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Develop and validation a nomogram to predict the recurrent probability in patients with major salivary gland cancer

机译:开发并验证列线图以预测重大涎腺癌患者的复发概率

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摘要

>Objectives: Prediction of recurrent risk in patients with major salivary gland carcinoma (MSGC) after surgical treatment is an important but difficult task because of a broad spectrum of tumor histological subtypes and diverse clinical behaviors. This study aimed to develop and validate a nomogram to predict the recurrent probability in patients with MSGC.>Methods: A total of 231 consecutive patients with MSGC received curative-intend surgery between 2002 and 2014 from one medical center were selected as the training set. Clinicopathologic variables with the most significant values in the multivariate Cox regression were selected to build into a nomogram to estimate the recurrence probability. An independent validation set of 139 patients treated at the same period from 3 other hospitals were selected for external validation and calibration.>Results: The nomogram was developed on six significant predictive factors, including the smoking history, tumor grade, perineural invasion, lymphatic invasion, pathologic T- and N-classification, of tumor recurrence retained in the multivariate Cox model. The nomogram had a highly predictive performance, with a bootstrapped corrected concordance index of 0.82 for the training set and 0.78 for the validation set. The nomogram showed good calibration in predict 2-year and 5-year recurrence probability both in the training and validation set.>Conclusions: We developed and externally validated an accurate nomogram for prediction the tumor recurrence probability of patients with MSGC after surgical treatment. This nomogram may be used to assist clinician and patient in elaborating the recurrent risk and making decision for appropriate adjuvant treatment.
机译:>目的:由于广泛的肿瘤组织学亚型和多样的临床行为,对手术后大涎腺癌(MSGC)患者的复发风险进行预测是一项重要而艰巨的任务。这项研究旨在开发和验证行列线图以预测MSGC患者的复发可能性。>方法: 2002年至2014年间,共有231例MSGC患者从一个医疗中心接受了治愈性手术。选择作为训练集。选择在多元Cox回归中具有最显着值的临床病理变量,将其构建为列线图以估计复发概率。选择了来自其他3家医院同时治疗的139名患者的独立验证集进行外部验证和校准。>结果:列线图是基于六个重要的预测因素开发的,包括吸烟史,肿瘤分级保留在多变量Cox模型中的肿瘤复发,神经周围浸润,淋巴管浸润,病理性T和N分类。列线图具有高度的预测性能,对于训练集,自举校正校正一致性指数为0.82,对于验证集,为0.78。在训练和验证组中,诺模图显示出对2年和5年复发率预测的良好校准。>结论:我们开发并在外部验证了准确的诺模图,以预测患有以下疾病的患者的复发率MSGC经过手术治疗。该诺模图可用于协助临床医生和患者详细说明复发风险并做出适当辅助治疗的决策。

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