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Record W2117829414 · doi:10.1542/peds.2005-0843

Changes in the Epidemiology of Thalassemia in North America: A New Minority Disease

2005· article· en· W2117829414 on OpenAlexaffabout
Elliott Vichinsky, Eric A. Macklin, John S. Waye, Fred Lorey, Nancy F. Olivieri

Bibliographic record

VenuePEDIATRICS · 2005
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsToronto General HospitalMcMaster University Medical Centre
FundersNational Center for Research ResourcesNational Heart, Lung, and Blood Institute
KeywordsThalassemiaMedicineHemoglobinopathyEpidemiologyDiseaseBeta thalassemiaPediatricsGenotypeGeneticsInternal medicineBiologyGene

Abstract

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OBJECTIVE: Changing patterns of immigration to North America, along with improved treatment, have altered the clinical spectrum of thalassemia, one of the world's most common genetic diseases. The new demography of the disease, with its widely variable phenotypes, has implications for its diagnosis, counseling, and management. Characterization of the new spectrum of this ancient disease, now predominated by minority groups, is essential for optimizing survival. METHODS: The National Institutes of Health-sponsored North American Thalassemia Clinical Research Network (TCRN) conducted a cross-sectional study of 721 patients with thalassemia syndromes. A detailed chart review was undertaken to define the relationships between ethnic origins, genotype, and phenotype. These results were compared with 3 previous surveys of similar regions. To determine if the TCRN patient epidemiology is representative of North American patients, 87 additional programs were reviewed, and hemoglobinopathy programs from the 2 largest thalassemia regions, Ontario and California, were analyzed. RESULTS: A total of 721 patients completed analysis in the TCRN study, including 389 (54%) patients with beta-thalassemia major, 105 (15%) patients with beta-thalassemia intermedia, 95 (13%) patients with hemoglobin E-beta-thalassemia, and 132 (18%) patients with alpha-thalassemia. beta-Thalassemia predominated in Eastern North America. Hemoglobin E-beta-thalassemia and alpha-thalassemia were common on the Western continent. Genotype broadly correlated with the clinical phenotype. However, there was marked heterogeneity in clinical phenotype among patients with similar globin mutations. In beta-thalassemia disorders, coinheritance of the alpha-thalassemia trait, triplication of alpha-thalassemia genes, and heterozygosity for the dominant beta-thalassemia allele affected the clinical phenotype. In alpha-thalassemia disorders, structural mutations such as hemoglobin H-Constant Spring resulted in a severe hemoglobin H phenotype. Sixty percent of patients received regular transfusions, and 86% received regular iron-chelation therapy. Increased survival and decreasing birth rates of Mediterranean patients resulted in an aging Greek/Italian population being replaced by a young Asian/Middle Eastern population. Now, Asian patients account for >50% of the thalassemia population. Evidence of increasing survival is reflected in an advancing mean age of white patients with thalassemia major (25 years, up from 11 years in 1974). The results of the non-TCRN thalassemia survey confirm these observations and describe a young multiethnic thalassemia population distributed throughout North America. Newborn-screening results suggest that thalassemia births in North America are increasing and reflect the change in genotype and phenotype observed in the TCRN populations. CONCLUSIONS: The epidemiology of thalassemia in North America reflects a heterogeneous group of diseases with new ethnicities, genotypes, and phenotypes. In these communities, physicians will need to provide education, prenatal diagnosis, counseling, and management of this newly diverse group of patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.282
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations133
Published2005
Admission routes2
Has abstractyes

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