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Review
. 2022 Oct 18;14(20):5101.
doi: 10.3390/cancers14205101.

Evolution of Head and Neck Cutaneous Squamous Cell Carcinoma Nodal Staging-An Australian Perspective

Michael J L Hurrell  1 , Tsu-Hui Hubert Low  1   2   3 , Ardalan Ebrahimi  4 , Michael Veness  5 , Bruce Ashford  6   7   8 , Sandro Porceddu  9   10 , Jonathan R Clark  1   3   11
Affiliations
Review

Evolution of Head and Neck Cutaneous Squamous Cell Carcinoma Nodal Staging-An Australian Perspective

Michael J L Hurrell et al. Cancers (Basel). .

Abstract

Cutaneous squamous cell carcinoma of the head and neck (HNcSCC) is one of the commonest malignancies. When patients present with regional metastatic disease, treatment escalation results in considerable morbidity and survival is markedly reduced. Owing to the high incidence, Australian institutions have been at the forefront of advocating for reliable, accurate, and clinically useful staging systems that recognise the distinct biological characteristics of HNcSCC. As a result, an extensive body of literature has been produced over the past two decades, which has defined critical prognostic factors, critiqued existing staging systems, and proposed alternative staging models. Notwithstanding, a suitable staging system has proved elusive. The goal of cancer staging is to group patients according to cancer characteristics for which survival differs between groups (distinctiveness), consistently decreases with increasing stage (monotonicity), and is similar within a group (homogeneity). Despite implementing major changes based on published data, the latest edition of the American Joint Committee on Cancer (AJCC) staging manual fails to satisfy these fundamental requirements. This review chronologically explores and summarises the Australian contribution to prognostication and nodal staging of HNcSCC and highlights the ongoing challenges.

Keywords: cancer staging; cutaneous; head and neck cancer; lymphatic metastasis; prognosis; skin; squamous cell carcinoma.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
DSS Analysis. RPA decision tree. Groups 1–5 represented in leaves with Cox hazard ratio and DSS ratio (number of events observed in group/overall group number).
Figure 2
Figure 2
OS analysis. RPA decision tree. Groups 1–5 represented in leaves with Cox hazard ratio and OS ratio (number of events observed in group/overall group number).
Figure 3
Figure 3
Kaplan–Meier curves with low, moderate, and high-risk groupings. (A) OS. (B) DSS.
See this image and copyright information in PMC

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