Meta-analyses

Association Between Adherence to Pharmacotherapy and Outcomes in Type 2 Diabetes: A Meta-analysis

  1. Kamlesh Khunti1,2⇑,
  2. Samuel Seidu1,2,
  3. Setor Kunutsor3 and
  4. Melanie Davies1,2
  1. 1Leicester Diabetes Centre, Leicester General Hospital, Leicester, U.K.
  2. 2Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, U.K.
  3. 3School of Clinical Sciences, University of Bristol, Southmead Hospital, Southmead, U.K.
  1. Corresponding author: Kamlesh Khunti, kk22{at}leicester.ac.uk.
Diabetes Care 2017 Nov; 40(11): 1588-1596. https://doi.org/10.2337/dc16-1925

Abstract

OBJECTIVE A previous study suggests an association between poor medication adherence and excess mortality in chronic disease. The purpose of this study was to assess the association between medication adherence and risk of cardiovascular disease (CVD), all-cause mortality, and hospitalization in type 2 diabetes.

RESEARCH DESIGN AND METHODS We conducted an electronic search on many electronic databases from inception to 27 April 2016. We selected randomized controlled trials and case-control and cohort studies reporting on CVD, all-cause mortality, or hospitalization outcomes by adherence in adults with type 2 diabetes. Two reviewers independently screened for eligible studies and extracted outcome data. Pooled relative risks (RRs) were calculated using a random-effects meta-analysis; risk of bias in each of the included studies was assessed using the GRADE approach.

RESULTS Eight observational studies were included (n = 318,125). The mean rate of poor adherence was 37.8% (95% CI 37.6–38.0). Adjusted estimates were provided by five studies only. The RRs of good (≥80%) versus poor adherence to medication were 0.72 (95% CI 0.62–0.82, I2 = 0%, three studies) for all-cause mortality and 0.90 (0.87–0.94, I2 = 63%, seven studies) for hospitalization. No evidence of small study bias was observed. Only one study reported CVD outcomes by adherence.

CONCLUSIONS We identified no trials reporting on outcomes by adherence, suggesting a systematic failure to include this information. Pooled estimates from available observational studies suggest that good medication adherence is associated with reduced risk of all-cause mortality and hospitalization in people with type 2 diabetes, although bias cannot be excluded as an explanation for these findings.

Introduction

Adherence refers to the extent to which patients take their medication regimen as prescribed by their health care provider (1). Pooled data suggest around a quarter of patients are nonadherent, and rates of adherence are higher among patients with acute conditions when compared with chronic conditions (2). Even in the resource-intensive setting of clinical trials, the average adherence rates for trial drugs in chronic disease are between 43 and 78% (3–5). A systematic review of 11 studies in patients with type 2 diabetes remaining on treatment with oral hypoglycemic agents (OHAs) for 6–24 months reported adherence rates of between 36 and 93% (6). Evidence from individual studies suggests that adherence is poorer among patients with depression (7) and multimorbidity (8,9) and those on polytherapy or twice-daily regimens compared with monotherapy and once-daily regimens, respectively (7,10,11).

The increasing global prevalence of type 2 diabetes, driven by rising rates of obesity and population aging (12), accounts for considerable cardiovascular morbidity and mortality. Despite evidence from randomized controlled trials demonstrating reductions in microvascular and macrovascular complications with improved control of glycemia (13–15), achievement of HbA1c goals has been elusive on a population level in Europe and the U.S. (16–18). Based on findings in patients with a range of chronic diseases (1), it is hypothesized that poor adherence, in part, contributes to adverse outcomes and higher health care costs (1). In a meta-analysis of 21 studies including participants across a range of conditions, good adherence was associated with an almost halving of all-cause mortality compared with poor adherence (19). Reports linking suboptimal adherence rates with poor control of modifiable risk factors in previous studies (20,21) suggest that failure to meet targets may be due, in part, to poor adherence. Whether these associations hold true in patients with type 2 diabetes remains unclear and will be important to resolve in order to guide strategies to reduce overall risk and attenuate premature mortality in type 2 diabetes. We conducted a systematic review and meta-analysis of relevant studies to quantify the relationship between medication adherence in type 2 diabetes and incident cardiovascular disease (CVD), all-cause mortality, and all-cause hospitalization.

Research Design and Methods

Study Selection

We sought randomized controlled trials and case-control and cohort studies that determined adherence at baseline and then recorded CVD (defined as fatal CVD, nonfatal myocardial infarction, or ischemic stroke) during follow-up. Data from studies recording cases of all-cause mortality and hospitalization (secondary outcomes) were also extracted. Prespecified inclusion criteria required studies that reported an objective measure of adherence with separate reporting of the primary or secondary outcome(s) among groups with good and poor adherence to antihyperglycemic or cardiovascular drug therapy. In the absence of a gold-standard method for estimation of adherence (22,23), acceptable methods to quantify adherence included pharmacy refill data, pill count, electronic drug monitoring systems, and self-reported measures in questionnaire or patient diaries. A threshold of 80% was used to define good adherence, the level at which patients have generally been categorized as adherent in the literature and trials outside those treating patients with HIV (1,24).

