A predictive survival model for patients with head and neck squamous cell carcinoma treated with immune check point inhibitors.


Journal

Oral oncology
ISSN: 1879-0593
Titre abrégé: Oral Oncol
Pays: England
ID NLM: 9709118

Informations de publication

Date de publication:
11 2020
Historique:
received: 09 03 2020
revised: 04 07 2020
accepted: 07 07 2020
pubmed: 24 7 2020
medline: 10 7 2021
entrez: 24 7 2020
Statut: ppublish

Résumé

ICIs have expanded treatment options for HNSCC. A minority of the patients respond to these expensive treatments. This is a single institutional retrospective review on 121 unresectable or metastatic HNSCC patients treated with ICIs. We predicted that inflammatory markers available through routine blood work, in addition to clinical characteristics may divide patients into groups more or less likely to respond to these agents. Here we develop and internally validate our nomogram to predict survival in patients treated with ICIs.

Sections du résumé

BACKGROUND
ICIs have expanded treatment options for HNSCC. A minority of the patients respond to these expensive treatments.
PATIENTS AND METHODS
This is a single institutional retrospective review on 121 unresectable or metastatic HNSCC patients treated with ICIs. We predicted that inflammatory markers available through routine blood work, in addition to clinical characteristics may divide patients into groups more or less likely to respond to these agents. Here we develop and internally validate our nomogram to predict survival in patients treated with ICIs.

Identifiants

pubmed: 32702630
pii: S1368-8375(20)30336-5
doi: 10.1016/j.oraloncology.2020.104900
pii:
doi:

Substances chimiques

Immune Checkpoint Inhibitors 0
Immune Checkpoint Proteins 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

104900

Informations de copyright

Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

M Bonomi (M)

Division of Medical Oncology, Ohio State University, Columbus, United States. Electronic address: marcelo.bonomi@osumc.edu.

P Bhateja (P)

Division of Medical Oncology, Ohio State University, Columbus, United States.

M Issa (M)

Division of Medical Oncology, Ohio State University, Columbus, United States.

B Klamer (B)

Department of Biomedical Informatics, Ohio State University, Columbus, United States.

X Pan (X)

Department of Biomedical Informatics, Ohio State University, Columbus, United States.

A Blakaj (A)

Division of Radiation Oncology, Yale University, New Haven, United States.

V Karivedu (V)

Division of Medical Oncology, Ohio State University, Columbus, United States.

L Mousa (L)

Division of Medical Oncology, Ohio State University, Columbus, United States.

D Mitchell (D)

Division of Radiation Oncology, Ohio State University, Columbus, United States.

M Gamez (M)

Division of Radiation Oncology, Ohio State University, Columbus, United States.

S Kang (S)

Division of Otolaryngology, Ohio State University, Columbus, United States.

Nolan B Seim (NB)

Division of Otolaryngology, Ohio State University, Columbus, United States.

M Old (M)

Division of Otolaryngology, Ohio State University, Columbus, United States.

R Carrau (R)

Division of Otolaryngology, Ohio State University, Columbus, United States.

J Rocco (J)

Division of Otolaryngology, Ohio State University, Columbus, United States.

D Blakaj (D)

Division of Radiation Oncology, Ohio State University, Columbus, United States.

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Classifications MeSH