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Huang SD, Bamba V, Bothwell S, Fechner PY, Furniss A, Ikomi C, Nahata L, Nokoff NJ, Pyle L, Seyoum H, Davis SM. Development and validation of a computable phenotype for Turner syndrome utilizing electronic health records from a national pediatric network. Am J Med Genet A 2024; 194:e63495. [PMID: 38066696 PMCID: PMC10939843 DOI: 10.1002/ajmg.a.63495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 11/07/2023] [Accepted: 11/22/2023] [Indexed: 12/19/2023]
Abstract
Turner syndrome (TS) is a genetic condition occurring in ~1 in 2000 females characterized by the complete or partial absence of the second sex chromosome. TS research faces similar challenges to many other pediatric rare disease conditions, with homogenous, single-center, underpowered studies. Secondary data analyses utilizing electronic health record (EHR) have the potential to address these limitations; however, an algorithm to accurately identify TS cases in EHR data is needed. We developed a computable phenotype to identify patients with TS using PEDSnet, a pediatric research network. This computable phenotype was validated through chart review; true positives and negatives and false positives and negatives were used to assess accuracy at both primary and external validation sites. The optimal algorithm consisted of the following criteria: female sex, ≥1 outpatient encounter, and ≥3 encounters with a diagnosis code that maps to TS, yielding an average sensitivity of 0.97, specificity of 0.88, and C-statistic of 0.93 across all sites. The accuracy of any estradiol prescriptions yielded an average C-statistic of 0.91 across sites and 0.80 for transdermal and oral formulations separately. PEDSnet and computable phenotyping are powerful tools in providing large, diverse samples to pragmatically study rare pediatric conditions like TS.
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Affiliation(s)
- Sarah D Huang
- Department of Pediatrics, University of Colorado, Aurora, Colorado, USA
- eXtraOrdinary Kids Turner Syndrome Clinic, Children's Hospital Colorado, Aurora, Colorado, USA
- Department of Genetics, Human Genetics and Genetic Counseling, Stanford University School of Medicine, Stanford, California, USA
| | - Vaneeta Bamba
- Division of Endocrinology and Diabetes, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Samantha Bothwell
- Department of Pediatrics, University of Colorado, Aurora, Colorado, USA
| | - Patricia Y Fechner
- Department of Pediatrics, Division of Endocrinology at Seattle Children's Hospital, University of Washington, Seattle, Washington, USA
| | - Anna Furniss
- ACCORDS, University of Colorado, Aurora, Colorado, USA
| | - Chijioke Ikomi
- Division of Endocrinology, Nemours Children's Health, Wilmington, Delaware, USA
| | - Leena Nahata
- Division of Endocrinology, Nationwide Children's Hospital, Columbus, Ohio, USA
| | - Natalie J Nokoff
- Department of Pediatrics, University of Colorado, Aurora, Colorado, USA
| | - Laura Pyle
- Department of Pediatrics, University of Colorado, Aurora, Colorado, USA
- Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, Colorado, USA
| | - Helina Seyoum
- Department of Pediatrics, University of Colorado, Aurora, Colorado, USA
- eXtraOrdinary Kids Turner Syndrome Clinic, Children's Hospital Colorado, Aurora, Colorado, USA
| | - Shanlee M Davis
- Department of Pediatrics, University of Colorado, Aurora, Colorado, USA
- eXtraOrdinary Kids Turner Syndrome Clinic, Children's Hospital Colorado, Aurora, Colorado, USA
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Huang SD, Bamba V, Bothwell S, Fechner PY, Furniss A, Ikomi C, Nahata L, Nokoff NJ, Pyle L, Seyoum H, Davis SM. Development and Validation of a Computable Phenotype for Turner Syndrome Utilizing Electronic Health Records from a National Pediatric Network. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.19.23292889. [PMID: 37502850 PMCID: PMC10371114 DOI: 10.1101/2023.07.19.23292889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Turner syndrome (TS) is a genetic condition occurring in ~1 in 2,000 females characterized by the complete or partial absence of the second sex chromosome. TS research faces similar challenges to many other pediatric rare disease conditions, with homogenous, single-center, underpowered studies. Secondary data analyses utilizing Electronic Health Record (EHR) have the potential to address these limitations, however, an algorithm to accurately identify TS cases in EHR data is needed. We developed a computable phenotype to identify patients with TS using PEDSnet, a pediatric research network. This computable phenotype was validated through chart review; true positives and negatives and false positives and negatives were used to assess accuracy at both primary and external validation sites. The optimal algorithm consisted of the following criteria: female sex, ≥1 outpatient encounter, and ≥3 encounters with a diagnosis code that maps to TS, yielding average sensitivity 0.97, specificity 0.88, and C-statistic 0.93 across all sites. The accuracy of any estradiol prescriptions yielded an average C-statistic of 0.91 across sites and 0.80 for transdermal and oral formulations separately. PEDSnet and computable phenotyping are powerful tools in providing large, diverse samples to pragmatically study rare pediatric conditions like TS.
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Affiliation(s)
- Sarah D Huang
- Department of Pediatrics, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045
- eXtraOrdinary Kids Turner Syndrome Clinic, Children's Hospital Colorado, Aurora, CO 80045
- Institute for Society and Genetics, University of California Los Angeles, Los Angeles, CA 90095
| | - Vaneeta Bamba
- Division Endocrinology and Diabetes, The Children's Hospital of Philadelphia, Philadelphia, PA 19104
| | - Samantha Bothwell
- Department of Pediatrics, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045
| | - Patricia Y Fechner
- Department of Pediatrics, University of Washington, Division of Endocrinology at Seattle Children's, Seattle, WA 98105
| | - Anna Furniss
- ACCORDS, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045
| | - Chijioke Ikomi
- Division of Endocrinology, Nemours Children's Health, Wilmington, DE 19803
| | - Leena Nahata
- Division of Endocrinology, Nationwide Children's Hospital, Columbus, OH 43205
| | - Natalie J Nokoff
- Department of Pediatrics, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045
| | - Laura Pyle
- Department of Pediatrics, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045
- Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO 80045
| | - Helina Seyoum
- Department of Pediatrics, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045
- eXtraOrdinary Kids Turner Syndrome Clinic, Children's Hospital Colorado, Aurora, CO 80045
| | - Shanlee M Davis
- Department of Pediatrics, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045
- eXtraOrdinary Kids Turner Syndrome Clinic, Children's Hospital Colorado, Aurora, CO 80045
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