We searched electronic databases without language restrictions (AMED, CINAHL, Embase, ERIC, HealthSTAR, Medline, PsycINFO, and Web of Science) from inception date to 27 April 2016. Both medical subject heading (MeSH) and keywords were used to search for terms related to type 2 diabetes, adherence, CVD, mortality, and hospitalization (Supplementary Fig. 1). We supplemented the search by examining reference lists of included studies, reviews (1,24), and meta-analyses (6,19).

Information on the following variables was independently obtained by two contributors: study design, study location, study size, measure of adherence, patient characteristics, and absolute event rates. Any conflicts were resolved by the lead author. Where studies reported duplicate data, the most recent report from the same cohort was used to reflect contemporary practice and increase power. This meta-analysis was conducted according to the protocol registered with PROSPERO (registration no. CRD42016041380) and in accordance with PRISMA and MOOSE guidelines (25,26) (Supplementary Tables 1 and 2).

Statistical Analysis

Where available, summary characteristics of subjects with good and poor adherence are presented as mean values weighted by study size. The relative risks (RRs) and 95% CIs for good versus poor adherence to medication were calculated for CVD, all-cause mortality, and all-cause hospitalization based on observed data for individual studies. Study-specific estimates were pooled using a random-effects meta-analysis with the DerSimonian and Laird method (27). A random-effects approach was taken in response to between-study heterogeneity anticipated in the effect size. Statistical heterogeneity of RR estimates was quantified using the I2 statistic (28). The I2 statistic is a measure of the proportion of total variation in effect size that is due to heterogeneity. Where not directly reported, crude event rates were calculated by dividing the absolute number of events by the total person-years of follow-up. Publication bias was assessed using Begg funnel plots and Egger regression symmetry tests where five or more studies were available for pooled analyses (29,30). Study quality was assessed using the Newcastle-Ottawa Scale for cohort studies, which awards a maximum of 9 points based on categories of selection (4 points), comparability (2 points), and outcome (3 points) (31). The quality of studies with scores of 7–9 was considered “good,” and those with scores between 4 and 6 and <4 as “moderate” and “poor,” respectively. Statistical analyses were two sided with a significance level of 0.05; calculations were performed with Stata release 11 (StataCorp, College Station, TX).

Results

Of 8,175 citations, we identified 105 studies for full-text review. Eight studies published between 2004 and 2015, reporting on 318,125 patients and 461,747 person-years of follow-up, were included in the final analyses (Fig. 1). All eligible studies reported on retrospective cohorts, sourced from a combination of administrative claims data (n = 6) (32–37), diabetes registry data (n = 1) (38), or primary care data sets (n = 1) (39). Observer agreement on which studies were eligible for inclusion was good (Cohen unweighted κ = 0.79). Only one study reported on the primary outcome (CVD) by adherence (32,39), whereas three and seven studies reported on all-cause mortality and all-cause hospitalization, respectively. Table 1 lists the characteristics of the included studies. All studies monitored adherence of antihyperglycemic medications as the exposure variable, with the exception of one study that measured combined adherence of OHAs, antihypertensives, and statins (38). Despite similarities in calculations used to define medication possession ratio and proportion of days covered, disparities exist between how included studies combined measures across different antihyperglycemic medication classes and other cardiovascular medications. A more detailed assessment of methodology used to determine adherence is available in Supplementary Table 3. Sample sizes ranged from 900 to 96,734, and the mean length of follow-up ranged from 12 to 24 months. The proportion of study participants with poor adherence varied from 25 to 91%, with a weighted mean of 37.8% (120,209 of 318,125). Mean quality scores (Newcastle-Ottawa Scale) were 8.0 and 7.1 for studies reporting on all-cause mortality and hospitalization, respectively (Supplementary Table 4).

Figure 1
Figure 1

Study selection. DM, diabetes.

View this table:
Table 1

Characteristics of included studies in the meta-analysis

Table 2 shows the crude event rates by adherence group in each of the included studies, in addition to adjusted estimates provided. The only study to report cardiovascular outcomes by adherence (32) showed a significant reduction in CVD events with good adherence (RR 0.68 [95% CI 0.66–0.71], P < 0.001). During a total of 193,468 person-years of follow-up, there were 10,396 incident cardiovascular events (crude event rate 53.7 per 1,000 person-years). Male sex, increasing age, greater comorbidity burden (Charlson comorbidity index), and high income were all associated with improved levels of adherence.

