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Original Contribution |

Persistence of Use of Lipid-Lowering Medications:  A Cross-National Study FREE

Jerry Avorn, MD; Johanne Monette, MD, MSc; Anne Lacour, PhD; Rhonda L. Bohn, MPH; Mark Monane, MD, MS; Helen Mogun, MS; Jacques LeLorier, MD, PhD
[+] Author Affiliations

From the Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Drs Avorn, Monette, and Monane and Mss Bohn and Mogun); and the Centre de Recherche, Hôtel-Dieu de Montréal, Université de Montréal, Montreal, Quebec (Drs Lacour and LeLorier).


JAMA. 1998;279(18):1458-1462. doi:10.1001/jama.279.18.1458.
Text Size: A A A
Published online

Context.— Although clinical trials have demonstrated the benefits of lipid-lowering therapy, little is known about how these drugs are prescribed or used in the general population.

Objective.— To estimate predictors of persistence with therapy for lipid-lowering drug regimens in typical populations of patients in the United States and Canada.

Design.— A cohort study defining all prescriptions filled for lipid-lowering drugs during 1 year, as well as patients' demographic and clinical characteristics.

Setting.— New Jersey's Medicaid and Pharmacy Assistance for the Aged and Disabled programs and Quebec's provincial medical care program.

Patients.— All continuously enrolled patients older than 65 years who filled 1 or more prescriptions for lipid-lowering drugs (N=5611 in the US programs, and N = 1676 drawn from a 10% sample in Quebec).

Main Outcome Measures.— Proportion of days during the study year for which patients had filled prescriptions for lipid-lowering drugs; predictors of good vs poor persistence with therapy.

Results.— In both populations, patients failed to fill prescriptions for lipid-lowering drugs for about 40% of the study year. Persistence rates with 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors were significantly higher than those seen with cholestyramine (64.3% vs 36.6% of days with drug available, respectively). Patients with hypertension, diabetes, or coronary artery disease had significantly higher rates of persistence with lipid-lowering regimens. In New Jersey, multivariable analysis indicated that the poorest patients (those enrolled in Medicaid) had lower rates of drug use than less indigent patients (those enrolled in Pharmacy Assistance for the Aged and Disabled) after adjusting for possible confounders, despite virtually complete drug coverage in both programs. When rates of use were measured in the US population for the 5 years following the study year, only 52% of surviving patients who were initially prescribed lipid-lowering drugs were still filling prescriptions for this drug class.

Conclusion.— In all populations studied, patients who were prescribed lipid-lowering drug regimens remained without filled prescriptions for over a third of the study year on average. Rates of persistence varied substantially with choice of agent prescribed, comorbidity, and socioeconomic status, despite universal coverage of prescription drug costs. After 5 years, about half of the surviving original cohort in the United States had stopped using lipid-lowering therapy altogether.

Figures in this Article

CLINICAL TRIALS have documented the clinical utility of lipid-lowering regimens in reducing cardiac morbidity and mortality in a variety of populations. However, evaluating the effectiveness of these drugs throughout the health care system requires an understanding of drug use and outcomes in actual free-living patient populations, as compared with rates seen in subjects recruited into controlled clinical trials.1 While randomized trials are invaluable in determining the efficacy of regimens under well-controlled circumstances, by definition they include only volunteer subjects and physicians, with medication provided and monitored in a setting of considerably greater surveillance than exists in routine practice.

Although some studies have examined use of lipid-lowering medications in health maintenance organizations,1,2 little is known about how these drugs are taken outside of managed care settings, and among patients older than 65 years, minorities, and the poor. Given the very large proportion of cardiac morbidity and mortality that occurs among the older population and the disproportionate burden of such outcomes among blacks and the poor, it is critical to understand how lipid-lowering drugs are used in patient populations at highest risk for cardiac disease.

Persistence with long-term medication of various kinds has been found to be approximately 50% in several studies.1,3,4 Lack of persistent use of a drug for a chronic condition may result from patient noncompliance or from a physician's decision to discontinue therapy if adverse effects are believed to outweigh benefits. Old age per se is not a risk factor for nonpersistence, but the number of prescribed medications is.5 Controversy persists on the role of lipid-lowering agents in the very old,68 but current evidence suggests that older patients can also benefit from reduction of hypercholesterolemia,9 and lifelong treatment is generally necessary to manage this condition.

