Predialysis Cardiovascular Disease Medication Adherence and Mortality After Transition to Dialysis

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disease is the leading cause of mortality in predialysis patients, 7 and antihypertensive medications, statins, and aspirin are widely used in the cardiovascular risk management of these patients. 80][11][12][13] However, little is known about the association of medication adherence during the predialysis period with all-cause and cardiovascular mortality after dialysis therapy initiation.
We investigated the association of adherence to medications targeting cardiovascular risk in the last year prior to initiating dialysis therapy with all-cause and cardiovascular mortality after dialysis therapy initiation in a cohort of US veterans with advanced chronic kidney disease (CKD) transitioning to dialysis therapy.We applied 3 methods of adherence determination using pharmacy databases: (1) proportion of days covered (PDC) and ( 2) medication possession ratio (MPR) to evaluate adherence (the extent to which patients follow prescribed dosing regimens) and ( 3) persistence with drug therapy (time from initial drug dispensation to "unauthorized" discontinuation).We hypothesized that lower medication adherence results in higher all-cause and cardiovascular mortality. METHODS

Study Population
We analyzed data from the Transition of Care in CKD (TC-CKD) Study, a retrospective cohort study examining US veterans with CKD transitioning to dialysis therapy from October 1, 2007, through September 30, 2011.A total of 52,172 patients were identified from the US Renal Data System (USRDS).We excluded patients whose medication adherence could not be calculated due to missing pharmacy data (n 5 19,697) and those who had lack of follow-up data (n 5 127).The final cohort consisted of 32,348 patients (Fig 1).

Covariates
Data from the USRDS Patient and Medical Evidence files were used to determine patients' baseline demographic information and type of vascular access at the time of dialysis therapy initiation.We used the national US Department of Veterans Affairs (VA) Corporate Data Warehouse LabChem data files to extract data about predialysis serum creatinine levels. 14Other laboratory variables were collected from the Decision Support System National Data Extracts Laboratory Results file, 15 and baseline values were defined as the last quarterly average before dialysis therapy initiation or the second-from-last quarterly average if the last data point was missing.Data for medication exposure were obtained from both Centers for Medicare & Medicaid Services (CMS; Medicare Part D) and VA pharmacy dispensation records. 16Patients who received at least 1 dispensation of outpatient medication within 1 year of dialysis therapy initiation were recorded as having been treated with these medications.Information about comorbid conditions at the time of dialysis therapy initiation was extracted from the VA Inpatient and Outpatient Medical SAS Datasets 17 and from CMS data sets using diagnostic and procedure codes.Cardiovascular/cerebrovascular disease was defined as the presence of diagnostic codes for coronary artery disease, angina, myocardial infarction, or cerebrovascular disease.We calculated Charlson Comorbidity Index score using the Deyo modification for administrative data sets, without including kidney disease. 18

Exposure Variables
Figure S1 (provided as online supplementary material) depicts schematics of different methods of adherence calculation.PDC was defined as proportion of days with drug available in the measurement period, capped at 100%.MPR was calculated as percentage of total days covered by the dispensed drug supply during the measurement period.Numerically, MPR can take values between 0% and .100%. 19,20For medication persistence, the following algorithm was used: persistence was coded as 1 (present) if a patient refilled each subsequent prescription with gaps not exceeding 60 days; otherwise, it was coded as 0 (absent, or nonpersistent). 20etailed information about each prescription was collected during the last year before dialysis therapy for the following cardiovascular drugs: angiotensin-converting enzyme inhibitors/ angiotensin receptor blockers, calcium channel blockers, bblockers, a-blockers, direct vasodilators, diuretics (loop and thiazide), aspirin, and statins.The index date was the date of the first available prescription (in the last year before dialysis therapy initiation) regardless of any prescriptions before this date.The last prescription had to be dispensed before dialysis therapy initiation, and the full prescription period was included in the denominator regardless of whether the supply lasted until after the dialysis therapy initiation date.Only outpatient prescriptions were taken into account.Any inpatient time was added to the denominator.Averaged values of the PDCs and MPRs of all medication groups were used as exposure variables in analyses.Medication adherence was categorized as follows: (1) for PDC: .80%,.60% to #80%, and #60%; (2) for MPR: $100%, .80% to ,100%, .60% to #80%, and #60%.We dichotomized medication persistence as average persistence , 50% or $50%, derived from individual drug prescription refills.PDCs and MPRs were also treated as continuous variables to examine nonlinear associations using restricted cubic spline analyses.

