Diagnostic Code-Based Screening for Identifying Children with Primary Hyperoxaluria.

2022

898-905

12/2022

1527-3792

PURPOSE: We evaluated the utility of diagnostic codes to screen for patients with primary hyperoxaluria (PH) and evaluate their positive predictive value (PPV) in identifying children with this rare condition in PEDSnet, a clinical research network of pediatric health systems that shares electronic health records data.

MATERIALS AND METHODS: We conducted a cross-sectional study of children who received care at 7 PEDSnet institutions from January 2009 through January 2021. We developed and applied screening criteria using diagnostic codes that generated 3 categories of the hypothesized probability of PH. Tier 1 had specific diagnostic codes for PH; tier 2 had codes for hyperoxaluria, oxalate nephropathy, or oxalosis; and tier 3 had a combination of ≥2 codes for disorder of carbohydrate metabolism and ≥1 code for kidney stones. We reviewed the electronic health records of patients with possible PH to confirm PH diagnosis and evaluate the accuracy and timing of diagnostic codes. The PPV of the codes was compared across tiers, time, PH type, and site.

RESULTS: We identified 341 patients in the screen; 33 had confirmed PH (9.7%). Tier 1 had the highest proportion of PH; however, the PPV was only 20%. The degree to which an institution accurately represented point of care diagnoses in the data extraction process was predictive of higher PPV. The PPV of diagnostic codes was highest for PH3 (100%) and lowest for PH1 (22.8%).

CONCLUSIONS: Diagnostic codes for PH have poor PPV. Findings suggest that one should be careful in research using large databases in which source validation is not possible.

10.1097/JU.0000000000002863

J Urol

35930731

Using a Multi-Institutional Pediatric Learning Health System to Identify Systemic Lupus Erythematosus and Lupus Nephritis: Development and Validation of Computable Phenotypes.

2021

2021 Nov 03

1555-905X

<p><strong>BACKGROUND AND OBJECTIVES: </strong>Performing adequately powered clinical trials in pediatric diseases, such as SLE, is challenging. Improved recruitment strategies are needed for identifying patients.</p>

<p><strong>DESIGN, SETTING, PARTICIPANTS, &amp; MEASUREMENTS: </strong>Electronic health record algorithms were developed and tested to identify children with SLE both with and without lupus nephritis. We used single-center electronic health record data to develop computable phenotypes composed of diagnosis, medication, procedure, and utilization codes. These were evaluated iteratively against a manually assembled database of patients with SLE. The highest-performing phenotypes were then evaluated across institutions in PEDSnet, a national health care systems network of &gt;6.7 million children. Reviewers blinded to case status used standardized forms to review random samples of cases (=350) and noncases (=350).</p>

<p><strong>RESULTS: </strong>Final algorithms consisted of both utilization and diagnostic criteria. For both, utilization criteria included two or more in-person visits with nephrology or rheumatology and ≥60 days follow-up. SLE diagnostic criteria included absence of neonatal lupus, one or more hydroxychloroquine exposures, and either three or more qualifying diagnosis codes separated by ≥30 days or one or more diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 100% (95% confidence interval [95% CI], 99 to 100), specificity was 92% (95% CI, 88 to 94), positive predictive value was 91% (95% CI, 87 to 94), and negative predictive value was 100% (95% CI, 99 to 100). Lupus nephritis diagnostic criteria included either three or more qualifying lupus nephritis diagnosis codes (or SLE codes on the same day as glomerular/kidney codes) separated by ≥30 days or one or more SLE diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 90% (95% CI, 85 to 94), specificity was 93% (95% CI, 89 to 97), positive predictive value was 94% (95% CI, 89 to 97), and negative predictive value was 90% (95% CI, 84 to 94). Algorithms identified 1508 children with SLE at PEDSnet institutions (537 with lupus nephritis), 809 of whom were seen in the past 12 months.</p>

<p><strong>CONCLUSIONS: </strong>Electronic health record-based algorithms for SLE and lupus nephritis demonstrated excellent classification accuracy across PEDSnet institutions.</p>

10.2215/CJN.07810621

Clin J Am Soc Nephrol

34732529

Behavioral Health Diagnoses in Youth With Gender Dysphoria Compared with Controls: A PEDSnet Study.

2021

2021 Sep 24

1097-6833

<p><strong>OBJECTIVE: </strong>To assess the odds of a psychiatric or neurodevelopmental diagnosis among youth with a diagnosis of gender dysphoria compared with matched controls in a large electronic health record dataset from six pediatric health systems, PEDSnet. We hypothesized that youth with gender dysphoria would have higher odds of having psychiatric and neurodevelopmental diagnoses than controls.</p>

<p><strong>STUDY DESIGN: </strong>All youth with a diagnosis of gender dysphoria (n=4,173 age at last visit 16.2 + 3.4) and at least one outpatient encounter were extracted from the PEDSnet database and propensity-score matched on 8 variables to controls without gender dysphoria (n=16,648, age at last visit 16.2 + 4.8) using multivariable logistic regression. The odds of having psychiatric and neurodevelopmental diagnoses were examined using generalized estimating equations.</p>