To measure actual use rates of lipid-lowering drugs in typical patients, we evaluated filled prescription rates and the factors associated with such use in 3 populations of patients receiving care in noncapitated settings, yet who were covered by health insurance programs that provided medications at little or no cost to enrollees.

Sources of Data

The US study population was drawn from enrollees in the New Jersey Medicaid program and that state's Pharmacy Assistance for the Aged and Disabled (PAAD) program for the period from January 1, 1990, to July 1, 1991. During the study period, eligibility for Medicaid required an annual income below the poverty level. By contrast, the state's PAAD program provided drug coverage to a less indigent population, with income ceilings of $15700 if single and $19250 if married. Information on all filled prescriptions was extracted from the paid claims files of these programs. Each such record contained information on the specific drug dispensed, dosage, quantity dispensed, and number of days' supply. Previous studies have reported a high degree of reliability and validity of Medicaid prescription data.1012 We then linked drug use data with information on other health service use to identify diagnoses and other clinical services used during the study period. All personal identifiers were removed prior to analysis to protect the confidentiality of program participants.

The Canadian population was drawn from a 10% random sample of the administrative files of the universal health care system of Quebec, the Régie de l'Assurance Maladie du Québec (RAMQ), covering the same time period. All Quebec residents 65 years and older are automatically enrolled in this program, and RAMQ administrative files contain demographic information on all enrollees. As in Medicaid, detailed information is also available for all medical services provided and prescriptions filled. Each claim record identifies the type of service or procedure provided and the location and type of institution where the service was provided. Each pharmacy record includes a drug code that identifies the name of the product, dosage, manufacturer, and dosage form, as well as data on cost, quantity dispensed, duration of the prescription, prescribing physician, and dispensing pharmacist. These data have high reliability and validity as well.13

During the study period, New Jersey's Medicaid and Quebec's RAMQ programs had no deductible or maximum benefit for drugs, and charged no copayment for prescribed medications, ensuring complete ascertainment of drug use. New Jersey's PAAD program had no deductible and no maximum benefit but had a nominal $2 copayment for each prescription filled. None of the programs had any formulary restrictions.

Identification of Study Subjects

Lipid-lowering drugs included all those in use during the study period: clofibrate, colestipol, cholestyramine, gemfibrozil, niacin, probucol, and 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors, including lovastatin, pravastatin, and simvastatin. We identified all enrollees in the New Jersey Medicaid and PAAD programs and in the Quebec RAMQ program who were 65 years or older on January 1, 1989, and who filled at least 1 prescription for any lipid-lowering drug. The index date for a given study subject was defined as the first date during 1990 on which a patient filled a prescription for 1 of these drugs. To ascertain ongoing program participation, subjects were required to have filled at least 1 prescription for any drug (including non–lipid-reducing drugs) during each of the 3 6-month periods preceding the index date as well as in each of the 3 consecutive 6-month periods following the index date. However, patients who died after the index date were retained in the analysis until their date of death.

New users were defined as those who had no prior lipid-lowering drug prescription filled during the 365 days preceding the index date. Long-term users were those who had filled 1 or more previous lipid-lowering drug prescriptions during the 365 days preceding the index date. The US subjects were required to have no nursing home residency during the study period to ensure comparability with the Canadian population, since data on medications dispensed to nursing home residents are not available in the Quebec RAMQ database.

We reviewed all health care use by each subject to ascertain the presence of markers for probable coronary artery disease (CAD), hypertension, and diabetes in the year prior to the index date. Markers for CAD included diagnosis of myocardial infarction or acute or chronic ischemic heart disease, coronary artery bypass graft or angioplasty, or the use of nitroglycerine and related nitrates. Markers for diabetes included the presence of that diagnosis or its specific complications, or the use of insulin or oral hypoglycemic agents. Markers for hypertension included the relevant diagnoses or complications identified as directly related to this condition, or the prescription of thiazides, angiotensin-converting enzyme inhibitors, or other common antihypertensive drugs. Calcium channel blocker or β-blocker use was considered a marker for hypertension if the patient did not have any markers for CAD. For each patient, we also ascertained other factors potentially related to persistence, including age, sex, number of prescriptions filled for other drugs, frequency of outpatient visits, and days of acute hospitalization in the year preceding the index date.

