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Evaluation of a multivariate model predicting noncompliance with medication regimens among renal transplant patients
1Department of Surgery, Montefiore Medical Center, Bronx, New York 10467, USA.
Background:
Because noncompliance with medication regimens is a major cause of renal allograft failure, we evaluated the stability over time of two logistic regression models (sets of variables) that predict noncompliance with immunosuppressive regimens.
Methods:
Models were based on questionnaire data from 1402 patients (all over 18, receiving cyclosporine or a cyclosporine-like replacement drug, and with a functioning renal graft). The same questionnaire was completed by a subset of 548 (39.1%) patients approximately 18 months later. The goodness of fit of each model to the new data set was tested.
Results:
The noncompliance logistic regression model including patient beliefs as well as patient and transplant characteristics was an excellent fit to the second data set. A noncompliance model composed of only patient and transplant characteristics fit the new data set less well.
Conclusions:
Clinicians and educators need to take explicit account of renal transplant patients' attitudes when evaluating risks of noncompliance and when developing interventions and educational programs to minimize noncompliance.