Department of Biostatistics, The University of Kansas Medical Center, The University of Kansas Cancer Center, MSN 1026, 3901 Rainbow Blvd, Kansas City, KS 66160, USA.
BMC Oral Health. 2013 Jan 1;13:1. doi: 10.1186/1472-6831-13-1.
Baseline and trend data for oral and pharyngeal cancer incidence is limited. A new algorithm was derived using the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database to create an algorithm to identify incident cases of oral and pharyngeal cancer using Medicare claims.
Using a split-sample approach, Medicare claims' procedure and diagnosis codes were used to generate a new algorithm to identify oral and pharyngeal cancer cases and validate its operating characteristics.
The algorithm had high sensitivity (95%) and specificity (97%), which varied little by age group, sex, and race and ethnicity.
Examples of the utility of this algorithm and its operating characteristics include using it to derive baseline and trend estimates of oral and pharyngeal cancer incidence. Such measures could be used to provide incidence estimates where they are lacking or to serve as comparator estimates for tumor registries.
口腔和咽癌发病的基线和趋势数据有限。本研究使用监测、流行病学和最终结果(SEER)-医疗保险关联数据库开发了一种新算法,利用医疗保险索赔来创建一种识别口腔和咽癌新发病例的算法。
使用拆分样本方法,利用医疗保险索赔的程序和诊断代码生成一种新算法来识别口腔和咽癌病例,并验证其操作特征。
该算法具有较高的敏感性(95%)和特异性(97%),其敏感性和特异性在年龄组、性别和种族和民族方面变化不大。
该算法的应用实例及其操作特征包括利用该算法来获得口腔和咽癌发病率的基线和趋势估计。这些措施可用于提供缺乏的发病率估计,或作为肿瘤登记处的比较估计。