Head and Neck Cancer Clinical Trial
Official title:
Prognostic Significance of Lymph Node Yield and Lymph Node Ratio in Patients Affected by Squamous Cell Carcinoma of the Oral Cavity, Hypopharynx and Larynx: a Prospective, Multicenter Observational Study
It is still unclear if Lymph Node Yield (LNY) and Lymph Node Ratio (LNR) may have a prognostic role in patients affected by carcinoma of the oral cavity and the oropharynx. Only retrospective studies are available. For this reason, this prospective, multi center, observational study should provide indications in this regard. Proper stratification by patients characteristics will allow to understand if LNY and LNR may enter in the future TNM staging system
Lymph node involvement is a fundamental prognostic factor in head and neck squamous cell
carcinoma (SCC). Lymph node yield (LNY), which is the number of lymph nodes retrieved after
neck dissection, and lymph node ratio (LNR), which is the ratio of positive lymph nodes out
of the total removed, are measurable indicators that may have the potential to be used as
prognostic factors. The present study is designed to define the exact role of LNY and LNR
regarding the overall and specific survival of patients affected by oral cavity and
oropharyngeal SCC.
This is a multicenter study involving tertiary care referral centers in Europe and North
America. Patients affected by oral cavity, HPV+ and HPV- oropharyngeal SCC undergoing neck
dissection will be consecutively enrolled and followed-up for up to 5 years. Patients and
disease characteristic will be properly recorded and centrally analyzed. The primary
end-point is to define reliable cut off- values for LNY and LNR which may serve as
prognosticators of survival. This will be achieved through the use of ROC curves. Secondary
outcomes will be the Overall survival (OS), Disease Specific Survival (DSS), and Progression
Free Survival Hazard Ratios (HR) at 2-, 3- and 5 years, which will be evaluated through the
Kaplan-Meier method and the difference in survival attested by the log-rank test. Univariate
and multivariate analysis will be performed to understand the association of various outcomes
with LNY and LNR.
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