Barlow William E, Chi Chen, Carney Patricia A, Taplin Stephen H, D'Orsi Carl, Cutter Gary, Hendrick R Edward, Elmore Joann G
Cancer Research and Biostatistics, 1730 Minor Ave, Ste. 1900, Seattle WA 98101, USA.
J Natl Cancer Inst. 2004 Dec 15;96(24):1840-50. doi: 10.1093/jnci/djh333.
Radiologists differ in their ability to interpret screening mammograms accurately. We investigated the relationship of radiologist characteristics to actual performance from 1996 to 2001.
Screening mammograms (n = 469,512) interpreted by 124 radiologists were linked to cancer outcome data. The radiologists completed a survey that included questions on demographics, malpractice concerns, years of experience interpreting mammograms, and the number of mammograms read annually. We used receiver operating characteristics (ROC) analysis to analyze variables associated with sensitivity, specificity, and the combination of the two, adjusting for patient variables that affect performance. All P values are two-sided.
Within 1 year of the mammogram, 2402 breast cancers were identified. Relative to low annual interpretive volume (< or =1000 mammograms), greater interpretive volume was associated with higher sensitivity (P = .001; odds ratio [OR] for moderate volume [1001-2000] = 1.68, 95% CI = 1.18 to 2.39; OR for high volume [>2000] = 1.89, 95% CI = 1.36 to 2.63). Specificity decreased with volume (OR for 1001-2000 = 0.65, 95% CI = 0.52 to 0.83; OR for more than 2000 = 0.76, 95% CI = 0.60 to 0.96), compared with 1000 or less (P = .002). Greater number of years of experience interpreting mammograms was associated with lower sensitivity (P = .001), but higher specificity (P = .003). ROC analysis using the ordinal BI-RADS interpretation showed an association between accuracy and both previous mammographic history (P = .012) and breast density (P<.001). No association was observed between accuracy and years interpreting mammograms (P = .34) or mammography volume (P = .94), after adjusting for variables that affect the threshold for calling a mammogram positive.
We found no evidence that greater volume or experience at interpreting mammograms is associated with better performance. However, they may affect sensitivity and specificity, possibly by determining the threshold for calling a mammogram positive. Increasing volume requirements is unlikely to improve overall mammography performance.
放射科医生在准确解读乳腺筛查钼靶片的能力上存在差异。我们调查了1996年至2001年间放射科医生的特征与实际表现之间的关系。
将124名放射科医生解读的469,512份乳腺筛查钼靶片与癌症结局数据相关联。放射科医生完成了一项调查,其中包括有关人口统计学、医疗事故担忧、解读钼靶片的年限以及每年解读的钼靶片数量的问题。我们使用受试者操作特征(ROC)分析来分析与敏感性、特异性以及两者组合相关的变量,并对影响表现的患者变量进行调整。所有P值均为双侧。
在钼靶检查后的1年内,共发现2402例乳腺癌。与低年度解读量(≤1000份钼靶片)相比,解读量越大,敏感性越高(P = 0.001;中等解读量[1001 - 2000]的优势比[OR] = 1.68,95%可信区间[CI] = 1.18至2.39;高解读量[>2000]的OR = 1.89,95%CI = 1.36至2.63)。与解读量为1000或更少相比,特异性随解读量增加而降低(1001 - 2000的OR = 0.65,95%CI = 0.52至0.83;超过2000的OR = 0.76,95%CI = 0.60至0.96)(P = 0.002)。解读钼靶片的年限越长,敏感性越低(P = 0.001),但特异性越高(P = 0.003)。使用有序乳腺影像报告和数据系统(BI-RADS)解读进行的ROC分析显示,准确性与既往钼靶检查史(P = 0.012)和乳腺密度(P<0.001)均相关。在调整影响钼靶片阳性判定阈值的变量后,未观察到准确性与解读钼靶片的年限(P = 0.34)或钼靶检查量(P = 0.94)之间存在关联。
我们没有发现证据表明解读钼靶片的量越大或经验越丰富与更好的表现相关。然而,它们可能会影响敏感性和特异性,可能是通过确定钼靶片阳性判定的阈值。增加工作量要求不太可能提高整体钼靶检查的表现。