Abstract
Data on the long‐term outcomes of the use of fixed‐dose combinations (FDCs) or free‐pill combinations (FPCs), titration of doses, and switching are currently unavailable for identifying a preferred strategy for adherence. In the lack of these evidences, adherence can be a useful guiding criteria. The authors conducted a retrospective cohort study using the BlueCross BlueShield of Texas (2008‐2012) database to compare adherence among 5998 patients who received treatment modifications (TMs). Results of the propensity score‐adjusted model indicate that FDC and uptitration strategies have higher odds of adherence compared with the switch strategy (P<.05). Among patients with a history of poor adherence, the odds of adherence were up to 26% higher for the FDC strategy compared with alternative strategies (P<.05). Factors including age, number of comedications, first‐line drug class, and health services utilization are associated with adherence. In conclusion, FDCs should be prioritized for TM, particularly if the patient has a history of poor adherence.
Seven of every 10 hypertensive patients in the United States use pharmacotherapy to treat their hypertension.1 Guidelines recommend monotherapy as the first‐line treatment for most patients diagnosed with hypertension,2 but efficacy‐ or tolerance‐related issues are common and necessitate modification of the monotherapy regimen.3, 4, 5 Healthcare providers often have to choose between treatment modification (TM) strategies including fixed‐dose combinations (FDCs) or free‐pill combinations (FPCs) (ie, addition strategy), uptitration (ie, increasing the drug dose), or switching to address efficacy‐related issues after first‐line treatment. Similarly, tolerance‐related issues are addressed by either switching, or downtitration (ie, decreasing the drug dose).
The expert panel appointed to the Eighth Joint National Committee (JNC 8) primarily recommends uptitration and addition (ie, FDC or a FPC) strategies for addressing efficacy‐related issues.2 Moreover, switching can also be an alternative to these strategies. A preferred strategy for TM was not recommended by the expert panel because of the lack of evidences regarding the long‐term cardiovascular (CV) outcomes and mortality of the alternative strategies used to address efficacy‐related issues.2 Knowledge regarding the strategies used for addressing tolerance‐related issues is also limited. Therefore, an intermediate outcome, such as adherence, can be a useful guiding criterion for selecting a TM strategy. Comparative data on adherence in the current literature are limited to FDC and FPC regimens. A direct comparison of adherence between addition, titration, and switching strategies is unavailable in the current literature.
Adherence is an essential component of pharmacotherapy. It increases the odds of attaining short‐term (ie, blood pressure [BP] control)6, 7, 8 and long‐term (ie, CV risk reduction)9, 10, 11, 12 outcomes. Adherence is one of the crucial factors for attainment of BP goal among patients who undergo TMs.13 However, given that TMs involve a change of dose, switch, or drug addition, they increase the risk of poor medication‐taking behavior in patients who need TMs by up to 25%.14 This risk is further elevated if patients have histories of poor adherence to their first‐line treatment. However, prior adherence has little impact on providers' decisions to modify treatment15 when limitations of first‐line monotherapy necessitate TMs. Given that TM predisposes patients to poor medication‐taking behavior, it is worthwhile to determine whether any differences exist in patient adherence to alternative TM strategies. The information will be useful for decision‐making, particularly in modifying regimens of patients with histories of nonadherent behavior. The objectives of this study were to compare the adherence profiles of alternative TM strategies and characterize the factors associated with adherence after TM.
