Speaker: Dr Matthew Baker, University of Strathclyde
Venue: Manchester Institute of Biotechnology, University of Manchester
Abstract:
Vibrational spectroscopic techniques, such as IR and Raman, have been successfully applied to the analysis of disease states over the past couple of decades. They are capable of rapid objective molecular discrimination of disease with the high sensitivity and specificity that is required by the modern clinic. In addition, they are able to diagnose disease earlier and without the intra-observer error associated with current diagnostic process.
It has recently been demonstrated that a spectroscopic test using blood-serum is able to effectively identify brain tumours in patients with sensitivities and specificities as high as 91.5% and 83% respectively. The approach employs Attenuated Total Reflectance - Fourier Transform Infrared (ATR-FTIR) spectroscopy to derive a disease specific spectroscopic signature, that using pattern recognition and machine learning algorithms is able to identify brain tumour cases. The ability to identify brain cancer cases based on serum samples alone raises the possibility of systematic screening prior to investigation with more expensive (MRI/CT imaging) and invasive (biopsy) tests. However, current methodology is currently limited to single patient analysis due to limitations in standard instrumentation. Here, we investigate the performance of a novel ATR-FTIR spectroscopic approach that allows automated, disposable, and multi-patient sampling. Our results indicate that this optimised approach is able to stratify brain tumour patients at performances equivalent and greater to previous approaches, with sensitivities and specificities as high as 91.5% and 92.3% respectively. In order to aid translation, a cost-effectiveness analysis (CEA) was conducted to calculate the effects on health outcomes and health service costs of introducing this technology as a triage tool in primary and secondary care. Results indicate that using a serum spectroscopy test for brain tumours in both scenarios may be considered highly cost-effective in an HTA agency decision making process. Incremental cost-effectiveness ratios were well below standard threshold values of 拢20,000 to 拢30,000 per quality adjusted life year (QALY) gained used in the UK, and similar thresholds used internationally. In primary care, the test has the potential to be both more effective and cost saving for the health service. This talk will also discuss current progress along the long and winding road to clinical translation and patient impact.
Venue: Manchester Institute of Biotechnology, University of Manchester
Abstract:
Vibrational spectroscopic techniques, such as IR and Raman, have been successfully applied to the analysis of disease states over the past couple of decades. They are capable of rapid objective molecular discrimination of disease with the high sensitivity and specificity that is required by the modern clinic. In addition, they are able to diagnose disease earlier and without the intra-observer error associated with current diagnostic process.
It has recently been demonstrated that a spectroscopic test using blood-serum is able to effectively identify brain tumours in patients with sensitivities and specificities as high as 91.5% and 83% respectively. The approach employs Attenuated Total Reflectance - Fourier Transform Infrared (ATR-FTIR) spectroscopy to derive a disease specific spectroscopic signature, that using pattern recognition and machine learning algorithms is able to identify brain tumour cases. The ability to identify brain cancer cases based on serum samples alone raises the possibility of systematic screening prior to investigation with more expensive (MRI/CT imaging) and invasive (biopsy) tests. However, current methodology is currently limited to single patient analysis due to limitations in standard instrumentation. Here, we investigate the performance of a novel ATR-FTIR spectroscopic approach that allows automated, disposable, and multi-patient sampling. Our results indicate that this optimised approach is able to stratify brain tumour patients at performances equivalent and greater to previous approaches, with sensitivities and specificities as high as 91.5% and 92.3% respectively. In order to aid translation, a cost-effectiveness analysis (CEA) was conducted to calculate the effects on health outcomes and health service costs of introducing this technology as a triage tool in primary and secondary care. Results indicate that using a serum spectroscopy test for brain tumours in both scenarios may be considered highly cost-effective in an HTA agency decision making process. Incremental cost-effectiveness ratios were well below standard threshold values of 拢20,000 to 拢30,000 per quality adjusted life year (QALY) gained used in the UK, and similar thresholds used internationally. In primary care, the test has the potential to be both more effective and cost saving for the health service. This talk will also discuss current progress along the long and winding road to clinical translation and patient impact.