Outcome Assessment
The coprimary outcomes of this study were all-cause and cardiovascular mortality after dialysis therapy initiation.Death dates were obtained from the USRDS and VA Vital Status Files (up to December 27, 2012).Cause of death was obtained from the USRDS (up to October 6, 2011).

Statistical Analysis
Data are presented as number and percentage for categorical variables and as mean 6 standard deviation or median and interquartile range (IQR) as appropriate.Categorical variables were compared with c 2 tests.Continuous variables were compared using t tests, Mann-Whitney U tests, or analysis of variance, as appropriate.We used Cox proportional hazard regressions to ) with the use of multiple imputation procedures (creating 5 data sets) using STATA's "mi" set of commands in sensitivity analyses.We also assessed the association of separate PDCs of each medication category with all-cause mortality as sensitivity analysis.
P values are 2 sided and reported as significant at ,0.05 for all analyses.All analyses were conducted using STATA MP, version 14 (STATA Corp LP).The study was approved by the institutional review boards of the Memphis and Long Beach VA Medical Centers, with exemption from informed consent.

Baseline Characteristics
Mean age of the cohort at baseline was 72 6 11 (standard deviation) years; 96% were men, 74% were white, 23% were African American, and 69% had diabetes.The median of the last pre-ESRD outpatient estimated glomerular filtration rate was 16 (IQR, 10-26) mL/min/1.73m 2 .Baseline characteristics of patients categorized by PDC categories are shown in Table 1.Patients with a higher PDC (.80%) were older; were more likely to be white and married; were more likely to initiate dialysis therapy with an arteriovenous fistula; were more likely to be receiving a statin and angiotensin-converting enzyme inhibitor/ angiotensin receptor blocker; had a higher prevalence of hypertension; had higher serum albumin and calcium levels; had lower serum phosphate, parathyroid hormone, total and low-density lipoprotein cholesterol levels, and urine albumin-creatinine ratios; and had more favorable metabolic and anemia markers (Table 1).Table S2 shows adherence parameters in different medication groups.In individual medication groups, PDC, MPR, and nonpersistence were very similar (Table S2).

