Abstract
HER-France is a French national database focused on HER2 status in breast cancer and provided by 125 pathology laboratories (PL) since 2011. PL used to compare their HER2 positivity (HER2+) rate with the calculated national average. To provide a more sensitive monitoring tool evaluating their practices quality through indicators, a new strategy considering a predicted estimate of HER2+ rate by PL instead of national average was investigated. Model to predict probability of HER2+ on core-needle biopsies (CNBs) was developed using penalized logistic regression on tumor characteristics. PL HER2+ rate estimations were obtained by averaging individual HER2+ probabilities. A PL having included more than 100 CNBs between January 2014 (ASCO-CAP recommendations) and April 2016 is considered as outlier when its averaging HER2+ predicted rate is outside a 99% confidence interval (CI) limits of its observed rate. Other indicators are absolute and relative percentage differences between observed and predicted HER2+ rates. Prediction accuracy (AUC) on 30,777 CNBs was higher than 0.77. Among the 56 PL with at least 100 CNBs (i.e. 95% of all the analysed CNBs), 6 (10.7%) were identified as outliers. Illustration with 4 PL: 2 not outliers: PL1 (n=676): observed rate: 13.6%; 99%CI: [10.2; 17.0]; predicted rate: 10.9%; absolute (relative) difference: 2.7 (20%) PL2 (n=2,062): observed rate: 9.1%; 99%CI: [7.4; 10.7]; predicted rate: 10.1%; absolute (relative) difference: 1.0 (11.8%) 2 outliers: PL3 (n=1,468): observed rate: 13.5%; 99%CI: [11.2; 15.8]; predicted rate: 10.9%; absolute (relative) difference: 2.6 (19%) PL4 (n=1,854): observed rate: 9.6%; 99%CI: [7.8; 11.4]; predicted rate: 12.0%; absolute (relative) difference: 2.4 (25%) PL tumor characteristics provide better accuracy in quality assessment practices than comparison to national average. Data mining models implemented in the HER-France monitoring web-based tool will help PL to assess their own rate through consistency indicators.
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