Evidence map›Paper›PMID 27574743›Full record

ArticleJournal of managed care & specialty pharmacy2016

Proximal Predictors of Long-Term Discontinuance with Noninsulin Antihyperglycemic Agents.

Bruce C Stuart, Xian Shen, Charlene C Quinn, Nicole Brandt, Pamela Roberto, F Ellen Loh, Franklin Hendrick, Caroline Kim, Xingyue Huang, Swapnil Rajpathak

Open access · bronzeAbstract read
In one paragraph

Article in Journal of managed care & specialty pharmacy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

10 authors at 1 institution in 1 country.

Bruce C Stuart1 University of Maryland School of Pharmacy, Baltimore, Maryland.
Xian Shen1 University of Maryland School of Pharmacy, Baltimore, Maryland.
Charlene C Quinn2 University of Maryland School of Medicine, Baltimore, Maryland.
Nicole Brandt1 University of Maryland School of Pharmacy, Baltimore, Maryland.
Pamela Roberto3 Pharmaceutical Research and Manufacturers of America, Washington, DC, and University of Maryland School of Pharmacy, Baltimore, Maryland.
F Ellen Loh1 University of Maryland School of Pharmacy, Baltimore, Maryland.
Franklin Hendrick1 University of Maryland School of Pharmacy, Baltimore, Maryland.
Caroline Kim1 University of Maryland School of Pharmacy, Baltimore, Maryland.
Xingyue Huang4 Merck Research Labs, Merck & Co., Kenilworth, New Jersey.
Swapnil Rajpathak4 Merck Research Labs, Merck & Co., Kenilworth, New Jersey.
University of Maryland, Baltimore · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNoninsulin antihyperglycemic agents (NAAs) are the mainstay of treatment for type 2 diabetes, yet persistence in NAA use is suboptimal in many diabetes patients. Most of the research on NAA discontinuance has focused on sociodemographic characteristics and general health status, but such factors are inherently limited in explaining dynamic events such as discontinuance.

objectiveTo assess the relative importance of static and proximal dynamic factors in explaining long-term NAA discontinuance among Medicare beneficiaries with diabetes.

methodsTwo sets of probability models were estimated to predict NAA discontinuance as a function of static variables (age, sex, race, original reason for Medicare entitlement, low-income subsidy and dual Medicare/Medicaid eligibility status, and disease burden) and 21 dynamic factors capturing month-by-month changes in drug use, health status, and use of medical services leading up to discontinuance (defined as month 0) and the previous 4 months (designated months -1 to -4) among 71,619 patients with diabetes enrolled in Medicare Part D plans in 2006-2008.

resultsStatic variables explained just 1.2% of the variance in probability of NAA discontinuance compared with 14% for all variables combined. Key time-related predictors of NAA discontinuance included discontinuation with angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEIs/ARBs) and statins, hypoglycemia, NAA usage gaps, insulin use, and discharge from hospitals and skilled nursing facilities (SNFs). The strongest significant predictors (P < 0.05) of NAA discontinuance were discontinuation with statins and ACEIs/ARBs in month 0 (predicted probabilities of 37% and 34%, respectively). Other variables that significantly increased the probability of NAA discontinuance by 10% or more were hypoglycemia in month 0 (14%) and month -1 (17%), discontinuance with ACEIs/ARBs in months -1 (15%) and -2 (10%), discontinuance with statins in month -1 (13%), and insulin use in month 0 (12%). Experiencing a previous gap in NAA therapy was associated with higher likelihood of discontinuance if the gap occurred in month -2 (10%) or month -4 (6%), but a gap in therapy in month -1 actually reduced the likelihood of discontinuance by 13%. Discharge from a hospital or SNF was consistently associated with higher probabilities of NAA discontinuance ranging between 4% and 10%, with higher probabilities occurring closer to month 0.

conclusionsA cascade of dynamic changes preceding discontinuance with NAA therapy among Medicare Part D enrollees with diabetes was observed between 2006 and 2008. Understanding that lack of persistence in drug use is a dynamic rather than a static phenomenon opens up new avenues for investigating and ultimately improving adherence behavior in the elderly. DISCLOSURES: This study was funded by Merck & Co. Huang and Raipathak are employees of Merck & Co. Brandt reports consultancy and speaker fees from Catapult, Omnicare, RAND, HRSA, CMS, and AGS Beers Criteria. Loh is currently employed at Touro College of Pharmacy. All other authors have no relevant potential conflicts of interest to disclose. Study concept and design were primarily contributed by Stuart, Quinn, and Brandt, along with Shen, Roberto, Hendrick, Huang, and Rajpathak. Shen, Loh, Hendrick, and Kim collected the data, and data interpretation was performed primarily by Stuart, Shen, and Roberto, assisted by Quinn, Brandt, Hendrick, Huang, and Rajpathak. The manuscript was written primarily by Stuart, with assistance from the other authors, and revised by Huang, Rajpathak, and Stuart, with assistance from the other authors.

Indexed as

Medication AdherenceAgedAged, 80 and overCohort StudiesDiabetes Mellitus, Type 2FemaleForecastingHumansHypoglycemic AgentsMaleMedicare Part DTime FactorsUnited StatesHypoglycemic Agents

Identifiers

PMID27574743
PMCPMC10398303
OpenAlexW2516872163

What OpenQuestion holds

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Registered trials

None linked

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.