Integrating cytokines and angiogenic factors and tumour bulk with selected clinical criteria improves determination of prognosis in advanced renal cell carcinoma.

BACKGROUND: In two clinical trials of the vascular endothelial growth factor (VEGF) receptor inhibitor pazopanib in advanced renal cell carcinoma (mRCC), we found interleukin-6 as predictive of pazopanib benefit. We evaluated the prognostic significance of candidate cytokines and angiogenic factors (CAFs) identified in that work relative to accepted clinical parameters. METHODS: Seven preselected plasma CAFs (interleukin-6, interleukin-8, osteopontin, VEGF, hepatocyte growth factor, tissue inhibitor of metalloproteinases (TIMP-1), and E-selectin) were measured using multiplex ELISA in plasma collected pretreatment from 343 mRCC patients participating in the phase 3 registration trial of pazopanib vs placebo (NCT00334282). Tumour burden (per sum of longest diameters (SLD)) and 10 other clinical factors were also analysed for association with overall survival (OS; based on initial treatment assignment). RESULTS: Osteopontin, interleukin-6, and TIMP-1 were independently associated with OS in multivariable analysis. A model combining the three CAFs and five clinical variables (including SLD) had higher prognostic accuracy than the International Metastatic Renal Cell Carcinoma Database Consortium criteria (concordance-index 0.75 vs 0.67, respectively), and distinguished two groups of patients within the original intermediate risk category. CONCLUSIONS: A prognostic model incorporating osteopontin, interleukin-6, TIMP-1, tumour burden, and selected clinical criteria increased prognostic accuracy for OS determination in mRCC patients.

Comparison of discriminatory power and accuracy of three lung cancer risk models.

BACKGROUND: Three lung cancer (LC) models have recently been constructed to predict an individual's absolute risk of LC within a defined period. Given their potential application in prevention strategies, a comparison of their accuracy in an independent population is important. METHODS: We used data for 3197 patients with LC and 1703 cancer-free controls recruited to an ongoing case-control study at the Harvard School of Public Health and Massachusetts General Hospital. We estimated the 5-year LC risk for each risk model and compared the discriminatory power, accuracy, and clinical utility of these models. RESULTS: Overall, the Liverpool Lung Project (LLP) and Spitz models had comparable discriminatory power (0.69), whereas the Bach model had significantly lower power (0.66; P=0.02). Positive predictive values were highest with the Spitz models, whereas negative predictive values were highest with the LLP model. The Spitz and Bach models had lower sensitivity but better specificity than did the LLP model. CONCLUSION: We observed modest differences in discriminatory power among the three LC risk models, but discriminatory powers were moderate at best, highlighting the difficulty in developing effective risk models.