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Using genetics to prioritize diagnoses for rheumatology outpatients with inflammatory arthritis.

ABSTRACT: It is challenging to quickly diagnose slowly progressing diseases. To prioritize multiple related diagnoses, we developed G-PROB (Genetic Probability tool) to calculate the probability of different diseases for a patient using genetic risk scores. We tested G-PROB for inflammatory arthritis-causing diseases (rheumatoid arthritis, systemic lupus erythematosus, spondyloarthropathy, psoriatic arthritis, and gout). After validating on simulated data, we tested G-PROB in three cohorts: 1211 patients identified by International Classification of Diseases (ICD) codes within the eMERGE database, 245 patients identified through ICD codes and medical record review within the Partners Biobank, and 243 patients first presenting with unexplained inflammatory arthritis and with final diagnoses by record review within the Partners Biobank. Calibration of G-probabilities with disease status was high, with regression coefficients from 0.90 to 1.08 (1.00 is ideal). G-probabilities discriminated true diagnoses across the three cohorts with pooled areas under the curve (95% CI) of 0.69 (0.67 to 0.71), 0.81 (0.76 to 0.84), and 0.84 (0.81 to 0.86), respectively. For all patients, at least one disease could be ruled out, and in 45% of patients, a likely diagnosis was identified with a 64% positive predictive value. In 35% of cases, the clinician's initial diagnosis was incorrect. Initial clinical diagnosis explained 39% of the variance in final disease, which improved to 51% (P < 0.0001) after adding G-probabilities. Converting genotype information before a clinical visit into an interpretable probability value for five different inflammatory arthritides could potentially be used to improve the diagnostic efficiency of rheumatic diseases in clinical practice.

SUBMITTER: Knevel R

PROVIDER: S-EPMC7341896 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Using genetics to prioritize diagnoses for rheumatology outpatients with inflammatory arthritis.

Knevel Rachel R le Cessie Saskia S Terao Chikashi C CC Slowikowski Kamil K Cui Jing J Huizinga Tom W J TWJ Costenbader Karen H KH Liao Katherine P KP Karlson Elizabeth W EW Raychaudhuri Soumya S

Science translational medicine 20200501 545

It is challenging to quickly diagnose slowly progressing diseases. To prioritize multiple related diagnoses, we developed G-PROB (Genetic Probability tool) to calculate the probability of different diseases for a patient using genetic risk scores. We tested G-PROB for inflammatory arthritis-causing diseases (rheumatoid arthritis, systemic lupus erythematosus, spondyloarthropathy, psoriatic arthritis, and gout). After validating on simulated data, we tested G-PROB in three cohorts: 1211 patients ...[more]

PMID: 32461333

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Project description:BackgroundWe aimed to characterize etanercept (ETN) use in juvenile idiopathic arthritis (JIA) patients enrolled in the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry.MethodsThe CARRA Registry is a convenience cohort of patients with paediatric onset rheumatic diseases, including JIA. JIA patients treated with ETN for whom the month and year of ETN initiation were available were included. Patterns of ETN and methotrexate (MTX) use were categorized as follows: combination therapy (ETN and MTX started concurrently), step-up therapy (MTX started first and ETN added later), switchers (MTX started and then stopped when or before ETN started), MTX add-on (ETN started first and MTX added later), and ETN only (no MTX use). Data were described using parametric and non-parametric statistics as appropriate.ResultsTwo thousand thirty-two of the five thousand six hundred forty-one patients with JIA met inclusion criteria (74% female, median age at diagnosis 6.0 years [interquartile range 2.0, 11.0]. Most patients (66.9%) were treated with a non-biologic disease modifying anti-rheumatic drug (DMARD), primarily MTX, prior to ETN. There was significant variability in patterns of MTX use prior to starting ETN. Step-up therapy was the most common approach. Only 34.0% of persistent oligoarticular JIA patients continued treatment with a non-biologic DMARD 3 months or more after ETN initiation. ETN persistence overall was 66.3, 49.4, and 37.3% at 24, 36 and 48 months respectively. ETN persistence among spondyloarthritis patients (enthesitis related arthritis and psoriatic JIA) varied by MTX initiation pattern, with higher ETN persistence rates in those who initiated combination therapy (68.9%) and switchers/ETN only (73.3%) patients compared to step-up (65.4%) and MTX add-on (51.1%) therapy.ConclusionThis study characterizes contemporary patterns of ETN use in the CARRA Registry. Treatment was largely in keeping with American College of Rheumatology guidelines.

Dataset Information

Using genetics to prioritize diagnoses for rheumatology outpatients with inflammatory arthritis.

Publications

Using genetics to prioritize diagnoses for rheumatology outpatients with inflammatory arthritis.

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