View this table:
Table 2

Outcomes by adherence of included studies in the meta-analysis

The association between medication adherence and all-cause mortality was reported in three studies involving 75,681 participants, 119,568 person-years of follow-up, and 1,189 deaths (1.6%). The pooled RR from these studies was 0.72 (95% CI 0.62–0.82, P < 0.001) for all-cause mortality when comparing good with poor adherence (Fig. 2). No heterogeneity was observed in the effect size between studies analyzed (I2 = 0.0%, Q statistic P = 0.65). Of three studies included in the pooled estimates for all-cause mortality, the prevalence of poor adherence varied widely. Zhu et al. (39) reported a prevalence of 90.6%, whereas the studies by Ho et al. (38) and Jha et al. (35) reported the prevalence of poor adherence as 21.3 and 24.8%, respectively. The RR after exclusion of the data from the Zhu et al. (39) study was not qualitatively different from the overall estimate presented above (RR 0.71 [95% CI 0.61–0.82]).

Figure 2
Figure 2

Association between medication adherence and all-cause mortality in type 2 diabetes.

Data on all-cause hospitalization were recorded across seven studies involving 221,391 individuals, 265,279 person-years of follow-up, and 46,535 hospitalization events. Good adherence was associated with benefits in reduced hospitalization rates (RR 0.90 [95% CI 0.87–0.94], P < 0.001). Each individual study considered in this analysis reported lower hospitalization rates among a group with good adherence (Fig. 3). Moderate heterogeneity was observed between studies; the I2 was 63.4% and Q statistic P = 0.012. There was no evidence of small study bias, such as publication bias with Egger test for hospitalization (P = 0.61) (Supplementary Fig. 2). Consistent with the analyses for all-cause mortality, two studies included in the pooled estimate for hospitalization reported a prevalence of poor adherence that was high as compared with the other studies. Whereas Zhu et al. (39) and Hong and Kang (33) noted poor adherence in 90.6 and 70.6%, respectively, the remaining studies’ prevalence of poor adherence ranged from 21.3 to 47.5%. Exclusion of these studies from the analysis produced an RR of 0.89 (95% CI 0.88–0.91, P < 0.001). In further subgroup analysis of studies using the medication possession ratio versus percentage of days covered methodology for measuring adherence, no qualitative differences were observed in effect size for all-cause hospitalization (Supplementary Fig. 3).

Figure 3
Figure 3

Association between medication adherence and all-cause hospitalization in type 2 diabetes.

Conclusions

This meta-analysis found that individuals with good adherence had a significant 10% lower rate of hospitalization events and a significant 28% lower rate of all-cause mortality when compared with a group with poor adherence. This study advances the existing literature on the impact of adherence on outcomes in diabetes in several ways. First, our analyses update and extend those of a report examining the association between adherence to drug therapy and mortality across a range of conditions, including HIV, myocardial infarction, heart failure, and hyperlipidemia (19). In that study conducted in 2006, good adherence corresponded with an ∼50% reduction in the risk of mortality when compared with individuals with poor drug compliance. The present meta-analysis provides additional estimates for the association between medication adherence and mortality specific to individuals with type 2 diabetes and adds new information on the risk of hospitalization. Second, another previous systematic review that described the extent of poor adherence among individuals with diabetes receiving OHAs reported adherence rates on a continuous scale that varied between 36 and 93% (6). This study did not evaluate any clinical outcomes, and because we found no information on our prespecified end points stratified by adherence on a continuous scale, our estimates are based on a binary measure of adherence (good vs. poor adherence). Our study goes beyond identifying the prevalence of poor adherence in diabetes by quantifying the association between adherence and clinically meaningful outcomes.

A previous systematic review previously reported on an association between better adherence and improved glycemic control (40). In that study, although better adherence was found to confer reduced health care utilization, this did not translate into reduced health care costs. These findings suggest that a possible explanation for a mortality benefit seen in this study among individuals with good adherence may, in part, relate to improved glycemic control given the established relationship between hyperglycemia and mortality (41). It is important to note that no causal association between adherence and poor outcome has been demonstrated in the current study, and previous work suggests the presence of a healthy adherer effect, whereby adherence to medication may be a proxy marker for good health behavior that reduces overall mortality (19). It was not possible to confirm the healthy adherer effect in our analyses as it relies on the reporting of outcomes among patients with good adherence to placebo therapy, which was not assessed in the observational studies included.

Despite consistent improvements in the quality of care for diabetes in recent decades (18,42), it remains a harbinger of substantial premature mortality. The presence of diabetes is associated with a 1.8-fold increase in the risk of death, and more than half of deaths are attributable to CVD (43). Recent data from the Swedish National Diabetes Register suggest that mortality in type 2 diabetes may be falling (44) as a result of more aggressive treatment with statins and blood pressure medications, in addition to improvements in glycemic control over time. The earlier use of diabetes drug classes with the ability to modify cardiovascular risk beyond glycemia may have a role in further reducing overall mortality; however, their full benefit will only be realized if patients can adhere to the prescribed regimens. Given that patients with type 2 diabetes can expect to take as many as five or more medications daily (45,46), the association between polypharmacy and poor adherence represents an additional challenge in this high-risk population (47,48).