Methods
We conducted a retrospective cohort study using the BlueCross BlueShield of Texas (BCBSTX) (2008‐2012) commercial claims data. Eligibility data, and medical and prescription claims were used for this study. Several selection criteria were applied to identify the analytical sample. We included participants who were 18 years and older as of the index date of monotherapy. A “new‐user” design16 with a minimum of 6 months of washout period (starting January 1, 2008 to June 30, 2008) was used to identify naive users of antihypertensive monotherapy. Patients with a pharmacy claim for antihypertensive drug during the washout period were excluded. Because patients initiating combination therapy are more likely to have stage 2 hypertension, which predisposes them to poor outcomes, these patients were excluded to minimize selection bias. At least one occurrence of a hypertension (International Classification of Diseases—Ninth Revision: 401.XX‐405.XX) diagnosis for an inpatient or outpatient visit during the washout period was required.17 We excluded pregnant women and patients who did not have prescription coverage through BCBSTX. Patients who met these eligibility criteria were followed from their index date of first‐line monotherapy up to 12 months to identify whether and when a TM occurred. Clinical parameters required to characterize TMs were unavailable in administrative claims data; therefore, we identified TMs based on assumptions inherent in the patterns of medication use. Generic Product Identifier codes, dosage, refill dates, and days' supply were used to identify four mutually exclusive TM groups: addition, patients who added a drug to their existing regimen without the deletion of initial monotherapy (or those patients who started a FPC or FDC regimen); uptitration, patients who had an increase in the dose or increase in the frequency of dose of the initial monotherapy; switch, patients who stopped their initial antihypertensive regimen and changed drug within the same class or to a different drug class; and downtitration, patients who had a decrease in the dose or decrease in the frequency of dose of the initial monotherapy.
Further, we classified patients in the addition group into those who used an FPC and those who used an FDC to compare them separately. The maximum allowable gap between the termination of initial monotherapy and beginning of TM for our study was set to 90 days to exclude nonpersistent patients.18, 19 Patients who had multiple TMs during the observation period were excluded to minimize measurement error in adherence due to the frequently changing refill patterns in their claims and to eliminate possible cases of resistant hypertension.
Baseline demographics of patients including age and sex were identified from the enrollment data. Baseline clinical characteristics were determined from medical claims. The burden of comorbidities was calculated using the Charlson Comorbidity Index (CCI).20 Number and type of comedications were determined from prescription claims over the post‐TM period. Information on days' supply and refill dates from prescription claims were used to calculate adherence. Adherence to first‐line monotherapy and adherence to the modified regimen (measured for a 12‐month duration following TM) was calculated using the proportion of days covered (PDC) ratio,21 and patients were classified as adherent if the PDC was >80%.22 The PDC ratio provides a more conservative estimate of medication adherence compared with other measures when multiple medications are intended to be used concomitantly.23 Mean PDC for the two drugs was calculated for those patients who added a drug to their regimen as separate pills (ie, FPC).24 PDC was adjusted for inpatient days if the patient was hospitalized during the observation period.25
Statistical Analysis
Descriptive statistics were used to summarize baseline characteristics of the cohort and differences were determined using chi‐square test and analysis of variance for categorical and continuous variables, respectively. Generalized linear models (GLMs) were used to compare mean adherence. Logistic regression models were used to compare the likelihood of adherence and to examine the factors associated with the likelihood of adherence. A subgroup analysis was conducted for comparing the likelihood of adherence among patients identified as nonadherent to their first‐line monotherapy. All models were adjusted using propensity score weights26 calculated using baseline characteristics including age, sex, CCI, drug class of first‐line monotherapy, number of comedications, type of comedications, time to TM, existing CV diseases, and health services utilization to adjust the regression models. Statistical significance was tested at P<.05. All analyses were conducted using SAS version 9.4 (SAS Institute Inc, Cary, NC). The study was approved by the Auburn University institutional review board.
Results
A sample of 5998 patients who received a TM and met the eligibility criteria was identified: addition (n=2602), uptitration (n=1659), switch (n=1282), and downtitration (n=455) (Figure). The baseline characteristics of these groups are presented in Table 1.
Figure 1.
Sample flow diagram. BCBSTX, BlueCross BlueShield of Texas; ICD‐9, International Classification of Diseases—Ninth Revision; addition group constitutes of free‐pill combination (n=1395) and fixed‐dose combination (n=1207) users. †Includes patients with a minimum of 12‐month follow‐up, without a gap that exceeds 90 days between the end of monotherapy and the start of the modified regimen and with no further modification.
Table 1.
