ArticleAmerican journal of hematology2026
Identification of Clinical Sub-Phenotypes of Sickle Cell Disease Using Latent Class Analysis.
Article in American journal of hematology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Sickle cell disease (SCD), a monogenic disorder, exhibits variable severity due to genetic and environmental modifiers. Prior studies have proposed hemolytic and vaso-occlusive sub-phenotypes based on limited data. We used latent class analysis (LCA) to identify complication-based sub-phenotypes in a large longitudinal cohort. From California administrative databases (1991-2019), we assembled a cohort of 7636 SCD patients (53% female). Disease-related complications (e.g., vaso-occlusive episodes [VOE], acute chest syndrome [ACS], avascular necrosis [AVN], chronic kidney disease [CKD], pulmonary hypertension, stroke, gallbladder disease, sepsis, obstructive lung disease, venous-thromboembolism [VTE], and leg ulcers) were extracted via ICD-9/10 codes. LCA models, stratified by sex, identified classes; we repeated the analysis in a younger sub-cohort (≤ 25 years; n = 2210). Males had higher cumulative incidences for recurrent ACS, AVN, gallbladder disease, obstructive lung disease (age 20), and leg ulcers/CKD (age 40). LCA revealed four classes in both sexes: Vaso-Occlusive (high VOE/ACS/AVN; 23% males, 15% females), Hemolytic (high CKD/pulmonary hypertension/stroke; 8% males, 13% females), Overlap (both patterns; 8% each), and Low Complications (62%-63%). In the younger cohort, classes were Vaso-Occlusive (8%), Hemolytic (3%), ACS-dominant (12%), and Low Complications (78%). Vaso-Occlusive, Hemolytic, and Overlap classes had elevated mortality (HR 1.3-2.4, p < 0.05) versus Low Complications; in youth, Hemolytic had the worst survival (HR 7.8, p < 0.001). LCA confirms the presence of vaso-occlusive and hemolytic sub-phenotypes, with low-complication groups predominant. Age-specific differences suggest evolving phenotypes, which can inform future targeted therapies and trials.
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