It also had the highest number of “unique to source” cases. Thirty-five per cent of HD patients were identified by a single database and only 4% by all explored sources. Point prevalence was 4.94 (95% CI: 3.23, 6.65) per 100,000 in December 2017, and showed an annual 6.1% increase from 1991 to 1999. Incidence and mortality trends remained stable since 1995–96, with mean annual rates per 100,000 of 0.36 (95% CI: 0.27, 0.47) and 0.23 (95% CI: 0.16, 0.32), respectively. Late-onset HD patients (23.1%), mean age at onset (49.6 years), age at death (66.6 years) and duration of disease (16.7 years) were slightly higher than previously reported. Conclusion HD did not experience true temporary variations in prevalence, incidence or mortality over 23 years of post-molecular testing in our population. Ascertainment bias may largely explain the worldwide heterogeneity in results of HD epidemiological estimates. Population-based rare diseases registries are valuable instruments for epidemiological studies on low prevalence genetic diseases, like HD, as long as they include validated data from multiple HIS and genetic/family information.

SpanishHTTgene study reveals haplotype and allelic diversity with possible implications for germline expansion dynamics in Huntington disease

“…If we compare our molecular results with data from other populations, the estimated HD Spanish prevalence is in the range of 4–9 per 100 000 ( 4 ). This figure is in concordance with results of a recent epidemiologic study, carried out in the north of Spain (4.9/100 000), using several health information systems, detailed family history and laboratory genetic data ( 17 ). Similar figures have also been observed in other northern and southern Spanish regions ( 18 , 19 ), confirming the relatively low HD prevalence within European countries.…”

A Systematic Literature Review of Health Information Systems for Healthcare

“…Globally, the need for HIS within the healthcare system is critical in the enhancement of healthcare. Many healthcare actions are dependent on the use of HIS [ 67 , 68 , 69 ]. This demand is substantiated by the offerings of HIS in tackling the transformation and digitalization confronting the healthcare system.…”

Prevalence and Incidence of Huntington's Disease: An Updated Systematic Review and Meta‐Analysis

“…The accuracy of the NHDD, assessed by determining the positive predictive value (the proportion of cases identified in the NHDD that were also present in the NRDR) was 0.48 (95% CI, 0.45–0.52). Using the population in Navarre, Spain, Vicente and colleagues sought to validate the accuracy and sensitivity of HD diagnostic codes in routinely collected health care information system data sets (Minimum Basic Data Set at Hospital Discharge, Electronic Clinical Records in Primary Care, Temporary Work Disability Registry, and Mortality Statistics) compared with medical records as the gold standard 33 . The combined health information system data sets yielded a positive predictive value of 71.8% (95% CI, 59.7–81.6) and a sensitivity of 82.2% (95% CI, 70.1–90.4), with substantial variability in sensitivity among individual data sets.…”