Multigene assays and molecular markers in breast cancer: systematic review of health economic analyses

Searching for the "Holy Grail" of breast cancer recurrence risk: a narrative review of the hunt for a better biomarker and the promise of circulating tumor DNA (ctDNA)

BACKGROUND

This paper is a narrative review of a major clinical challenge at the heart of breast cancer care: determining which patients are at risk of recurrence, which require systemic therapy, and which remain at risk in the survivorship phase of care despite initial therapy.

METHODS

We review the literature on prognostic and predictive biomarkers in breast cancer with a focus on detection of minimal residual disease.

RESULTS

While we have many tools to estimate and refine risk that are used to individualize local and systemic therapy, we know that we continue to over treat many patients and undertreat others. Many patients also experience what is, at least in hindsight, needless fear of recurrence. In this review, we frame this dilemma for the practicing breast oncologist and discuss the search for what we term the "holy grail" of breast cancer evaluation: the ideal biomarker of residual distant disease. We review the history of attempts to address this problem and the up-to-date science on biomarkers, circulating tumor cells and circulating tumor DNA (ctDNA).

CONCLUSION

This review suggests that the emerging promise of ctDNA may help resolve a crticical dilemma at the heart of breast cancer care, and improve prognostication, treatment selection, and outcomes for patients with breast cancer.

Prediction of a Multi-Gene Assay (Oncotype DX and Mammaprint) Recurrence Risk Group Using Machine Learning in Estrogen Receptor-Positive, HER2-Negative Breast Cancer-The BRAIN Study

This study aimed to develop a machine learning-based prediction model for predicting multi-gene assay (MGA) risk categories. Patients with estrogen receptor-positive (ER+)/HER2- breast cancer who had undergone Oncotype DX (ODX) or MammaPrint (MMP) were used to develop the prediction model. The development cohort consisted of a total of 2565 patients including 2039 patients tested with ODX and 526 patients tested with MMP. The MMP risk prediction model utilized a single XGBoost model, and the ODX risk prediction model utilized combined LightGBM, CatBoost, and XGBoost models through soft voting. Additionally, the ensemble (MMP + ODX) model combining MMP and ODX utilized CatBoost and XGBoost through soft voting. Ten random samples, corresponding to 10% of the modeling dataset, were extracted, and cross-validation was performed to evaluate the accuracy on each validation set. The accuracy of our predictive models was 84.8% for MMP, 87.9% for ODX, and 86.8% for the ensemble model. In the ensemble cohort, the sensitivity, specificity, and precision for predicting the low-risk category were 0.91, 0.66, and 0.92, respectively. The prediction accuracy exceeded 90% in several subgroups, with the highest prediction accuracy of 95.7% in the subgroup that met Ki-67 <20 and HG 1~2 and premenopausal status. Our machine learning-based predictive model has the potential to complement existing MGAs in ER+/HER2- breast cancer.

Young Women with Breast Cancer: The Current Role of Precision Oncology

Young adults aged 40 years and younger with breast cancer represent less than 5% of all breast cancer cases, yet it is the leading cause of death among young women with cancer worldwide. Breast cancer that develops at a young age is more aggressive and has biological features that carry an increased risk of relapse and death. Young adults are more likely to have a genetic predisposition and key biomarkers, including endocrine receptors, the HER2 receptor, and proliferation biomarkers, that appear different compared to older adults. Despite being more aggressive, management strategies are largely the same irrespective of age. Given the higher rates of genetic predisposition, fast access to genetic counselling and testing is a necessity. In this review, the biological differences in young adult breast cancer and the current role precision medicine holds in the treatment of young adults with breast cancer are explored. Given the relatively high risk of relapse, developing novel genomic tools to refine the treatment options beyond the current standard is critical. Existing predictive genomic tests require careful interpretation with consideration of the patient's clinical and pathological features in the young patient cohort. Careful evaluation is also required when considering extended endocrine therapy options. Improved characterization of mutations occurring in tumors using next-generation sequencing could identify important driver mutations that arise in young women. Applying the advances of precision medicine equitably to patients in resource-rich and low- and middle-income countries will be critical to impacting the survival of young adults with breast cancer worldwide.

Cost-utility analysis of genomic profiling in early breast cancer in Colombia

BACKGROUND

In Colombia, the best strategy to establish indication for adjuvant chemotherapy in early breast cancer (EBC) remains unknown. This study aimed to identify the cost-utility of Oncotype DX™ (ODX) or Mammaprint™ (MMP) tests to establish the necessity of adjuvant chemotherapy.

METHODS

This study used an adapted decision-analytic model to compare cost and outcomes of care between ODX or MMP tests and routine care without ODX or MMP tests (adjuvant chemotherapy for all patients) over a 5-year time horizon from the perspective of the Colombian National Health System (NHS; payer). Inputs were obtained from national unit cost tariffs, published literature, and clinical trial database. The study population comprised women with hormone-receptor-positive (HR +), HER2-negative, lymph-node-negative (LN0) EBC with high-risk clinical criteria for recurrence. The outcome measures were discounted incremental cost-utility ratio (ICUR; 2021 United States dollar per quality-adjusted life-year [QALY] gained) and net monetary benefit (NMB). Probabilistic (PSA) and deterministic sensitivity analysis (DSA) were performed.

