Estimating Rare Disease Prevalence From Administrative Hospitalization Databases

Burden of rare genetic disorders in India: twenty-two years' experience of a tertiary centre

BACKGROUND

Rare disorders comprise of ~ 7500 different conditions affecting multiple systems. Diagnosis of rare diseases is complex due to dearth of specialized medical professionals, testing labs and limited therapeutic options. There is scarcity of data on the prevalence of rare diseases in different populations. India being home to a large population comprising of 4600 population groups, of which several thousand are endogamous, is likely to have a high burden of rare diseases. The present study provides a retrospective overview of a cohort of patients with rare genetic diseases identified at a tertiary genetic test centre in India.

RESULTS

Overall, 3294 patients with 305 rare diseases were identified in the present study cohort. These were categorized into 14 disease groups based on the major organ/ organ system affected. Highest number of rare diseases (D = 149/305, 48.9%) were identified in the neuromuscular and neurodevelopmental (NMND) group followed by inborn errors of metabolism (IEM) (D = 47/305; 15.4%). Majority patients in the present cohort (N = 1992, 61%) were diagnosed under IEM group, of which Gaucher disease constituted maximum cases (N = 224, 11.2%). Under the NMND group, Duchenne muscular dystrophy (N = 291/885, 32.9%), trinucleotide repeat expansion disorders (N = 242/885; 27.3%) and spinal muscular atrophy (N = 141/885, 15.9%) were the most common. Majority cases of β-thalassemia (N = 120/149, 80.5%) and cystic fibrosis (N = 74/75, 98.7%) under the haematological and pulmonary groups were observed, respectively. Founder variants were identified for Tay-Sachs disease and mucopolysaccharidosis IVA diseases. Recurrent variants for Gaucher disease (GBA:c.1448T > C), β-thalassemia (HBB:c.92.+5G > C), non-syndromic hearing loss (GJB2:c.71G > A), albinism (TYR:c.832 C > T), congenital adrenal hyperplasia (CYP21A2:c.29-13 C > G) and progressive pseudo rheumatoid dysplasia (CCN6:c.298T > A) were observed in the present study.

CONCLUSION

The present retrospective study of rare disease patients diagnosed at a tertiary genetic test centre provides first insight into the distribution of rare genetic diseases across the country. This information will likely aid in drafting future health policies, including newborn screening programs, development of target specific panel for affordable diagnosis of rare diseases and eventually build a platform for devising novel treatment strategies for rare diseases.

Prevalence and incidence of neuromuscular conditions in the UK between 2000 and 2019: A retrospective study using primary care data

BACKGROUND

In the UK, large-scale electronic primary care datasets can provide up-to-date, accurate epidemiological information on rarer diseases, where specialist diagnoses from hospital discharges and clinic letters are generally well recorded and electronically searchable. Current estimates of the number of people living with neuromuscular disease (NMD) have largely been based on secondary care data sources and lacked direct denominators.

OBJECTIVE

To estimate trends in the recording of neuromuscular disease in UK primary care between 2000-2019.

METHODS

The Clinical Practice Research Datalink (CPRD) database was searched electronically to estimate incidence and prevalence rates (per 100,000) for a range of NMDs in each year. To compare trends over time, rates were age standardised to the most recent CPRD population (2019).

RESULTS

Approximately 13 million patients were actively registered in each year. By 2019, 28,230 active patients had ever received a NMD diagnosis (223.6), which was higher among males (239.0) than females (208.3). The most common classifications were Guillain-Barre syndrome (40.1), myasthenia gravis (33.7), muscular dystrophy (29.5), Charcot-Marie-Tooth (29.5) and inflammatory myopathies (25.0). Since 2000, overall prevalence grew by 63%, with the largest increases seen at older ages (≥65-years). However, overall incidence remained constant, though myasthenia gravis incidence has risen steadily since 2008, while new cases of muscular dystrophy fell over the same period.

CONCLUSIONS

Lifetime recording of many NMDs on primary care records exceed current estimates of people living with these conditions; these are important data for health service and care planning. Temporal trends suggest this number is steadily increasing, and while this may partially be due to better recording, it cannot be simply explained by new cases, as incidence remained constant. The increase in prevalence among older ages suggests increases in life expectancy among those living with NMDs may have occurred.

