Department of Family and Community Medicine and Center for Healthcare Policy and Research, University of California, Davis, Sacramento, CA 95817, USA.
J Natl Cancer Inst. 2011 Aug 3;103(15):1152-61. doi: 10.1093/jnci/djr206. Epub 2011 Jul 27.
Computer-aided detection (CAD) is applied during screening mammography for millions of US women annually, although it is uncertain whether CAD improves breast cancer detection when used by community radiologists.
We investigated the association between CAD use during film-screen screening mammography and specificity, sensitivity, positive predictive value, cancer detection rates, and prognostic characteristics of breast cancers (stage, size, and node involvement). Records from 684 956 women who received more than 1.6 million film-screen mammograms at Breast Cancer Surveillance Consortium facilities in seven states in the United States from 1998 to 2006 were analyzed. We used random-effects logistic regression to estimate associations between CAD and specificity (true-negative examinations among women without breast cancer), sensitivity (true-positive examinations among women with breast cancer diagnosed within 1 year of mammography), and positive predictive value (breast cancer diagnosed after positive mammograms) while adjusting for mammography registry, patient age, time since previous mammography, breast density, use of hormone replacement therapy, and year of examination (1998-2002 vs 2003-2006). All statistical tests were two-sided.
Of 90 total facilities, 25 (27.8%) adopted CAD and used it for an average of 27.5 study months. In adjusted analyses, CAD use was associated with statistically significantly lower specificity (OR = 0.87, 95% confidence interval [CI] = 0.85 to 0.89, P < .001) and positive predictive value (OR = 0.89, 95% CI = 0.80 to 0.99, P = .03). A non-statistically significant increase in overall sensitivity with CAD (OR = 1.06, 95% CI = 0.84 to 1.33, P = .62) was attributed to increased sensitivity for ductal carcinoma in situ (OR = 1.55, 95% CI = 0.83 to 2.91; P = .17), although sensitivity for invasive cancer was similar with or without CAD (OR = 0.96, 95% CI = 0.75 to 1.24; P = .77). CAD was not associated with higher breast cancer detection rates or more favorable stage, size, or lymph node status of invasive breast cancer.
CAD use during film-screen screening mammography in the United States is associated with decreased specificity but not with improvement in the detection rate or prognostic characteristics of invasive breast cancer.
计算机辅助检测 (CAD) 每年在美国数百万女性的筛查性乳房 X 光检查中使用，尽管尚不确定当社区放射科医生使用 CAD 时是否能提高乳腺癌的检出率。
我们研究了在胶片筛查乳房 X 光检查中使用 CAD 与特异性、敏感性、阳性预测值、乳腺癌检出率以及乳腺癌的预后特征（分期、大小和淋巴结受累）之间的关联。我们对 1998 年至 2006 年期间在美国七个州的乳腺癌监测联盟设施中接受超过 160 万次胶片筛查乳房 X 光检查的 684956 名女性的记录进行了分析。我们使用随机效应逻辑回归来估计 CAD 与特异性（无乳腺癌女性的真阴性检查）、敏感性（在乳房 X 光检查后 1 年内被诊断为乳腺癌的女性的真阳性检查）和阳性预测值（在阳性乳房 X 光检查后被诊断为乳腺癌的女性）之间的关联，同时调整了乳房 X 光检查登记处、患者年龄、上次乳房 X 光检查后的时间、乳房密度、激素替代疗法的使用情况以及检查年份（1998-2002 年与 2003-2006 年）。所有统计学检验均为双侧检验。
在 90 个设施中，有 25 个（27.8%）采用了 CAD，并将其平均用于 27.5 个研究月。在调整后的分析中，CAD 的使用与统计学上显著较低的特异性（比值比 [OR] = 0.87，95%置信区间 [CI] = 0.85 至 0.89，P <.001）和阳性预测值（OR = 0.89，95% CI = 0.80 至 0.99，P =.03）相关。CAD 与总体敏感性的非统计学显著增加（OR = 1.06，95% CI = 0.84 至 1.33，P =.62）归因于导管原位癌的敏感性增加（OR = 1.55，95% CI = 0.83 至 2.91；P =.17），尽管 CAD 对浸润性癌的敏感性与有无 CAD相似（OR = 0.96，95% CI = 0.75 至 1.24；P =.77）。CAD 与更高的乳腺癌检出率或更有利的浸润性乳腺癌分期、大小或淋巴结状态无关。
在美国，在胶片筛查乳房 X 光检查中使用 CAD 与特异性降低有关，但与提高乳腺癌的检出率或浸润性乳腺癌的预后特征无关。
