Baselga J.,Massachusetts General Hospital |
Segalla J.G.M.,Fundacao Dr. Amaral Carvalho |
Roche H.,Institute Claudius Regaud |
Del Giglio A.,Federal University of ABC |
And 18 more authors.
Journal of Clinical Oncology | Year: 2012
Purpose: Sorafenib is a multikinase inhibitor with antiangiogenic/ antiproliferative activity. A randomized, double-blind, placebo-controlled phase IIB trial assessed sorafenib with capecitabine for locally advanced or metastatic human epidermal growth factor receptor 2 (HER2) -negative breast cancer. Patients and Methods: Patients were randomly assigned to first- or second-line capecitabine 1,000 mg/m 2 orally twice a day for days 1 to 14 of every 21-day cycle with sorafenib 400 mg orally twice a day or placebo. The primary end point was progression-free survival (PFS). Results: In total, 229 patients were enrolled. The addition of sorafenib to capecitabine resulted in a significant improvement in PFS versus placebo (median, 6.4 v 4.1 months; hazard ratio [HR], 0.58; 95% CI, 0.41 to 0.81; P = .001) with sorafenib favored across subgroups, including first-line (HR, 0.50; 95% CI, 0.30 to 0.82) and second-line (HR, 0.65; 95% CI, 0.41 to 1.04) treatment. There was no significant improvement for overall survival (median, 22.2 v 20.9 months; HR, 0.86; 95% CI, 0.61 to 1.23; P = .42) and overall response (38% v 31%; P = .25). Toxicities (sorafenib v placebo) of any grade included rash (22% v 8%), diarrhea (58% v 30%), mucosal inflammation (33% v 21%), neutropenia (13% v 4%), hypertension (18% v 12%), and hand-foot skin reaction/handfoot syndrome (HFSR/HFS; 90% v 66%); grade 3 to 4 toxicities were comparable between treatment arms except HFSR/HFS (44% v 14%). Reasons for discontinuation in the sorafenib and placebo arms included disease progression (63% v 82%, respectively), adverse events (20% v 9%, respectively), and death (0% v 1%, respectively). Conclusion: Addition of sorafenib to capecitabine improved PFS in patients with HER2-negative advanced breast cancer. The dose of sorafenib used in this trial resulted in unacceptable toxicity for many patients. A phase III confirmatory trial has been initiated with a reduced sorafenib dose. © 2012 by American Society of Clinical Oncology. Source
Pajares B.,Hospital Clinico Universitario Virgen Of La Victoria |
Pollan M.,Institute Salud Carlos III |
Martin M.,Complutense University of Madrid |
Mackey J.R.,Medical Cross Cancer Institute |
And 16 more authors.
Breast Cancer Research | Year: 2013
Introduction: Obesity is an unfavorable prognostic factor in breast cancer (BC) patients regardless of menopausal status and treatment received. However, the association between obesity and survival outcome by pathological subtype requires further clarification.Methods: We performed a retrospective analysis including 5,683 operable BC patients enrolled in four randomized clinical trials (GEICAM/9906, GEICAM/9805, GEICAM/2003-02, and BCIRG 001) evaluating anthracyclines and taxanes as adjuvant treatments. Our primary aim was to assess the prognostic effect of body mass index (BMI) on disease recurrence, breast cancer mortality (BCM), and overall mortality (OM). A secondary aim was to detect differences of such prognostic effects by subtype.Results: Multivariate survival analyses adjusting for age, tumor size, nodal status, menopausal status, surgery type, histological grade, hormone receptor status, human epidermal growth factor receptor 2 (HER2) status, chemotherapy regimen, and under-treatment showed that obese patients (BMI 30.0 to 34.9) had similar prognoses to that of patients with a BMI < 25 (reference group) in terms of recurrence (Hazard Ratio [HR] = 1.08, 95% Confidence Interval [CI] = 0.90 to 1.30), BCM (HR = 1.02, 0.81 to 1.29), and OM (HR = 0.97, 0.78 to 1.19). Patients with severe obesity (BMI ≥ 35) had a significantly increased risk of recurrence (HR = 1.26, 1.00 to 1.59, P = 0.048), BCM (HR = 1.32, 1.00 to 1.74, P = 0.050), and OM (HR = 1.35, 1.06 to 1.71, P = 0.016) compared to our reference group. The prognostic effect of severe obesity did not vary by subtype.Conclusions: Severely obese patients treated with anthracyclines and taxanes present a worse prognosis regarding recurrence, BCM, and OM than patients with BMI < 25. The magnitude of the harmful effect of BMI on survival-related outcomes was similar across subtypes. © 2013 Pajares et al.; licensee BioMed Central Ltd. Source
Bastien R.R.,Arup |
Rodriguez-Lescure A.,Hospital Universitario Of Elche |
Ebbert M.T.,Arup |
Prat A.,University of North Carolina at Chapel Hill |
And 31 more authors.
