Clinically high-risk breast cancer displays markedly discordant molecular risk predictions between the MammaPrint and EndoPredict tests.
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SUBMITTER: Jahn SW
PROVIDER: S-EPMC7283343 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionCorrect risk assessment of disease recurrence in patients with early breast cancer is critically important to detect patients who may be spared adjuvant chemotherapy. In clinical practice this is increasingly done based on the results of gene expression assays. In the present study we compared the concordance of the 70-gene signature MammaPrint (MP) with the 12 gene assay EndoPredict (EP).MethodsRepresentative tissue of 48 primary tumours was analysed with the MP during routine diagnostic purposes. Corresponding formalin-fixed, paraffin-embedded tissue was thereafter analysed by the EP test. Risk categories of both tests were compared.Results41 of 48 tumours could be directly compared by both tests. Of the 17 MP low risk cases, only 9 were considered low risk by EP (53% agreement) and of the 24 MP high risk cases, 18 were high risk by EP (75% agreement). Discrepancies occurred in 14 of 41 cases (34.1%). There was only a weak and non-significant correlation between the MP and EP test with an overall concordance of only 66%. The original therapeutic recommendation was based on the MP and would have been changed in 38% of the patients following EP test results. 4 patients developed distant metastases. The respective tumours of these patients were all classified as high risk by the EP, but only 3 were classified as high risk by the MP.ConclusionBoth tests resulted in different treatment recommendations for a significant proportion of patients and cannot be used interchangeably. The results underscore the urgent need for further comparative analyses of multi-genomic tests to avoid misclassification of disease recurrence risk in breast cancer patients.
| S-EPMC5574574 | biostudies-literature
Project description:PurposeTo compare the concordance in risk classification between the EndoPredict and the MammaPrint scores obtained for the same cancer samples on 40 estrogen-receptor positive/HER2-negative breast carcinomas.MethodsFormalin-fixed, paraffin-embedded invasive breast carcinoma tissues that were previously analyzed with MammaPrint as part of routine care of the patients, and were classified as high-risk (20 patients) and low-risk (20 patients), were selected to be analyzed by the EndoPredict assay, a second generation gene expression test that combines expression of 8 genes (EP score) with two clinicopathological variables (tumor size and nodal status, EPclin score).ResultsThe EP score classified 15 patients as low-risk and 25 patients as high-risk. EPclin re-classified 5 of the 25 EP high-risk patients into low-risk, resulting in a total of 20 high-risk and 20 low-risk tumors. EP score and MammaPrint score were significantly correlated (p = 0.008). Twelve of 20 samples classified as low-risk by MammaPrint were also low-risk by EP score (60%). 17 of 20 MammaPrint high-risk tumors were also high-risk by EP score. The overall concordance between EP score and MammaPrint was 72.5% (κ = 0.45, (95% CI, 0.182 to 0.718)). EPclin score also correlated with MammaPrint results (p = 0.004). Discrepancies between both tests occurred in 10 cases: 5 MammaPrint low-risk patients were classified as EPclin high-risk and 5 high-risk MammaPrint were classified as low-risk by EPclin and overall concordance of 75% (κ = 0.5, (95% CI, 0.232 to 0.768)).ConclusionsThis pilot study demonstrates a limited concordance between MammaPrint and EndoPredict. Differences in results could be explained by the inclusion of different gene sets in each platform, the use of different methodology, and the inclusion of clinicopathological parameters, such as tumor size and nodal status, in the EndoPredict test.
