Incorporation of stromal tumor-infiltrating lymphocytes into an early death prediction model significantly improves net reclassification for outcome estimation in advanced buccal cancer

IF 2.1 2区 医学 Q2 DENTISTRY, ORAL SURGERY & MEDICINE
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Abstract

We explored the impact of stromal tumor-infiltrating lymphocytes (sTILs) on the prognostic value of an early death model for advanced buccal cancer. We assessed 121 patients with advanced buccal cancer who underwent primary tumor resection at a medical center. Predictors of early death and 5-year overall survival (OS) were analyzed using Cox regression models. Performance of models was evaluated with the Harrell C and Akaike information criterion. The net reclassification improvement of the early death model was also calculated relative to the 5-year OS model for one-year all-cause mortality. A total of 121 patients with advanced buccal cancer were recruited. Mean age was 56.1 ± 9.8 years; 117 (96.7%) patients were male. sTILs ≤30%, clinical nodal disease, pathological nodal disease, poor differentiation, lymphovascular invasion, perineural invasion, WPOI 5, and no adjuvant radiotherapy were risk factors for early death in univariate analysis. In multivariate analysis, clinical TNM, sTILs, clinical nodal disease, poor differentiation, lymphovascular invasion, and no adjuvant RT were independent factors for early death. sTILs, pathological nodal disease, poor differentiation, lymphovascular invasion, and no adjuvant RT were independent factors for early death in the multivariate model with pathological TNM. The discriminatory ability was better for early death model for 1-year all-cause mortality. Finally, incorporation of sTILs into the early death model increased net reclassification by 21% for the clinical TNM model and 28% for the pathological TNM model. Addition of sTILs improved the early death model, which may help physicians to identify high-risk patients for more intensive treatment and follow-up.

将基质肿瘤浸润淋巴细胞纳入早期死亡预测模型可显著提高晚期口腔癌预后评估的净重分类率
我们探讨了基质肿瘤浸润淋巴细胞(sTILs)对晚期口腔癌早期死亡模型预后价值的影响。我们对在一家医疗中心接受原发性肿瘤切除术的121名晚期口腔癌患者进行了评估。我们使用 Cox 回归模型分析了早期死亡和 5 年总生存期(OS)的预测因素。使用 Harrell C 和 Akaike 信息标准对模型的性能进行了评估。此外,还计算了早期死亡模型相对于 5 年 OS 模型对一年全因死亡率的净再分类改进。共招募了 121 名晚期口腔癌患者。在单变量分析中,sTILs ≤30%、临床结节病、病理结节病、分化不良、淋巴管侵犯、神经周围侵犯、WPOI 5和未接受辅助放疗是早期死亡的风险因素。在多变量分析中,临床 TNM、sTILs、临床结节病、分化差、淋巴管侵犯和未辅助 RT 是早期死亡的独立因素;在与病理 TNM 的多变量模型中,sTILs、病理结节病、分化差、淋巴管侵犯和未辅助 RT 是早期死亡的独立因素。早期死亡模型对1年全因死亡率的判别能力更强。最后,将 sTILs 纳入早期死亡模型可使临床 TNM 模型的净重新分类率提高 21%,病理 TNM 模型的净重新分类率提高 28%。加入sTILs后,早期死亡模型得到了改善,这可能有助于医生识别高危患者,为其提供更深入的治疗和随访。
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来源期刊
CiteScore
5.20
自引率
22.60%
发文量
117
审稿时长
70 days
期刊介绍: The Journal of Cranio-Maxillofacial Surgery publishes articles covering all aspects of surgery of the head, face and jaw. Specific topics covered recently have included: • Distraction osteogenesis • Synthetic bone substitutes • Fibroblast growth factors • Fetal wound healing • Skull base surgery • Computer-assisted surgery • Vascularized bone grafts
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