Factors Influencing the Outcome of Head and Neck Cancer of Unknown Primary (HNCUP)

Author:

Balk Matthias,Rupp RobinORCID,Mantsopoulos KonstantinosORCID,Sievert MattiORCID,Gostian Magdalena,Allner Moritz,Grundtner Philipp,Eckstein Markus,Iro Heinrich,Hecht MarkusORCID,Gostian Antoniu-OresteORCID

Abstract

Background: This study on patients with head and neck cancer of unknown primary (HNCUP) assesses the impact of surgical and non-surgical treatment modalities and the tumour biology on the oncological outcome. Methods: A total of 80 patients with HNCUP (UICC I–IV) were treated with simultaneous neck dissection followed by adjuvant therapy, between 1 January 2007 and 31 March 2020. As the primary objective, the influence of treatment modalities on the overall survival (OS), the disease-specific survival (DSS) and the progression-free survival (PFS) were analysed in terms of cox regression and recursive partitioning. The tumour biology served as secondary objectives. Results: The 5-year OS for the entire cohort was 67.7%, (95% CI: 54.2–81.2%), the 5-year DSS was 82.3% (72.1–92.5%) and the 5-year PFS was 72.8% (61.8–83.8%). Cox regression revealed that patients undergoing adjuvant radiotherapy only had a four times higher risk to die compared to patients receiving chemoradiation therapy (HR = 4.45 (1.40; 14.17), p = 0.012). The development of distant metastases had a significantly negative impact on OS (HR = 8.24 (3.21–21.15), p < 0.001) and DSS (HR = 23.79 (6.32–89.56), p < 0.001). Recursive portioning underlined the negative influence of distant metastases on OS (3.2-fold increase in death probability) and DSS (4.3-fold increase in death probability), while an UICC stage of IVb increased the risk for further progression of the disease by a factor of 2. Conclusions: The presence of distant metastases as well as adjuvant treatment with radiation without concomitant chemotherapy, were among others, significant predictors for the overall survival of HNCUP patients, with distant metastases being the most significant predictor.

Publisher

MDPI AG

Subject

General Medicine

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