German Robert R, Wike Jennifer M, Bauer Katrina R, Fleming Steven T, Trentham-Dietz Amy, Namiak Mary, Almon Lyn, Knight Karen, Perkins Carin
National Program of Cancer Registries (NPCR), Centers for Disease Control and Prevention (CDC), Atlanta, GA 30341, USA.
J Registry Manag. 2011 Summer;38(2):75-86.
The Breast and Prostate Cancer Data Quality and Patterns of Care (POC-BP) Study enabled a reabstraction study of the quality of population-based, central cancer registry data on the characteristics and initial treatment of breast cancer in females and prostate cancer in the United States.
Stratified random samples of 9,103 female breast cancers and 8,995 prostate cancers were available for the analysis, using the independently reabstracted data as the gold standard to compute measurements of agreement.
A slight majority (53% [8/15]) of the cancer site and treatment combinations showed kappa statistics > or = 0.60 and percent agreements, sensitivities, and predictive values positive > or = 80%: surgery and radiation for the 2 cancers, radiation completed and chemotherapy for breast cancer, and radiation modality and hormone therapy for prostate cancer. The qualities of the Collaborative Stage (CS) site-specific factors and derived variables for the 2 cancers were inconsistent, which confirmed the need to evaluate the recently-implemented CS algorithm.
The data quality analysis from POC-BP underscores the importance of examining the quality of specific data variables by cancer site, thereby highlighting those variables for which data collection procedures could be improved.
乳腺癌和前列腺癌数据质量与治疗模式（POC-BP）研究对美国女性乳腺癌和前列腺癌基于人群的中央癌症登记数据的特征及初始治疗质量进行了重新提取研究。
采用独立重新提取的数据作为计算一致性测量的金标准，对9103例女性乳腺癌和8995例前列腺癌的分层随机样本进行分析。
略超过半数（53%[8/15]）的癌症部位和治疗组合的kappa统计量≥0.60，百分比一致性、敏感性和阳性预测值≥80%：两种癌症的手术和放疗、乳腺癌的放疗完成情况和化疗、前列腺癌的放疗方式和激素治疗。两种癌症的协作分期（CS）部位特异性因素和派生变量的质量不一致，这证实了评估最近实施的CS算法的必要性。
POC-BP的数据质量分析强调了按癌症部位检查特定数据变量质量的重要性，从而突出了那些数据收集程序可改进的变量。
