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应用“阳性预测值-召回率图”来监测性能,并为筛查放射科医生提供建议。

Applying the "positive predictive value-recall diagram" to monitor performance and provide recommendations for screening radiologists.

作者信息

Geertse Tanya D, Tetteroo Eric, Smid-Geirnaerdt Maartje J A, Duijm Lucien E M, Pijnappel Ruud M, van der Waal Daniëlle, Broeders Mireille J M

机构信息

Dutch Expert Centre for Screening (LRCB), Nijmegen, The Netherlands.

Department of Radiology, Amphia Hospital, Breda, The Netherlands.

出版信息

Eur Radiol. 2025 Sep 4. doi: 10.1007/s00330-025-11978-3.

Abstract

OBJECTIVES

To evaluate the suitability of "positive predictive value-recall" (PPV-recall) diagrams for monitoring performance and providing recommendations for groups of radiologists (RUs or reading units) in breast cancer screening.

MATERIALS AND METHODS

This retrospective study used datasets from triennial quality assurance audits within the Dutch screening programme. The recall rate (RR), cancer detection rate (CDR), and PPV between 2010 and 2019 were plotted in PPV-recall diagrams separately for initial and subsequent screening. Using PPV-recall diagrams per year we compared variations in performance of the RUs within the screening programme. Each group's screening behaviour characteristics were evaluated over time with RU-specific PPV-recall diagrams and related audit recommendations.

RESULTS

The dataset comprised the aggregated results of 779,887 initial and 6,021,598 subsequent screenings read by 12 RUs between 2010 and 2019. The PPV-recall diagrams showed substantial variations in the individual RU performance over time, with PPVs ranging between 4.9 and 23.7% for initial and 21.2-54.3% for subsequent screening. Target values were less often met for initial (2010: 0 RUs; 2019: 5 RUs) than for subsequent screening (2010: 8 RUs; 2019: 10 RUs), resulting in more recommendations regarding initial screening (24 versus 13). All recommendations focused on adjusting RR, which often (17 out of 24) changed in the recommended direction, though not always sufficient to meet target values.

CONCLUSION

PPV-recall diagrams offer valuable insights into variations and interrelationships between screening outcomes, helping the audit team in providing recommendations for improvement. However, feedback based on these diagrams alone may not always be sufficient for individual radiologists to achieve these improvements.

KEY POINTS

Question Can positive predictive value (PPV)-recall diagrams help audit teams provide recommendations to radiologists to enhance their reading performance in a breast cancer screening programme? Findings PPV-recall diagrams help audit teams identify screening outcome variation. Recall rates often changed in the desired direction after recommendations, but did not always meet targets. Clinical relevance Incorporating PPV-recall diagrams into quality assurance audits in breast cancer screening can support audit teams to provide recommendations to radiologists to maximise cancer detection and minimise false positives. Radiologists may need additional individual feedback to optimally achieve these improvements.

摘要

目的

评估“阳性预测值-召回率”(PPV-召回率)图表在监测乳腺癌筛查中放射科医生组(RU或读片单元)的表现及提供建议方面的适用性。

材料与方法

这项回顾性研究使用了荷兰筛查项目中每三年一次的质量保证审计数据集。分别针对初次和后续筛查,将2010年至2019年期间的召回率(RR)、癌症检出率(CDR)和PPV绘制在PPV-召回率图表中。使用每年的PPV-召回率图表,我们比较了筛查项目中各RU表现的差异。通过特定RU的PPV-召回率图表和相关审计建议,对每组的筛查行为特征进行了长期评估。

结果

该数据集包含了2010年至2019年间12个RU对779,887例初次筛查和6,021,598例后续筛查的汇总结果。PPV-召回率图表显示,各RU的表现随时间有显著差异,初次筛查的PPV范围在4.9%至23.7%之间,后续筛查的PPV范围在21.2%至54.3%之间)。初次筛查(2010年:0个RU;2019年:5个RU)达到目标值的情况比后续筛查(2010年:8个RU;2019年:10个RU)少,因此关于初次筛查的建议更多(24条对13条)。所有建议都集中在调整RR上,RR通常(24条中有17条)朝着建议的方向改变,尽管并不总是足以达到目标值。

结论

PPV-召回率图表为筛查结果之间的差异和相互关系提供了有价值的见解,有助于审计团队提供改进建议。然而,仅基于这些图表的反馈可能并不总是足以让个体放射科医生实现这些改进。

关键点

问题 阳性预测值(PPV)-召回率图表能否帮助审计团队向放射科医生提供建议,以提高他们在乳腺癌筛查项目中的读片表现? 发现 PPV-召回率图表有助于审计团队识别筛查结果差异。建议后召回率通常朝着期望的方向变化,但并不总是达到目标。 临床意义 将PPV-召回率图表纳入乳腺癌筛查的质量保证审计中,可以支持审计团队向放射科医生提供建议,以最大限度地提高癌症检出率并最小化假阳性。放射科医生可能需要额外的个体反馈才能最佳地实现这些改进。

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