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Developing an individualized treatment rule for Veterans with major depressive disorder using electronic health records.
Zainal, Nur Hani; Bossarte, Robert M; Gildea, Sarah M; Hwang, Irving; Kennedy, Chris J; Liu, Howard; Luedtke, Alex; Marx, Brian P; Petukhova, Maria V; Post, Edward P; Ross, Eric L; Sampson, Nancy A; Sverdrup, Erik; Turner, Brett; Wager, Stefan; Kessler, Ronald C.
Afiliação
  • Zainal NH; Department of Health Care Policy, Harvard Medical School, Boston, MA, USA.
  • Bossarte RM; Department of Psychiatry and Behavioral Neurosciences, University of South Florida, Tampa, FL, USA.
  • Gildea SM; Department of Health Care Policy, Harvard Medical School, Boston, MA, USA.
  • Hwang I; Department of Health Care Policy, Harvard Medical School, Boston, MA, USA.
  • Kennedy CJ; Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
  • Liu H; Department of Health Care Policy, Harvard Medical School, Boston, MA, USA.
  • Luedtke A; Center of Excellence for Suicide Prevention, Canandaigua VA Medical Center, Canandaigua, NY, USA.
  • Marx BP; Department of Statistics, University of Washington, Seattle, WA, USA.
  • Petukhova MV; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Post EP; National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA.
  • Ross EL; Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA.
  • Sampson NA; Department of Health Care Policy, Harvard Medical School, Boston, MA, USA.
  • Sverdrup E; Center for Clinical Management Research, VA Ann Arbor Health Care System, Ann Arbor, MI, USA.
  • Turner B; Department of Medicine, University of Michigan Medical School, Ann Arbor, MI, USA.
  • Wager S; Department of Psychiatry, Larner College of Medicine, University of Vermont, Burlington, VT, USA.
  • Kessler RC; Department of Health Care Policy, Harvard Medical School, Boston, MA, USA.
Mol Psychiatry ; 29(8): 2335-2345, 2024 Aug.
Article em En | MEDLINE | ID: mdl-38486050
ABSTRACT
Efforts to develop an individualized treatment rule (ITR) to optimize major depressive disorder (MDD) treatment with antidepressant medication (ADM), psychotherapy, or combined ADM-psychotherapy have been hampered by small samples, small predictor sets, and suboptimal analysis methods. Analyses of large administrative databases designed to approximate experiments followed iteratively by pragmatic trials hold promise for resolving these problems. The current report presents a proof-of-concept study using electronic health records (EHR) of n = 43,470 outpatients beginning MDD treatment in Veterans Health Administration Primary Care Mental Health Integration (PC-MHI) clinics, which offer access not only to ADMs but also psychotherapy and combined ADM-psychotherapy. EHR and geospatial databases were used to generate an extensive baseline predictor set (5,865 variables). The outcome was a composite measure of at least one serious negative event (suicide attempt, psychiatric emergency department visit, psychiatric hospitalization, suicide death) over the next 12 months. Best-practices methods were used to adjust for nonrandom treatment assignment and to estimate a preliminary ITR in a 70% training sample and to evaluate the ITR in the 30% test sample. Statistically significant aggregate variation was found in overall probability of the outcome related to baseline predictors (AU-ROC = 0.68, S.E. = 0.01), with test sample outcome prevalence of 32.6% among the 5% of patients having highest predicted risk compared to 7.1% in the remainder of the test sample. The ITR found that psychotherapy-only was the optimal treatment for 56.0% of patients (roughly 20% lower risk of the outcome than if receiving one of the other treatments) and that treatment type was unrelated to outcome risk among other patients. Change in aggregate treatment costs of implementing this ITR would be negligible, as 16.1% fewer patients would be prescribed ADMs and 2.9% more would receive psychotherapy. A pragmatic trial would be needed to confirm the accuracy of the ITR.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Psicoterapia / Veteranos / Transtorno Depressivo Maior / Medicina de Precisão / Registros Eletrônicos de Saúde / Antidepressivos Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Psicoterapia / Veteranos / Transtorno Depressivo Maior / Medicina de Precisão / Registros Eletrônicos de Saúde / Antidepressivos Idioma: En Ano de publicação: 2024 Tipo de documento: Article