Technology transfer model for Austrian higher education institutions

The aim of this paper is to present the findings of a PhD research (Heinzl 2007, Unpublished PhD Thesis) conducted on the Universities of Applied Sciences in Austria. Four of the models that emerge from this research are: Generic Technology Transfer Model (Sect. 5.1); Idiosyncrasies Model for the Austrian Universities of Applied Sciences (Sect. 5.2); Idiosyncrasies-Technology Transfer Effects Model (Sect. 5.3); Idiosyncrasies-Technology Transfer Cumulated Effects Model (Sect. 5.3). The primary and secondary research methods employed for this study are: literature survey, focus groups, participant observation, and interviews. The findings of the research contribute to a conceptual design of a technology transfer system which aims to enhance the higher education institutions' technology transfer performance. © 2012 Springer Science+Business Media, LLC

The effects of idiosyncrasies of Austrian universities of applied sciences on their technology transfer performance

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Prognosis of patients with hepatocellular carcinoma treated with immunotherapy - development and validation of the CRAFITY score.

BACKGROUND Immunotherapy with atezolizumab plus bevacizumab represents the new standard of care in systemic front-line treatment of hepatocellular carcinoma (HCC). Prognostic biomarkers are an unmet need. METHODS Patients with HCC put on PD-(L)1-based immunotherapy in 6 European centers (training set; n=190) and in 8 European centers (validation set; n=102) were included. We investigated the prognostic value of baseline variables on overall survival by using a Cox model in the training set and developed the easily applicable CRAFITY (CRP and AFP in ImmunoTherapY) score. The score was validated in the independent, external cohort, and evaluated in a cohort of patients treated with sorafenib (n=204). RESULTS Baseline serum alpha-fetoprotein ≥100 ng/ml (HR, 1.7; p=0.007) and C-reactive protein ≥1 mg/dl (HR, 1.7; p=0.007) were identified as independent prognostic factors in multivariable analysis and were used to develop the CRAFITY score. Patients who fulfilled no criterion (0 points; CRAFITY-low) had the longest median overall survival (27.6 (95%CI, 19.5-35.8) months), followed by those fulfilling one criterion (1 point; CRAFITY-intermediate; 11.3 (95%CI, 8.0-14.6) months), and patients meeting both criteria (2 points; CRAFITY-high; 6.4 (95%CI, 4.8-8.1) months; p<0.001). Additionally, best radiological response (complete response/partial response/stable disease/progressive disease) was significantly better in patients with lower CRAFITY score (CRAFITY-low:9%/20%/52%/20% vs. CRAFITY-intermediate:3%/25%/36%/36% vs. CRAFITY-high:2%/15%/22%/61%; p=0.003). These results were confirmed in the independent validation set as well as in different subgroups including Child-Pugh A and B, performance status 0 and ≥1, and first-line and later lines. In the sorafenib cohort, CRAFITY was associated with survival, but not radiological response. CONCLUSIONS The CRAFITY score is associated with survival and radiological response. The score may help with patient counseling, but requires prospective validation. LAY SUMMARY The immunotherapy based regimen of atezolizumab plus bevacizumab represents the new standard of care in systemic first-line therapy of hepatocellular carcinoma (HCC). Biomarkers to predict treatment outcome are an unmet need in patients undergoing immunotherapy for HCC. We developed and externally validated a score that predicts outcome in patients with HCC undergoing immunotherapy with immune checkpoint blockers