Diabetes patients had higher scores on the Potential for Benefit Scale (PBS) if they had lower blood sugar levels and adhered more closely to treatment.
There is considerable variation in how patients respond to a given treatment. Several factors determine treatment response: disease severity, physiologic, biologic, or genetic factors, vulnerability to side effects and the presence of comorbid conditions. Practicing physicians need a way to predict how treatment will affect specific subgroups of patients. Researchers have used individual measures to identify subgroups. A composite measure, summarizing individual characteristics, could improve the precision of clinical studies and enable clinicians to maximize treatment benefits.
This article describes the development of a new composite measure of potential treatment response, the PBS. The authors collected data for patients with at least one visit for Type-2 Diabetes within the year prior to the study. The conceptual framework for the study integrated several approaches to health behavior and illness management; the framework proposed that: “immutable characteristics” (e.g., age or race/ethnicity) and “mutable characteristics” (e.g., health profiles and treatment contexts), contribute to the formation of specific patient subgroups, each demonstrating a potential benefit from treatment.
- Patients who demonstrated the highest levels of treatment adherence were in the highest PBS quartile (i.e., they showed the greatest potential treatment benefit); those in the lowest quartile had the poorest adherence levels.
- Patients with the lowest levels of glycated hemoglobin were in the highest PBS quartile.
This article describes an initial test of the PBS, a composite measure of patient treatment response. The results suggest that PBS can predict treatment response among patient subgroups.