Evidence map›Paper›PMID 26308221›Full record

ArticleJournal of managed care & specialty pharmacy2015

Treatment Patterns of Anti-Vascular Endothelial Growth Factor and Laser Therapy Among Patients with Diabetic Macular Edema.

Shan Jiang, Jamie C Barner, Chanhyun Park, You-Li Ling

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in Journal of managed care & specialty pharmacy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 3 pooled it
1.7field-weighted citation impact, top 16% of its field
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

11 citing papers in PubMed, 3 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
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  4. Review
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  6. Review of clinical studies and recommendation for a therapeutic flow chart for diabetic macular edema.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2021
    Review
  7. Article
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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 at 1 institution in 1 country.

Shan JiangThe University of Texas at Austin, PHR 3.210B, Mail Code A1930, Austin, TX 78712-0124. jbarner@austin.utexas.edu.
Jamie C Barner
Chanhyun Park
You-Li Ling
Pharmerit (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetic macular edema (DME) is a form of diabetic retinopathy caused by continued leakage from retinal blood vessels. The use of anti-vascular endothelial growth factor (VEGF) injections has gained in popularity in the treatment of DME due to satisfactory efficacy, while laser photocoagulation is still the first-line therapy. Examining anti-VEGF treatment patterns may improve understanding of real-world medication-taking behaviors.

objectivesTo (a) compare demographic and clinical characteristics and treatment patterns of anti-VEGF (bevacizumab, ranibizumab, and pegaptanib) and laser therapies among DME patients and (b) determine predictors of switching and anti-VEGF therapy initiation.

methodsA retrospective cohort analysis was conducted with Texas Medicaid medical and prescription claims (January 1, 2008-December 31, 2012) for patients who were aged 18-63 years, continuously enrolled 1 year pre- and post-index, diagnosed with DME and treated with anti-VEGF or laser therapies. Treatment patterns included treatment frequency and switching between anti-VEGF and laser therapies. Logistic regression and multinomial analysis were used to determine factors associated with switching and initiation of anti-VEGF therapy, while controlling for demographic and clinical characteristics.

resultsDME patients (N = 2,201) were aged 54.7 (SD ± 7.9) years; 63.1% were female; 59.1% were Hispanic; and 10.3% were visually impaired. CCI mean score was 6.5 (SD ± 3.1), and patients were on 2.6 (SD ± 3.3) unique prescription medications. Anti-VEGF users had significantly (P  less than  0.0001) fewer prescriptions compared with laser users (1.9 [SD ± 3.1) vs. 2.8 [SD ± 3.3], respectively). Laser was the most commonly used (84.9%) therapy from 2009 to 2011; however, anti-VEGF use increased from 11.7% in 2009 to 21.8% in 2011 (P  less than  0.0001). Patients received 1.5 (SD ± 0.7) laser surgeries compared with 1.7 (SD ± 1.1) anti-VEGF injections per eye annually. Switching from laser to anti-VEGF injections was 9.7%, while switching from anti-VEGF injections to laser surgery was 42.2%. Patients who switched from anti-VEGF injections to laser surgery were more likely to be Hispanic (OR = 1.415, 95% CI = 1.037-1.930); male (OR = 1.341, 95% CI = 1.053-1.709); have fewer prescriptions (OR = 0.944, 95% CI = 0.905-0.985); and less likely to have no visual impairment (OR = 0.641, 95% CI = 0.449-0.915). Multinomial regression results showed anti-VEGF users were more likely to remain on the same therapy if they had more prescriptions (OR = 1.094, 95% CI = 1.029-1.172) or were female (OR = 1.441, 95% CI = 1.024-2.041). Anti-VEGF initiators had fewer prescriptions (OR = 0.917, 95% CI = 0.868-0.947) and initiated in 2011 vs. 2009 (OR = 2.363, 95% CI = 1.777-3.141).

conclusionsAlthough anti-VEGF use is increasing, laser use is still more prevalent. Over 40% of patients who initiated on anti-VEGF injections switched to laser surgery. Additional research should be conducted to determine factors associated with this high rate of switching.

Indexed as

AdolescentAdultAngiogenesis InhibitorsAptamers, NucleotideBevacizumabCohort StudiesDiabetic RetinopathyFemaleHumansLaser TherapyLogistic ModelsMacular EdemaMaleMiddle AgedRanibizumabRetrospective StudiesAngiogenesis InhibitorsAptamers, NucleotideBevacizumabpegaptanibRanibizumabVascular Endothelial Growth Factor A

Identifiers

PMID26308221
PMCPMC10397800
OpenAlexW2289847121

What OpenQuestion holds

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Registered trials

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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.