<p><strong>RESULTS: </strong>Youth with gender dysphoria had higher odds of psychiatric (OR: 4.0 [95% CI: 3.8, 4.3] P &lt; .0001) and neurodevelopmental diagnoses (1.9 [1.7, 2.0], p&lt;0.0001). Youth with gender dysphoria were more likely to have a diagnosis across all psychiatric disorder sub-categories, with particularly high odds of mood disorder (7.3 [6.8, 7.9], p&lt;0.0001) and anxiety (5.5 [5.1, 5.9], p&lt;0.0001). Youth with gender dysphoria had a greater odds of autism spectrum disorder (2.6, [2.2, 3.0], p&lt;0.0001).</p>

<p><strong>CONCLUSIONS: </strong>Youth with gender dysphoria at large pediatric health systems have greater odds of psychiatric and several neurodevelopmental diagnoses compared with youth without gender dysphoria. Further studies are needed to evaluate changes in mental health over time with access to gender affirming care.</p>

10.1016/j.jpeds.2021.09.032

J Pediatr

34571022

Using Electronic Health Record Data to Rapidly Identify Children with Glomerular Disease for Clinical Research.

2019

2427-2435

2019 Dec

1533-3450

<p><strong>BACKGROUND: </strong>The rarity of pediatric glomerular disease makes it difficult to identify sufficient numbers of participants for clinical trials. This leaves limited data to guide improvements in care for these patients.</p>

<p><strong>METHODS: </strong>The authors developed and tested an electronic health record (EHR) algorithm to identify children with glomerular disease. We used EHR data from 231 patients with glomerular disorders at a single center to develop a computerized algorithm comprising diagnosis, kidney biopsy, and transplant procedure codes. The algorithm was tested using PEDSnet, a national network of eight children's hospitals with data on &gt;6.5 million children. Patients with three or more nephrologist encounters (=55,560) not meeting the computable phenotype definition of glomerular disease were defined as nonglomerular cases. A reviewer blinded to case status used a standardized form to review random samples of cases (=800) and nonglomerular cases (=798).</p>

<p><strong>RESULTS: </strong>The final algorithm consisted of two or more diagnosis codes from a qualifying list or one diagnosis code and a pretransplant biopsy. Performance characteristics among the population with three or more nephrology encounters were sensitivity, 96% (95% CI, 94% to 97%); specificity, 93% (95% CI, 91% to 94%); positive predictive value (PPV), 89% (95% CI, 86% to 91%); negative predictive value, 97% (95% CI, 96% to 98%); and area under the receiver operating characteristics curve, 94% (95% CI, 93% to 95%). Requiring that the sum of nephrotic syndrome diagnosis codes exceed that of glomerulonephritis codes identified children with nephrotic syndrome or biopsy-based minimal change nephropathy, FSGS, or membranous nephropathy, with 94% sensitivity and 92% PPV. The algorithm identified 6657 children with glomerular disease across PEDSnet, ≥50% of whom were seen within 18 months.</p>

<p><strong>CONCLUSIONS: </strong>The authors developed an EHR-based algorithm and demonstrated that it had excellent classification accuracy across PEDSnet. This tool may enable faster identification of cohorts of pediatric patients with glomerular disease for observational or prospective studies.</p>

10.1681/ASN.2019040365

J. Am. Soc. Nephrol.

31732612

Unintended consequences of evolution of the Common Terminology Criteria for Adverse Events.

2019

e27747

2019 Apr 09

1545-5017

<p><strong>BACKGROUND: </strong>Adverse events (AEs) on Children's Oncology Group (COG) trials are reported manually by clinical research assistants (CRAs). The Common Terminology Criteria for Adverse Events (CTCAE) was developed to provide standardized definitions for identifying and grading AEs. The CTCAE has expanded significantly over its five versions, but the impact of CTCAE definitional changes has not been examined.</p>

<p><strong>PROCEDURE: </strong>This study compared AE number and ascertainment among the first four CTCAE versions using a case vignette. Each CTCAE version was used to create a list of AEs and grades by two separate CRAs.</p>

<p><strong>RESULTS: </strong>The CTCAE expanded from 9 categories and 49 AEs in v1.0 to 26 categories and 790 AEs in v4.0. CRAs independently selected different approaches to AE ascertainment-comprehensive and parsimonious. The number of AEs identified in the parsimonious approach was stable with 10-14 in each CTC version. The comprehensive approach identified 9, 20, 29, and 37 AEs in CTC versions 1.0, 2.0, 3.0, and 4.0, respectively. Only approximately 65% of AEs were conclusively graded in versions 2.0 to 4.0 using the comprehensive approach.</p>

<p><strong>CONCLUSIONS: </strong>CTCAE has increased in complexity. Although this increased complexity allows for more granular AE reporting, these data demonstrate potential unintended negative consequences of increasing CTC AE complexity, including the risk of varying approaches to AE capture. A comprehensive evaluation of CTC AE definitions and CRA reporting practices across COG institutions and AEs are needed to improve the accuracy and efficiency of AE reporting.</p>

10.1002/pbc.27747

Pediatr Blood Cancer

30968531