Greater attainment of treatment targets for HbA1c (20,21), blood pressure (49), and LDL cholesterol (38) have all been linked to medication adherence. It is therefore vital that health care professionals can recognize and treat poor adherence. This is particularly relevant in type 2 diabetes where patients require increasingly complex treatment regimens that result from deterioration in glycemia with disease progression and the development of multiple comorbidities. Unfortunately, interventions to improve adherence have been met with mixed results, and those that have achieved success have done so at significant cost and by complex means (50). In a recent update of a Cochrane review on the subject across many conditions, even the most effective interventions did not lead to large improvements in adherence (50). Adherence has been called the “next frontier in quality improvement” (51), and without effective strategies to improve it on a population level, progress in clinical outcomes in type 2 diabetes achieved over recent decades may plateau, in spite of improvements in conventional quality of care indicators and the range of therapies available.

Despite limited success in preventing or delaying complications of type 2 diabetes in high-income countries, the rapid escalation in numbers of those affected in developing countries is of great concern. In developed countries, the burden of diabetes is thought to account for ∼5–14% of health care spending (52,53), yet less than a quarter of this cost is related to the management of diabetes itself; the treatment of complications of the disease accounts for the remaining budget (52). In developing countries, where prevalence is rising most quickly and 80% of diabetes case subjects live (54), expenditure on diabetes as a proportion of total health budget is currently low and the cost of treating complications alone has the potential to absorb a large proportion of existing health care budgets (53). The estimates presented in this study suggest that efforts to improve adherence may help to reduce the frequency of hospitalization in type 2 diabetes, with possible implications for cost savings on a population level. It should be reiterated that our findings do not imply causation; however, it is plausible that efforts to improve adherence may prevent unplanned hospital visits and help to divert resources toward preventive medicine, which should be the cornerstone of any successful public health policy in diabetes.

Our findings add to calls for high quality studies on interventions to improve adherence in type 2 diabetes in clinical practice settings. Further investigation with access to individual participant data is required to establish the mechanisms behind the protective effect of adherence and to guide strategies for improving adherence. In particular, the absence of any clinical trial data in the present analyses suggests a systematic failure to report outcomes in subgroups stratified by adherence. Some 66 studies identified in our search reported on the prevalence of poor adherence or a mean adherence rate but failed to report on outcomes as a function of adherence and were therefore excluded from our analyses. Given the placebo-controlled nature of many clinical trials, an opportunity to study the healthy adherer effect was lost. Unresolved questions relate to whether the improvement in clinical outcomes observed in people with good adherence is due to improved control of modifiable risk, a healthy adherer effect, or other as yet unmeasured factors. Whether good adherence is associated with benefits for the prevention of diabetes-specific complications also merits further consideration, as they carry significant morbidity and mortality and account for a disproportionate share of overall health care expenditure.

A key strength of the current study is the size of included studies. The pooled cohorts for all-cause mortality and hospitalization outcomes involved 119,569 and 265,279 person-years of follow-up, respectively. There are certain limitations with this study. First, and common to all meta-analyses that lack individual participant data, the RRs presented are not adjusted for potential confounding variables. Meta-analyses of crude estimates from observational studies may be subject to residual confounding. We were unable to produce any estimates using adherence on a continuous scale as all included studies reported on outcomes in binary groups (good vs. poor adherence). The cohorts studied differed between, and within, studies in their baseline characteristics. Given the limited number of studies, we were unable to assess the associations by relevant subgroups, including by medication class and other important clinical factors, such as duration of diabetes. Despite conducting a detailed literature search, we found only a single study meeting our eligibility requirements that reported on cardiovascular events separately among groups with good and poor adherence. We were therefore unable to assess the association with adherence beyond its findings. There are a wide range of measures of adherence; the most commonly encountered methods were medication possession ratios and percentage of days covered. The variety of adherence measures is problematic for comparisons across studies, and consensus for a uniform methodology of reporting adherence in clinical trials and observational studies is needed. Although direct measures of adherence that record the level of medication or its metabolite in the blood, for example, are considered more robust than indirect methods such as pill counting, these are not practical in routine clinical practice or for large epidemiological studies. Poor adherence in clinical trials also poses problems for power calculations as an assumed treatment effect may be attenuated by missed doses or persistence failure (55). In the absence of a gold-standard measure and threshold for good adherence, we took a pragmatic approach to define good adherence as 80%, which is common in the literature. Again, individual participant data linking numerical values for adherence with outcome may have yielded greater precision in our estimates. The limited number of studies precluded the ability to investigate the possibility of publication bias in greater detail. Last, with the exception of one study that considered adherence across three classes of medications, all studies reported adherence rates to antihyperglycemic therapy only. In a real-world setting, patients with type 2 diabetes are frequently prescribed a range of medication classes to modify cardiovascular risk, including blood pressure treatments and statins. We were unable to differentiate the impact of adherence to other medications apart from antihyperglycemic agents.

