How Decision Makers Learn to Choose Organizational Performance Measures

This study, framed by decision making, program theory, and performance measurement theory, explored the knowledge and experience that enable decision makers to identify organizational performance measures. It used a mixed method, exploratory sequential research design to discover the experience, knowledge, and skills (EKS) senior decision makers felt were important in learning to choose organizational performance measures. From the analyzed interviews, a survey was designed to measure the importance of the EKS characteristics. Qualitative analysis identified 55 life, work, or educational experience; knowledge; or skill characteristics and 23 effective measure characteristics. Regression analysis and PCA were used to extract 6 components. One-way ANOVA found no significant differences in these factors between gender groups, age groups, and process complexity levels, but found differences for decision-making tenure. MANOVA found no significant differences by the same dimensions. The limited sample size and high number of variables confounded component extraction. Further research with a suitable sample size is required before findings can be generalized

89Zr-Bevacizumab PET:Potential Early Indicator of Everolimus Efficacy in Patients with Metastatic Renal Cell Carcinoma

Currently, biomarkers that predict the efficacy of everolimus in metastatic renal cell carcinoma (mRCC) patients are lacking. Everolimus inhibits vascular endothelial growth factor A (VEGF-A) expression. We performed PET scans on mRCC patients with 89Zr-bevacizumab, a VEGF-A–binding antibody tracer. The aims were to determine a change in tumor tracer uptake after the start of everolimus and to explore whether 89Zr-bevacizumab PET can identify patients with early disease progression. Methods: 89Zr-bevacizumab PET was done before and 2 and 6 wk after the start of everolimus, 10 mg/d, in mRCC patients. Routine CT scans were performed at baseline and every 3 mo thereafter. Tumor tracer uptake was quantified using SUVmax. The endpoints were a change in tumor tracer uptake and treatment response on CT after 3 mo. Results:Thirteen patients participated. The median SUVmax of 94 tumor lesions was 7.3 (range, 1.6–59.5). Between patients, median tumor SUVmax varied up to 8-fold. After 2 wk, median SUVmax was 6.3 (1.7–62.3), corresponding to a mean decrease of 9.1% (P < 0.0001). Three patients discontinued everolimus early. At 6 wk, a mean decrease in SUVmax of 23.4% compared with baseline was found in 70 evaluable lesions of 10 patients, with a median SUVmax of 5.4 (1.1–49.4, P < 0.0001). All 10 patients who continued treatment had stable disease at 3 mo. Conclusion: Everolimus decreases 89Zr-bevacizumab tumor uptake. Further studies are warranted to evaluate the predictive value of 89Zr-bevacizumab PET for everolimus antitumor efficacy