P2-12-12: Prognostic Utility of Breast Cancer Index for Late Relapse in Patients with Early Stage Breast Cancer.

2011 ◽  
Author(s):  
CA Schnabel ◽  
Y Zhang ◽  
NC Kesty ◽  
MG Erlander
Keyword(s):  
Breast Cancer ◽  
Early Stage ◽  
Early Stage Breast Cancer ◽  
Late Relapse ◽  
Breast Cancer Index ◽  
Prognostic Utility

Prediction of early and late distant recurrence in early-stage breast cancer with Breast Cancer Index.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 594-594
Author(s):  
Yi Zhang ◽  
Catherine A. Schnabel ◽  
Brock Schroeder ◽  
Piiha-Lotta Jerevall ◽  
Rachel Catherine Jankowitz ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Cancer Patients ◽  
Distant Metastasis ◽  
Early Stage ◽  
Distant Recurrence ◽  
Early Stage Breast Cancer ◽  
Breast Cancer Patients ◽  
Risk Of Recurrence ◽  
Breast Cancer Index

594 Background: Breast Cancer Index (BCI) is a continuous risk index based on the combination of HOXB13:IL17BR (H:I) and the Molecular Grade Index (MGI) that estimates the individual risk of recurrence in ER+, LN- breast cancer patients. In the current study, a modified BCI model was developed using untreated breast cancer patients in order to evaluate its pure prognostic value, and to better optimize BCI for both early and late risk assessment. Methods: A model was built by linearly combining H:I and MGI weighted by their corresponding Cox regression coefficients using ER+ LN- patients from the untreated arm of the prospective Stockholm trial (N=283). Validation was performed in 2 independent ER+, LN- cohorts: the TAM arm of the Stockholm trial (N=317), and a multisite cohort of TAM-treated patients (N=358). Correlation of BCI with distant metastasis was evaluated by Kaplan-Meier analysis using the log rank test, and multivariate analysis adjusting for standard prognostic factors was performed using Cox proportional hazards. Results: The BCI linear model was significantly associated with risk of cumulative (0-10y), early (<5y) and late (≥5y) distant metastasis. Based on pre-specified cutpoints, BCI classified 64% and 55% patients as low-, 21% and 22% as intermediate-, and 16% and 23% as high-risk, with 10-y rates of distant recurrence (95% CI) of 4.8% (1.7-7.8%) and 6.6% (2.9–10.0%), 11.7% (3.1–19.5%) and 23.3% (12.3-33.0%), 21.1% (18.5–32.0%) and 35.8% (24.5–45.5%), in the Stockholm TAM and multisite cohort, respectively. Conclusions: BCI demonstrated significant prognostic performance beyond clinicopathological factors to predict cumulative, early and late risk of recurrence in early stage breast cancer patients. Use of BCI at diagnosis should enable clinicians to identify patients who are at high risk of late recurrence and may benefit from an additional 5y of hormonal therapy. [Table: see text]

A Novel Breast Cancer Index for Prediction of Distant Recurrence in HR+ Early-Stage Breast Cancer with One to Three Positive Nodes

2017 ◽  
Vol 23 (23) ◽  
pp. 7217-7224 ◽  
Author(s):  
Yi Zhang ◽  
Brock E. Schroeder ◽  
Piiha-Lotta Jerevall ◽  
Amy Ly ◽  
Hannah Nolan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Early Stage ◽  
Distant Recurrence ◽  
Early Stage Breast Cancer ◽  
Breast Cancer Index

scholarly journals MicroRNAs Regulating Tumor and Immune Cell Interactions in the Prediction of Relapse in Early Stage Breast Cancer

Biomedicines ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 421
Author(s):  
Chara Papadaki ◽  
Konstantina Thomopoulou ◽  
Alexia Monastirioti ◽  
George Koronakis ◽  
Maria A. Papadaki ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Immune Cell ◽  
Early Stage ◽  
Early Stage Breast Cancer ◽  
Late Relapse ◽  
Lymph Node Status ◽  
Axillary Lymph ◽  
Tumor Immune Escape ◽  
Healthy Women

MicroRNAs (miRNAs) are involved in the regulation of immune response and hold an important role in tumor immune escape. We investigated the differential expression of the immunomodulatory miR-10b, miR-19a, miR-20a, miR-126, and miR-155 in the plasma of healthy women and patients with early stage breast cancer and interrogated their role in the prediction of patients’ relapse. Blood samples were obtained from healthy women (n = 20) and patients with early stage breast cancer (n = 140) before adjuvant chemotherapy. Plasma miRNA expression levels were assessed by RT-qPCR. Relapse predicting models were developed using binary logistic regression and receiver operating curves (ROC) were constructed to determine miRNA sensitivity and specificity. Only miR-155 expression was lower in patients compared with healthy women (p = 0.023), whereas miR-155 and miR-10b were lower in patients who relapsed compared with healthy women (p = 0.039 and p = 0.002, respectively). MiR-155 expression combined with axillary lymph node infiltration and tumor grade demonstrated increased capability in distinguishing relapsed from non-relapsed patients [(area under the curve, (AUC = 0.861; p < 0.001)]. Combined miR-19a and miR-20a expression had the highest performance in discriminating patients with early relapse (AUC = 0.816; p < 0.001). Finally, miR-10b in combination with lymph node status and grade had the highest accuracy to discriminate patients with late relapse (AUC = 0.971; p < 0.001). The robustness of the relapse predicting models was further confirmed in a 10-fold cross validation. Deregulation of circulating miRNAs involved in tumor-immune interactions may predict relapse in early stage breast cancer. Their successful clinical integration could potentially address the significance challenge of treatment escalation or de-escalation according to the risk of recurrence.

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