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Efficacy of Bright Light Treatment, Fluoxetine, and the Combination in Patients With Nonseasonal Major Depressive Disorder

2015· article· en· W2179425605 on OpenAlexafffund
Raymond W. Lam, Anthony Levitt, Robert D. Levitan, Erin E. Michalak, Amy Cheung, Rachel Morehouse, Rajamannar Ramasubbu, Lakshmi N. Yatham, Edwin M. Tam

Bibliographic record

VenueJAMA Psychiatry · 2015
Typearticle
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsUniversity of CalgaryDalhousie UniversityUniversity of TorontoCentre for Addiction and Mental HealthSunnybrook Health Science CentreSaint John Regional HospitalHealth Sciences CentreUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsFluoxetinePlaceboLight therapyMajor depressive disorderRandomized controlled trialInternal medicineMedicineAntidepressantPsychiatryPsychologyMoodCircadian rhythm

Abstract

fetched live from OpenAlex

IMPORTANCE: Bright light therapy is an evidence-based treatment for seasonal depression, but there is limited evidence for its efficacy in nonseasonal major depressive disorder (MDD). OBJECTIVE: To determine the efficacy of light treatment, in monotherapy and in combination with fluoxetine hydrochloride, compared with a sham-placebo condition in adults with nonseasonal MDD. DESIGN, SETTING, AND PARTICIPANTS: Randomized, double-blind, placebo- and sham-controlled, 8-week trial in adults (aged 19-60 years) with MDD of at least moderate severity in outpatient psychiatry clinics in academic medical centers. Data were collected from October 7, 2009, to March 11, 2014. Analysis was based on modified intent to treat (randomized patients with ≥1 follow-up rating). INTERVENTIONS: Patients were randomly assigned to (1) light monotherapy (active 10,000-lux fluorescent white light box for 30 min/d in the early morning plus placebo pill); (2) antidepressant monotherapy (inactive negative ion generator for 30 min/d plus fluoxetine hydrochloride, 20 mg/d); (3) combination light and antidepressant; or (4) placebo (inactive negative ion generator plus placebo pill). MAIN OUTCOMES AND MEASURES: Change score on the Montgomery-Åsberg Depression Rating Scale (MADRS) from baseline to the 8-week end point. Secondary outcomes included response (≥50% reduction in MADRS score) and remission (MADRS score ≤10 at end point). RESULTS: A total of 122 patients were randomized (light monotherapy, 32; fluoxetine monotherapy, 31; combination therapy, 29; placebo, 30). The mean (SD) changes in MADRS score for the light, fluoxetine, combination, and placebo groups were 13.4 (7.5), 8.8 (9.9), 16.9 (9.2), and 6.5 (9.6), respectively. The combination (effect size [d] = 1.11; 95% CI, 0.54 to 1.64) and light monotherapy (d = 0.80; 95% CI, 0.28 to 1.31) were significantly superior to placebo in the MADRS change score, but fluoxetine monotherapy (d = 0.24; 95% CI, -0.27 to 0.74) was not superior to placebo. For the respective placebo, fluoxetine, light, and combination groups at the end point, response was achieved by 10 (33.3%), 9 (29.0%), 16 (50.0%), and 22 (75.9%) and remission was achieved by 9 (30.0%), 6 (19.4%), 14 (43.8%), and 17 (58.6%). Combination therapy was superior to placebo in MADRS response (β = 1.70; df = 1; P = .005) and remission (β = 1.33; df = 1; P = .02), with numbers needed to treat of 2.4 (95% CI, 1.6 to 5.8) and 3.5 (95% CI, 2.0 to 29.9), respectively. All treatments were generally well tolerated, with few significant differences in treatment-emergent adverse events. CONCLUSIONS AND RELEVANCE: Bright light treatment, both as monotherapy and in combination with fluoxetine, was efficacious and well tolerated in the treatment of adults with nonseasonal MDD. The combination treatment had the most consistent effects. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00958204.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.225
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations271
Published2015
Admission routes2
Has abstractyes

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