Cancer Treatment Data in Central Cancer Registries: When Are Supplemental Data Needed?
Cancer Treatment Data in Central Cancer Registries: When Are Supplemental Data Needed?
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DOI：
10.1177/11769351221112457
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发表时间：
2022
影响因子：
2
通讯作者：
Perraillon MC
中科院分区：
文献类型：
--
作者：
Bradley CJ;Liang R;Jasem J;Lindrooth RC;Sabik LM;Perraillon MC
我们评估了科罗拉多所有付款人索赔数据库（APCD）和科罗拉多中央癌症登记处（CCCR）之间的治疗一致性，以探讨APCD是否可以增加登记数据。我们比较了乳腺癌的治疗一致性，一个广泛研究的网站与住院报告来源和选择白血病，往往诊断门诊。我们分析了癌症类型和治疗，患者人口统计学，报告来源和健康保险的一致性，计算灵敏度，特异性，阳性预测值（PPV）和Kappa统计。我们估计了一个调整后的逻辑回归模型，以评估APCD是否在统计学上显著报告了额外的癌症导向治疗。在患有乳腺癌的女性中，14%的化疗治疗没有出现在CCCR中。缺失治疗在50岁以下女性（15%）、75岁及以上患者（19%）、农村居民（17%）和报告来源为门诊患者（22%）中更为常见。观察到白血病患者的类似和更明显的模式。每种癌症口服治疗的一致性较低。灵敏度和PPV较高，Kappa统计量中等。当报告来源为门诊设施时，APCD识别乳腺癌患者额外治疗的可能性降低5.3个百分点，识别额外治疗的可能性增加10个百分点。需要一个强大的数据基础设施来调查需要人口水平分析的研究问题，特别是寻求减少健康不平等和支付者之间比较的问题，包括医疗保险优势和收费服务。APCD数据是建立癌症基础设施的一步，特别是对于居住在农村地区和/或接受门诊中心护理的患者。
We evaluated treatment concordance between the Colorado All Payer Claims Database (APCD) and the Colorado Central Cancer Registry (CCCR) to explore whether APCDs can augment registry data. We compare treatment concordance for breast cancer, an extensively studied site with an inpatient reporting source and select leukemias that are often diagnosed outpatient. We analyzed concordance by cancer type and treatment, patient demographics, reporting source, and health insurance, calculating the sensitivity, specificity, positive predictive values (PPV) and Kappa statistics. We estimated an adjusted logistic regression model to assess whether the APCD statistically significantly reports additional cancer-directed treatments. Among women with breast cancer, 14% had chemotherapy treatments that were absent from the CCCR. Missing treatments were more common among women younger than age 50 (15%) and patients aged 75 and older (19%), rural residents (17%), and when the reporting source was outpatient (22%). Similar and more pronounced patterns for people with leukemia were observed. Concordance for oral treatments was lower for each cancer. Sensitivity and PPVs were high, with moderate Kappa statistics. The APCD was 5.3 percentage points less likely to identify additional treatments for breast cancer patients and 10 percentage points more likely to identify additional treatments when the reporting source was an outpatient facility. A robust data infrastructure is needed to investigate research questions that require population-level analyses, particularly for questions seeking to reduce health inequity and comparisons across payers, including Medicare Advantage and fee-for-service. APCD data are a step toward creating an infrastructure for cancer, particularly for patients who reside in rural areas and/or receive care from outpatient centers.
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SEER 治疗数据与医疗保险索赔的比较。
影响因子：
3
作者：
Noone AM;Lund JL;Mariotto A;Cronin K;McNeel T;Deapen D;Warren JL
通讯作者：
Warren JL
影响因子：
3
作者：
Cooper, GS;Yuan, Z;Rimm, AA
通讯作者：
Rimm, AA
影响因子：
4.2
作者：
Hashibe, Mia;Ou, Judy Y;Sweeney, Carol
通讯作者：
Sweeney, Carol
DOI：
10.1093/jncimonographs/lgaa005
发表时间：
2020-05-01
期刊：
Journal of the National Cancer Institute Monographs
影响因子：
--
作者：
Lam, Clara J. K.;Enewold, Lindsey;Mariotto, Angela B.
通讯作者：
Mariotto, Angela B.
DOI：
10.1093/jncimonographs/lgz033
发表时间：
2020-05-01
期刊：
Journal of the National Cancer Institute Monographs
影响因子：
--
作者：
Lam, Clara J. K.;Warren, Joan L.;Mariotto, Angela B.
通讯作者：
Mariotto, Angela B.