In this meta-analysis, better adherence to medication in adults with type 2 diabetes is associated with reduced rates of all-cause mortality and hospitalization. In conjunction with previous studies, these data should encourage health care professionals to routinely assess adherence in clinical practice and make efforts to improve it where it falls below 80%. In addition, our findings should serve to reinforce to patients the importance of taking medications as prescribed, in order to avoid premature death and preventable admissions to the hospital. We identified no randomized controlled trial reporting on outcomes stratified by adherence, suggesting a systematic failure to publish this important information. Efforts should be made to report on subgroups by adherence where possible in the clinical trial setting. Finally, high quality studies examining the effectiveness of interventions to improve adherence in chronic disease are needed to guide international efforts to curb the effects of the diabetes epidemic.

Article Information

Acknowledgments. The authors thank Jack Brownrigg and Reza Hajhosseiny (Spotlight Research Ltd.) for performing the searches and providing medical editorial assistance.

Funding. K.K., S.S., and M.D. acknowledge the support of the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care–East Midlands (CLAHRC–EM) and the NIHR Leicester–Loughborough Diet, Lifestyle and Physical Activity Biomedical Research Unit.

Duality of Interest. Funding for medical editorial support was provided by AstraZeneca UK Limited. K.K. has received funds for research and honoraria for speaking at meetings and/or served on advisory boards for AstraZeneca, Eli Lilly and Company, Novartis, Pfizer, Servier, Sanofi, Merck Sharp & Dohme, and Novo Nordisk. S.S. has received honoraria for speaking at meetings and serving on advisory boards for Novartis, Novo Nordisk, Janssen, Merck Sharp & Dohme, Eli Lilly and Company, and Boehringer Ingelheim. M.D. has acted as consultant, advisory board member, and speaker for Novo Nordisk, Sanofi, Eli Lilly and Company, Merck Sharp & Dohme, Boehringer Ingelheim, AstraZeneca, and Janssen and as a speaker for Mitsubishi Tanabe Pharma Corporation. M.D. has received grants in support of investigator and investigator-initiated trials from Novo Nordisk, Sanofi, and Eli Lilly and Company. No other potential conflicts of interest relevant to this article were reported.

Author Contributions. K.K. conceived and designed the study, provided oversight for the statistical analysis, and drafted the manuscript. S.S., S.K., and M.D. conceived the study and critically appraised the manuscript. All authors read and approved the final manuscript.

Footnotes

  • Received September 7, 2016.
  • Accepted April 25, 2017.
http://www.diabetesjournals.org/content/license

Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More information is available at http://www.diabetesjournals.org/content/license.

