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Antidepressant Response Trajectories and Associated Clinical Prognostic Factors Among Older Adults

2015· article· en· W1531988994 on OpenAlexaff
Stephen F. Smagula, Meryl A. Butters, Stewart Anderson, Eric J. Lenze, Mary Amanda Dew, Benoit H. Mulsant, Francis E. Lotrich, Howard Aizenstein, Charles F. Reynolds

Bibliographic record

VenueJAMA Psychiatry · 2015
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Center for Advancing Translational SciencesNational Institute of Mental HealthNational Institute on Aging
KeywordsVenlafaxineLate life depressionMajor depressive disorderDepression (economics)Rating scaleAntidepressantMedicinePsychologyLongitudinal studyInternal medicineTreatment-resistant depressionPsychiatryCognitionAnxiety

Abstract

fetched live from OpenAlex

IMPORTANCE: More than 50% of older adults with late-life major depressive disorder fail to respond to initial treatment with first-line pharmacological therapy. OBJECTIVES: To assess typical patterns of response to an open-label trial of extended-release venlafaxine hydrochloride (venlafaxine XR) for late-life depression and to evaluate which clinical factors are associated with the identified longitudinal response patterns. DESIGN, SETTING, AND PARTICIPANTS: Group-based trajectory modeling was applied to data from a 12-week open-label pharmacological trial conducted in specialty care as part of the Incomplete Response in Late Life: Getting to Remission Study. Clinical prognostic factors, including domain-specific cognitive performance and individual depression symptoms, were examined in relation to response trajectories. Participants included 453 adults aged 60 years or older with current major depressive disorder. The study was conducted between August 2009 and August 2014. INTERVENTION: Open-label venlafaxine XR (titrated up to 300 mg/d) for 12 weeks. MAIN OUTCOMES AND MEASURES: Subgroups exhibiting similar response patterns were derived from repeated measures of overall depression severity obtained using the Montgomery-Asberg Depression Rating Scale. RESULTS: Among the 453 study participants, 3 subgroups with differing baseline depression severity clearly responded to treatment: one group with the lowest baseline severity had a rapid response (n = 69 [15.23%]), and distinct responses were also apparent among groups starting at moderate (n = 108 [23.84%]) and higher (n = 25 [5.52%]) baseline symptom levels. Three subgroups had nonresponding trajectories: 2 with high baseline symptom levels (totaling 35.98%: high, nonresponse 1, n = 110 [24.28%]; high, nonresponse 2, n = 53 [11.70%]) and 1 with moderate baseline symptom levels (n = 88 [19.43%]). Several factors were independently associated with having a nonresponsive trajectory, including greater baseline depression severity, longer episode duration, less subjective sleep loss, more guilt, and more work/activity impairment (P < .05). Higher delayed memory (list recognition) performance was independently associated with having a rapid response (adjusted odds ratio = 2.22; 95% CI, 1.18-4.20). CONCLUSIONS AND RELEVANCE: Based on the observed trajectory patterns, patients who have late-life depression with high baseline depression severity are unlikely to respond after 12 weeks of treatment with venlafaxine XR. However, high baseline depression severity alone may be neither a necessary nor sufficient predictor of treatment nonresponse. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00892047.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.319
Teacher spread0.291 · 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 designObservational
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

Citations73
Published2015
Admission routes1
Has abstractyes

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