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Implementing Adjusted Imaging Metrics Within Roche With the Metrics Champion Consortium: Experiences and Outcome
Andrew McDonald1, Gudrun Zahlmann1
11 F. Hoffmann-La Roche Ltd, Basel, Switzerland.
Purpose:
To implement adjusted performance imaging metrics on imaging clinical trials of a pharmaceutical company (Roche) in a business relationship with preferred imaging providers and to report on findings and lessons learned.
Methods:
In 2009 the Metrics Champion Consortium provided the first imaging metrics for use in clinical trials as industry consensus. Roche reviewed, adjusted, excluded, and extended these metrics and defined target values per metric in order to implement them in all clinical trials with 7 preferred providers.
Results:
Roche preferred providers were able to report on all 19 metrics (8 unchanged Metrics Champion Consortium, 7 adjusted, and 4 Roche defined). Seventy-three Roche studies over 27 months form the basis for reporting; data are provided as mean and standard deviation per disease area with number of studies and for all studies reported for the specific metric for all providers. Disease areas are oncology, central nervous system, and inflammation. Seventeen metrics have proven to be useful; 2 metrics did not provide sufficient information; and 4 metrics need adjustments of target values.
Limitations:
Imaging trial-related metrics are a new concept, and Roche and providers had to develop the same consistent understanding of content and how to report a specific metric. The 73 studies covered all phases and disease areas, which made it difficult at times to compare results.
Conclusions:
Imaging metrics in clinical trials are a useful tool in improving timeliness and quality of imaging data, enhancing trial processes, and governing sponsor/provider relationships. It increases the transparency in the business relationship and in the different clinical trial-related process steps. The use of metrics highlights critical topics, such as reading and adjudication, and enables parties to take actions to improve performance. Disease area-related reporting needs more data for specific improvements.
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