The influence of tumor volume on the risk of distant metastases in head and neck squamous cell carcinomas

Julie Kjems*, Katrin Elisabet Håkansson, Claus Andrup Kristensen, Jesper Grau Eriksen, Morten Horsholt Kristensen, Anne Ivalu Sander Holm, Jens Overgaard, Christian Rønn Hansen, Ruta Zukauskaite, Jørgen Johansen, Ivan Richter Vogelius, Jeppe Friborg

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

Abstract

Background and purpose: Distant metastases (DM) in head and neck squamous cell carcinomas (HNSCC) are in most circumstances non-curable. The TNM staging system is insufficient to predict the risk of DM. This study investigates if the DM risk can be predicted using a multivariate model including pre-treatment total tumor volume for both p16-positive oropharyngeal squamous cell carcinoma (OPSCC) and all other sites (other HNSCC). Materials and methods: The study includes patients with localized pharyngeal and laryngeal squamous cell carcinomas treated with primary radiotherapy from 2008-2017 from three head and neck cancer centers. Patients were identified in the Danish Head and Neck Cancer (DAHANCA) database. Total (nodal and primary) tumor volume (Gross Tumor Volume, GTV) was extracted from local treatment planning systems. The GTV was grouped by volume (cm3) in four intervals and included in a multivariate Cox proportional hazard regression controlled for pre-selected clinical values incl. stage. Results: The study includes 2,865 patients, of which 321 (11 %) had DM post-treatment. The risk of DM was assessed in a multivariate model based on 2,751 patients (p16-positive OPSCC: 1,032; and other HNSCC: 1,719). There was a significant association between GTV and the risk of DM, and in tumor volumes ≥ 50 cm3 hazard ratios of 7.6 (2.5–23.4) for p16-positive OPSCC and 4.1 (2.3–7.2) in other HNSCC were observed. Conclusion: Tumor volume is an independent risk factor for DM. The addition of total tumor volume to a predictive model is important to identify subgroups of HNSCC patients at high risk of DM.

OriginalsprogEngelsk
Artikelnummer109771
TidsskriftRadiotherapy and Oncology
Vol/bind186
ISSN0167-8140
DOI
StatusUdgivet - sep. 2023

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