Department of Clinical Specialistic and Dental Sciences, Marche Polytechnic University, Ancona, Italy.
Department of Biomedical Sciences and Public Health, Marche Polytechnic University, Ancona, Italy.
Oral Surg Oral Med Oral Pathol Oral Radiol. 2018 Nov;126(5):415-423. doi: 10.1016/j.oooo.2018.07.052. Epub 2018 Aug 18.
In this study, we evaluated the 8th edition of American Joint Committee on Cancer (AJCC) staging criteria and lymph node ratio (LNR) to identify patients affected by squamous cell carcinoma of the tongue (SCCT) with a poor prognosis.
Seventy-three cases of SCCT were analyzed retrospectively. Tumor staging was revised according to the 7th and 8th editions of the AJCC criteria. Depth of invasion (DOI), extranodal extension (ENE), and LNR were evaluated.
Twenty-five cases were reclassified: 17 patients received an upstage in the staging score, and in 8 cases in the same stage group, pT or pN was changed. In the pT-upstaged group, 7 patients experienced recurrence, and 8 died. In the pN-upstaged group, 9 patients developed recurrence, and 10 died. The number of disease recurrence or death was higher in the groups of patients who received an upstage in pN and in the staging score (P < .05). The pN-upstaged group showed worse disease-free survival (DFS) and overall survival (OS) (P < .05). LNR was higher in patients with recurrence, and among these, LNR was lower in patients with ENE (P <.05).
The 8th edition of the AJCC criteria allows for better stratification of patients with SCCT. The implementation of ENE and LNR to pN classification seems to identify patients with worse DFS and OS.
本研究评估了第 8 版美国癌症联合委员会(AJCC)分期标准和淋巴结比率(LNR),以确定患有舌鳞状细胞癌(SCCT)预后不良的患者。
回顾性分析了 73 例 SCCT 病例。根据第 7 版和第 8 版 AJCC 标准修订肿瘤分期。评估了肿瘤侵犯深度(DOI)、淋巴结外扩展(ENE)和 LNR。
25 例病例重新分类:17 例患者分期评分升高,8 例患者在同一分期组中 pT 或 pN 发生变化。在 pT 分期升高组中,7 例患者复发,8 例患者死亡。在 pN 分期升高组中,9 例患者复发,10 例患者死亡。在 pN 分期升高和分期评分升高的患者中,疾病复发或死亡的数量更高(P <.05)。pN 分期升高组的无病生存率(DFS)和总生存率(OS)更差(P <.05)。复发患者的 LNR 较高,其中 ENE 的 LNR 较低(P <.05)。
第 8 版 AJCC 标准可更好地对 SCCT 患者进行分层。将 ENE 和 LNR 纳入 pN 分类似乎可以识别出 DFS 和 OS 较差的患者。