References

  1. ↵
    1. Osterberg L,
    2. Blaschke T
    . Adherence to medication. N Engl J Med 2005;353:487–497pmid:16079372
    OpenUrlCrossRefPubMedWeb of Science
  2. ↵
    1. DiMatteo MR
    . Variations in patients’ adherence to medical recommendations: a quantitative review of 50 years of research. Med Care 2004;42:200–209pmid:15076819
    OpenUrlCrossRefPubMedWeb of Science
  3. ↵
    1. Cramer J,
    2. Rosenheck R,
    3. Kirk G,
    4. Krol W,
    5. Krystal J; VA Naltrexone Study Group 425
    . Medication compliance feedback and monitoring in a clinical trial: predictors and outcomes. Value Health 2003;6:566–573pmid:14627063
    OpenUrlCrossRefPubMedWeb of Science
    1. Waeber B,
    2. Leonetti G,
    3. Kolloch R,
    4. McInnes GT
    . Compliance with aspirin or placebo in the Hypertension Optimal Treatment (HOT) study. J Hypertens 1999;17:1041–1045pmid:10419079
    OpenUrlCrossRefPubMedWeb of Science
  5. ↵
    1. Claxton AJ,
    2. Cramer J,
    3. Pierce C
    . A systematic review of the associations between dose regimens and medication compliance. Clin Ther 2001;23:1296–1310pmid:11558866
    OpenUrlCrossRefPubMedWeb of Science
  6. ↵
    1. Cramer JA
    . A systematic review of adherence with medications for diabetes. Diabetes Care 2004;27:1218–1224pmid:15111553
    OpenUrlAbstract/FREE Full Text
  7. ↵
    1. Ciechanowski PS,
    2. Katon WJ,
    3. Russo JE
    . Depression and diabetes: impact of depressive symptoms on adherence, function, and costs. Arch Intern Med 2000;160:3278–3285pmid:11088090
    OpenUrlCrossRefPubMedWeb of Science
  8. ↵
    1. Marcum ZA,
    2. Gellad WF
    . Medication adherence to multidrug regimens. Clin Geriatr Med 2012;28:287–300pmid:22500544
    OpenUrlCrossRefPubMed
  9. ↵
    1. Gallacher KI,
    2. Batty GD,
    3. McLean G, et al
    . Stroke, multimorbidity and polypharmacy in a nationally representative sample of 1,424,378 patients in Scotland: implications for treatment burden. BMC Med 2014;12:151pmid:25280748
    OpenUrlCrossRefPubMed
  10. ↵
    1. Dezii CM,
    2. Kawabata H,
    3. Tran M
    . Effects of once-daily and twice-daily dosing on adherence with prescribed glipizide oral therapy for type 2 diabetes. South Med J 2002;95:68–71pmid:11827247
    OpenUrlPubMedWeb of Science
  11. ↵
    1. Donnan PT,
    2. MacDonald TM,
    3. Morris AD
    . Adherence to prescribed oral hypoglycaemic medication in a population of patients with type 2 diabetes: a retrospective cohort study. Diabet Med 2002;19:279–284pmid:11942998
    OpenUrlCrossRefPubMedWeb of Science
  12. ↵
    1. Zimmet P,
    2. Alberti KG,
    3. Shaw J
    . Global and societal implications of the diabetes epidemic. Nature 2001;414:782–787pmid:11742409
    OpenUrlCrossRefPubMedWeb of Science
  13. ↵
    1. UK Prospective Diabetes Study (UKPDS) Group
    . Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet 1998;352:837–853pmid:9742976
    OpenUrlCrossRefPubMedWeb of Science
    1. Patel A,
    2. MacMahon S,
    3. Chalmers J, et al.; ADVANCE Collaborative Group
    . Intensive blood glucose control and vascular outcomes in patients with type 2 diabetes. N Engl J Med 2008;358:2560–2572pmid:18539916
    OpenUrlCrossRefPubMedWeb of Science
  15. ↵
    1. Boussageon R,
    2. Bejan-Angoulvant T,
    3. Saadatian-Elahi M, et al
    . Effect of intensive glucose lowering treatment on all cause mortality, cardiovascular death, and microvascular events in type 2 diabetes: meta-analysis of randomised controlled trials. BMJ 2011;343:d4169pmid:21791495
    OpenUrlAbstract/FREE Full Text
  16. ↵
    1. Care Quality Commission
    . The State of Health Care and Adult Social Care in England in 2011/12. London, The Stationery Office, 2012
    1. Stone MA,
    2. Charpentier G,
    3. Doggen K, et al.; GUIDANCE Study Group
    . Quality of care of people with type 2 diabetes in eight European countries: findings from the Guideline Adherence to Enhance Care (GUIDANCE) study. Diabetes Care 2013;36:2628–2638pmid:23628621
    OpenUrlAbstract/FREE Full Text
  18. ↵
    1. Ali MK,
    2. Bullard KM,
    3. Saaddine JB,
    4. Cowie CC,
    5. Imperatore G,
    6. Gregg EW
    . Achievement of goals in U.S. diabetes care, 1999-2010. N Engl J Med 2013;368:1613–1624pmid:23614587
    OpenUrlCrossRefPubMedWeb of Science
  19. ↵
    1. Simpson SH,
    2. Eurich DT,
    3. Majumdar SR, et al
    . A meta-analysis of the association between adherence to drug therapy and mortality. BMJ 2006;333:15pmid:16790458
    OpenUrlAbstract/FREE Full Text
  20. ↵
    1. Alvarez Guisasola F,
    2. Tofé Povedano S,
    3. Krishnarajah G,
    4. Lyu R,
    5. Mavros P,
    6. Yin D
