Multivariate prediction of the probability of recurrence in patients with carcinoma of the parotid gland
Multivariate prediction of the probability of recurrence in patients with carcinoma of the parotid gland
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DOI：
10.1002/cncr.22647
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发表时间：
2007-05-15
期刊：
影响因子：
6.2
通讯作者：
Onate-Ocana, Luis F.
中科院分区：
文献类型：
--
作者：
Carrillo, Jose F.;Vazquez, Rafael;Onate-Ocana, Luis F.
背景腮腺癌是一种罕见的肿瘤，并且在文献中关于这些肿瘤的系列报道相对较少。本研究的目的是确定腮腺癌患者的预后因素，并制定一种方法来确定复发的可能性。1981年1月至2004年12月在作者所在机构接受治疗并完成治疗的腮腺癌患者构成研究组。采用Kaplan-Meier法计算无病生存期。采用Logistic回归分析确定复发相关的预后因素。纳入127名患者（64名男性和63名女性）;他们的平均年龄为53岁。34.6%的患者诊断为粘液表皮样癌，15.7%的患者诊断为腺样囊性癌，14.3%的患者诊断为腺癌，9.4%的患者诊断为腺泡细胞癌。中位无病生存期为8.3年（95%置信区间[95% CI]，4.3 - 12.2年）。Logistic回归分析证实肿瘤分类、面神经麻痹、肿瘤分化程度、患者年龄和手术切缘是复发相关因素（P <0.00001）。使用该模型，定义了3个术后风险组-高风险、中风险和低风险，其复发率分别为71.4%、43.1%和8.8%（P =.0001）。这些组的5年无病生存率分别为18.7%、53.9%和99.9%（P =.00001）。在这项研究中，作者确定了几个重要的预后因素。因此，他们提出了一种预后评分分类，可以直接计算给定患者的复发风险，这可能有助于定义治疗策略，目标患者咨询和设计未来的试验。癌症2007; 109：2043 - 51。(C)2007年美国癌症协会。
BACKGROUND. Parotid gland carcinoma is an infrequent tumor, and series that report on these neoplasms are relatively scarce in the literature. The objective of the current study was to identify prognostic factors in patients with parotid gland carcinoma and to develop a method for defining the probability of recurrence.METHODS. Patients with parotid gland carcinoma who were treated at the authors' institution from January 1981 through December 2004 and who completed treatment constituted the study group. Disease-free survival was calculated by using the Kaplan-Meier method. Logistic regression analysis was employed to define the recurrence-associated prognostic factors.RESULTS. one hundred twenty-seven patients were included (64 men and 63 women); their mean age was 53 years. Mucoepidermoid carcinoma was diagnosed in 34.6% of patients, adenoid cystic was diagnosed in 15.7% of patients, adenocarcinoma was diagnosed in 14.3% of patients, and acinic cell carcinoma was diagnosed in 9.4% of patients. The median disease-free survival was 8.3 years (95% confidence interval [95% CI], 4.3-12.2 years). Logistic regression analysis confirmed tumor classification, facial nerve palsy, grade of tumor differentiation, patient age, and surgical margins as recurrence-associated factors (P < .00001). Using this model, 3 postoperative risk groups were defined-high- risk, intermediate-risk, and low-risk-that had recurrence frequencies of 71.4%, 43.1%, and 8.8%, respectively (P = .0001). The 5-year disease-free survival rates for these groups were 18.7%, 53.9%, and 99.9%, respectively (P = .00001).CONCLUSIONS. In this study, the authors identified several significant prognostic factors. Consequently, they have proposed a prognostic score categorization that allows for a straightforward calculation of the risk of recurrence for a given patient that may help to define therapeutic strategies, target patient counseling, and design future trials. Cancer 2007;109:2043-51. (C) 2007 American Cancer Society.