Huntington's disease in the United States: Variation by demographic and socioeconomic factors

BACKGROUND

Despite extensive research regarding the etiology of Huntington's disease, relatively little is known about the epidemiology of this rare disorder, particularly in the United States where there are no national-scale estimates of the disease.

OBJECTIVES

To provide national-scale estimates of Huntington's disease in a U.S. population and to test whether disease rates are increasing, and whether frequency varies by race, ethnicity, or other factors.

METHODS

Using an insurance database of over 67 million enrollees, we retrospectively identified a cohort of 3,707 individuals diagnosed with Huntington's disease between 2003 and 2016. We estimated annual incidence, annual diagnostic frequency, and tested for trends over time and differences in diagnostic frequency by sociodemographic characteristics.

RESULTS

During the observation period, the age-adjusted cumulative incidence rate was1.22 per 100,000 persons (95% confidence interval: 1.53, 1.65), and age-adjusted diagnostic frequency was 6.52 per 100,000 persons (95% confidence interval: 5.31, 5.66); both rates remained relatively stable over the 14-year period. We identified several previously unreported differences in Huntington's disease frequency by self-reported sex, income, and race/ethnicity. However, racial/ethnic differences were of lower magnitude than have previously been reported in other country-level studies.

CONCLUSIONS

In these large-scale estimates of U.S. Huntington's disease epidemiology, we found stable disease frequency rates that varied by several sociodemographic factors. These findings suggest that disease patterns may be more driven by social or environmental factors than has previously been appreciated. Results further demonstrate the potential utility of administrative Big Data in rare disease epidemiology when other data sources are unavailable. © 2019 International Parkinson and Movement Disorder Society.

The collective impact of rare diseases in Western Australia: an estimate using a population-based cohort

PURPOSE

It has been argued that rare diseases should be recognized as a public health priority. However, there is a shortage of epidemiological data describing the true burden of rare diseases. This study investigated hospital service use to provide a better understanding of the collective health and economic impacts of rare diseases.

METHODS

Novel methodology was developed using a carefully constructed set of diagnostic codes, a selection of rare disease cohorts from hospital administrative data, and advanced data-linkage technologies. Outcomes included health-service use and hospital admission costs.

RESULTS

In 2010, cohort members who were alive represented approximately 2.0% of the Western Australian population. The cohort accounted for 4.6% of people discharged from hospital and 9.9% of hospital discharges, and it had a greater average length of stay than the general population. The total cost of hospital discharges for the cohort represented 10.5% of 2010 state inpatient hospital costs.

CONCLUSIONS

This population-based cohort study provides strong new evidence of a marked disparity between the proportion of the population with rare diseases and their combined health-system costs. The methodology will inform future rare-disease studies, and the evidence will guide government strategies for managing the service needs of people living with rare diseases.Genet Med advance online publication 22 September 2016.

Computing disease incidence, prevalence and comorbidity from electronic medical records

Electronic medical records (EMR) represent a convenient source of coded medical data, but disease patterns found in EMRs may be biased when compared to surveys based on sampling. In this communication we draw attention to complications that arise when using EMR data to calculate disease prevalence, incidence, age of onset, and disease comorbidity. We review known solutions to these problems and identify challenges for future work.

Population-based analysis of hospitalizations in a West-European region revealed major changes in hospital utilization for patients with systemic lupus erythematosus over the period 2001-2012

OBJECTIVE

The objective of this paper is to evaluate hospital admissions in systemic lupus erythematosus (SLE) patients through a retrospective population-based study analyzing hospitalization data during 2001-2012 in Sardinia, an Italian region with universal health system coverage.

METHODS

Data on the hospital discharge records with the ICD-9-CM code for SLE (710.0) were obtained from the Department of Health and Hygiene and analyzed, mostly focusing on primary and non-primary diagnosis and Diagnosis-Related Group (DRG) code. In order to establish the significance of the annual trend for number and type of primary and non-primary discharge diagnosis, the two-tailed Cochran-Armitage test for trend was applied. In order to estimate SLE prevalence, data from administrative database and medical records were assembled.