    . Hypoglycaemic symptoms, treatment satisfaction, adherence and their associations with glycaemic goal in patients with type 2 diabetes mellitus: findings from the Real-Life Effectiveness and Care Patterns of Diabetes Management (RECAP-DM) Study. Diabetes Obes Metab 2008;10(Suppl. 1):25–32pmid:18435671
    OpenUrlCrossRefPubMedWeb of Science
  21. ↵
    1. Rhee MK,
    2. Slocum W,
    3. Ziemer DC, et al
    . Patient adherence improves glycemic control. Diabetes Educ 2005;31:240–250pmid:15797853
    OpenUrlCrossRefPubMedWeb of Science
  22. ↵
    1. Wagner JH,
    2. Justice AC,
    3. Chesney M,
    4. Sinclair G,
    5. Weissman S,
    6. Rodriguez-Barradas M; VACS 3 Project Team
    . Patient- and provider-reported adherence: toward a clinically useful approach to measuring antiretroviral adherence. J Clin Epidemiol 2001;54(Suppl. 1):S91–S98pmid:11750214
    OpenUrlCrossRefPubMedWeb of Science
  23. ↵
    1. Alcoba M,
    2. Cuevas MJ,
    3. Perez-Simon M-R, et al.; HAART Adherence Working Group for the Province of Leon, Spain
    . Assessment of adherence to triple antiretroviral treatment including indinavir: role of the determination of plasma levels of indinavir. J Acquir Immune Defic Syndr 2003;33:253–258pmid:12794563
    OpenUrlCrossRefPubMedWeb of Science
  24. ↵
    1. Ho PM,
    2. Bryson CL,
    3. Rumsfeld JS
    . Medication adherence: its importance in cardiovascular outcomes. Circulation 2009;119:3028–3035pmid:19528344
    OpenUrlAbstract/FREE Full Text
  25. ↵
    1. Stroup DF,
    2. Berlin JA,
    3. Morton SC, et al
    . Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000;283:2008–2012pmid:10789670
    OpenUrlCrossRefPubMedWeb of Science
  26. ↵
    1. Moher D,
    2. Liberati A,
    3. Tetzlaff J,
    4. Altman DG; PRISMA Group
    . Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 2009;151:264–269, W64pmid:19622511
    OpenUrlCrossRefPubMedWeb of Science
  27. ↵
    1. DerSimonian R,
    2. Laird N
    . Meta-analysis in clinical trials. Control Clin Trials 1986;7:177–188pmid:3802833
    OpenUrlCrossRefPubMedWeb of Science
  28. ↵
    1. Higgins JP,
    2. Thompson SG,
    3. Deeks JJ,
    4. Altman DG
    . Measuring inconsistency in meta-analyses. BMJ 2003;327:557–560pmid:9310563
    OpenUrlFREE Full Text
  29. ↵
    1. Egger M,
    2. Davey Smith G,
    3. Schneider M,
    4. Minder C
    . Bias in meta-analysis detected by a simple, graphical test. BMJ 1997;315:629–634pmid:9310563
    OpenUrlAbstract/FREE Full Text
  30. ↵
    1. Rothstein H,
    2. Sutton A,
    3. Borenstein M
    1. Sterne J,
    2. Becker B,
    3. Egger M
    . The funnel plot. In Publication Bias in Meta-analysis: Prevention, Assessment and Adjustments. Rothstein H, Sutton A, Borenstein M, Eds. Chichester, U.K., Wiley, 2005
  31. ↵
    Wells GASB, O’Connell D, Peterson JE, Welch V, Losos M, Tugwell P. The Newcastle-Ottawa Scale (NOS) for assessing the quality of non-randomised studies in meta-analyses, 2000. Available from http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. Accessed 20 May 2017
  32. ↵
    1. Gibson TB,
    2. Song X,
    3. Alemayehu B, et al
    . Cost sharing, adherence, and health outcomes in patients with diabetes. Am J Manag Care 2010;16:589–600pmid:20712392
    OpenUrlPubMedWeb of Science
  33. ↵
    1. Hong JS,
    2. Kang HC
    . Relationship between oral antihyperglycemic medication adherence and hospitalization, mortality, and healthcare costs in adult ambulatory care patients with type 2 diabetes in South Korea. Med Care 2011;49:378–384pmid:21368684
    OpenUrlCrossRefPubMedWeb of Science
    1. Encinosa WE,
    2. Bernard D,
    3. Dor A
    . Does prescription drug adherence reduce hospitalizations and costs? The case of diabetes. Adv Health Econ Health Serv Res 2010;22:151–173pmid:20575232
    OpenUrlCrossRefPubMed
  35. ↵
    1. Jha AK,
    2. Aubert RE,
    3. Yao J,
    4. Teagarden JR,
    5. Epstein RS
    . Greater adherence to diabetes drugs is linked to less hospital use and could save nearly $5 billion annually. Health Aff (Millwood) 2012;31:1836–1846pmid:22869663
    OpenUrlAbstract/FREE Full Text
    1. Lau DT,
    2. Nau DP
    . Oral antihyperglycemic medication nonadherence and subsequent hospitalization among individuals with type 2 diabetes. Diabetes Care 2004;27:2149–2153pmid:15333476
    OpenUrlAbstract/FREE Full Text
  37. ↵
    1. White TJ,
    2. Vanderplas A,
    3. Chang E,
    4. Dezii CM,
    5. Abrams GD
    . The costs of non-adherence to oral antihyperglycemic medication in individuals with diabetes mellitus and concomitant diabetes mellitus and cardiovascular disease in a managed care environment. Disease Management & Health Outcomes 2004;12:181–188
    OpenUrl
  38. ↵
    1. Ho PM,