Baseline Characteristics of the Treatment Modification Cohort
| Characteristics, No. (%) | Treatment Modification Strategy | P Value | |||
|---|---|---|---|---|---|
| Addition (n=2602) | Uptitration (n=1659) | Switch (n=1282) | Downtitration (n=455) | ||
| Age, y | |||||
| 18–24 | 23 (0.88) | 28 (1.69) | 20 (1.56) | 7 (1.54) | <.001 |
| 25–35 | 182 (6.99) | 201 (12.12) | 161 (12.56) | 53 (11.65) | |
| 36–59 | 1912 (73.48) | 1191 (71.79) | 911 (71.06) | 324 (71.21) | |
| 60 and older | 485 (18.64) | 239 (14.41) | 190 (14.32) | 71 (15.60) | |
| Male sex | 1473 (56.61) | 995 (59.98) | 670 (52.26) | 259 (56.92) | <.001 |
| Comorbidity index | |||||
| 0 | 1542 (59.26) | 1074 (64.74) | 812 (63.34) | 300 (65.93) | <.001 |
| 1 | 636 (24.44) | 381 (22.97) | 298 (23.24) | 93 (20.44) | |
| 2 | 215 (8.26) | 109 (6.57) | 90 (7.02) | 39 (8.57) | |
| ≥3 | 209 (8.03) | 95 (5.73) | 82 (6.40) | 23 (6.40) | |
| First‐line drug | |||||
| Diuretics | 300 (11.53) | 88 (5.30) | 141 (11.00) | 25 (5.49) | <.001 |
| Beta‐blockers | 551 (13.76) | 260 (15.67) | 234 (18.25) | 78 (17.14) | |
| CCBs | 546 (20.98) | 196 (11.81) | 134 (10.45) | 39 (8.57) | |
| ACE inhibitors | 847 (32.55) | 976 (58.83) | 582 (45.40) | 270 (59.34) | |
| ARBs | 358 (32.55) | 139 (8.38) | 191 (14.90) | 43 (9.45) | |
| Number of comedications, mean (±standard deviation)a | 4.40 (2.22) | 4.01 (2.11) | 4.46 (2.17) | 4.25 (2.17) | <.001 |
| Comedication typea | |||||
| Antihyperlipidemic | 618 (23.75) | 359 (21.64) | 258 (20.12) | 101 (22.20) | .06 |
| Antidiabetic | 201 (7.72) | 93 (5.61) | 59 (4.60) | 33 (7.25) | <.001 |
| Time to TM in days, mean (±standard deviation) | 133.34 (90.97) | 102.00 (84.88) | 162.18 (98.68) | 145.58 (103.75) | <.001 |
| Cardiovascular diseasesb | |||||
| Ischemic heart diseases | 156 (6.00) | 66 (3.98) | 55 (4.29) | 21 (4.62) | .04 |
| Congestive heart failure | 44 (1.69) | 26 (1.57) | 19 (1.48) | 6 (1.32) | .79 |
| Peripheral vascular diseases | 42 (1.61) | 21 (1.27) | 21 (1.64) | 5 (1.10) | .90 |
| Cerebrovascular diseases | 76 (2.92) | 38 (2.29) | 30 (2.34) | 16 (3.52) | .37 |
| Healthcare utilizationb | |||||
| Inpatient visits | |||||
| 0 | 2458 (94.47) | 1576 (95.00) | 1215 (94.77) | 430 (94.51) | .65 |
| 1–15 | 51 (1.96) | 36 (2.17) | 19 (1.48) | 9 (1.98) | |
| >15 | 93 (3.57) | 47 (2.83) | 48 (3.74) | 16 (3.52) | |
| Outpatient visits | |||||
| 0–3 | 177 (6.80) | 169 (10.19) | 109 (8.50) | 42 (9.23) | <.001 |
| 4–7 | 174 (6.69) | 132 (7.96) | 94 (7.33) | 38 (8.35) | |
| >7 | 2251 (86.51) | 1358 (81.86) | 1079 (84.17) | 375 (82.42) | |
Abbreviations: ACEs, angiotensin‐converting enzyme; ARBs, angiotensin receptor blockers; CCBs, calcium channel blockers.
aMeasured during the follow‐up period from prescription claims.
bMeasured at baseline from medical claims.
