Sprague Brian L, Arao Robert F, Miglioretti Diana L, Henderson Louise M, Buist Diana S M, Onega Tracy, Rauscher Garth H, Lee Janie M, Tosteson Anna N A, Kerlikowske Karla, Lehman Constance D
From the Departments of Surgery, Radiology, and Biochemistry, University of Vermont Cancer Center, University of Vermont, 1 S Prospect St, UHC Room 4425, Burlington, VT 05401 (B.L.S.); Group Health Research Institute, Group Health Cooperative, Seattle, Wash (R.F.A., D.S.M.B.); Division of Biostatistics, Department of Public Health Sciences, University of California Davis School of Medicine, Davis, Calif (D.L.M.); Departments of Radiology and Epidemiology, University of North Carolina, Chapel Hill, NC (L.M.H.); The Dartmouth Institute for Health Policy and Clinical Practice and Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH (T.O., A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of Radiology, University of Washington School of Medicine, Seattle, Wash (J.M.L.); Department of Medicine, Department of Epidemiology and Biostatistics, and General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, San Francisco, Calif (K.K.); and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (C.D.L.).
Radiology. 2017 Apr;283(1):59-69. doi: 10.1148/radiol.2017161519. Epub 2017 Feb 28.
Purpose To establish contemporary performance benchmarks for diagnostic digital mammography with use of recent data from the Breast Cancer Surveillance Consortium (BCSC). Materials and Methods Institutional review board approval was obtained for active or passive consenting processes or to obtain a waiver of consent to enroll participants, link data, and perform analyses. Data were obtained from six BCSC registries (418 radiologists, 92 radiology facilities). Mammogram indication and assessments were prospectively collected for women undergoing diagnostic digital mammography and linked with cancer diagnoses from state cancer registries. The study included 401 548 examinations conducted from 2007 to 2013 in 265 360 women. Results Overall diagnostic performance measures were as follows: cancer detection rate, 34.7 per 1000 (95% confidence interval [CI]: 34.1, 35.2); abnormal interpretation rate, 12.6% (95% CI: 12.5%, 12.7%); positive predictive value (PPV) of a biopsy recommendation (PPV), 27.5% (95% CI: 27.1%, 27.9%); PPV of biopsies performed (PPV), 30.4% (95% CI: 29.9%, 30.9%); false-negative rate, 4.8 per 1000 (95% CI: 4.6, 5.0); sensitivity, 87.8% (95% CI: 87.3%, 88.4%); and specificity, 90.5% (95% CI: 90.4%, 90.6%). Among cancers detected, 63.4% were stage 0 or 1 cancers, 45.6% were minimal cancers, the mean size of invasive cancers was 21.2 mm, and 69.6% of invasive cancers were node negative. Performance metrics varied widely across diagnostic indications, with cancer detection rate (64.5 per 1000) and abnormal interpretation rate (18.7%) highest for diagnostic mammograms obtained to evaluate a breast problem with a lump. Compared with performance during the screen-film mammography era, diagnostic digital performance showed increased abnormal interpretation and cancer detection rates and decreasing PPVs, with less than 70% of radiologists within acceptable ranges for PPV and PPV. Conclusion These performance measures can serve as national benchmarks that may help transform the marked variation in radiologists' diagnostic performance into targeted quality improvement efforts. RSNA, 2017 Online supplemental material is available for this article.
目的 利用来自乳腺癌监测协会(BCSC)的最新数据,建立诊断性数字乳腺摄影的当代性能基准。材料与方法 获得机构审查委员会批准,采用主动或被动同意程序,或获得同意豁免以招募参与者、链接数据并进行分析。数据来自六个BCSC登记处(418名放射科医生,92个放射科设施)。对接受诊断性数字乳腺摄影的女性前瞻性收集乳腺X线摄影指征和评估结果,并与州癌症登记处的癌症诊断结果相链接。该研究纳入了2007年至2013年期间在265360名女性中进行的401548次检查。结果 总体诊断性能指标如下:癌症检出率为每1000人34.7例(95%置信区间[CI]:34.1,35.2);异常解读率为12.6%(95%CI:12.5%,12.7%);活检推荐的阳性预测值(PPV)为27.5%(95%CI:27.1%,27.9%);所进行活检的PPV为30.4%(95%CI:29.9%,30.9%);假阴性率为每1000人4.8例(95%CI:4.6,5.0);灵敏度为87.8%(95%CI:87.3%,88.4%);特异度为90.5%(95%CI:90.4%,90.6%)。在检测出的癌症中,63.4%为0期或1期癌症,45.6%为微小癌,浸润性癌的平均大小为21.2mm,69.6%的浸润性癌无淋巴结转移。性能指标在不同诊断指征间差异很大,对于为评估有肿块的乳腺问题而进行的诊断性乳腺X线摄影,癌症检出率(每1000人64.5例)和异常解读率(18.7%)最高。与屏-片乳腺摄影时代的性能相比,诊断性数字乳腺摄影的性能显示异常解读率和癌症检出率增加,PPV降低,不到70%的放射科医生的PPV和PPV在可接受范围内。结论 这些性能指标可作为全国性基准,有助于将放射科医生诊断性能的显著差异转化为有针对性的质量改进措施。RSNA,2017 本文有在线补充材料。