Evaluation of a novel model incorporating serological indicators into the conventional TNM staging system for nasopharyngeal carcinoma.

ABSTRACT

BACKGROUND: Non-anatomical factors significantly affect treatment guidance and prognostic prediction in nasopharyngeal carcinoma (NPC) patients. Here, we developed a novel survival model by combining conventional TNM staging and serological indicators. METHODS: We retrospectively enrolled 10,914 eligible patients with nonmetastatic NPC over 2009-2017 and randomly divided them into training (n = 7672) and validation (n = 3242) cohorts. The new staging system was constructed based on T category, N category, and pretreatment serological markers by using recursive partitioning analysis (RPA). RESULTS: In multivariate Cox analysis, pretreatment cell-free Epstein-Barr virus (cfEBV) DNA levels of >2000 copies/mL [HROS (95 % CI) = 1.78 (1.57-2.02)], elevated lactate dehydrogenase (LDH) levels [HROS (95 % CI) = 1.64 (1.41-1.92)], and C-reactive protein-to-albumin ratio (CAR) of >0.04 [HROS (95 % CI) = 1.20 (1.07-1.34)] were associated with negative prognosis (all P < 0.05). Through RPA, we stratified patients into four risk groups RPA I (n = 3209), RPA II (n = 2063), RPA III (n = 1263), and RPA IV (n = 1137), with 5-year overall survival (OS) rates of 93.2 %, 86.0 %, 80.6 %, and 71.9 % (all P < 0.001), respectively. Compared with the TNM staging system (eighth edition), RPA risk grouping demonstrated higher prognostic prediction efficacy in the training [area under the curve (AUC) = 0.661 vs. 0.631, P < 0.001] and validation (AUC = 0.687 vs. 0.654, P = 0.001) cohorts. Furthermore, our model could distinguish sensitive patients suitable for induction chemotherapy well. CONCLUSION: Our novel RPA staging model outperformed the current TNM staging system in prognostic prediction and clinical decision-making. We recommend incorporating cfEBV DNA, LDH, and CAR into the TNM staging system.