Joshua D Rosenblat1, Yena Lee2, Roger S McIntyre3. 1. Resident of Psychiatry, Clinician Scientist Stream, University of Toronto, Toronto, Ontario, Canada,. Electronic address: joshua.rosenblat@utoronto.ca. 2. Graduate Student, University of Toronto, Toronto, Ontario, Canada,. Electronic address: yenalee.lee@mail.utoronto.ca. 3. Head, Mood Disorder Psychopharmacology Unit, University Health Network, Professor of Psychiatry and Pharmacology, University of Toronto, 399 Bathurst Street, MP 9-325, Toronto, Ontario M5T 2S8, Canada,. Electronic address: roger.mcintyre@uhn.ca.
Abstract
BACKGROUND: Pharmacogenomic testing has recently become scalable and available to guide the treatment of major depressive disorder (MDD). The objective of the current meta-analysis was to determine if guidance from pharmacogenomic testing results in relatively higher rates of remission and response compared to treatment as usual (i.e., 'unguided' trial-and-error method) in adults with MDD. METHODS: Article databases were systematically searched from inception to December 2, 2017 for human studies assessing the clinical utility of pharmacogenomics in the acute treatment of MDD. Treatment outcomes in MDD may be defined continuously or categorically (i.e., response/remission). Herein, we delimit our focus on categorical outcomes. Using a random-effects model, data was pooled to determine the risk ratio (RR) of response and remission, respectively, in the pharmacogenomic-guided treatment group compared to the unguided group. RESULTS: Four randomized controlled trials (RCTs) and two open-label, controlled cohort studies were included. The pooled RR for treatment response comparing guided versus unguided treatment was 1.36 (95% confidence interval [CI] = 1.14 to 1.62; p = 0.0006; n = 799) in favour of guided treatment. The pooled RR for remission was 1.74 (95%CI = 1.09 to 2.77; p = 0.02, n = 735) also in favour of guided treatment. Heterogeneity in study results suggest that different genetic tests may variably impact response and remission rates. LIMITATIONS: The available evidence is limited, with significant methodological deficiencies. CONCLUSION: The current analysis provides preliminary support for improved response and remission rates in MDD when treatment is guided by pharmacogenomics.
BACKGROUND: Pharmacogenomic testing has recently become scalable and available to guide the treatment of major depressive disorder (MDD). The objective of the current meta-analysis was to determine if guidance from pharmacogenomic testing results in relatively higher rates of remission and response compared to treatment as usual (i.e., 'unguided' trial-and-error method) in adults with MDD. METHODS: Article databases were systematically searched from inception to December 2, 2017 for human studies assessing the clinical utility of pharmacogenomics in the acute treatment of MDD. Treatment outcomes in MDD may be defined continuously or categorically (i.e., response/remission). Herein, we delimit our focus on categorical outcomes. Using a random-effects model, data was pooled to determine the risk ratio (RR) of response and remission, respectively, in the pharmacogenomic-guided treatment group compared to the unguided group. RESULTS: Four randomized controlled trials (RCTs) and two open-label, controlled cohort studies were included. The pooled RR for treatment response comparing guided versus unguided treatment was 1.36 (95% confidence interval [CI] = 1.14 to 1.62; p = 0.0006; n = 799) in favour of guided treatment. The pooled RR for remission was 1.74 (95%CI = 1.09 to 2.77; p = 0.02, n = 735) also in favour of guided treatment. Heterogeneity in study results suggest that different genetic tests may variably impact response and remission rates. LIMITATIONS: The available evidence is limited, with significant methodological deficiencies. CONCLUSION: The current analysis provides preliminary support for improved response and remission rates in MDD when treatment is guided by pharmacogenomics.
Authors: Abdullah Al Maruf; Mikayla Fan; Paul D Arnold; Daniel J Müller; Katherine J Aitchison; Chad A Bousman Journal: Can J Psychiatry Date: 2020-02-17 Impact factor: 4.356
Authors: Marin Veldic; Ahmed T Ahmed; Caren J Blacker; Jennifer R Geske; Joanna M Biernacka; Kristin L Borreggine; Katherine M Moore; Miguel L Prieto; Jennifer L Vande Voort; Paul E Croarkin; Astrid A Hoberg; Simon Kung; Renato D Alarcon; Nicola Keeth; Balwinder Singh; William V Bobo; Mark A Frye Journal: Front Pharmacol Date: 2019-02-19 Impact factor: 5.810
Authors: Benjamin Laplace; Benjamin Calvet; Aurelie Lacroix; Stephane Mouchabac; Nicolas Picard; Murielle Girard; Eric Charles Journal: J Pers Med Date: 2021-05-21