Utility of Candidate Genes From an Algorithm Designed to Predict Genetic Risk for Opioid Use Disorder

JAMA Network Open, Journal Year: 2025, Volume and Issue: 8(1), P. e2453913 - e2453913

Published: Jan. 9, 2025

Importance Recently, the US Food and Drug Administration gave premarketing approval to an algorithm based on its purported ability identify individuals at genetic risk for opioid use disorder (OUD). However, clinical utility of candidate variants included in has not been independently demonstrated. Objective To assess 15 from intended predict OUD risk. Design, Setting, Participants This case-control study examined association with using electronic health record data December 20, 1992, September 30, 2022. Electronic data, including pharmacy records, were accrued participants Million Veteran Program across exposure (n = 452 664). Cases identified International Classification Diseases, Ninth Revision , or Tenth diagnostic codes, controls no diagnosis. Exposures Number alleles present variants. Main Outcome Measures Performance identifying assessed via logistic regression machine learning models. Results A total 664 (including 33 669 OUD) had a mean (SD) age 61.15 (13.37) years, 90.46% male; sample was ancestrally diverse (with genetically inferred European, African, admixed American ancestries). Using Nagelkerke R 2 collectively, genes accounted 0.40% variation In comparison, sex alone 3.27% variation. The ensemble learning. model as predictive factors correctly classified 52.83% (95% CI, 52.07%-53.59%) independent testing sample. Conclusions Relevance this suggest that approved do meet reasonable standards efficacy Given algorithm’s limited accuracy, care would lead high rates both false-positive false-negative findings. More clinically useful models are needed developing OUD.

Language: Английский

---

Response to the SAMHSA Clinical Advisory: Considerations for Genetic Testing in the Assessment of Substance Use Disorder Risk

Substance Abuse and Rehabilitation, Journal Year: 2025, Volume and Issue: Volume 16, P. 23 - 26

Published: Jan. 1, 2025

Language: Английский

---

The Police Opioid Seizure Temporal Risk (POSTeR) model of increased exposure to fatal overdose

International Journal of Drug Policy, Journal Year: 2025, Volume and Issue: 139, P. 104789 - 104789

Published: April 10, 2025

Language: Английский

---

Deriving a PolyeXposure Score for Substance Use Onset in Adolescents Using the Adolescent Brain Cognitive Development Study

Published: Jan. 1, 2025

Language: Английский

---

Candidate Genes from an FDA-Approved Algorithm Fail to Predict Opioid Use Disorder Risk in Over 450,000 Veterans

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: May 16, 2024

Abstract Importance Recently, the Food and Drug Administration gave pre-marketing approval to algorithm based on its purported ability identify genetic risk for opioid use disorder. However, clinical utility of candidate genes comprising has not been independently demonstrated. Objective To assess 15 variants in from an intended predict disorder risk. Design This case-control study examined association with using available electronic health record data December 20, 1992 September 30, 2022. Setting Electronic data, including pharmacy records, Million Veteran Program participants across United States. Participants were opioid-exposed individuals enrolled (n = 452,664). Opioid cases identified International Classification Disease diagnostic codes, controls no diagnosis. Exposures Number alleles present variants. Main Outcome Measures Predictive performance assessed via logistic regression machine learning models. Results exposed (n=33,669 cases) average 61.15 (SD 13.37) years old, 90.46% male, had varied similarity global reference panels. Collectively, accounted 0.4% variation The accuracy ensemble model as predictors was 52.8% (95% CI 52.1 - 53.6%) independent testing sample. Conclusions Relevance Candidate that comprise approved do meet reasonable standards efficacy predicting Given algorithm’s limited predictive accuracy, care would lead high rates false positive negative findings. More clinically useful models are needed at developing Key Points Question How well designed disorder, which recently received by Administration, perform a large, sample? Findings In over 450,000 individuals, collectively this sample, SNPs predicted level near random chance (52.8%). Meaning assessing

Language: Английский

---

Genes in context: path to more precise risk prediction in psychiatry?

The British Journal of Psychiatry, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 2

Published: Oct. 18, 2024

This guest editorial describes the importance of converging genetics and psychosocial epidemiology research methods to understand biopsychosocial etiology psychiatric phenotypes.

Language: Английский

---

Year 2024 in review - Acute pain management

Anesteziologie a intenzivní medicína, Journal Year: 2024, Volume and Issue: 35(5), P. 329 - 335

Published: Dec. 19, 2024

Článek přináší vybraný přehled prací a témat, která byla v oblasti léčby akutní bolesti publikována za posledních zhruba 14 měsíců. Věnuje se novinkám systémové analgezii, postupech vybraným mezinárodním doporučením.

---