Definition of Persistence

Persistence was measured by determining the quantity dispensed and number of days' supply data recorded on each filled prescription for each patient. This made it possible to measure the number of days a patient had lipid-reducing medication available during the 365-day study period (days covered). For each cohort member, the denominator represented the total duration of possible drug use during the study year, generally 365 days. (For patients who died within the 365 days following the index date, the denominator represented the total duration of days from the index date to the date of death.) For patients simultaneously taking 2 or more agents in this class, if 1 such prescription was dispensed during the time interval of a previous prescription, the overlapping number of days of available therapy was not duplicated. This analysis was repeated for all prescriptions for lipid-lowering drugs filled by each patient in the 365 days after the index date for each patient.

To estimate persistence with specific agents, we first classified subjects according to the lipid-lowering prescription filled on their index date, and excluded the small number of patients who on this date filled multiple prescriptions from this class. Subsequent analyses measured the rate of switching from and to each drug studied. Finally, to build a multiple regression model of predictors of persistence, we categorized subjects into 2 groups, those whose filled prescriptions were adequate to cover 80% or more of the study year vs those whose filled prescriptions covered less than 80% of the study year.

Long-term Follow-up

For the US populations, we obtained complete filled prescription data from January 1, 1990, through June 30, 1996, for the entire original cohort. We then examined these data for the period July 1, 1995, to June 30, 1996, to measure long-term drug use rates for all surviving subjects.

Statistical Analysis

The likelihood of 80% or more persistence with lipid-lowering therapy vs 80% or less persistence was estimated from odds ratios calculated through unconditional logistic regression14 using the SAS CATMOD procedure.15 Confidence intervals for the estimated odds ratios and significance tests for differences from the null value were calculated using the estimated SEs.16 Potential determinants of persistence in the regression model included age; sex; presence of markers for hypertension, diabetes, and CAD; number of filled prescriptions excluding lipid-lowering drugs; number of outpatient visits; and number of days of hospitalization during the preceding year. Two-tailed P values less than .05 were considered significant.

Measurement of Compliance

In New Jersey, 5611 patients met study criteria, as did 1676 patients in Quebec. During the 1-year study period, 79 patients died in the New Jersey population and 47 in Quebec. Analysis of filled prescriptions revealed that average persistence with lipid-lowering therapy, measured as the mean percentage of days in the study year in which patients had filled prescriptions available, was 59.0% (±30.3%; median, 62.2%) for the New Jersey population and 62.6% (±29.0%; median, 70.1%) for the Quebec population. In New Jersey and in Quebec, respectively, 11.6% and 14.8% failed to fill any additional prescriptions for a lipid-lowering drug after filling the prescription on their index date, and 34.1% and 38.9% of patients had medication available during 80% or more of the year.

The most commonly prescribed lipid-lowering drugs were, in decreasing order, an HMG-CoA reductase inhibitor (New Jersey, 39.4%; Quebec, 28.6%) and gemfibrozil (New Jersey, 35.9%; Quebec, 30.1%), followed by cholestyramine in New Jersey (13.2%) and by nicotinic acid in Quebec (16.5%). Clofibrate was used by 86 patients in the New Jersey population of lipid-lowering drug users, and by 186 in Quebec. On the index date in the New Jersey population, only 39 patients (0.7%) were simultaneously prescribed 2 agents from this class, of whom 21 were receiving cholestyramine in combination with another lipid-lowering drug. In Quebec, 20 (1.1%) were simultaneously prescribed 2 such agents on the index date, of whom 10 were receiving cholestyramine in combination with another lipid-lowering drug.

