Contributions
Abstract: 19
Type: Hot Topic
Abstract Category: N/A
Despite the increasing importance of Magnetic Resonance Imaging and other paraclinical markers, clinical documentation has a central role both in clinical trials and in daily management of patients suffering from Multiple Sclerosis (MS). Clinical assessment including quantification of disability progression (usually defined by the expanded disability status scale, EDSS) are still important end-points in phase 3 trials for approval of new disease modifying treatments. However, clinical assessment is prone to a high level of subjectivity and depends on many factors, e.g. the rater's experience. Thus, standardization of clinical assessment and documentation is crucial for a reliable measurement of clinical disability. To achieve this, several efforts were made in the last years.
For example, the “Three-Dimensional (MSDS3D)” system is an electronic large-scale documentation system, which supports clinicians with standardized interfaces via touchscreen terminals and devices, apps, or web browser. The Multiple Sclerosis Performance Test (MSPT) is a tablet-based app providing quantitative data on walking speed, balance, manual dexterity, visual function and cognitive processing speed. Moreover, an algorithm-based electronic version of Neurostatus-EDSS, the Neurostatus-eEDSS, provides real-time feedback to the raters and reduces inconsistencies in the assessment. It allows for direct storage of full scale clinical data in electronic format. To increase objectivity and sensitivity of the clinical assessment itself, Kinect-camera-based algorithms were developed. The “Assess MS system” uses advanced machine learning algorithms to analyze 3D-depth-sensor recordings of MS patients performing standard motor tests. It allows a finer grading of motor dysfunction and can potentially track clinical disability over time. Finally, a standardized capture interface for clinical data sets (CDS) is currently in development. It standardizes data capture, storage and exchange among different academic projects and clinical trials based on REDCap, a web application for online data capture.
The use of new technologies and electronic tools for capturing and storing clinical data could provide a standardized, more reliable and sensitive way for clinical documentation in MS. This development is crucial for clinical routine and clinical studies, particularly in progressive MS, where only slight clinical changes are seen during the timespan that is analysed in clinical trials.
Disclosure: Marcus D´Souza has received travel support from Bayer AG, Teva Pharmaceuticals and Sanofi Genzyme and research support from the University Hospital Basel.
Abstract: 19
Type: Hot Topic
Abstract Category: N/A
Despite the increasing importance of Magnetic Resonance Imaging and other paraclinical markers, clinical documentation has a central role both in clinical trials and in daily management of patients suffering from Multiple Sclerosis (MS). Clinical assessment including quantification of disability progression (usually defined by the expanded disability status scale, EDSS) are still important end-points in phase 3 trials for approval of new disease modifying treatments. However, clinical assessment is prone to a high level of subjectivity and depends on many factors, e.g. the rater's experience. Thus, standardization of clinical assessment and documentation is crucial for a reliable measurement of clinical disability. To achieve this, several efforts were made in the last years.
For example, the “Three-Dimensional (MSDS3D)” system is an electronic large-scale documentation system, which supports clinicians with standardized interfaces via touchscreen terminals and devices, apps, or web browser. The Multiple Sclerosis Performance Test (MSPT) is a tablet-based app providing quantitative data on walking speed, balance, manual dexterity, visual function and cognitive processing speed. Moreover, an algorithm-based electronic version of Neurostatus-EDSS, the Neurostatus-eEDSS, provides real-time feedback to the raters and reduces inconsistencies in the assessment. It allows for direct storage of full scale clinical data in electronic format. To increase objectivity and sensitivity of the clinical assessment itself, Kinect-camera-based algorithms were developed. The “Assess MS system” uses advanced machine learning algorithms to analyze 3D-depth-sensor recordings of MS patients performing standard motor tests. It allows a finer grading of motor dysfunction and can potentially track clinical disability over time. Finally, a standardized capture interface for clinical data sets (CDS) is currently in development. It standardizes data capture, storage and exchange among different academic projects and clinical trials based on REDCap, a web application for online data capture.
The use of new technologies and electronic tools for capturing and storing clinical data could provide a standardized, more reliable and sensitive way for clinical documentation in MS. This development is crucial for clinical routine and clinical studies, particularly in progressive MS, where only slight clinical changes are seen during the timespan that is analysed in clinical trials.
Disclosure: Marcus D´Souza has received travel support from Bayer AG, Teva Pharmaceuticals and Sanofi Genzyme and research support from the University Hospital Basel.