Valuing quality of life and improvements in glycemic control in people with type 2 diabetes

Outcomes research is used increasingly for assessing the health economic benefits of new therapeutic programs and interventions. The measurement properties of the outcomes assessment tools are important. If overlooked, they can mislead health care administrators and caregivers regarding the importance and value of these programs and interventions. We reviewed the literature and conducted two analyses to determine the absolute, relative, and operative quality-of-life ranges for people with type 2 diabetes. Quality of life and fasting blood glucose and HbA1c concentrations were measured at baseline and at 4, 8, and 12 weeks of treatment in 569 men and women randomized to either glipizide gastrointestinal therapeutic system (GITS) or placebo in a double-blind, multicenter clinical trial. A subgroup of 290 patients completed a diabetes-specific health states questionnaire at endpoint (week 12 or early termination) rating 10 health-state descriptions on a health thermometer scale ranging from 0 (death) to 100 (full health). Health losses at the higher end of the scale had a greater negative utility than did comparable losses at lower health states, indicating patients' strong preferences for maintaining asymptomatic or mildly symptomatic conditions. Patients rated their current health state at 83.4 +/- 0.8% of full health and indicated that a loss of 27 points below this value would prevent them from living and working as they currently do. The calibration analysis applied to the quality-of-life scales suggested that the targeted range for clinical investigation and quality-of-care evaluation must be more narrowly focused. Effect sizes as seemingly small as 2% (0.25 responsiveness units) on the absolute scale can correspond to quality-of-life losses of 15-20% on the personal operative scale. Differences in glycemic control clearly affected quality of life. Those patients with the best HbA1c responses (decreasing 1.5% or more from baseline) versus those with the worst responses (increasing 1.5% or more from baseline) were separated by 0.6 responsiveness units for the overall quality-of-life summary measure. The calibration analysis suggested that this degree of better glycemic control provides a nearly 50% gain in quality of life according to personal expectations within the operative range. In conclusion, general measures of quality of life may be too crude and insensitive to capture the important gains in health outcomes due to new therapeutic interventions and programs in diabetes. Quality-of-care evaluations for diabetes are at risk of favoring inferior programs with lower costs simply because gains or losses in health outcomes go undetected.