RESULTS

This study included 6222 hospitalizations in 1675 patients (87% women). Hospitalizations with SLE as primary diagnosis were 3782 (58.0%) and significantly decreased during the study period. The annual number of renal, hematologic and neuropsychiatric disorders as non-primary diagnosis associated with SLE remained constant; however, their percentage increased (p < 0.0001) because of a declining number of admissions for SLE without associated diagnosis and without complications. Hospitalizations with SLE as non-primary diagnosis showed a significant upward trend in number and percentage of cerebrovascular accident (p = 0.0004), acute coronary syndrome (p = 0.0004) and chronic renal failure (p = 0.0003) as underlying primary diagnosis, while complications of pregnancy, labor and childbirth (p = 0.3375), malignancies (p = 0.6608) and adverse drug reactions (p = 0.2456) did not show statistically significant changes. Infections showed an increasing trend between 2001 and 2012 but did not reach statistical significance (p = 0.0304). After correction for hospitalization (93.8%) and survival (91.1%) rates calculated over the study period, the 2012 SLE prevalence in Sardinia was estimated to be 99.3 per 100,000 inhabitants.

CONCLUSIONS

While overall hospitalizations for SLE patients declined, those for cerebrovascular accident, acute coronary syndrome and chronic renal failure as underlying primary diagnosis increased during the study period.

A population-based registry as a source of health indicators for rare diseases: the ten-year experience of the Veneto Region's rare diseases registry

Background

Although rare diseases have become a major public health issue, there is a paucity of population-based data on rare diseases. The aim of this epidemiological study was to provide descriptive figures referring to a sizable group of unrelated rare diseases.

Methods

Data from the rare diseases registry established in the Veneto Region of north-east Italy (population 4,900,000), referring to the years from 2002 to 2012, were analyzed. The registry is based on a web-based system accessed by different users. Cases are enrolled by two different sources: clinicians working at Centers of expertise officially designated to diagnose and care patients with rare diseases and health professionals working in the local health districts. Deaths of patients are monitored by Death Registry.

Results

So far, 19,547 patients with rare diseases have been registered, and 23% of them are pediatric cases. The overall raw prevalence of the rare diseases monitored in the population under study is 33.09 per 10,000 inhabitants (95% CI 32.56-33.62), whilst the overall incidence is 3.85 per 10,000 inhabitants (95% CI 3.67-4.03). The most commonly-recorded diagnoses belong to the following nosological groups: congenital malformations (Prevalence: 5.45/10,000), hematological diseases (4.83/10,000), ocular disorders (4.47/10,000), diseases of the nervous system (3.51/10,000), and metabolic disorders (2,95/10,000). Most of the deaths in the study population occur among pediatric patients with congenital malformations, and among adult cases with neurological diseases. Rare diseases of the central nervous system carry the highest fatality rate (71.36/1,000). Rare diseases explain 4.2% of general population Years of Life Lost (YLLs), comparing to 1.2% attributable to infectious diseases and 2.6% to diabetes mellitus.

Conclusions

Our estimates of the burden of rare diseases at population level confirm that these conditions are a relevant public health issue. Our snapshot of their epidemiology is important for public health planning purposes, going to show that population-based registries are useful tools for generating health indicators relating to a considerable number of rare diseases, rather than to specific conditions.

Reported numbers of patients with rare diseases based on ten-year longitudinal national disability registries in Taiwan

This paper aims to describe a general demographic picture of patients with rare diseases in Taiwan and particularly focuses on the prevalence of rare diseases over time, age and gender distributions. We analyzed data mainly from the national disability registry from 2002 to 2011 in Taiwan, Republic of China. The results showed that the number of rare diseases increased from 93 to 193 between 2002 and 2011 and that the prevalence of rare diseases increased from 0.02 to 0.74 per 10,000 people in this time period. The gender ratio (male/female) was between 1.02 and 1.13 during this time period, with male cases representing a higher percentage than female cases in the rare disease population. The occurrence of rare diseases was significantly increased in children 3-5 years of age and elementary school children 6-14 years of age. The data also revealed that the occurrence of rare diseases in Taiwan was attributed primarily to pathogenic diseases and secondarily to genetic diseases. To obtain precise epidemiological data on rare diseases for future healthcare planning, this study highlights the importance of the cooperation of healthcare authorities with the social welfare department to strengthen the ability of the public healthcare system to regularly monitor and measure the occurrence of rare diseases in the community.

