Adherence and Persistence with Drug Therapy among Fibromyalgia Patients: Data from a Large Health Maintenance Organization
Bibliographic record
Abstract
OBJECTIVE: To assess 1-year persistence and adherence rates with drug therapy among patients with fibromyalgia (FM) and to identify factors associated with therapy discontinuation. METHODS: This retrospective, cohort study included members ≥ 21 years old from the Maccabi Healthcare Services, a large health maintenance organization in Israel, who were diagnosed with FM from 2008 through 2011. Medications of interest included the anticonvulsant pregabalin, antidepressants [selective serotonin reuptake inhibitor (SSRI), serotonin/norepinephrine reuptake inhibitor (SNRI)], and tricyclic antidepressants (TCA). Time to treatment discontinuation and proportion of days covered (PDC) with FM-specific therapies during the year from first dispensed were analyzed. PDC < 20% was considered low adherence and PDC ≥ 80% was considered high adherence. Logistic regression models were constructed for multivariable analyses. RESULTS: Overall, 3932 patients with FM were included; 88.7% were female. Pre-diagnosis use of medication of interest was documented in 41% of the study population. Of the remaining 2312 patients, 56.1% were issued a prescription, 45.0% were dispensed at least 1 medication in the year following diagnosis, and only 28.8% had prescriptions filled twice within the first year from diagnosis. Among newly prescribed patients, 1-year discontinuation was highest for TCA (91.0%) and lowest for SSRI/SNRI antidepressants (73.7%). Over half of the patients (60.5%) had fewer than 20% of the days covered by any medication during the year and only 9.3% were very adherent (PDC ≥ 80%). CONCLUSION: This study clearly shows that in an Israeli "real-life" population of patients with FM, persistence and adherence with FM therapy in the year following diagnosis is remarkably low.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".