| S-EPMC5590847 | biostudies-literature
Project description:We aimed to develop a prediction MammaPrint (MMP) genomic risk assessment nomogram model for hormone-receptor positive (HR+) and human epidermal growth factor receptor-2 negative (HER2-) breast cancer and minimal axillary burden (N0-1) tumors using clinicopathological factors of patients who underwent an MMP test for decision making regarding adjuvant chemotherapy. A total of 409 T1-3 N0-1 M0 HR + and HER2- breast cancer patients whose MMP genomic risk results and clinicopathological factors were available from 2017 to 2020 were analyzed. With randomly selected 306 patients, we developed a nomogram for predicting a low-risk subgroup of MMP results and externally validated with remaining patients (n = 103). Multivariate analysis revealed that the age at diagnosis, progesterone receptor (PR) score, nuclear grade, and Ki-67 were significantly associated with MMP risk results. We developed an MMP low-risk predictive nomogram. With a cut off value at 5% and 95% probability of low-risk MMP, the nomogram accurately predicted the results with 100% positive predictive value (PPV) and negative predictive value respectively. When applied to cut-off value at 35%, the specificity and PPV was 95% and 86% respectively. The area under the receiver operating characteristic curve was 0.82 (95% confidence interval [CI] 0.77 to 0.87). When applied to the validation group, the nomogram was accurate with an area under the curve of 0.77 (95% CI 0.68 to 0.86). Our nomogram, which incorporates four traditional prognostic factors, i.e., age, PR, nuclear grade, and Ki-67, could predict the probability of obtaining a low MMP risk in a cohort of high clinical risk patients. This nomogram can aid the prompt selection of patients who does not need additional MMP testing.
| S-EPMC8648770 | biostudies-literature
Project description:BackgroundMammaPrint (MMP) helps clinicians identify the ideal time for adjuvant treatment for patients with early HR+/HER2- breast cancer. We aimed to validate a nomogram designed to predict probability of low risk of MMP results and to evaluate the difference in survival outcome between two groups divided by nomogram score.MethodsIn this retrospective cohort study, we evaluated 172 patients from Asan Medical Center, Seoul, Korea, who underwent breast cancer surgery and MMP during 2020-2021. First, we validated the nomogram by calculating the area under the curve (AUC) and using calibration. Additionally, with the data of 1,835 T1-3N0-1M0 HR+/HER2- patients from Asan Medical Center during 2010-2013, we compared the disease-free survival (DFS), overall survival (OS), and breast cancer-specific survival (BCSS) rates by Kaplan-Meier analysis between the two groups divided by nomogram total point (TP) of 183.ResultsThe AUC calculated by validation of 172 patients was 0.73 (95% confidence interval [CI], 0.66-0.81). The discrimination and calibration of the prediction model were satisfactory following additional validation of 1835 patients. The high-risk and low-risk groups had different 5-year OS (97.9% vs. 98.1%, p = 0.056), DFS (98.6% vs. 99.4%, p = 0.008), and BCSS rates (98.6% vs. 99.4%, p = 0.002).ConclusionFor treatment decision-making among clinically high-risk patients with HR+/HER2- and node-positive disease, the nomogram showed satisfactory performance in predicting patients with low genomic risk. Survival outcome significantly differed between two groups divided by nomogram TP. More studies are needed to validate this model in international cohorts and large prospective cohorts from other institutions.
| S-EPMC9789221 | biostudies-literature
Project description:A property of diagnostic tests and risk models deserving more attention is risk stratification, defined as the ability of a test or model to separate those at high absolute risk of disease from those at low absolute risk. Risk stratification fills a gap between measures of classification (ie, area under the curve (AUC)) that do not require absolute risks and decision analysis that requires not only absolute risks but also subjective specification of costs and utilities. We introduce mean risk stratification (MRS) as the average change in risk of disease (posttest-pretest) revealed by a diagnostic test or risk model dichotomized at a risk threshold. Mean risk stratification is particularly valuable for rare conditions, where AUC can be high but MRS can be low, identifying situations that temper overenthusiasm for screening with the new test/model. We apply MRS to the controversy over who should get testing for mutations in BRCA1/2 that cause high risks of breast and ovarian cancers. To reveal different properties of risk thresholds to refer women for BRCA1/2 testing, we propose an eclectic approach considering MRS and other metrics. The value of MRS is to interpret AUC in the context of BRCA1/2 mutation prevalence, providing a range of risk thresholds at which a risk model is "optimally informative," and to provide insight into why net benefit arrives to its conclusion.
