Predicting response to pembrolizumab in metastatic melanoma by a new personalization algorithm
At present, immune checkpoint inhibitors, such as pembrolizumab, are widely used in the therapy of advanced non-resectable melanoma, as they induce more durable responses than other available treatments. However, the overall response rate does not exceed 50% and, considering the high costs and low l...
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| Main Authors: | , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
07 October 2019
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| In: |
Journal of translational medicine
Year: 2019, Volume: 17, Pages: 1-15 |
| ISSN: | 1479-5876 |
| DOI: | 10.1186/s12967-019-2081-2 |
| Online Access: | Verlag, Volltext: https://doi.org/10.1186/s12967-019-2081-2 Verlag: https://doi.org/10.1186/s12967-019-2081-2 
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| Author Notes: | Neta Tsur, Yuri Kogan, Evgenia Avizov-Khodak, Désirée Vaeth, Nils Vogler, Jochen Utikal, Michal Lotem & Zvia Agur |
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| 520 | |a At present, immune checkpoint inhibitors, such as pembrolizumab, are widely used in the therapy of advanced non-resectable melanoma, as they induce more durable responses than other available treatments. However, the overall response rate does not exceed 50% and, considering the high costs and low life expectancy of nonresponding patients, there is a need to select potential responders before therapy. Our aim was to develop a new personalization algorithm which could be beneficial in the clinical setting for predicting time to disease progression under pembrolizumab treatment. | ||
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