Prognostic Score Predicts Survival in HPV-Negative Head and Neck Squamous Cell Cancer Patients
Prognostic Score Predicts Survival in HPV-Negative Head and Neck Squamous Cell Cancer Patients
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预后评分可预测 HPV 阴性头颈鳞状细胞癌患者的生存率
DOI：
10.7150/ijbs.33329
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发表时间：
2019-01-01
影响因子：
9.2
通讯作者：
Graviss, Edward A.
中科院分区：
文献类型：
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作者：
Qian, Xu;Nguyen, Duc T.;Graviss, Edward A.
虽然头颈部鳞状细胞癌(HNSCC)患者的死亡率很高，但标准化的预后工具是不可用的。因此，迫切需要一个经过验证的简单预后评分系统来帮助预测这些高危患者的死亡率。目前的研究旨在开发和内部验证人类乳头瘤病毒(HPV)非依赖性HNSCC患者总体死亡率的预后评分系统。对来自癌症基因组图谱数据库的400名已知HPV-RNA阴性的连续患者的数据进行了分析。使用Logistic回归贝塔系数建立了一个预测患者总死亡率的预后模型，并创建了一个简单的风险评分。该模型使用Bootstrap验证进行了内部验证，重复次数为2000次。在最终的模型中，五个协变量(年龄、PT、PN、神经侵袭和EAp53评分)被用来发展死亡风险评分。根据预后评分分为低危(96分)、中危(96-121分)和高危(≥122分)三组，生存率分别为76%、62%和35%。所提出的模型在发展(AUC=0.76；95%CI 0.70，0.81)和Bootstrap验证(AUC=0.76；95%CI 0.70，0.81)方面都有很好的区分性，无显著意义的Hosmer-Lemesow卡方为6.17(p=0.63)。所提出的预后评分系统易于用于预测患者的总体死亡率，并且还有助于在管理HNSCC患者的同时适当地分配医疗资源。应该进行外部验证(如果需要的话，包括重新校准)，以测试模型在不同人群中的普适性。
Although patients having head and neck squamous cell carcinoma (HNSCC) have high mortality, standardized prognostic tools are unavailable. As such, having a validated simple prognostic scoring system to help predict mortality in these high-risk patients is urgently needed. The current study aimed to develop and internally validate a prognostic scoring system for overall mortality in human papillomavirus (HPV)-independent HNSCC patients. Data on 400 consecutive patients from the Cancer Genome Atlas database with a known HPV-RNA negative status were analyzed. A prognostic model to predict patient overall mortality was developed using the logistic regression beta coefficients and a simple risk score was created. The model was internally validated using bootstrap validation with 2000 replications. Five covariates (age, pT, pN, perineural invasion, and EAp53 score) were used in the development of the mortality risk score in the final model. Three risk groups were stratified based on the prognostic scores: low-risk (<96 points), medium-risk (96-121 points), and high-risk (≥122 points) with a survival of 76%, 62% and 35%, respectively. The proposed model presented good discrimination in both the development (AUC = 0.76; 95% CI 0.70, 0.81) and bootstrap validation (AUC = 0.76; 95% CI 0.70, 0.81) with a non-significant Hosmer-Lemeshow chi-square of 6.17 (p = 0.63). The proposed prognostic scoring system is easy to use to predict patient overall mortality and could also help in the appropriate allocation of medical resources while managing HNSCC patients. External validation (including re-calibration if needed) should be conducted to test the model's generalizability in different populations.