Compliance According to Drug Type

In both the United States and Canada, the highest compliance was associated with the use of an HMG CoA reductase inhibitor (64.3% ± 29.8% of days covered), while the lowest was associated with the use of cholestyramine (36.6% ± 29.1% of days covered) (Figure 1). No differences were seen among the reductase inhibitors. After controlling for individual patients' demographic and clinical characteristics, US patients who were prescribed an HMG-CoA reductase inhibitor had an odds ratio for good persistence of about double that seen in patients prescribed other lipid-lowering drugs, particularly bile acid sequestrants cholestyramine and colestipol (odds ratio, 2.01; 95% confidence interval, 1.79-2.25). For each drug, persistence was similar in both populations, but slightly higher in Quebec than in New Jersey.

Graphic Jump Location
Figure 1.—Persistence measured as the proportion of days covered for each specific lipid-lowering drug regimen. Patients are classified according to the prescription filled on the index date. HMG-CoA indicates 3-hydroxy-3-methylglutaryl coenzyme A.
Relationship Between Patient Characteristics and Persistence

Table 1 presents the demographic characteristics of patients with persistence of 80% or more compared with patients with persistence of less than 80%. Logistic regression models revealed the same associations for predictors of persistence found by univariate analysis in both populations, so only results for the multivariate logistic regression analyses are reported in Table 2. In both populations, better levels of persistence were associated with the presence of risk factors for future cardiac events, including hypertension, diabetes, and CAD. As expected, long-term lipid-lowering drug users had significantly higher persistence than new users (Table 2). These findings did not vary if cutoffs other than 80% were used.

Table Graphic Jump LocationTable 2.—Relationship Between Patient Characteristics and High Persistence*

Persistence did not differ by sex, but tended to decrease with increasing age. In the New Jersey population, Medicaid enrollees were much less likely than PAAD enrollees to have high rates of persistence, even after controlling for the demographic and clinical factors described. New Jersey patients with prescriptions for more than 16 drug products per year were less likely to continue to fill prescriptions for lipid-lowering drugs; a similar trend was seen in Quebec. Excluding all patients who filled only a single prescription for a lipid-lowering drug did not alter the findings.

Switching of Therapies

We classified patients according to the agent prescribed on their index date and also identified those who were switched to another lipid-lowering drug or had a second one added during the study year. In both populations, about 15% of patients had an additional such agent prescribed after their index date (Figure 2). In New Jersey, a second drug was prescribed to 25.6% of patients taking cholestyramine, 25.6% of those taking probucol, but only 10.0% of those taking an HMG-CoA reductase inhibitor. These proportions were virtually identical in the Quebec population. In both populations an HMG-CoA reductase inhibitor was the agent most commonly added or substituted, followed by gemfibrozil and cholestyramine.

Graphic Jump Location
Figure 2.—Medication use among patients who never filled a second prescription, or who switched to another drug class. For a given drug class, each bar indicates the proportion who stopped therapy entirely or switched to another lipid-lowering drug.
Long-term Follow-up

Of the 5611 patients originally studied in the US cohorts, 4092 (72.9%) were still alive and receiving services from the Medicaid or PAAD programs during the period from July 1, 1995, through June 30, 1996. Only about half of these patients who were taking lipid-lowering drugs in the original study year filled 1 or more prescriptions for any lipid-lowering drug during the follow-up year of 1995-1996 (2111 or 51.6%).

Several methods are available to study actual drug use in typical practice settings. Pill counts and drug level determinations (when available) are reliable but impractical on a population-wide basis. Patient recall is frequently inaccurate and biased by a reluctance to admit "improper" behavior. Subjective estimates of persistence by physicians and nurses are often unreliable means of assessing patients' medication use,17 with clinicians often failing to detect markedly poor compliance in routine practice situations.18

Analyzing automated records of prescriptions actually filled makes it possible to use a standardized measure from pharmacy data or a large fiscal database to define continuity of medication use and gaps in therapy. Although filling a prescription is not identical to consuming the drug, patterns of ongoing prescription filling represent the most accurate way of estimating actual medication use in large populations. These data from 3 large patient populations in 2 countries present a picture of striking nonpersistence with lipid-lowering therapy. Incomplete persistence with a prescribed medication can contribute substantially to the variability observed in its therapeutic outcome.19 It has been estimated that good persistence will result in a 39% reduction in cholesterol level, while poor persistence will result in a decrease of only 11%.20 The data presented here come from diverse populations of typical patients and physicians, enhancing their generalizability to routine health care practices. The period of time described preceded the widespread dissemination of data from several recent studies, and it is possible that physicians and patients pursue lipid-lowering regimens more vigorously at present than in previous years. However, the follow-up data through mid-1996 allow little room for such optimism. Furthermore, in the case of hypertension, poor persistence has been reported years after the publication of pivotal studies documenting the efficacy of these drugs.21

