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Erschienen in:
07.05.2019 | Preclinical study
Clinical and analytical validation of Ki-67 in 9069 patients from IBCSG VIII + IX, BIG1-98 and GeparTrio trial: systematic modulation of interobserver variance in a comprehensive in silico ring trial
Erschienen in: Breast Cancer Research and Treatment | Ausgabe 3/2019
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Purpose
Ki-67 has been clinically validated for risk assessment in breast cancer, but the analytical validation and cutpoint-definition remain a challenge. Intraclass correlation coefficients (ICCs) are a statistical parameter for Ki-67 interobserver performance. However, the maximum degree of variance among pathologists allowed for meaningful biomarker results has not been defined.
Methods
Different amounts of variance were added to central pathology Ki-67 data (n = 9069) from three cohorts (IBCSGVIII + IX, BIG1-98, GeparTrio) by simulation of 4500 evaluations for each cohort, which were grouped by ICCs, ranging from excellent (ICC = 0.9) to poor concordance (ICC = 0.1). Endpoints were disease-free survival (DFS) and pathological complete response (pCR, GeparTrio).
Results
Ki-67 was a significant continuous prognostic marker for DFS over a wide range of cutpoints between 8% and 30% in all three cohorts. In our modelling approach, Ki-67 was a stable prognostic marker despite increased interpathologist variance. Even for a poor ICC of 0.5, one or more significant Ki-67 cutoffs were detected in 86.8% (GeparTrio), 92.4% (IBCSGVIII + IX) and 100% of analyses (BIG1-98). Similarly, in GeparTrio, even with an extremely low ICC of 0.2, 99.6% of analyses were significant for pCR.
Conclusions
Our study shows that Ki-67 is a continuous marker which is extremely robust to pathologist variation. Even if only 50% of variance is attributable to true Ki-67-based proliferation (ICC = 0.5), this information is sufficient to obtain statistically significant differences in clinical cohorts. This stable performance explains the observation that many Ki-67 studies achieve significant results despite relevant interobserver variance and points to a high clinical validity of this biomarker. For clinical decisions based on analysis of individual patient data, ongoing efforts to further reduce interobserver variability, including ring trials and standardized guidelines as well as image analysis approaches, should be continued.