Evidence map›Paper›PMID 22792005›Full record

ArticleJournal of pain research2012

Predictors of duloxetine adherence and persistence in patients with fibromyalgia.

Zhanglin Cui, Yang Zhao, Diego Novick, Douglas Faries

Abstract read
In one paragraph

Article in Journal of pain research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Zhanglin CuiEli Lilly and Company, Indianapolis, IN, USA.
Yang Zhao
Diego Novick
Douglas Faries

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesAdherence to medication for the treatment of fibromyalgia (FM) is predictive of lower overall health-care costs, and thus a lower burden on both patients and providers. The objectives of this study were to examine the predictors of adherence to and persistence with duloxetine therapy among commercially insured FM patients, and to identify subgroups of patients with high duloxetine persistence and adherence. STUDY

designThis cross-sectional, retrospective study analyzed medical and pharmacy records over 1 year for patients in the US aged 18-64 years with FM who initiated (no prior 90-day use) duloxetine treatment in 2008.

methodsAdherence to duloxetine was measured by medication possession ratio (MPR), with high adherence defined as MPR ≥ 0.8. Persistence was defined as the duration of therapy from the index date to the earliest of: the ending date of the last prescription, the date of the first gap of >15 days between prescriptions, or the end of the study period (12 months). Demographic and clinical predictors of adherence were examined via multiple logistic regression (MLR), and subgroups of duloxetine-persistent and -adherent patients were identified using classification and regression trees (CART).

resultsAmong 4660 duloxetine patients, 33% achieved high adherence. Factors associated with high adherence from MLR included older age, North Central and Northeast regions, prior venlafaxine, pregabalin, selective serotonin reuptake inhibitor (SSRI), or other antidepressant use, or comorbid dyslipidemia or osteoarthritis (all P < 0.05). CART analysis revealed that patients with prior antidepressant use, aged ≥46, or prior osteoarthritis had higher MPR (all P < 0.05), and patients aged ≥45 with a history of SSRI, venlafaxine, or anticonvulsant use had longer duration of therapy (all P < 0.05).

conclusionsPatients with high adherence to and persistence with duloxetine were significantly older and had prior antidepressant use.

Indexed as

duloxetinefibromyalgiamedication adherencemedication persistencesubgroup analysis

Identifiers

PMID22792005
PMCPMC3392711

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.