    2. Rumsfeld JS,
    3. Masoudi FA, et al
    . Effect of medication nonadherence on hospitalization and mortality among patients with diabetes mellitus. Arch Intern Med 2006;166:1836–1841pmid:17000939
    OpenUrlCrossRefPubMedWeb of Science
  39. ↵
    1. Zhu VJ,
    2. Tu W,
    3. Rosenman MB,
    4. Overhage JM
    . Nonadherence to oral antihyperglycemic agents: subsequent hospitalization and mortality among patients with type 2 diabetes in clinical practice. Stud Health Technol Inform 2015;216:60–63pmid:26262010
    OpenUrlPubMed
  40. ↵
    1. Asche C,
    2. LaFleur J,
    3. Conner C
    . A review of diabetes treatment adherence and the association with clinical and economic outcomes. Clin Ther 2011;33:74–109pmid:21397776
    OpenUrlCrossRefPubMed
  41. ↵
    1. Riddle MC,
    2. Ambrosius WT,
    3. Brillon DJ, et al.; Action to Control Cardiovascular Risk in Diabetes Investigators
    . Epidemiologic relationships between A1C and all-cause mortality during a median 3.4-year follow-up of glycemic treatment in the ACCORD trial. Diabetes Care 2010;33:983–990pmid:20427682
    OpenUrlAbstract/FREE Full Text
  42. ↵
    1. Campbell SM,
    2. Reeves D,
    3. Kontopantelis E,
    4. Sibbald B,
    5. Roland M
    . Effects of pay for performance on the quality of primary care in England. N Engl J Med 2009;361:368–378pmid:19625717
    OpenUrlCrossRefPubMedWeb of Science
  43. ↵
    1. Seshasai SRK,
    2. Kaptoge S,
    3. Thompson A, et al.; Emerging Risk Factors Collaboration
    . Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med 2011;364:829–841pmid:21366474
    OpenUrlCrossRefPubMedWeb of Science
  44. ↵
    1. Tancredi M,
    2. Rosengren A,
    3. Svensson A-M, et al
    . Excess mortality among persons with type 2 diabetes. N Engl J Med 2015;373:1720–1732pmid:26510021
    OpenUrlCrossRefPubMed
  45. ↵
    1. Ibrahim IA,
    2. Kang E,
    3. Dansky KH
    . Polypharmacy and possible drug-drug interactions among diabetic patients receiving home health care services. Home Health Care Serv Q 2005;24:87–99pmid:16236661
    OpenUrlCrossRefPubMed
  46. ↵
    1. Grant RW,
    2. Devita NG,
    3. Singer DE,
    4. Meigs JB
    . Polypharmacy and medication adherence in patients with type 2 diabetes. Diabetes Care 2003;26:1408–1412pmid:12716797
    OpenUrlAbstract/FREE Full Text
  47. ↵
    1. Austin RP
    . Polypharmacy as a risk factor in the treatment of type 2 diabetes. Diabetes Spectrum 2006;19:13–16
    OpenUrlFREE Full Text
  48. ↵
    1. Emslie-Smith A,
    2. Dowall J,
    3. Morros A
    . The problem of polypharmacy in type 2 diabetes. British Journal of Diabetes & Vascular Disease 2003;3:54–56
    OpenUrl
  49. ↵
    1. Bramley TJ,
    2. Gerbino PP,
    3. Nightengale BS,
    4. Frech-Tamas F
    . Relationship of blood pressure control to adherence with antihypertensive monotherapy in 13 managed care organizations. J Manag Care Pharm 2006;12:239–245pmid:16623608
    OpenUrlPubMedWeb of Science
  50. ↵
    Haynes RB, Ackloo E, Sahota N, McDonald HP, Yao X. Interventions for enhancing medication adherence. Cochrane Databse Syst Rev 2008;2:CD000011
  51. ↵
    1. Heidenreich PA
    . Patient adherence: the next frontier in quality improvement. Am J Med 2004;117:130–132pmid:15234651
    OpenUrlCrossRefPubMedWeb of Science
  52. ↵
    1. Hex N,
    2. Bartlett C,
    3. Wright D,
    4. Taylor M,
    5. Varley D
    . Estimating the current and future costs of type 1 and type 2 diabetes in the UK, including direct health costs and indirect societal and productivity costs. Diabet Med 2012;29:855–862pmid:22537247
    OpenUrlCrossRefPubMed
  53. ↵
    1. Zhang P,
    2. Zhang X,
    3. Brown J, et al
    . Global healthcare expenditure on diabetes for 2010 and 2030. Diabetes Res Clin Pract 2010;87:293–301pmid:20171754
    OpenUrlCrossRefPubMedWeb of Science
  54. ↵
    1. Shaw JE,
    2. Sicree RA,
    3. Zimmet PZ
    . Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract 2010;87:4–14pmid:19896746
    OpenUrlCrossRefPubMedWeb of Science
  55. ↵
    1. Little RJ,
    2. D’Agostino R,
    3. Cohen ML, et al
    . The prevention and treatment of missing data in clinical trials. N Engl J Med 2012;367:1355–1360pmid:23034025
    OpenUrlCrossRefPubMedWeb of Science
View Abstract
Back to top
View Selected Citations (0)
Print
Download PDF
Article Alerts
Email Article
Citation Tools
Add to Selected Citations

Association Between Adherence to Pharmacotherapy and Outcomes in Type 2 Diabetes: A Meta-analysis
Kamlesh Khunti, Samuel Seidu, Setor Kunutsor, Melanie Davies
Diabetes Care Nov 2017, 40 (11) 1588-1596; DOI: 10.2337/dc16-1925
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo

Jump to section