The data demonstrate better persistence with HMG-CoA reductase inhibitors and considerably worse persistence with the bile acid sequestrants, especially in the US populations. These findings may reflect the greater convenience of dosing regimens for the reductase inhibitors, or the differing side-effect profiles of these drugs.2224 The need for more detailed patient counseling for the more demanding niacin or bile acid sequestrant regimens may also have played a role. Even after adjustment for health care resource use, patients with hypertension, diabetes, and CAD adhered to their regimens more consistently than did those without such risk factors.

Of particular concern is our observation that in the US data, even after controlling for clinical and demographic differences, Medicaid enrollees, who are indigent, were only 58% as likely to continue their therapy as PAAD enrollees, who have higher annual incomes. Previous analyses have not consistently found sociodemographic factors to be associated with lower rates of adherence to drug regimens.2528 However, Medicaid patients, by virtue of greater poverty, may differ in their access to health services as well as in level of education or basic health knowledge, which may explain their lower rates of medication use.

These findings depict persistence of drug use in a set of fiscally generous insurance systems. The Medicaid, PAAD, and Quebec systems all provide comprehensive coverage of drug benefits for participating patients. Our data are a reminder that adequate payment mechanisms are not in themselves sufficient to guarantee appropriate use of covered services, and persistence is likely to be even worse for these drugs in patients who must bear their considerable cost out-of-pocket.29 In a patient population without drug coverage, the higher use rates seen with the newer agents compared with niacin might be reduced because of their cost differential. Research is needed on drug-use patterns in the large proportion of patients of all ages who receive little or no reimbursement for pharmacy expenditures.

Discontinuing beneficial medication can cause preventable morbidity and impose a considerable clinical and financial burden on the health care system.30 As additional evidence emerges on the utility of lipid reduction in reducing cardiac morbidity and mortality, a comprehensive approach will be required to the care of patients with hyperlipidemia, including monitoring of filled prescription patterns, patient and clinician education, and reinforcement of patients' knowledge of their risk factor status and its management.