Mean Adherence
Mean adherence (measured as PDC) was highest for the uptitration strategy (0.70±0.29) followed by addition (0.68±0.27), downtitration (0.68±0.30), and switch (0.64±0.32) strategies. Differences in mean adherence between alternative TM strategies is presented in Table 2. Among alternatives for addressing efficacy issues, adherence was significantly lower for addition and switch strategies compared with the uptitration strategy (P<.05), and it was significantly higher for the addition compared with the switch strategy (mean difference [MD], 0.041; P<.05). Among alternatives for addressing tolerance‐related issues, the downtitration strategy had higher adherence compared with the switch strategy (MD, 0.045; P<.05).
Table 2.
Differences in Mean Adherence and Odds of Adherence Between Treatment Modification Strategies
| Strategies | Difference Between Meanadherence | Odds Ratio for Adherence (95% Confidence Interval) |
|---|---|---|
| Addition vs uptitration | −0.024a | 0.80 (0.71–0.90)a |
| Addition vs switch | 0.041a | 0.97 (0.84–1.11) |
| Switch vs uptitration | −0.064a | 0.83 (0.71–0.96)a |
| Downtitration vs switch | 0.045a | 1.06 (0.86–1.31) |
Significant at P<.05.
Next, we compared mean adherence for FPCs (n=1395) and FDCs (n=1207) separately. Adherence for FPC and FDC strategies were 0.67±0.25 and 0.69±0.29, respectively. Result of the GLM shows that adherence was significantly higher for the uptitration compared with the FPC strategy (MD, 0.035; P<.05) and significantly lower for the switch compared with the FDC strategy (MD, −0.054; P<.05). Difference in mean adherence between FDC and uptitration and FDC and FPC strategies were not statistically significant. The difference in adherence between FPC and switch strategies was also not significant.
Odds of Adherence
The likelihood of adherence between competing strategies is presented in Table 2. Result of the logistic regression indicates that patients who added drugs (odds ratio [OR], 0.80; 95% confidence interval [CI], 0.71–0.90) and those who switched drugs (OR, 0.82; 95% CI, 0.71–0.95) were less likely to be adherent compared with those who uptitrated drug dose. There were no significant differences in the likelihood of adherence between addition and switch strategy, or between downtitration and switch strategy.
The differences in our main analyses were consistent and more prominent after classifying patients in the addition strategy into those using FPCs and FDCs. Patients using FPCs were less likely to be adherent than those who uptitrated or switched drugs. On the contrary, the odds of adherence for FDCs were not different compared with uptitration but they were higher when compared with switching (OR, 1.22; 95% CI, 1.04–1.44). Comparing FPCs and FDCs, the odds of adherence were lower for FPCs (OR, 0.62; 95% CI, 0.53–0.73).
Factors Associated With the Likelihood of Adherence
We examined the factors associated with the likelihood of being adherent after TM (Table 3). Older age (OR, 1.03; 95% CI, 1.02–1.03), higher number of concomitant medications (OR, 1.03; 95% CI, 1.00–1.06), and higher frequency of outpatient visits (OR, 1.01; 95% CI, 1.00–1.01) were associated with a higher likelihood of being adherent. Moreover, the likelihood of being adherent was found to be higher for patients treated with angiotensin‐converting enzyme (ACE) inhibitors or calcium channel blockers (CCBs) as first‐line monotherapy compared with those treated with diuretics. Higher frequency of inpatient visits (OR, 0.95; 95% CI, 0.92–0.98) was associated with a lower likelihood of being adherent after TM.
Table 3.
