Minimal residual disease monitoring in multiple myeloma: a comparison between allelic-specific oligonucleotide real-time quantitative polymerase chain reaction and flow cytometry.

BACKGROUND AND OBJECTIVES: Minimal residual disease (MRD) studies are useful in multiple myeloma (MM). However, the definition of the best technique and clinical utility are still unresolved issues. The aim of this study was to analyze and compare the clinical utility of MRD studies in MM with two different techniques: allelic-specific oligonucleotide real-time quantitative PCR (ASO-RQ-PCR), and flow cytometry (FCM). DESIGN AND METHODS: Bone marrow samples from 32 MM patients who had achieved complete response after transplantation were evaluated by ASO-RQ-PCR, using TaqMan technology, and multiparametric FCM. RESULTS: ASO-RQ-PCR was only applicable in 75% of patients for a variety of technical reasons, while FCM was applicable in up to 90%. Therefore, simultaneous PCR/FCM analysis was possible in only 24 patients. The number of residual tumor cells identified by both techniques was very similar (mean=0.29%, range=0.001-1.61%, correlation coefficient=0.861). However, RQ-PCR was able to detect residual myelomatous cells in 17 patients while FCM only did so in 11; thus, 6 cases were FCM negative but PCR positive, all of them displaying a very low number of clonal cells (median=0.014%, range=0.001-0.11). Using an MRD threshold of 0.01% (10(-4)) two risk groups with significantly different progression-free survival could be identified by either PCR (34 vs. 15m, p=0.04) or FCM (27 vs. 10m, p=0.05). INTERPRETATION AND CONCLUSIONS: Although MRD evaluation by ASO-RQ-PCR is slightly more sensitive and specific than FCM, it is applicable in a lower proportion of MM patients and is more time-consuming, while both techniques provide similar prognostic information.

Impacts of FDI Renewable Energy Technology Spillover on China's Energy Industry Performance

Environmental friendly renewable energy plays an indispensable role in energy industry development. Foreign direct investment (FDI) in advanced renewable energy technology spillover is promising to improve technological capability and promote China’s energy industry performance growth. In this paper, the impacts of FDI renewable energy technology spillover on China’s energy industry performance are analyzed based on theoretical and empirical studies. Firstly, three hypotheses are proposed to illustrate the relationships between FDI renewable energy technology spillover and three energy industry performances including economic, environmental, and innovative performances. To verify the hypotheses, techniques including factor analysis and data envelopment analysis (DEA) are employed to quantify the FDI renewable energy technology spillover and the energy industry performance of China, respectively. Furthermore, a panel data regression model is proposed to measure the impacts of FDI renewable energy technology spillover on China’s energy industry performance. Finally, energy industries of 30 different provinces in China based on the yearbook data from 2005 to 2011 are comparatively analyzed for evaluating the impacts through the empirical research. The results demonstrate that FDI renewable energy technology spillover has positive impacts on China’s energy industry performance. It can also be found that the technology spillover effects are more obvious in economic and technological developed regions. Finally, four suggestions are provided to enhance energy industry performance and promote renewable energy technology spillover in China.