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Clinical characteristics of patient selection and imaging predictors of outcome in solid tumors treated with checkpoint-inhibitors

Overview of attention for article published in European Journal of Nuclear Medicine and Molecular Imaging, August 2017
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Title
Clinical characteristics of patient selection and imaging predictors of outcome in solid tumors treated with checkpoint-inhibitors
Published in
European Journal of Nuclear Medicine and Molecular Imaging, August 2017
DOI 10.1007/s00259-017-3802-5
Pubmed ID
Authors

Sabrina Rossi, Luca Toschi, Angelo Castello, Fabio Grizzi, Luigi Mansi, Egesta Lopci

Abstract

The rapidly evolving knowledge on tumor immunology and the continuous implementation of immunotherapy in cancer have recently led to the FDA and EMA approval of several checkpoint inhibitors as immunotherapic agents in clinical practice. Anti-CTLA-4, anti-PD-1, and anti-PDL-1 antibodies are becoming standard of care in advanced melanoma, as well as in relapsed or metastatic lung and kidney cancer, demonstrating higher and longer response compared to standard chemotherapy. These encouraging results have fostered the evaluation of these antibodies either alone or in combination with other therapies in several dozen clinical trials for the treatment of multiple tumor types. However, not all patients respond to immune checkpoint inhibitors, hence, specific biomarkers are necessary to guide and monitor therapy. The utility of PD-L1 expression as a biomarker has varied in different clinical trials, but, to date, no consensus has been reached on whether PD-L1 expression is an ideal marker for response and patient selection; approximately 20-25% of patients will respond to immunotherapy with checkpoint inhibitors despite a negative PD-L1 staining. On the other hand, major issues concern the evaluation of objective response in patients treated with immunotherapy. Pure morphological criteria as commonly used in solid tumors (i.e. RECIST) are not sufficient because change in size is not an early and reliable marker of tumor response to biological therapies. Thus, the scientific community has required a continuous adaptation of immune-related response criteria (irRC) to overcome the problem. In this context, metabolic information and antibody-based imaging with positron emission tomography (PET) have been investigated, providing a powerful approach for an optimal stratification of patients at staging and during the evaluation of the response to therapy. In the present review we provide an overview on the clinical characteristics of patient selection when using imaging predictors of outcome in solid tumors treated with checkpoint-inhibitors.

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Geographical breakdown

Country Count As %
Unknown 66 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 21%
Other 8 12%
Student > Ph. D. Student 8 12%
Student > Master 8 12%
Student > Bachelor 6 9%
Other 9 14%
Unknown 13 20%
Readers by discipline Count As %
Medicine and Dentistry 28 42%
Biochemistry, Genetics and Molecular Biology 5 8%
Neuroscience 4 6%
Agricultural and Biological Sciences 4 6%
Immunology and Microbiology 3 5%
Other 7 11%
Unknown 15 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 August 2017.
All research outputs
#19,323,874
of 23,923,788 outputs
Outputs from European Journal of Nuclear Medicine and Molecular Imaging
#2,554
of 3,348 outputs
Outputs of similar age
#224,828
of 289,922 outputs
Outputs of similar age from European Journal of Nuclear Medicine and Molecular Imaging
#27
of 43 outputs
Altmetric has tracked 23,923,788 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,348 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 289,922 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.