Andrade SE, Walker AM, Gottlieb LK.  et al.  Discontinuation of antihyperlipidemic drugs.  N Engl J Med.1995;332:1125-1131.
Oster G, Borok GM, Menzin J.  et al.  Cholesterol-Reduction Intervention Study (CRIS).  Arch Intern Med.1996;156:731-739.
Cramer JA, Mattson RH, Prevey ML, Scheyer RD, Ouellette VL. How often is medication taken as prescribed?  JAMA.1989;261:3273-3277.
Monane M, Bohn R, Gurwitz JH, Glynn RJ, Avorn J. Noncompliance with congestive heart failure therapy in the elderly.  Arch Intern Med.1994;154:433-437.
Salzman C. Medication compliance in the elderly.  J Clin Psychiatry.1995;56(suppl 1):18-22.
American College of Physicians.  Guidelines for using serum cholesterol, high-density lipoprotein cholesterol, and triglyceride levels as screening tests for preventing coronary heart disease in adults.  Ann Intern Med.1996;124:515-517.
Krumholz HM, Seeman TE, Merrill SS.  et al.  Lack of association between cholesterol and coronary heart disease mortality and morbidity and all-cause mortality in persons older than 70 years.  JAMA.1994;272:1335-1340.
Hulley SB, Newman TB. Cholesterol in the elderly: is it important?  JAMA.1994;272:1372-1374.
Sacks FM. The effect of pravastatin on coronary events after myocardial infarction in patients with average cholesterol levels.  N Engl J Med.1996;335:1001-1009.
Bright RA, Avorn J, Everitt DE. Medicaid data as a resource for epidemiologic studies: strengths and limitations.  J Clin Epidemiol.1989;42:937-945.
Avorn J, Soumerai SB. Improving drug-therapy decisions through educational outreach.  N Engl J Med.1983;308:1457-1463.
Ray WA, Griffin MR. Use of Medicaid data for pharmacoepidemiology.  Am J Epidemiol.1989;129:837-849.
Tamblyn R, Lavoie G, Petrella L, Monette J. The use of prescription claims database in pharmacoepidemiological research.  J Clin Epidemiol.1995;48:999-1009.
Cox DR. Analysis of Binary Data.  London, England: Chapman & Hall; 1990.
SAS Institute Inc.  The CATMOD procedure. In: SAS/STAT User's Guide. Release 6.03. Cary, NC: SAS Institute Inc; 1988:405-517.
Rosner B. Hypothesis testing: categorical data. In: Fundamentals of Biostatistics. Boston, Mass: PWS Publishers; 1986:302-367.
Caron HS, Roth HP. Patients' cooperation with a medical regimen.  JAMA.1968;203:922-926.
Evans L, Spelman M. The problem of noncompliance with drug therapy.  Drugs.1983;25:63-76.
Efron B, Fedman D. Compliance as an explanatory variable in clinical trials.  J Am Stat Assoc.1991;86(413):9-26.
National Council on Patient Information and Education.  Talk About Information and Education.  Washington, DC: National Council on Patient Information and Education; 1990.
Monane M, Bohn RL, Gurwitz JH, Glynn RJ, Levin R, Avorn J. Compliance with antihypertensive therapy among elderly Medicaid enrollees.  Am J Public Health.1996;86:1805-1808.
Bradford RH, Shear CL, Chremos AN.  et al.  Expanded Clinical Evaluation of Lovastatin (EXCEL) study results, I.  Arch Intern Med.1991;151:43-49.
Mellies MJ, DeVault AR, Kassler-Taub K, McGovern ME, Pan HY. Pravastatin experience in elderly and non-elderly patients.  Atherosclerosis.1993;101:97-110.
LaRosa JC, Applegate W, Crouse III JR.  et al.  Cholesterol lowering in the elderly.  Arch Intern Med.1994;154:529-539.
Stephenson BJ, Rowe BH, Haynes B, Macharia WM, Leon G. Is this patient taking the treatment as prescribed?  JAMA.1993;269:2779-2781.
Rosenstock IM. Adoption and maintenance of lifestyle modifications.  Am J Prev Med.1988;4:349-352.
Spaeth GL. Visual loss in a glaucoma clinic, I.  Invest Ophthalmol.1970;9:73-82.
Hershey JC, Morton BG, Davis JB, Reichgott MJ. Patient compliance with antihypertensive medication.  Am J Public Health.1980;70:1081-1089.
Glickman L, Bruce EA, Caro FG, Avorn J. Physicians' knowledge of drug costs for the elderly.  J Am Geriatr Soc.1994;42:992-996.
Donovan JL. Patient decision making: the missing ingredient in compliance research.  Int J Technol Assess Health Care.1995;11:443-455.

Figures

Graphic Jump Location
Figure 1.—Persistence measured as the proportion of days covered for each specific lipid-lowering drug regimen. Patients are classified according to the prescription filled on the index date. HMG-CoA indicates 3-hydroxy-3-methylglutaryl coenzyme A.
Graphic Jump Location
Figure 2.—Medication use among patients who never filled a second prescription, or who switched to another drug class. For a given drug class, each bar indicates the proportion who stopped therapy entirely or switched to another lipid-lowering drug.

Tables

Table Graphic Jump LocationTable 2.—Relationship Between Patient Characteristics and High Persistence*

