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Comparison of Amitriptyline and US Food and Drug Administration–Approved Treatments for Fibromyalgia

2022· review· en· W4280507539 on OpenAlexaff
H Farag, Ismaeel Yunusa, Hardik Goswami, Ihtisham Sultan, Joanne Doucette, Tewodros Eguale

Bibliographic record

VenueJAMA Network Open · 2022
Typereview
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsDuloxetinePregabalinFibromyalgiaMedicineAmitriptylineMilnacipranRandomized controlled trialInternal medicineAdverse effectDiscontinuationPharmacologyAnesthesiaAntidepressantAlternative medicine

Abstract

fetched live from OpenAlex

Importance: Amitriptyline is an established medication used off-label for the treatment of fibromyalgia, but pregabalin, duloxetine, and milnacipran are the only pharmacological agents approved by the US Food and Drug Administration (FDA) to treat fibromyalgia. Objective: To investigate the comparative effectiveness and acceptability associated with pharmacological treatment options for fibromyalgia. Data Sources: Searches of PubMed/MEDLINE, Cochrane Library, Embase, and Clinicaltrials.gov were conducted on November 20, 2018, and updated on July 29, 2020. Study Selection: Randomized clinical trials (RCTs) comparing amitriptyline or any FDA-approved doses of investigated drugs. Data Extraction and Synthesis: This study follows the Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline. Four independent reviewers extracted data using a standardized data extraction sheet and assessed quality of RCTs. A random-effects bayesian network meta-analysis (NMA) was conducted. Data were analyzed from August 2020 to January 2021. Main Outcomes and Measures: Comparative effectiveness and acceptability (defined as discontinuation of treatment owing to adverse drug reactions) associated with amitriptyline (off-label), pregabalin, duloxetine, and milnacipran (on-label) in reducing fibromyalgia symptoms. The following doses were compared: 60-mg and 120-mg duloxetine; 150-mg, 300-mg, 450-mg, and 600-mg pregabalin; 100-mg and 200-mg milnacipran; and amitriptyline. Effect sizes are reported as standardized mean differences (SMDs) for continuous outcomes and odds ratios (ORs) for dichotomous outcomes with 95% credible intervals (95% CrIs). Findings were considered statistically significant when the 95% CrI did not include the null value (0 for SMD and 1 for OR). Relative treatment ranking using the surface under the cumulative ranking curve (SUCRA) was also evaluated. Results: A total of 36 studies (11 930 patients) were included. The mean (SD) age of patients was 48.4 (10.4) years, and 11 261 patients (94.4%) were women. Compared with placebo, amitriptyline was associated with reduced sleep disturbances (SMD, -0.97; 95% CrI, -1.10 to -0.83), fatigue (SMD, -0.64; 95% CrI, -0.75 to -0.53), and improved quality of life (SMD, -0.80; 95% CrI, -0.94 to -0.65). Duloxetine 120 mg was associated with the highest improvement in pain (SMD, -0.33; 95% CrI, -0.36 to -0.30) and depression (SMD, -0.25; 95% CrI, -0.32 to -0.17) vs placebo. All treatments were associated with inferior acceptability (higher dropout rate) than placebo, except amitriptyline (OR, 0.78; 95% CrI, 0.31 to 1.66). According to the SUCRA-based relative ranking of treatments, duloxetine 120 mg was associated with higher efficacy for treating pain and depression, while amitriptyline was associated with higher efficacy for improving sleep, fatigue, and overall quality of life. Conclusions and Relevance: These findings suggest that clinicians should consider how treatments could be tailored to individual symptoms, weighing the benefits and acceptability, when prescribing medications to patients with fibromyalgia.

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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)0.026
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.026
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.061
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.019
Bibliometrics0.0040.004
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.118
GPT teacher head0.422
Teacher spread0.304 · 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 designNot applicable
Domainnot available
GenreReview

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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Citations77
Published2022
Admission routes1
Has abstractyes

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