How effective is algorithm-guided treatment for depressed inpatients? results from the randomized controlled multicenter German algorithm project 3 trial

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Mazda Adli - , Charité – Universitätsmedizin Berlin, Center for Psychiatry, Psychotherapy and Psychosomatic Medicine (Autor:in)
  • Katja Wiethoff - , Charité – Universitätsmedizin Berlin (Autor:in)
  • Thomas C. Baghai - , Charité – Universitätsmedizin Berlin, Universität Regensburg (Autor:in)
  • Robert Fisher - , East London NHS Foundation Trust (Autor:in)
  • Florian Seemüller - , kbo-Lech-Mangfall-Klinik, Garmisch-Partenkirchen gGmbH (Autor:in)
  • Gregor Laakmann - , Ludwig-Maximilians-Universität München (LMU) (Autor:in)
  • Peter Brieger - , kbo-Isar-Amper-Klinikum München gGmbH (Autor:in)
  • Joachim Cordes - , Heinrich Heine Universität Düsseldorf (Autor:in)
  • Jaroslav Malevani - , Heinrich Heine Universität Düsseldorf (Autor:in)
  • Gerd Laux - , InnKlinikum (Altötting, Mühldorf, Burghausen, Haag) (Autor:in)
  • Iris Hauth - , St. Joseph Krankenhaus Berlin Tempelhof (Autor:in)
  • Hans Jürgen Möller - , Ludwig-Maximilians-Universität München (LMU) (Autor:in)
  • Klaus Thomas Kronmüller - , LWL-Klinikum Gütersloh (Autor:in)
  • Michael N. Smolka - , Klinik und Poliklinik für Psychiatrie und Psychotherapie (Autor:in)
  • Peter Schlattmann - , Friedrich-Schiller-Universität Jena (Autor:in)
  • Maximilian Berger - , Heinrich Heine Universität Düsseldorf (Autor:in)
  • Roland Ricken - , Charité – Universitätsmedizin Berlin (Autor:in)
  • Thomas J. Stamm - , Charité – Universitätsmedizin Berlin (Autor:in)
  • Andreas Heinz - , Charité – Universitätsmedizin Berlin (Autor:in)
  • Michael Bauer - , Klinik und Poliklinik für Psychiatrie und Psychotherapie (Autor:in)

Abstract

Background: Treatment algorithms are considered as key to improve outcomes by enhancing the quality of care. This is the first randomized controlled study to evaluate the clinical effect of algorithm-guided treatment in inpatients with major depressive disorder.Methods: Inpatients, aged 18 to 70 years with major depressive disorder from 10 German psychiatric departments were randomized to 5 different treatment arms (from 2000 to 2005), 3 of which were standardized stepwise drug treatment algorithms (ALGO). The fourth arm proposed medications and provided less specific recommendations based on a computerized documentation and expert system (CDES), the fifth arm received treatment as usual (TAU). ALGO included 3 different second-step strategies: Lithium augmentation (ALGO LA), antidepressant dose-escalation (ALGO DE), and switch to a different antidepressant (ALGO SW). Time to remission (21-item Hamilton Depression Rating Scale .9) was the primary outcome. Results: Time to remission was significantly shorter for ALGO DE (n = 91) compared with both TAU (n = 84) (HR = 1.67; P = .014) and CDES (n = 79) (HR = 1.59; P = .031) and ALGO SW (n = 89) compared with both TAU (HR = 1.64; P = .018) and CDES (HR = 1.56; P = .038). For both ALGO LA (n = 86) and ALGO DE, fewer antidepressant medications were needed to achieve remission than for CDES or TAU (P < .001). Remission rates at discharge differed across groups; ALGO DE had the highest (89.2%) and TAU the lowest rates (66.2%). Conclusions: A highly structured algorithm-guided treatment is associated with shorter times and fewer medication changes to achieve remission with depressed inpatients than treatment as usual or computerized medication choice guidance.

Details

OriginalspracheEnglisch
Seiten (von - bis)721-730
Seitenumfang10
FachzeitschriftInternational journal of neuropsychopharmacology
Jahrgang20
Ausgabenummer9
PublikationsstatusVeröffentlicht - 1 Sept. 2017
Peer-Review-StatusJa

Externe IDs

PubMed 28645191
ORCID /0000-0002-2666-859X/work/161890536
ORCID /0000-0001-5398-5569/work/161890773

Schlagworte

Schlagwörter

  • Antidepressants, German Algorithm Project, Medical Decision Making, Treatment Algorithms, Treatment-Resistant Depression