Racial and Ethnic Differences in Pediatric Pulmonary Hypertension: An Analysis of the Pediatric Pulmonary Hypertension Network Registry.

OBJECTIVE: To investigate racial and ethnic differences in pulmonary hypertension subtypes and survival differences in a pediatric population. STUDY DESIGN: This was a retrospective analysis of a cohort of patients with pulmonary hypertension (aged ≤18 years) enrolled in the Pediatric Pulmonary Hypertension Network registry between 2014 and 2018, comprising patients at eight Pediatric Centers throughout North America (n = 1417). RESULTS: Among children diagnosed after the neonatal period, pulmonary arterial hypertension was more prevalent among Asians (OR, 1.83; 95% CI, 1.21-2.79; P = .0045), lung disease-associated pulmonary hypertension among blacks (OR, 2.09; 95% CI, 1.48-2.95; P < .0001), idiopathic pulmonary arterial hypertension among whites (OR, 1.58; 95% CI, 1.06-2.41; P = .0289), and pulmonary veno-occlusive disease among Hispanics (OR, 6.11; 95% CI, 1.34-31.3; P = .0184). Among neonates, persistent pulmonary hypertension of the newborn (OR, 4.07; 95% CI, 1.54-10.0; P = .0029) and bronchopulmonary dysplasia (OR, 8.11; 95% CI, 3.28-19.8; P < .0001) were more prevalent among blacks, and congenital diaphragmatic hernia was more prevalent among whites (OR, 2.29; 95% CI, 1.25-4.18; P = .0070). An increased mortality risk was observed among blacks (HR, 1.99; 95% CI, 1.03-3.84; P = .0396), driven primarily by the heightened mortality risk among those with lung disease-associated pulmonary hypertension (HR, 2.84; 95% CI, 1.15-7.04; P = .0241). CONCLUSIONS: We found significant racial variability in the prevalence of pulmonary hypertension subtypes and survival outcomes among children with pulmonary hypertension. Given the substantial burden of this disease, further studies to validate phenotypic differences and to understand the underlying causes of survival disparities between racial and ethnic groups are warranted.

Learning a Comorbidity-Driven Taxonomy of Pediatric Pulmonary Hypertension.

RATIONALE: Pediatric pulmonary hypertension (PH) is a heterogeneous condition with varying natural history and therapeutic response. Precise classification of PH subtypes is, therefore, crucial for individualizing care. However, gaps remain in our understanding of the spectrum of PH in children. OBJECTIVE: We seek to study the manifestations of PH in children and to assess the feasibility of applying a network-based approach to discern disease subtypes from comorbidity data recorded in longitudinal data sets. METHODS AND RESULTS: A retrospective cohort study comprising 6 943 263 children (<18 years of age) enrolled in a commercial health insurance plan in the United States, between January 2010 and May 2013. A total of 1583 (0.02%) children met the criteria for PH. We identified comorbidities significantly associated with PH compared with the general population of children without PH. A Bayesian comorbidity network was constructed to model the interdependencies of these comorbidities, and network-clustering analysis was applied to derive disease subtypes comprising subgraphs of highly connected comorbid conditions. A total of 186 comorbidities were found to be significantly associated with PH. Network analysis of comorbidity patterns captured most of the major PH subtypes with known pathological basis defined by the World Health Organization and Panama classifications. The analysis further identified many subtypes documented in only a few case studies, including rare subtypes associated with several well-described genetic syndromes. CONCLUSIONS: Application of network science to model comorbidity patterns recorded in longitudinal data sets can facilitate the discovery of disease subtypes. Our analysis relearned established subtypes, thus validating the approach, and identified rare subtypes that are difficult to discern through clinical observations, providing impetus for deeper investigation of the disease subtypes that will enrich current disease classifications.

A Computable Phenotype Improves Cohort Ascertainment in a Pediatric Pulmonary Hypertension Registry.

OBJECTIVES: To compare registry and electronic health record (EHR) data mining approaches for cohort ascertainment in patients with pediatric pulmonary hypertension (PH) in an effort to overcome some of the limitations of registry enrollment alone in identifying patients with particular disease phenotypes. STUDY DESIGN: This study was a single-center retrospective analysis of EHR and registry data at Boston Children's Hospital. The local Informatics for Integrating Biology and the Bedside (i2b2) data warehouse was queried for billing codes, prescriptions, and narrative data related to pediatric PH. Computable phenotype algorithms were developed by fitting penalized logistic regression models to a physician-annotated training set. Algorithms were applied to a candidate patient cohort, and performance was evaluated using a separate set of 136 records and 179 registry patients. We compared clinical and demographic characteristics of patients identified by computable phenotype and the registry. RESULTS: The computable phenotype had an area under the receiver operating characteristics curve of 90% (95% CI, 85%-95%), a positive predictive value of 85% (95% CI, 77%-93%), and identified 413 patients (an additional 231%) with pediatric PH who were not enrolled in the registry. Patients identified by the computable phenotype were clinically distinct from registry patients, with a greater prevalence of diagnoses related to perinatal distress and left heart disease. CONCLUSIONS: Mining of EHRs using computable phenotypes identified a large cohort of patients not recruited using a classic registry. Fusion of EHR and registry data can improve cohort ascertainment for the study of rare diseases. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02249923.