RESULTS

ODX increases QALYs by 0.05 and MMP by 0.03 with savings of $2374 and $554 compared with the standard strategy, respectively, and were cost-saving in cost-utility plane. NMB for ODX was $2203 and for MMP was $416. Both tests dominate the standard strategy. Sensitivity analysis revealed that with a threshold of 1 gross domestic product per capita, ODX will be cost-effective in 95.5% of the cases compared with 70.2% cases involving MMP.DSA showed that the variable with significant influence was the monthly cost of adjuvant chemotherapy. PSA revealed that ODX was a consistently superior strategy.

CONCLUSIONS

Genomic profiling using ODX or MMP tests to define the need of adjuvant chemotherapy treatment in patients with HR + and HER2 -EBC is a cost-effective strategy that allows Colombian NHS to maintain budget.

Predicting tumour radiosensitivity to deliver precision radiotherapy

Owing to advances in radiotherapy, the physical properties of radiation can be optimized to enable individualized treatment; however, optimization is rarely based on biological properties and, therefore, treatments are generally planned with the assumption that all tumours respond similarly to radiation. Radiation affects multiple cellular pathways, including DNA damage, hypoxia, proliferation, stem cell phenotype and immune response. In this Review, we summarize the effect of these pathways on tumour responses to radiotherapy and the current state of research on genomic classifiers designed to exploit these variations to inform treatment decisions. We also discuss whether advances in genomics have generated evidence that could be practice changing and whether advances in genomics are now ready to be used to guide the delivery of radiotherapy alone or in combination.

The Rochester Modified Magee Algorithm (RoMMa): An Outcomes Based Strategy for Clinical Risk-Assessment and Risk-Stratification in ER Positive, HER2 Negative Breast Cancer Patients Being Considered for Oncotype DX® Testing

INTRODUCTION

Multigene genomic profiling has become the standard of care in the clinical risk-assessment and risk-stratification of ER⁺, HER2^- breast cancer (BC) patients, with Oncotype DX^® (ODX) emerging as the genomic profile test with the most support from the international community. The current state of the health care economy demands that cost-efficiency and access to testing must be considered when evaluating the clinical utility of multigene profile tests such as ODX. Several studies have suggested that certain lower risk patients can be identified more cost-efficiently than simply reflexing all ER⁺, HER2^- BC patients to ODX testing. The Magee equations^TM use standard histopathologic data in a set of multivariable models to estimate the ODX recurrence score. Our group published the first outcome data in 2019 on the Magee equations^TM, using a modification of the Magee equations^TM combined with an algorithmic approach-the Rochester Modified Magee algorithm (RoMMa). There has since been limited published outcome data on the Magee equations^TM. We present additional outcome data, with considerations of the TAILORx risk-stratification recommendations.

METHODS

355 patients with an ODX recurrence score, and at least five years of follow-up or a BC recurrence were included in the study. All patients received either Tamoxifen or an aromatase inhibitor. None of the patients received adjuvant systemic chemotherapy.

RESULTS

There was no significant difference in the risk of recurrence in similar risk categories (very low risk, low risk, and high risk) between the average Modified Magee score and ODX recurrence score with the chi-square test of independence (p > 0.05) or log-rank test (p > 0.05). Using the RoMMa, we estimate that at least 17% of individuals can safely avoid ODX testing.

CONCLUSION

Our study further reinforces that BC patients can be confidently stratified into lower and higher-risk recurrence groups using the Magee equations^TM. The RoMMa can be helpful in the initial clinical risk-assessment and risk-stratification of BC patients, providing increased opportunities for cost savings in the health care system, and for clinical risk-assessment and risk-stratification in less-developed geographies where multigene testing might not be available.

Cost-effectiveness analysis of Oncotype DX from a Brazilian private medicine perspective: a GBECAM multicenter retrospective study

Background

Oncotype DX (ODX) is a validated assay for the prediction of risk of recurrence and benefit of chemotherapy (CT) in both node negative (N0) and 1-3 positive nodes (N1), hormone receptor positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) early breast cancer (eBC). Due to limited access to genomic assays in Brazil, treatment decisions remain largely driven by traditional clinicopathologic risk factors. ODX has been reported to be cost-effective in different health system, but limited data are available considering the reality of middle-income countries such as Brazil. We aim to evaluate the cost-effectiveness of ODX across strata of clinical risk groups using data from a dataset of patients from Brazilian institutions.