| S-EPMC6827980 | biostudies-literature
Project description:PURPOSE:Evaluating consecutive early breast cancer patients, we analyzed both the impact of EndoPredict® on clinical decisions as well as clinico-pathological factors influencing the decision to perform this gene expression test. METHODS:Hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative early breast cancer patients treated between 2011 and 2016 were included in this study to investigate the role of EndoPredict® (EPclin) in the treatment of early breast cancer. A main study aim was to analyze the changes in therapy recommendations with and without EPclin. In addition, the impact of clinico-pathological parameters for the decision to perform EPclin was examined by Pearson's chi-squared test (?2-test) and Fisher's exact test as well as univariate and multivariate logistic regressions. RESULTS:In a cohort of 869 consecutive early HR-positive, HER-negative breast cancer patients, EPclin was utilized in 156 (18.0%) patients. EPclin led to changes in therapy recommendations in 33.3% (n?=?52), with both therapy escalation in 19.2% (n?=?30) and de-escalation in 14.1% (n?=?22). The clinico-pathological factors influencing the use of EPclin were age (P?<?0.001, odds ratio [OR] 0.498), tumor size (P?=?0.011, OR 0.071), nodal status (P?=?0.021, OR 1.674), histological grade (P?=?0.043, OR 0.432), and Ki-67 (P?<?0.001, OR 3.599). CONCLUSIONS:EPclin led to a change in therapy recommendations in one third of the patients. Clinico-pathological parameters such as younger age, smaller tumor size, positive nodal status, intermediate histological grade and intermediate Ki-67 had a significant influence on the use of EndoPredict®.
| S-EPMC7275019 | biostudies-literature
Project description:The findings from genome-wide association studies hold enormous potential for novel insight into disease mechanisms. A major challenge in the field is to map these low-risk association signals to their underlying functional sequence variants (FSV). Simple sequence study designs are insufficient, as the vast numbers of statistically comparable variants and a limited knowledge of noncoding regulatory elements complicate prioritization. Furthermore, large sample sizes are typically required for adequate power to identify the initial association signals. One important question is whether similar sample sizes need to be sequenced to identify the FSVs. Here, we present a proof-of-principle example of an extreme discordant design to map FSVs within the 2q33 low-risk breast cancer locus. Our approach employed DNA sequencing of a small number of discordant haplotypes to efficiently identify candidate FSVs. Our results were consistent with those from a 2,000-fold larger, traditional imputation-based fine-mapping study. To prioritize further, we used expression-quantitative trait locus analysis of RNA sequencing from breast tissues, gene regulation annotations from the ENCODE consortium, and functional assays for differential enhancer activities. Notably, we implicate three regulatory variants at 2q33 that target CASP8 (rs3769823, rs3769821 in CASP8, and rs10197246 in ALS2CR12) as functionally relevant. We conclude that nested discordant haplotype sequencing is a promising approach to aid mapping of low-risk association loci. The ability to include more efficient sequencing designs into mapping efforts presents an opportunity for the field to capitalize on the potential of association loci and accelerate translation of association signals to their underlying FSVs. Cancer Res; 76(7); 1916-25. ©2016 AACR.
| S-EPMC4873429 | biostudies-literature
Project description:Most node-negative breast cancer patients are older and postmenopausal and are increasingly being offered adjuvant chemotherapy despite their low overall risk of distant relapse. A molecular diagnostic test with high negative predictive value (NPV) for distant metastasis in this subgroup would spare many older breast cancer patients adjuvant treatment.We determined the NPV and positive predictive value of the MammaPrint assay in breast cancer patients who were consecutively diagnosed and treated at the Massachusetts General Hospital between 1985 and 1997. Primary tumors from 100 patients with node-negative, invasive breast cancer (median age, 62.5 years; median follow-up, 11.3 years) were subjected to MammaPrint analysis and classified as being at either low or high risk for distant metastasis.The MammaPrint 70-gene signature displayed excellent NPV as in previous studies, correctly identifying 100% of women at low risk for distant metastases at 5 years. However, this assay had a lower positive predictive value (12% at 5 years) than previously observed.The MammaPrint assay was originally designed to identify younger breast cancer patients at low risk for distant metastasis, who might consequently be spared systemic treatment. We show here that the same signature has a very high NPV for distant recurrence after adjuvant treatment in older breast cancer patients.