References

Andrade SE, Walker AM, Gottlieb LK.  et al.  Discontinuation of antihyperlipidemic drugs.  N Engl J Med.1995;332:1125-1131.
Oster G, Borok GM, Menzin J.  et al.  Cholesterol-Reduction Intervention Study (CRIS).  Arch Intern Med.1996;156:731-739.
Cramer JA, Mattson RH, Prevey ML, Scheyer RD, Ouellette VL. How often is medication taken as prescribed?  JAMA.1989;261:3273-3277.
Monane M, Bohn R, Gurwitz JH, Glynn RJ, Avorn J. Noncompliance with congestive heart failure therapy in the elderly.  Arch Intern Med.1994;154:433-437.
Salzman C. Medication compliance in the elderly.  J Clin Psychiatry.1995;56(suppl 1):18-22.
American College of Physicians.  Guidelines for using serum cholesterol, high-density lipoprotein cholesterol, and triglyceride levels as screening tests for preventing coronary heart disease in adults.  Ann Intern Med.1996;124:515-517.
Krumholz HM, Seeman TE, Merrill SS.  et al.  Lack of association between cholesterol and coronary heart disease mortality and morbidity and all-cause mortality in persons older than 70 years.  JAMA.1994;272:1335-1340.
Hulley SB, Newman TB. Cholesterol in the elderly: is it important?  JAMA.1994;272:1372-1374.
Sacks FM. The effect of pravastatin on coronary events after myocardial infarction in patients with average cholesterol levels.  N Engl J Med.1996;335:1001-1009.
Bright RA, Avorn J, Everitt DE. Medicaid data as a resource for epidemiologic studies: strengths and limitations.  J Clin Epidemiol.1989;42:937-945.
Avorn J, Soumerai SB. Improving drug-therapy decisions through educational outreach.  N Engl J Med.1983;308:1457-1463.
Ray WA, Griffin MR. Use of Medicaid data for pharmacoepidemiology.  Am J Epidemiol.1989;129:837-849.
Tamblyn R, Lavoie G, Petrella L, Monette J. The use of prescription claims database in pharmacoepidemiological research.  J Clin Epidemiol.1995;48:999-1009.
Cox DR. Analysis of Binary Data.  London, England: Chapman & Hall; 1990.
SAS Institute Inc.  The CATMOD procedure. In: SAS/STAT User's Guide. Release 6.03. Cary, NC: SAS Institute Inc; 1988:405-517.
Rosner B. Hypothesis testing: categorical data. In: Fundamentals of Biostatistics. Boston, Mass: PWS Publishers; 1986:302-367.
Caron HS, Roth HP. Patients' cooperation with a medical regimen.  JAMA.1968;203:922-926.
Evans L, Spelman M. The problem of noncompliance with drug therapy.  Drugs.1983;25:63-76.
Efron B, Fedman D. Compliance as an explanatory variable in clinical trials.  J Am Stat Assoc.1991;86(413):9-26.
National Council on Patient Information and Education.  Talk About Information and Education.  Washington, DC: National Council on Patient Information and Education; 1990.
Monane M, Bohn RL, Gurwitz JH, Glynn RJ, Levin R, Avorn J. Compliance with antihypertensive therapy among elderly Medicaid enrollees.  Am J Public Health.1996;86:1805-1808.
Bradford RH, Shear CL, Chremos AN.  et al.  Expanded Clinical Evaluation of Lovastatin (EXCEL) study results, I.  Arch Intern Med.1991;151:43-49.
Mellies MJ, DeVault AR, Kassler-Taub K, McGovern ME, Pan HY. Pravastatin experience in elderly and non-elderly patients.  Atherosclerosis.1993;101:97-110.
LaRosa JC, Applegate W, Crouse III JR.  et al.  Cholesterol lowering in the elderly.  Arch Intern Med.1994;154:529-539.
Stephenson BJ, Rowe BH, Haynes B, Macharia WM, Leon G. Is this patient taking the treatment as prescribed?  JAMA.1993;269:2779-2781.
Rosenstock IM. Adoption and maintenance of lifestyle modifications.  Am J Prev Med.1988;4:349-352.
Spaeth GL. Visual loss in a glaucoma clinic, I.  Invest Ophthalmol.1970;9:73-82.
Hershey JC, Morton BG, Davis JB, Reichgott MJ. Patient compliance with antihypertensive medication.  Am J Public Health.1980;70:1081-1089.
Glickman L, Bruce EA, Caro FG, Avorn J. Physicians' knowledge of drug costs for the elderly.  J Am Geriatr Soc.1994;42:992-996.
Donovan JL. Patient decision making: the missing ingredient in compliance research.  Int J Technol Assess Health Care.1995;11:443-455.

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Phytonutrients as therapeutic agents. J Complement Integr Med Published online Jul 22, 2014.;