Generic Versions of Narrow Therapeutic Index Drugs: A National Survey of Pharmacists' Substitution Beliefs and Practices

The proportional odds model for ordinal logistic regression provides a useful extension of the binary logistic model to situations where the response variable takes on values in a set of ordered categories. The model may be represented by a series of logistic regressions for dependent binary variables, with common regression parameters reflecting the proportional odds assumption. Key to the valid application of the model is the assessment of the proportionality assumption. An approach is described arising from comparisons of the separate (correlated) fits to the binary logistic models underlying the overall model. Based on asymptotic distributional results, formal goodness-of-fit measures are constructed to supplement informal comparisons of the different fits. A number of proposals, including application of bootstrap simulation, are discussed and illustrated with a data example.

A large proportion of Americans are enrolled in 3-tier pharmacy benefit plans. We studied whether patients enrolled in such plans who receive generic or preferred brand-name agents when initiating chronic therapy were more adherent to treatment than those who received nonpreferred brand-name medications. We analyzed pharmacy claims filled between October 1, 2001, and October 1, 2003, from a large health plan for 6 classes of chronic medications: 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors, calcium channel blockers, oral contraceptives, orally inhaled corticosteroids, angiotensin receptor blockers, and angiotensin-converting enzyme inhibitors. We measured adherence as the proportion of days covered (PDC) in each drug class during the first year of therapy. We evaluated how the formulary status of the initial prescription (generic, preferred, or nonpreferred) influenced PDC and adequate adherence, defined as PDC greater than 80%, over the subsequent year. A total of 7532 new prescriptions were filled in 1 of the classes evaluated: 1747 (23.2%) for nonpreferred medications, 4376 (58.1%) for preferred drugs, and 1409 (18.7%) for generic drugs. After controlling for patient sociodemographic characteristics and drug class, PDC was 12.6% greater for patients initiated on generic medications vs nonpreferred medications (58.8% vs 52.2%; P<.001). The PDC was 8.8% greater for patients initiated on preferred vs nonpreferred medications (56.8% vs 52.2%; P<.001). Patients initiated on generic and preferred medications had 62% and 30% greater odds, respectively, of achieving adequate adherence compared with those who received nonpreferred medications. In 3-tier pharmacy benefit plans, prescribing generic or preferred medications within a therapeutic class is associated with improvements in adherence to therapy.

The most commonly prescribed oral anticoagulants worldwide are the vitamin K antagonists (VKAs) such as warfarin. Factors affecting the pharmacokinetics of VKAs are important because deviations from their narrow therapeutic window can result in bleedings due to over-anticoagulation or thrombosis because of under-anticoagulation. In addition to pharmacodynamic interactions (e.g., augmented bleeding risk for concomitant use of NSAIDs), interactions with drugs, foods, herbs, and over-the-counter medications may affect the risk/benefit ratio of VKAs. Direct oral anticoagulants (DOACs) including Factor Xa inhibitors (rivaroxaban, apixaban and edoxaban) and thrombin inhibitor (dabigatran) are poised to replace warfarin. Phase-3 studies and real-world evaluations have established that the safety profile of DOACs is superior to those of VKAs. However, some pharmacokinetic and pharmacodynamic interactions are expected. Herein we present a critical review of VKAs and DOACs with focus on their potential for interactions with drugs, foods, herbs and over-the-counter medications.