Incorporation of log odds of positive lymph nodes into the AJCC TNM classification improves prediction of survival in oral cancer. (8th January 2017)

• Record Type: Journal Article
• Authors: Lee, C.‐C.; Lin, Y.‐S.; Kang, B.‐H.; Chang, K.‐P.; Chi, C.‐C.; Lin, M.‐Y.; Su, H.‐H.; Chang, T.‐S.; Chen, H.‐C.; Chen, P.‐C.; Huang, W.‐L.; Huang, C.‐I.; Chou, P.; Yang, C.‐C.
• Is Part Of: Clinical otolaryngology. Volume 42:Number 2(2017:Apr.)
• Page Start: 425
• Page End: 432
• Publication Date: 2017-01-08
• Subjects: Otolaryngology -- Periodicals; 617.51005
• DOI: 10.1111/coa.12809
• Languages: English
• ISSNs: 1749-4478

Abstract

Abstract : Objectives: To assess the prognostic performance of a new N classification that incorporates the log odds of positive lymph nodes (LODDS) into the routinely used pathological N classification for oral squamous cell carcinoma (OSCC) patients. Design: Retrospective cohort study utilising LODDS into pN category was performed, and the AJCC TNM stage and T‐New N‐M stage were compared with respect to 5‐year disease‐specific survival (DSS) rates. The discriminability was evaluated from the linear trend chi‐square test, Akaike information criterion (AIC) and Harrell's c‐statistic. Setting: Medical centrer in Taiwan. Participants: A total of 463 patients received primary surgery and neck dissection between 2004 and 2013 for OSCC. Main outcome measures: The discriminability for 5‐year DSS rates. Results: The median follow‐up period was 54 months, the mean patient age was 54 ± 11 years and 428 patients (92.4%) were male. The patients with higher LODDS had worse 5‐year DSS rates. Incorporation of LODDS into the prognostic model based on the seventh edition of the TNM classification significantly improved discriminative performance for 5‐year DSS with a lower AIC (1883 versus 1897), and higher prediction accuracy (Harrell's c‐statistic: 0.768 versus 0.764). Conclusions: By utilising a merger of the LODDS and pN classifications to create a new N classification has better discriminatory and predictive ability than pathological TNM staging and could help identify high‐risk patients for intense adjuvant therapy.