Factors Associated With the Likelihood of Adherence After Treatment Modification
| Factor | Categorical Model |
|---|---|
| Odds Ratio (95% Confidence Interval) | |
| Age | 1.03 (1.02–1.03)a |
| Female sex | 0.94 (0.84–1.05) |
| Comorbidities | 0.95 (0.90–1.00) |
| Existing cardiovascular diseases (yes vs no) | |
| Cerebrovascular diseases | 0.93 (0.67–1.30) |
| Ischemic heart diseases | 0.95 (0.74–1.22) |
| Congestive heart failure | 0.98 (0.64–1.52) |
| Peripheral vascular diseases | 1.21 (0.78–1.89) |
| Drug class of first‐line treatment | |
| ACE inhibitors vs ARBs | 1.06 (0.89–1.26) |
| ACE inhibitors vs BBs | 1.00 (0.86–1.17) |
| ACE inhibitors vs CCBs | 0.91 (0.77–1.07) |
| ACE inhibitors vs diuretics | 1.23 (1.01–1.49)a |
| ARBs vs BBs | 0.95 (0.79–1.15) |
| ARBs vs CCBs | 0.85 (0.70–1.05) |
| ARBs vs diuretic | 1.15 (0.92–1.46) |
| BBs vs CCBs | 0.91 (0.75–1.09) |
| BBs vs diuretics | 1.22 (0.98–1.52) |
| CCBs vs diuretics | 1.35 (1.08–1.69)a |
| Time‐to‐treatment modification | 1.00 (0.99–1.00) |
| Number of comedications | 1.03 (1.00–1.06)a |
| Type of comedications (yes vs no) | |
| Antidiabetic | 1.05 (0.83–1.31) |
| Antihyperlipidemic | 1.09 (0.96–1.24) |
| Health services utilization | |
| Inpatient visits | 0.95 (0.92–0.98)a |
| Outpatient visits | 1.01 (1.00–1.01)a |
Abbreviations: ACEs, angiotensin‐converting enzyme; ARBs, angiotensin receptor blockers; BBs, β‐blockers; CCBs, calcium channel blockers.
aSignificant at P<.05.
Subgroup Analysis of Patients Not Adherent to First‐Line Monotherapy
A subgroup analysis was performed for 2271 patients who were not adherent to their first‐line monotherapy. Because there were significant differences between FPCs and FDCs in our main analyses, the subgroup analysis was conducted by classifying the addition group. The analysis highlighted the larger gaps in the odds of adherence in this subgroup of patients compared with the odds estimated in our main analyses (Table 4).
Table 4.
Likelihood of Adherence by Treatment Modification Strategies in Patients Nonadherent to First‐Line Monotherapy
| Strategies | Odds Ratio (95% Confidence Interval) |
|---|---|
| FPCs vs FDCs | 0.32 (0.24–0.44)a |
| FPCs vs switch | 0.41 (0.30–0.56)a |
| FPCs vs uptitration | 0.56 (0.39–0.80)a |
| FDCs vs switch | 1.26 (1.01–1.57)a |
| FDCs vs uptitration | 1.73 (1.30–2.30)a |
| Switch vs uptitration | 1.37 (1.03–1.83)a |
| Downtitration vs switch | 0.98 (0.71–1.36) |
Abbreviations: FDCs, fixed‐dose combinations; FPCs, free‐pill combinations.
aSignificant at P<.05.
Patients using FDCs were more likely to be adherent compared with those who uptitrated drug dose or switched drugs. The likelihood of being adherent to FDCs was higher compared with switching (OR, 1.26; 95% CI, 1.01–1.57) and uptitration (OR, 1.73; 95% CI, 1.30–2.30) strategies. In addition, patients who used FPCs were less adherent than those using FDCs (OR, 0.32; 95% CI, 0.24–0.44), those who switched drugs (OR, 0.41; 95% CI, 0.30–0.56), and those who uptitrated dose (OR, 0.56; 95% CI, 0.39–0.80). Overall, the likelihood of adherence to FPCs was at least 32% lower compared with other strategies in this subgroup. On the other hand, the likelihood of adherence was at least 26% higher with FDCs compared with alternative strategies.