Surveillance of bleeding disorders, Texas, 2007

BACKGROUND

In 2007, some 1261 patients with hemophilia or other bleeding disorders were seen at federally funded hemophilia treatment centers (HTCs) in Texas. Although HTCs function as sites for passive surveillance of bleeding disorders, annual HTC visit data likely underestimate true prevalence of the disease due to the infrequent nature of healthcare utilization for this population.

PURPOSE

The main aim of this study was to compare two alternative methods for estimating prevalence of hemophilia and to describe the challenges associated with making valid prevalence estimates. Each method utilized a separate data source, with the goal of validating one or both of the methods, compared to the gold standard of active case finding.

METHODS

Two data sets, one describing treatment of hemophilia in an outpatient setting at HTCs and one describing treatment and care of patients in a hospital inpatient setting, were used to calculate annual prevalence estimates of hemophilia among men in Texas in 2007. The prevalence estimates resulting from each of the two methods were compared to each other and to past estimates based on active surveillance.

RESULTS

Calculations based on HTC data resulted in estimated prevalence rates of 8.9 and 2.1/100,000 male population for hemophilia A and B, respectively. Prevalence estimates based on hospital discharge data yielded rates of 12.3 and 2.9/100,000 males for hemophilia A and B, respectively.

CONCLUSIONS

Hemophilia is a rare, chronic disease with high treatment costs. Prevalence estimates based on HTC and hospital discharge data were similar to each other as well as to active surveillance prevalence estimates in published literature.

[Epidemiologic challenges in rare diseases]

Rare diseases, often called "orphan diseases", are a special challenge for epidemiologic research. Apart from the mere logistic effort for sample collection, there are considerable implications in statistical methodology. Usually one will not find enough cases of an orphan disease in a random sample from the population at risk. Furthermore, random error plays a more important role for decreasing probability of disease. Critical issues related to total population sampling, active and passive surveillance and capture-recapture methods are discussed. Challenges in risk factor research and related to therapeutic or preventive trials are presented. Examples from epidemiologic practice are given.

Development and verification of a "virtual" cohort using the National VA Health Information System

BACKGROUND

The VA's integrated electronic medical record makes it possible to create a "virtual" cohort of veterans with and without HIV infection to monitor trends in utilization, toxicity, and outcomes.

OBJECTIVES

We sought to develop a virtual cohort of HIV-infected veterans by adapting an existing algorithm, verifying this algorithm against independent clinical data, and finally identifying demographically-similar HIV-uninfected comparators.

RESEARCH DESIGN

Subjects were identified from VA administrative data in fiscal years 1998-2003 using a modified existing algorithm, then linked with Immunology Case Registry (ICR, the VA's HIV registry) and Pharmacy Benefits Management (centralized database of outpatient prescriptions) to verify accuracy of identification. The algorithm was modified to maximize positive predictive value (PPV) against ICR. Finally, 2 HIV-uninfected comparators were matched to each HIV-infected subject.

RESULTS

Using a single HIV code, 30,564 subjects were identified (positive predictive value 69%). Modification to require >1 outpatient or 1 inpatient code improved the positive predictive value to 88%. The lack of confirmatory laboratory and pharmacy data for the majority of subjects with a single outpatient code also supported this change. Of subjects identified with the modified algorithm, 89% had confirmatory evidence. When the modified algorithm was applied to fiscal years 1997-2004, 33,420 HIV-infected subjects were identified. Two HIV-uninfected comparators were matched to each subject for an overall cohort sample of 100,260.

CONCLUSIONS

In the HAART era, HIV-related codes are sufficient for identifying HIV-infected subjects from administrative data when patients with a single outpatient code are excluded. A large cohort of HIV-infected subjects and matched comparators can be identified from existing VA administrative datasets.