DISCUSSION
In a large cohort of patients with advanced CKD, we examined the association between 1-year predialysis adherence to cardiovascular medications and all-cause and cardiovascular mortality following dialysis therapy initiation.We used a pharmacy database analysis to assess 2 parts of medication adherence: adherence and persistence. 21Inadequate adherence to cardiovascular pharmacotherapy was associated with reduced survival independent of demographic, comorbid condition, and laboratory characteristics.3][24][25] These factors are difficult or impossible to modify but bear importance in the risk stratification and estimation of prognosis after initiating renal replacement therapy.For example, a new prediction risk score was recently developed based on demographic and comorbid condition characteristics to help with shared decision making about dialysis therapy initiation in elderly patients with ESRD. 25 However, it is equally important to understand potentially modifiable predialysis risk factors and behaviors influencing survival after initiating dialysis therapy.4][5][6]26 The quality of predialysis care as defined by the number of provider visits before ESRD onset was also shown to influence survival.One study found that patients having 3 or more predialysis visits in the 6-month period before dialysis therapy initiation had 28% higher survival compared with patients who had fewer than 3 visits during the same period. 27n addition to number of visits, nephrology care of 6 months' duration or less before ESRD onset was linked to 23% to 27% higher 1-year all-cause mortality in 2 recent studies. 28,29o our knowledge, no other studies have attempted to evaluate the influence of predialysis adherence to cardiovascular medications on all-cause and cardiovascular mortality after initiation of dialysis therapy.However, adequate adherence to cardiovascular medications has been shown to be associated with better outcomes in the general population. 9,13,30A large meta-analysis including 1,978,919 individuals concluded that good medication adherence to antihypertensive drugs was associated with 45% lower risk for all-cause mortality and good adherence to statins was associated with 29% reduced risk for death. 11Our study involved a population of patients with advanced CKD transitioning to dialysis therapy, and its results further strengthen the overall importance of adherence to cardiovascular drugs.Because cardiovascular death is the main cause of morbidity and mortality in patients with CKD, 7 it is biologically plausible that patients adherent to cardiovascular drugs may retain better cardiovascular health and live longer after they progress to ESRD.Therefore, adherence to cardiovascular medications should be monitored and reinforced.Adherence to medications is a complex behavior that is influenced by a broad array of factors, including those related to the patient, condition, therapy, socioeconomic background, and health care system.Therefore, providers should be familiar with available methods for adherence screening 21 and routinely apply them while treating patients with CKD.The PDC, MPR, and persistence methods that were used in the current study are indirect screening methods for the evaluation of medication-taking behavior based on pharmacy database evaluation. 31,32In the absence of a gold standard of adherence assessment, pharmacy database analysis is becoming the most practical way to assess real-world adherence, especially using large databases.This method is easily quantifiable and objective.In addition, it allows evaluation of 2 aspects of medication-taking behavior: (1) adherence, the extent to which patients follow prescribed dosing regimens (assessed by and MPR), and (2) persistence, the duration from initiation to unauthorized discontinuation of therapy.In the current study, we modified the approach to persistence assessment and used a prescription date closest to the 1-year predialysis mark as the initial date and evaluated subsequent 12-month persistence.The PDC and MPR are both related to the number of available medication doses given out in relationship to the number of days during the period of interest.The key difference is that PDC is capped at 100% because the number of days covered by a drug cannot exceed 100%.Numerically, MPR can exceed 100% and therefore it can account for medication overfills; alas, it has been contended that MPR might overestimate medication adherence.
Our study has large sample size and event numbers and is representative of male veterans who received care in the VA system in the entire United States.This study must be interpreted in light of several limitations.Our study was observational and hence the results do not allow us to infer causality, but merely associations.Most of our patients consisted of male US veterans; therefore, results may not be generalizable to women or the general US population.Although we adjusted our analyses for a variety of important covariates as potential confounders, we cannot eliminate the possibility of unmeasured confounders, such as proteinuria and quality of nephrology care.Several limitations of pharmacy database analysis need to be acknowledged.Although we applied 3 accepted methods of adherence determination using pharmacy databases, we did not have data about discontinuation orders for these drugs, so we were not able to differentiate between discontinuation by indication versus self-discontinuation (ie, nonadherence) by patients.The dispensation of medicine does not guarantee its consumption and does not give information about when medications are taken by patients.Additionally, patients should be enrolled in a closed pharmacy system; in our cohort, it is possible that some veterans received medications outside the 2 evaluated pharmacy systems (VA and Medicare Part D).Another limitation of our study is that we only included patients who survived until dialysis therapy initiation; therefore, we were not able to examine patients with chronic kidney failure receiving conservative management (ie, no dialysis).Finally, we had large amounts of missing data for some laboratory values; therefore, we were not able to include these variables in our main multivariable model.However, models that included these variables and the multiple imputation models led to similar conclusions.Adherence to cardiovascular medications is emerging as a novel risk factor for mortality after initiating dialysis therapy.Poor predialysis medication adherence and persistence in the year preceding ESRD onset are associated with increased all-cause and cardiovascular mortality.Our findings may have important implications for the management of predialysis patients due to the potentially modifiable nature of medication-taking behavior.It would be very useful if pharmacies and/or insurance companies could start the routine provision of pharmacy dispensation records with calculations of adherence and persistence, which would allow providers to have an opportunity to discuss barriers and encourage medication adherence.Future prospective studies are needed to understand adherence barriers and develop measures enhancing adherence to cardiovascular drugs in patients with advanced CKD.