Discussion
Adherence can be a useful guiding criterion for selecting a TM strategy after first‐line treatment. Our study found significant differences in mean adherence between alternative TM strategies. For example, the difference between the two competing strategies for addressing efficacy‐related issues—addition and uptitration—was significant in our main analyses. We conducted further analyses by classifying the addition group to compare FDC, FPC, uptitration, and switch strategies. Although poor adherence remained consistent for the FPC strategy when compared with uptitration and switch strategies, adherence to the FDC strategy was higher compared with the switch strategy and was not significantly different compared with the uptitration strategy. One previous study found that patients using an FDC had approximately 12% higher adherence (P<.0001) compared with those who uptitrated the dose of diuretic.27 The difference in mean adherence between these two groups were not significant in our main analyses. The two strategies that have been most frequently compared and extensively published are FPCs and FDCs. Results of the meta‐analysis of these studies showed that patients taking FDCs have a significantly higher adherence rate compared with those taking FPCs (MD, 13.31; 95% CI, 8.26–18.35).28 To the best of our knowledge, a comparative assessment of adherence of other competing TM strategies has not been published.
Differences in the odds of adherence were remarkable. Our initial analyses showed that patients who switch or add drugs have lower odds of adherence compared with those who uptitrate dose. However, after classifying the addition strategy, the FDC strategy had a higher likelihood of adherence compared with the switch strategy. Moreover, the likelihood was not different compared with the uptitration strategy. In summary, the results of our main analysis indicate that in the general hypertensive population, FDC and uptitration strategies both have equal adherence and just in terms of patient adherence (ie, without regard to BP), these strategies may be preferred over switching for addressing efficacy‐related issues with first‐line treatment.
We performed a subgroup analysis to compare the odds of adherence after TM among patients who were not adherent to their first‐line drug and found much larger differences in the odds of adherence compared with the general hypertensive cohort. FDCs had a notably higher odds of adherence in this subgroup compared with alternative strategies (26% and 73% higher compared with switch and uptitration strategies, respectively). Studies comparing adherence in a patient subgroup with previous monotherapy exposure are currently unavailable. However, one previous study reported that patients newly starting monotherapy are 50% less likely to be adherent compared with those starting FDCs.27 Contrary to the FDCs, FPCs had about 60% lower likelihood of adherence compared with alternative strategies. Many studies comparing FPCs with FDCs have been published previously. A meta‐analysis of these studies shows that patients taking FDCs are more likely to be adherent compared with those taking FPCs (relative risk, 2.13; 95% CI, 1.11–4.09), which is consistent with our results.28
Use of drugs in combination, such as that in FDCs, has also been shown to have higher effectiveness compared with alternative strategies. For instance, the 2013 European Society of Hypertension and European Society of Cardiology guidelines mention that the physiological and pharmacologic action between different drug classes used in combination can lead to greater BP reduction and also cause fewer side effects compared with using a single agent. Moreover, a recent meta‐analysis showed that BP reduction by using two drugs in combination is approximately five times greater than doubling the dose of one drug.29 Despite the superior efficacy profile, combination therapies remain underutilized in the hypertensive patient population including high‐risk hypertensive patients.30, 31 For instance, in a previous study of the National Health and Nutrition Examination Survey (NHANES) III, only 50% of the treated hypertensive patients with elevated serum creatinine levels reported the use of antihypertensive drug and of those treated patients.32 In another study of NHANES, about one third of patients with chronic kidney disease were using a single antihypertensive drug to control their BP.31 One of the major reasons for underutilization is attributable to the reluctance of healthcare providers to use an “aggressive” treatment approach such as combination therapy.8, 33 This reluctance may be the result of the common perceptions surrounding aggressive treatment approaches such as (1) the complexity of regimen, (2) increase in pill burden, (3) increase in treatment‐related side effects, and (4) concerns about cost‐effectiveness.34 Combination therapy administered as an FDC has superior efficacy and better tolerance, which is supplemented by higher adherence. Therefore, healthcare providers should not be reluctant and prioritize the use of FDCs over uptitration and switching strategies for addressing efficacy‐related issues, particularly if a patient has a history of poor adherence.
Results of our study do not indicate whether the switching or downtitration strategies have a better adherence profile for addressing tolerance‐related issues. Adherence was only about 6% higher for downtitration compared with switching in our main analysis. Moreover, no significant differences were found between the two strategies in the subgroup analysis. Given that antihypertensive drugs have a dose‐response relationship, downtitrating dose is expected to reduce treatment efficacy. Therefore, if compromise on efficacy is not feasible, switching may be a preferred approach.