| S-EPMC3089800 | biostudies-literature
Project description:BACKGROUND:Increased usage of genomic risk assessment assays suggests increased reliance on data provided by these assays to guide therapy decisions. The current study aimed to assess the change in treatment decision and physician confidence based on the 70-gene risk of recurrence signature (70-GS, MammaPrint) and the 80-gene molecular subtype signature (80-GS, BluePrint) in early stage breast cancer patients. METHODS:IMPACt, a prospective, case-only study, enrolled 452 patients between November 2015 and August 2017. The primary objective population included 358 patients with stage I-II, hormone receptor-positive, HER2-negative breast cancer. The recommended treatment plan and physician confidence were captured before and after receiving results for 70-GS and 80-GS. Treatment was started after obtaining results. The distribution of 70-GS High Risk (HR) and Low Risk (LR) patients was evaluated, in addition to the distribution of 80-GS compared to IHC status. RESULTS:The 70-GS classified 62.5% (n?=?224/358) of patients as LR and 37.5% (n?=?134/358) as HR. Treatment decisions were changed for 24.0% (n?=?86/358) of patients after receiving 70-GS and 80-GS results. Of the LR patients initially prescribed CT, 71.0% (44/62) had CT removed from their treatment recommendation. Of the HR patients not initially prescribed CT, 65.1% (41/63) had CT added. After receiving 70-GS results, CT was included in 83.6% (n?=?112/134) of 70-GS HR patient treatment plans, and 91.5% (n?=?205/224) of 70-GS LR patient treatment plans did not include CT. For patients who disagreed with the treatment recommended by their physicians, most (94.1%, n?=?16/17) elected not to receive CT when it was recommended. For patients whose physician-recommended treatment plan was discordant with 70-GS results, discordance was significantly associated with age and lymph node status. CONCLUSIONS:The IMPACt trial showed that treatment plans were 88.5% (n?=?317/358) in agreement with 70-GS results, indicating that physicians make treatment decisions in clinical practice based on the 70-GS result. In clinically high risk, 70-GS Low Risk patients, there was a 60.0% reduction in treatment recommendations that include CT. Additionally, physicians reported having greater confidence in treatment decisions for their patients in 72% (n?=?258/358) of cases after receiving 70-GS results. TRIAL REGISTRATION:"Measuring the Impact of MammaPrint on Adjuvant and Neoadjuvant Treatment in Breast Cancer Patients: A Prospective Registry" (NCT02670577) retrospectively registered on Jan 27, 2016.
| S-EPMC6995096 | biostudies-literature
Project description:BackgroundMammaPrint® is a microarray-based gene expression test cleared by the US Food and Drug Administration to assess recurrence risk in early-stage breast cancer, aimed to guide physicians in making neoadjuvant and adjuvant treatment decisions. The increase in the incidence of invasive lobular carcinomas (ILCs) over the past decades and the modest representation of ILC in the MammaPrint development data set calls for a stratified survival analysis dedicated to this specific subgroup.Study aimThe current study aimed to validate the prognostic value of the MammaPrint test for breast cancer patients with early-stage ILCs.Materials and methodsUnivariate and multivariate survival associations for overall survival (OS), distant metastasis-free interval (DMFI), and distant metastasis-free survival (DMFS) were studied in a study population of 217 early-stage ILC breast cancer patients from five different clinical studies.Results and discussionA significant association between MammaPrint High Risk and poor clinical outcome was shown for OS, DMFI, and DMFS. A subanalysis was performed on the lymph node-negative study population. In the lymph node-negative study population, we report an up to 11 times higher change in the diagnosis of an event in the MammaPrint High Risk group. For DMFI, the reported hazard ratio is 11.1 (95% confidence interval = 2.3-53.0).ConclusionStudy results validate MammaPrint as an independent factor for breast cancer patients with early-stage invasive lobular breast cancer. Hazard ratios up to 11 in multivariate analyses emphasize the independent value of MammaPrint, specifically in lymph node-negative ILC breast cancers.
| S-EPMC5153320 | biostudies-literature