Figure 2 .
Figure 2. Association between percentage of days a participant had medication available (proportion of days covered [PDC]) in the last year before end-stage renal disease and (A) post-dialysis therapy initiation all-cause mortality and (B) cardiovascular (CV) mortality using fractional polynomials and restricted cubic splines (model adjusted for age; sex; race; marital status; zip code; Charlson Comorbidity Index score; presence of diabetes, congestive heart failure, cardiovascular/ cerebrovascular disease, depression, and anxiety; and type of vascular access).

Figure 3 .
Figure 3. Association between percentages of days a participant had medication available (proportion of days covered [PDC]) in the last year before end-stage renal disease and post-dialysis therapy initiation mortality in different subgroups of patients using adjusted Cox regression analyses (model adjusted for age, sex, race, marital status, zip code, Charlson Comorbidity Index [CCI] score, presence of diabetes, congestive heart failure [CHF], cardiovascular [CVD]/cerebrovascular disease, presence of depression, presence of anxiety, and type of vascular access).Abbreviations: CI, confidence interval; HR, hazard ratio.

Table 2 .
Association of PDC With All-Cause Mortality After Dialysis Therapy Initiation

Table 3 .
Association of PDC With Cardiovascular Mortality After Dialysis Therapy Initiation 2 plus Charlson Comorbidity Index score and presence of diabetes, congestive heart failure, cardiovascular/cerebrovascular disease, depression, anxiety, and type of vascular access; and model 4: adjusted for model 3 plus blood/serum hemoglobin, bicarbonate, albumin, and urea nitrogen levels and last estimated glomerular filtration rate before end-stage renal disease.

Table 4 .
Association of Medication Persistence With All-Cause Mortality After Dialysis Therapy Initiation Medication persistence defined as patient refilling prescription without a gap exceeding 60 days.Model 1: unadjusted; model 2: adjusted for age, sex, race/ethnicity, marital status, and ZIP code; model 3: adjusted for model 2 plus Charlson Comorbidity Index score and presence of diabetes, congestive heart failure, cardiovascular/cerebrovascular disease, depression, anxiety, and type of vascular access; and model 4: adjusted for model 3 plus blood/serum hemoglobin, bicarbonate, albumin, and urea nitrogen levels and last estimated glomerular filtration rate before end-stage renal disease.Abbreviations: CI, confidence interval; HR, hazard ratio.Figure 4. Association between medication persistence (less 60-day prescription refill gap for .50% of medications) in the last year before end-stage renal disease and post-dialysis therapy initiation mortality in different subgroups of patients using adjusted Cox regression analyses (model adjusted for age, sex, race, marital status, zip code, Charlson Comorbidity Index [CCI] score, presence of diabetes, congestive heart failure [CHF], cardiovascular [CVD]/cerebrovascular disease, presence of depression, presence of anxiety, and type of vascular access).

Table 5 .
Association of Medication Persistence With Cardiovascular Mortality After Dialysis Therapy InitiationNote: Persistence defined as patient refilling prescription without a gap exceeding 60 days.Model 1: unadjusted; model 2: adjusted for age, sex, race/ethnicity, marital status, and ZIP code; model 3: adjusted for model 2 plus Charlson Comorbidity Index score and presence of diabetes, congestive heart failure, cardiovascular/cerebrovascular disease, depression, anxiety, and type of vascular access; and model 4: adjusted for model 3 plus blood/serum hemoglobin, bicarbonate, albumin, and urea nitrogen levels and last estimated glomerular filtration rate before end-stage renal disease.Abbreviations: CI, confidence interval; HR, hazard ratio.