The factors associated with adherence after TM have not been previously published. Older age, use of certain drug class as first‐line, higher number of comedications, lower frequency of inpatient visits, and higher frequency of outpatient visits significantly improved the likelihood of adherence after TM in our study. Previous studies have shown that demographic factors of the patients such as younger age,35, 36, 37 female sex,36, 37 and black race35, 38 are associated with lower odds of adherence to antihypertensive drugs. Although not significant in our study, clinical factors such as presence of certain comorbid conditions and higher burden of comorbidities have been shown to be associated with poor adherence to antihypertensive regimen.35, 38, 39
Drug‐related factors are also known to be associated with patient adherence to their regimen. Generally, a high burden of comedications increases nonadherent behavior.40 In our study, higher burden of comedications was associated with higher adherence. Two previous studies have reported similar results. One observational study reported lower likelihood of adherence for patients taking three or fewer drugs compared with those taking more than three drugs (OR, 0.77; 95% CI, 0.73–0.95).41 Another cohort study reported a higher likelihood of adherence with five or more concomitant drugs compared with fewer concomitant medications.12 Because patients in our cohort were taking an average of four medications in addition to their antihypertensive drug, it is possible that the high medication burden may have influenced patient's perception of illness, leading to better adherence.42 Next, the use of ACE inhibitors or CCBs was associated with higher adherence after TM compared with those who were treated with diuretics as first‐line monotherapy. Adherence and persistence to an antihypertensive regimen has been shown to vary across drug classes used for first‐line treatment, and these differences are attributable to the relative efficacy and safety of these drug classes.43, 44
Finally, a strong association between patients' health services utilization and adherence has been shown in previous studies.40, 45 Frequent follow‐up visits with healthcare providers have been shown to be associated with higher adherence rates.46 Another study reported higher odds of adherence in patients who had multiple physician visits (OR, 2.2; 95% CI, 1.8–2.5).47 On the contrary, higher inpatient visits were shown to decrease the likelihood of persistence.48 Results of our analysis resonate with these studies. Given that patients receiving TM are at greater risk for nonpersistent behavior,14 it is important that the healthcare provider assesses all these factors when modifying the treatment regimen.
Study Limitations
As with any study, the results of our study should be interpreted within the context of the limitations. Lifestyle factors such as diet and physical activity, which may be associated with adherence, were unavailable. We identified TMs based on patterns inherent in the patients' refill history instead of actual data on BP or tolerability. It is possible that the provider may have modified the patients' regimen for reasons not related to efficacy or tolerability of the first‐line monotherapy (ie, cost, provider preference, or treatment dissatisfaction). Adherence was calculated using a proxy measure (ie, refill history) from the patient's claims data, which may not necessarily indicate that the patient was taking medications as recommended. Our study is observational in nature with inherent limitations related to the possibility of selection bias and unobserved confounding. Finally, results of our study are not generalizable to the US population as our sample is representative of participants covered through a commercial health insurance provider in one state.
Conclusions
FDCs have a superior adherence profile and should be preferred over uptitration and switching for addressing efficacy‐related issues with first‐line monotherapy, particularly among patients with a history of poor adherence to their regimen. For addressing tolerance issues with first‐line monotherapy, switching may be preferred over downtitration if compromise on efficacy is not feasible. Demographic and clinical factors are associated with adherence after a TM, and profiling these factors is important when recommending TMs. Further research is required to generate evidence comparing the long‐term CV outcomes of the alternative TM strategies.
Funding
The data set used in this study was created for dissertational research on the patterns of treatment modifications in hypertensive patients. Data and database development support were provided by the University of Texas School of Public Health/BlueCross Blue Shield of Texas research program in payment systems and policy.
Competing Interests
In the past 3 years, Richard Hansen, PhD, has received consulting funds from Daiichi Sankyo and has provided expert testimony for Allergan and Boehringer Ingelheim. All other authors have no known conflicts of interest.
J Clin Hypertens (Greenwich). 2016;18:934–941. DOI: 10.1111/jch.12799. © 2016 Wiley Periodicals, Inc.
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