| Literature DB >> 28877230 |
Johannes Ettl1, Evelyn Klein1, Alexander Hapfelmeier2, Kirsten Grosse Lackmann1, Stefan Paepke1, Christoph Petry3, Katja Specht4, Laura Wolff1, Heinz Höfler4, Marion Kiechle1.
Abstract
BACKGROUND: Adjuvant therapy decisions in early breast cancer are based on accurate risk assessment. Urokinase plasminogen activator (uPA) and plaminogen activator inhibitor-1 (PAI-1) have been the first biomarkers in hormone receptor (HR) positive breast cancer to reach highest level of evidence. The EndoPredict test (EPclin) combines gene expression information with nodal status and tumor size. The aim of this prospective study was to compare uPA/PAI-1 and EPclin as prognostic biomarkers with regard to feasibility, risk stratification and impact on adjuvant therapy recommendation. MATERIALS ANDEntities:
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Year: 2017 PMID: 28877230 PMCID: PMC5587293 DOI: 10.1371/journal.pone.0183917
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Tumor characteristics.
| Characteristic | number of pt (n = 395) | % |
|---|---|---|
| pT1a | 22 | 5,6 |
| pT1b | 69 | 17.5 |
| pT1c | 152 | 38,5 |
| pT2 | 136 | 34,4 |
| pT3 | 16 | 4 |
| ductal | 279 | 70,6 |
| lobular | 74 | 18,7 |
| ductulo-lobular | 19 | 4,8 |
| tubular | 16 | 4,1 |
| mucinous | 4 | 1 |
| papillary | 1 | 0,3 |
| medullary | 2 | 0,5 |
| G1 | 80 | 20,3 |
| G2 | 255 | 64,6 |
| G3 | 60 | 15,1 |
| pN0 | 304 | 77 |
| pN+ (mi) | 14 | 3,5 |
| pN+ (1–3) | 77 | 19,5 |
Fig 1Distribution of risk classes based on EPclin and uPA/PAI-1 test results.
Fig 2EPclin shows a stronger correlation with grading than uPA/PAI-1.
(A) Distribution of the EPclin class as a function of histopathological parameter of grading. Spearman's correlation rho = 0.32; p<0.001. The width of the bars represents the number of observations. (B) Distribution of the protease class as a function of histopathological parameter of grading. Spearman's correlation rho = 0.17; p = 0.021. The width of the bars represents the number of observations.
Fig 3Moderate correlation between EPclin and uPA.
Relations are quantified by Spearman’s rank correlation coefficient (r). Allocation to risk classes is indicated by dashed lines. Corresponding concordance is measured by Cohen's kappa (κ).
Fig 4Very weak correlation between EPclin and PAI-1.
Relations are quantified by Spearman’s rank correlation coefficient (r). Allocation to risk classes is indicated by dashed lines. Corresponding concordance is measured by Cohen's kappa (κ).
Risk classification by EPclin vs. uPA/PAI-1.
| n = 190 | uPA/PAI-1 high risk | uPA/PAI-1 low risk |
|---|---|---|
| EPclin high risk | 52 (27%) | 27 (15%) |
| EPclin low risk | 50 (26%) | 61 (32%) |
Decision impact by EPclin vs. uPA/PAI-1.
| n = 190 | no impact according to uPA/PAI-1 | minus CTX according to uPA/PAI-1 | plus CTX according to uPA/PAI-1 |
|---|---|---|---|
| no impact according to EPclin | 90 (47%) | 10 (5%) | 3 (2%) |
| minus CTX according to EPclin | 53 (28%) | 32 (17%) | 0 |
| plus CTX according to EPclin | 1 (0.5%) | 0 | 1 (0.5%) |
Fig 5Decision impact by EPclin in the overall study population.
Interdisciplinary tumor conference was aware of both EPclin and uPA/PAI-1 results.
Fig 6Decision impact by EPclin is stronger compared to decision impact by uPA/PAI-1.
(A) Decision impact by uPA/PAI-1. (B) Decision impact by EPclin.