Artificial Intelligence Estimates the Importance of Baseline Factors in Predicting Response to Anti-PD1 in Metastatic Melanoma.

Journal: American journal of clinical oncology

PMID: 31261257

Abstract

OBJECTIVE: Prognosis of patients with metastatic melanoma has dramatically improved over recent years because of the advent of antibodies targeting programmed cell death protein-1 (PD1). However, the response rate is ~40% and baseline biomarkers for the outcome are yet to be identified. Here, we aimed to determine whether artificial intelligence might be useful in weighting the importance of baseline variables in predicting response to anti-PD1.

Authors

Alice Indini

Department of Medical Oncology and Hematology, Melanoma Medical Oncology Unit.
Lorenza Di Guardo

Department of Medical Oncology and Hematology, Melanoma Medical Oncology Unit.
Carolina Cimminiello

Department of Medical Oncology and Hematology, Melanoma Medical Oncology Unit.
Filippo de Braud

Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Milan, Italy.
Michele Del Vecchio

Department of Medical Oncology and Hematology, Melanoma Medical Oncology Unit.

Keywords

Age Factors Aged Female Forecasting Humans L-Lactate Dehydrogenase Lymphocyte Count Male Melanoma Middle Aged Mucous Membrane Neoplasms, Unknown Primary Neural Networks, Computer Neutrophils Programmed Cell Death 1 Receptor Retrospective Studies Skin Neoplasms Survival Rate Treatment Outcome Uveal Neoplasms

External Resources

View on PubMed Access via DOI PubMed (31261257)

Artificial Intelligence Estimates the Importance of Baseline Factors in Predicting Response to Anti-PD1 in Metastatic Melanoma.

Abstract

Authors

Keywords

External Resources

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