Monitoring compliance in clinical trials

Systemic lupus erythematosus in three ethnic groups. XVIII. Factors predictive of poor compliance with study visits

OBJECTIVE

To determine the baseline factors predictive of poor compliance with study visits in a longitudinal multiethnic lupus cohort study.

METHODS

Patients with systemic lupus erythematosus (n = 344) representing a total of 2,069 potential study visits were studied. Of the participants, 24.4% were Hispanic, 43.3% African American, and 32.3% Caucasian. Noncompliance was defined as missing 2 or more study visits. For the purpose of these analyses, visits completed only by review of medical records were considered missing. Baseline socioeconomic-demographic, clinical, and psychosocial features between compliant and noncompliant patients were compared. Variables with P < 0.10 were then entered into a multivariable logistic regression analysis with compliance being the dependent variable.

RESULTS

There were 178 compliant and 166 noncompliant patients. Noncompliant patients were more likely to be young, unmarried, of African American ethnicity, live closer to the medical centers, and have longer disease duration and greater disease activity as assessed by the physician than the compliant patients. In the multivariable model, longer disease duration (P = 0.010), higher level of disease activity (P = 0.009), and shorter distance to travel to study visits (P = 0.046) were predictors of noncompliance; their odds ratios and confidence intervals were below 1.

CONCLUSIONS

We have identified baseline patient characteristics that may predict noncompliance with study visits (disease duration, disease activity, and distance to the medical center). This information will serve as the basis for developing interventions to curtail noncompliance. Our data may have applicability in other lupus cohort studies.

Relationship between psychosocial variables and compliance in patients with heart failure

OBJECTIVE

The purpose of this study was to describe the socio-demographic, psychosocial, and social support variables that predict compliance to treatment regimens in HF patients.

DESIGN AND SETTING

Semistructured interviews were conducted on 82 patients at an outpatient heart failure clinic to gather data related to compliance behaviors. Five standardized instruments were used to gather data on patients' psychosocial health status and perceived social support.

RESULTS

The overall compliance rate was 85.13 (10.01%). Higher levels of compliance (> 90%) were noted for follow-up appointments, medications, smoking, and alcohol cessation. Poor compliance was observed with dietary and exercise recommendations (71% and 53%, respectively). In a multivariate model, higher education, higher mental and physical health status and neuroticism independently contributed to 24% of the variance in overall compliance.

CONCLUSION

The study supports that HF patients had poor compliance with dietary and exercise regimens. Since following a dietary and exercise regimen has been demonstrated to reduce morbidity in this population, strategies to increase compliance should be rigorously pursued [corrected].

Which statin is most efficient for the treatment of hypercholesterolemia? A cost-effectiveness analysis

A review of the cost-effectiveness literature indicated that the hydroxymethylglutaryl coenzyme A-reductase inhibitor fluvastatin is more cost-effective for achieving minor-to-moderate reductions in low-density lipoprotein cholesterol (LDL-C) levels than 3 other statins: lovastatin, pravastatin, and simvastatin. The main goal of this study was to verify the applicability of these conclusions to Spanish health care costs and patterns of resource consumption related to the treatment of hypercholesterolemia. A stochastic simulation model was used to predict both the costs and effects of treating high-risk hypercholesterolemic patients with fluvastatin, lovastatin, pravastatin, or simvastatin. Epidemiologic data were used to find a suitable theoretic probability distribution model for baseline LDL-C values in high-risk hypercholesterolemic patients. The model was then used to generate 10,000 random observations of baseline LDL-C values; the corresponding LDL-C values after a 2-year treatment period were predicted as a function of the baseline value and the percentage reduction expected with a particular statin and dose, according to the results obtained in 2 meta-analyses. The probability of treatment discontinuation was also taken into account using estimates obtained in usual practice. The effects of treatment were expressed as the rate of success in achieving the goal level of LDL-C, as defined in the current Spanish recommendations for the treatment of hypercholesterolemia. The average costs of treatment were computed from both the social and public-financing perspectives, including the cost of lipid-lowering drugs, physician visits, laboratory tests, and days off work, as appropriate. The occurrence of nonscheduled visits and workdays lost because of side effects were taken into account to compute indirect costs relevant to the social perspective. The potential costs of treating side effects were ignored. A cost-effectiveness analysis was performed to compare the cost-effectiveness ratios obtained with each of the 4 statins considered in this study. Model-based predictions of the effects, total costs, and cost-effectiveness ratios were made. Cost-effectiveness ratios were interpreted as the cost per patient meeting the goal of therapy, according to current Spanish recommendations. The data showed that fluvastatin had the lowest cost-effectiveness ratios when LDL-C levels required reduction to < or =25% of baseline levels. In this situation, fluvastatin was more cost-effective than lovastatin, pravastatin, or simvastatin from public-financing and social perspectives.

Measurement of patient compliance and the interpretation of randomized clinical trials

The aim of this review is to demonstrate why the management of compliance, although not an explicit feature of the rules of Good Clinical Practice, is essential to the successful conduct of clinical trials and in correct interpretation of the results. Methods to measure compliance in randomized clinical trials are also described. The relevant literature was retrieved by a manual search of the Cumulated Index Medicus 1975-1989 and a MEDLINE computer search of publications in 1990 using the Medical Subject Headings "patient compliance" and "clinical trials". All retrieved articles are discussed. Research into patient compliance has stagnated because of the lack of a "gold" standard of measurement. Nevertheless, management of compliance at the different stages of clinical trials is necessary; at trial design, compliance should be taken into account in sample size calculations; during the conduct of a trial, compliance should be monitored in order to safeguard the power of the study; and in interpretation of trial results, compliance data are helpful both in order to avoid erroneous conclusions and to enrich the value of the data. Compliance should be measured in all limbs of randomized trials, including the placebo limb, without breaking trial blinding. A classification of compliance behaviour into six types (complier, partial complier, overuser, erratic user, partial dropout and dropout) is proposed, based on the changes in the risk-benefit ratio produced by non-compliance. The use of deuterium oxide, low dose phenobarbitone (2 mg per day), digoxin (2.2 micrograms per day) and the new electronic monitoring devices are suitable methods for measurement in clinical trials.