Chapter title |
Advances in adjuvant therapy: potential for prognostic and predictive biomarkers.
|
---|---|
Chapter number | 4 |
Book title |
Molecular Diagnostics for Melanoma
|
Published in |
Methods in molecular biology, January 2014
|
DOI | 10.1007/978-1-62703-727-3_4 |
Pubmed ID | |
Book ISBNs |
978-1-62703-726-6, 978-1-62703-727-3
|
Authors |
Diwakar Davar, Ahmad A Tarhini, Helen Gogas, John M Kirkwood, Davar D, Tarhini AA, Gogas H, Kirkwood JM, Ahmad A. Tarhini, John M. Kirkwood, Davar, Diwakar, Tarhini, Ahmad A., Gogas, Helen, Kirkwood, John M. |
Abstract |
Melanoma is the third most common skin cancer but accounts for the majority of skin cancer-related mortality. The rapidly rising incidence and younger age at diagnosis has made melanoma a leading cause of lost productive years of life and has increased the urgency of finding improved adjuvant therapy for melanoma. Interferon-α was approved for the adjuvant treatment of resected high-risk melanoma following studies that demonstrated improvements in relapse-free survival and overall survival that were commenced nearly 30 years ago. The clinical benefits associated with this agent have been consistently observed across multiple studies and meta-analyses in terms of relapse rate, and to a smaller and less-consistent degree, mortality. However, significant toxicity and lack of prognostic and/or predictive biomarkers that would allow greater risk-benefit ratio have limited the more widespread adoption of this modality.Recent success with targeted agents directed against components of the MAP-kinase pathway and checkpoint inhibitors have transformed the treatment landscape in metastatic disease. Current research efforts are centered around discovering predictive/prognostic biomarkers and exploring the options for more effective regimens, either singly or in combination. |
X Demographics
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Unknown | 1 | 100% |
Demographic breakdown
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 22 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Other | 3 | 14% |
Student > Ph. D. Student | 3 | 14% |
Student > Doctoral Student | 2 | 9% |
Professor > Associate Professor | 2 | 9% |
Student > Bachelor | 2 | 9% |
Other | 3 | 14% |
Unknown | 7 | 32% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 7 | 32% |
Biochemistry, Genetics and Molecular Biology | 2 | 9% |
Agricultural and Biological Sciences | 2 | 9% |
Arts and Humanities | 1 | 5% |
Nursing and Health Professions | 1 | 5% |
Other | 2 | 9% |
Unknown | 7 | 32% |