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Record W4406588954 · doi:10.1007/s40801-024-00478-3

Mental Health-Related Disability Days and Costs Among Patients with Treatment-Resistant Depression Initiated on Esketamine Nasal Spray and Conventional Therapies in the USA

2025· article· en· W4406588954 on OpenAlexaff
Manish K. Jha, Maryia Zhdanava, Aditi Shah, Arthur Voegel, Anabelle Tardif‐Samson, Dominic Pilon, Kruti Joshi

Bibliographic record

VenueDrugs - Real World Outcomes · 2025
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsGroup for Research in Decision Analysis
FundersJanssen Scientific Affairs
KeywordsNasal sprayDepression (economics)Treatment-resistant depressionMedicineMental healthPsychiatryNasal administrationMajor depressive disorderPharmacologyCognition

Abstract

fetched live from OpenAlex

Treatment-resistant depression (TRD) is related to disproportionate unemployment and productivity burden in the USA. The current study describes real-world mental health (MH)-related disability days and costs of patients with TRD initiated on esketamine nasal spray or conventional therapies in the USA. Adults with TRD were selected from Merative™ MarketScan ® Commercial database (from January 2016 to January 2023) and classified into four cohorts (esketamine, ECT [electroconvulsive therapy], TMS [transcranial magnetic stimulation], and SGA [second-generation antipsychotics] augmentation) based on therapy initiated (index date) on/after 5 March 2019 (esketamine approval date for TRD). Patients had ≥ 12 months of health plan eligibility pre-index date and disability information available pre- and post-index in the Merative™ MarketScan ® Health and Productivity Management database (from January 2016 to December 2021). MH-related disability days (i.e., short- or long-term) and associated costs (US dollars [USD] 2022) were reported per-patient-per-month for the 6 months pre- and post-index. The study comprised four cohorts: esketamine ( n = 107; mean age: 45.5 years, female: 54.2%), ECT ( n = 55; mean age: 47.6 years, female: 41.8%), TMS ( n = 443; mean age: 46.1 years, female: 57.3%), and SGA ( n = 4374; mean age: 44.8 years, female: 59.1%). In month 6 pre-index, mean number of MH-related disability days was 1.7 in the esketamine cohort, 1.2 in the TMS cohort, 1.3 in the ECT cohort, and 0.8 in the SGA augmentation cohort; mean MH-related disability costs were US $443 in the esketamine cohort, US $339 in the TMS cohort, US $178 in the ECT cohort, and US $143 in the SGA augmentation cohort. In all cohorts, a peak in mean MH-related disability days and costs was observed 1 month after therapy initiation followed by a decreasing trend. In month 6 post-index versus month 6 pre-index, the mean number of MH-related disability days trended lower in the esketamine cohort (− 0.4 days), remained the same in the TMS cohort and largely the same in the SGA augmentation cohort (+ 0.1 days), and trended higher (+ 1.6 days) in the ECT cohort. In the same timeframe, MH-related disability costs trended lower in the esketamine and TMS cohorts, with observed reductions of US $312 and US $123, respectively. Costs remained largely the same in the SGA augmentation cohort (+ US $26), and trended higher (+ US $353) in the ECT cohort. In this descriptive study, initiation of esketamine was associated with trends toward lower MH-related disability days and costs. Conventional therapies demonstrated varied patterns, with no consistent trend toward reductions in disability days across all therapies and no observed cost-savings trends for SGA augmentation and ECT. These trends suggest potential economic and societal gains of esketamine treatment for TRD but warrant further investigation with larger samples and robust statistical comparisons.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.014
GPT teacher head0.300
Teacher spread0.286 · 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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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