BMC Medical Genomics | Year: 2012
Background: Many methodologies have been used in research to identify the intrinsic subtypes of breast cancer commonly known as Luminal A, Luminal B, HER2-Enriched (HER2-E) and Basal-like. The PAM50 gene set is often used for gene expression-based subtyping; however, surrogate subtyping using panels of immunohistochemical (IHC) markers are still widely used clinically. Discrepancies between these methods may lead to different treatment decisions. Methods. We used the PAM50 RT-qPCR assay to expression profile 814 tumors from the GEICAM/9906 phase III clinical trial that enrolled women with locally advanced primary invasive breast cancer. All samples were scored at a single site by IHC for estrogen receptor (ER), progesterone receptor (PR), and Her2/neu (HER2) protein expression. Equivocal HER2 cases were confirmed by chromogenic in situ hybridization (CISH). Single gene scores by IHC/CISH were compared with RT-qPCR continuous gene expression values and intrinsic subtype assignment by the PAM50. High, medium, and low expression for ESR1, PGR, ERBB2, and proliferation were selected using quartile cut-points from the continuous RT-qPCR data across the PAM50 subtype assignments. Results: ESR1, PGR, and ERBB2 gene expression had high agreement with established binary IHC cut-points (area under the curve (AUC)0.9). Estrogen receptor positivity by IHC was strongly associated with Luminal (A and B) subtypes (92%), but only 75% of ER negative tumors were classified into the HER2-E and Basal-like subtypes. Luminal A tumors more frequently expressed PR than Luminal B (94% vs 74%) and Luminal A tumors were less likely to have high proliferation (11% vs 77%). Seventy-seven percent (30/39) of ER-/HER2+ tumors by IHC were classified as the HER2-E subtype. Triple negative tumors were mainly comprised of Basal-like (57%) and HER2-E (30%) subtypes. Single gene scoring for ESR1, PGR, and ERBB2 was more prognostic than the corresponding IHC markers as shown in a multivariate analysis. Conclusions: The standard immunohistochemical panel for breast cancer (ER, PR, and HER2) does not adequately identify the PAM50 gene expression subtypes. Although there is high agreement between biomarker scoring by protein immunohistochemistry and gene expression, the gene expression determinations for ESR1 and ERBB2 status was more prognostic. © 2012 Bastien et al. Source
Ebbert M.T.W.,University of Utah |
Ebbert M.T.W.,Arup |
Bastien R.R.L.,Arup |
Boucher K.M.,University of Utah |
And 7 more authors.
Journal of Clinical Bioinformatics | Year: 2011
Background: Multivariate assays (MVAs) for assisting clinical decisions are becoming commonly available, but due to complexity, are often considered a high-risk approach. A key concern is that uncertainty on the assay's final results is not well understood. This study focuses on developing a process to characterize error introduced in the MVA's results from the intrinsic error in the laboratory process: sample preparation and measurement of the contributing factors, such as gene expression.Methods: Using the PAM50 Breast Cancer Intrinsic Classifier, we show how to characterize error within an MVA, and how these errors may affect results reported to clinicians. First we estimated the error distribution for measured factors within the PAM50 assay by performing repeated measures on four archetypal samples representative of the major breast cancer tumor subtypes. Then, using the error distributions and the original archetypal sample data, we used Monte Carlo simulations to generate a sufficient number of simulated samples. The effect of these errors on the PAM50 tumor subtype classification was estimated by measuring subtype reproducibility after classifying all simulated samples. Subtype reproducibility was measured as the percentage of simulated samples classified identically to the parent sample. The simulation was thereafter repeated on a large, independent data set of samples from the GEICAM 9906 clinical trial. Simulated samples from the GEICAM sample set were used to explore a more realistic scenario where, unlike archetypal samples, many samples are not easily classified.Results: All simulated samples derived from the archetypal samples were classified identically to the parent sample. Subtypes for simulated samples from the GEICAM set were also highly reproducible, but there were a non-negligible number of samples that exhibit significant variability in their classification.Conclusions: We have developed a general methodology to estimate the effects of intrinsic errors within MVAs. We have applied the method to the PAM50 assay, showing that the PAM50 results are resilient to intrinsic errors within the assay, but also finding that in non-archetypal samples, experimental errors can lead to quite different classification of a tumor. Finally we propose a way to provide the uncertainty information in a usable way for clinicians. © 2011 Ebbert et al; licensee BioMed Central Ltd. Source