A decision analysis model for elective neck dissection in patients with cT1-2 cN0 oral squamous cell carcinoma

Neck metastasis from oral squamous cell carcinoma (OSCC) has a significant impact on disease-specific and overall survival. Physical examination and imaging exams are used to stage the neck, but preoperative neck staging cannot reliably differentiate between metastatic and non-metastatic nodes. The decision to perform elective neck dissection (END) should consider the probability of neck metastasis and the harm of unnecessary surgery. We evaluate if this model can be used to decide treatment and the net benefit with different strategies. We reviewed patients treated from January, 1985 to December, 2012. Inclusion criteria were histological diagnosis of OSCC, initial surgery and primary tumour in the oral cavity staged as cT1-2 cN0. Development of a predictive model for metastatic nodes used patients submitted to END. The probability of neck metastasis was calculated and decision curve analysis was performed. We considered two interventions: watchful waiting and END, and two outcomes, regional recurrence and disease-free survival. We developed the model using logistic regression after multiple inputs with neck metastasis as an outcome. The initial model included all demographic and pathological variables. This model has an area under the curve (AUC) of 0.8423, a positive predictive value (PPV) of 70.7% and a negative predictive value (NPV) of 80.2%. We used LASSO for coefficient reduction and variable selection. This model has an AUC of 0.8265 with PPV of 68.3% and NPV of 80.2%. For neck recurrence, the curves of “treat all by watchful waiting” and “treat none by watchful waiting” crossed at the prevalence of neck metastasis. When focusing on disease-free survival, the decision analysis curve shows a pattern where the predictive model provides a net benefit if used to choose treatment from a 20% until a 54% threshold.