A Multicentre Study of Staging and Prognosis in Head & Neck Cutaneous Squamous Cell Carcinoma with Lymph Node Metastases

Abstract

An accurate staging system is essential for all cancers with risk stratification guiding treatment decisions and allowing clinicians to counsel patients. The standard staging system used worldwide is the Tumour, Node, Metastasis (TNM) staging system developed by the American Joint Committee on Cancer (AJCC). The TNM stage for HNcSCC with nodal metastases is based on the pathological lymph node (pN) classification used for mucosal head and neck cancers. In the 8th edition Staging Manual published in 2017, the AJCC introduced extranodal extension (ENE) to the pN classification, upstaging patients with ENE to either pN2a or pN3b categories and therefore TNM Stage IV. Despite the intuitive appeal of introducing ENE into the staging system given it is a well-accepted prognostic factor in head and neck cancer, several Australian studies comparing the prognostic performance of the 7th and 8th edition TNM systems in patients with HNcSCC with lymph node metastases found the 8th edition system had very low predictive power. These findings highlighted the need to develop a nodal staging system specific to HNcSCC and prompted the current PhD thesis. We aimed to: 1) critically assess the prognostic performance of the 8th edition AJCC staging system using objective statistical measures of model performance; 2) to compare the performance of the 8th edition TNM staging system with several previously published alternative staging systems (N1S3 and ITEM) designed specifically to predict disease-specific survival in patients with HNcSCC with nodal metastases; 3) to define important prognostic factors in HNcSCC with nodal metastases, with a focus on analysing issues relevant to staging and prognosis to inform future revisions of the HNcSCC staging. The thesis was based on a retrospective cohort of 1309 patients with HNcSCC with metastases to parotid and/or cervical nodes, treated between 1980-2017 with curative intent surgery +/- adjuvant radiotherapy, with a median follow-up of 3.2 years. We showed based on objective statistical measures that the TNM staging performs poorly and violates all the characteristics of an ideal staging system with poor balance between groups, low predictive power and lack of monotonicity, hazard discrimination and hazard consistency. Perhaps the most important findings relate to ENE which was present far more frequently in HNcSCC than mucosal cancers. We demonstrated that the AJCC system ascribes excessive weight to ENE and results in the vast majority of patients being inappropriately classified as TNM Stage IV despite many having an excellent prognosis. Importantly, we demonstrated that additional information on the number of nodal metastases as a categorical variable with 1-2, 3-4 and >=5 nodes should be included in the staging system. Another key finding was that immunosuppression is an independent strong adverse prognostic factor irrespective of the cause and merits incorporation into the prognostic stage groups of the TNM. Finally, perineural invasion was consistently associated with reduced survival and we recommend consideration of adding clinical perineural invasion into the staging system. Our analysis of the influence of the primary tumour (T stage) in the presence of nodal metastases cast doubt on its prognostic value in this context and suggests a re-evaluation is required. Finally, we were the first group to examine determinants of distant metastatic failure in HNcSCC and developed a simple intuitive distant metastasis risk score that stratified risk of distant metastatic failure well and may prove useful in clinical decision making. This thesis has established the need for major changes to the nodal staging system for HNcSCC and provides insights on important prognostic factors to help guide this process. We hope that a system specific to HNcSCC can be developed and validated that reflects its distinct tumour biology and provides clinicians with a more accurate tool to risk stratify patients. Show more