Methods

Clinicopathologic and ODX information were analyzed for patients with T1-T3, N0-N1, HR+/HER2- eBC who had an ODX performed between 2005 and 2020. Projections of CT indication by clinicopathologic criteria were based on binary clinical risk categorization based on the Adjuvant! Algorithm. The ODX score was correlated with the indication of CT according to TAILORx and RxPONDER data. Two decision-tree models were developed. In the first model, low and high clinical risk patients were included while in the second, only high clinical risk patients were included. The cost for ODX and CT was based on the Brazilian private medicine perspective.

Results

In all, 645 patients were analyzed; 411 patients (63.7%) had low clinical risk and 234 patients (36.3%) had high clinical risk disease. The ODX indicated low (<11), intermediate (11-25), and high (>25) risk in 119 (18.4%), 415 (64.3%), and 111 (17.2%) patients, respectively. Among 645 patients analyzed in the first model, ODX was effective (5.6% reduction in CT indication) though with an incremental cost of United States Dollar (US$) 2288.87 per patient. Among 234 patients analyzed in the second model (high clinical risk only), ODX led to a 57.7% reduction in CT indication and reduced costs by US$ 4350.66 per patient.

Conclusions

Our study suggests that ODX is cost-saving for patients with high clinical risk HR+/HER2- eBC and cost-attractive for the overall population in the Brazilian private medicine perspective. Its incorporation into routine practice should be strongly considered by healthcare providers.

The impact of age on health utility values for older women with early-stage breast cancer: a systematic review and meta-regression

INTRODUCTION

An increasing number of postmenopausal women are diagnosed with breast cancer at an older age (≥ 70 years). There is a lack of synthesised health utility data to support decision-making for managing breast cancer in this older population. This study aimed to identify the availability of, and the subsequent impact of age on, health state utility values (HSUVs) measured by the EQ-5D for older women with early-stage breast cancer.

METHOD

This systematic review identified EQ-5D (3L or 5L version) HSUVs for postmenopausal women with early-stage breast cancer. Studies were identified from a previous systematic review (inception to 2009) and an electronic database search (Medline and Embase; 2009 to September 2021). Mean HSUVs were summarised by health state. Quality appraisal was performed on studies reporting HSUVs for older ages (≥ 70 years). Multivariable meta-regression assessed the association between HSUVs and age, health state, treatments received, and time of measuring the utility values (greater or less than one year post-treatment).

RESULTS

Fifty EQ-5D HSUVs were identified from 13 studies. Mean HSUVs decreased as health state worsened: from the stable (mean=0.83) to progression (mean=0.79) and advanced (mean=0.68) states. Two studies reported six HSUVs estimated from the sample of women with a mean age ≥ 70. Meta-regression model fit improved by including age as an independent variable and attenuated the estimated utility decrements associated with worse health states. Utility decrements for the progression and advanced states were -0.052 (95%CI: -0.097, -0.007) and -0.143 (95%CI: -0.264, -0.022) respectively. The breast cancer-specific utility decrement associated with a one-year increase in age was -0.001 (95%CI: -0.004, 0.002).

CONCLUSION

Relevant and accurate HSUVs are essential to help support decision-making about the most effective and cost-effective ways to manage early-stage breast cancer in older women. Age has a vital role in determining health utility values in this population. This study provides analysts and decision-makers with HSUVs and utility decrements that reflect the disease process in this older population.

Hospital Rurality and Gene Expression Profiling for Early-Stage Breast Cancer among Iowa Residents (2010-2018)

Objective

Given the challenges rural cancer patients face in accessing cancer care as well as the slower diffusion and adoption of new medical technologies among rural providers, the aim of our study was to examine trends in gene expression profiling (GEP) testing and evaluate the association between hospital rurality and receipt of GEP testing.

Methods

Data from the Iowa Cancer Registry (ICR) were used to identify women with newly diagnosed, histologically confirmed breast cancer from 2010 through 2018 who met eligibility criteria for GEP testing. Patients were allocated to the hospitals where their most definitive surgical treatment was received, and Rural-Urban Commuting Area codes were used to categorize hospitals into urban (N = 43), large rural (N = 16), and small rural (N = 48). Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression to evaluate the association between hospital rurality and GEP test use, adjusting for demographic and clinical characteristics. The association between test result and treatment received was assessed among patients who received Oncotype DX (ODX) testing.

Results

Of 6,726 patients eligible for GEP test use, 46% (N = 3,069) underwent testing with 95% receiving ODX. While overall GEP testing rates increased over time from 42% between 2010 and 2012 to 51% between 2016 and 2018 (P _trend < 0.0001), use continued to be the lowest among patients treated at hospitals in small rural areas. The odds of GEP testing remained significantly lower among patients treated at hospitals located in small rural areas (aOR 0.55; 95% CI 0.43-0.71), after adjusting for demographic and clinical characteristics. ODX recurrence scores were highly correlated with chemotherapy use across all strata of hospital rurality.

Conclusions

GEP testing continues to be underutilized, especially among those treated at small rural hospitals. Targeted interventions aimed at increasing rates of GEP testing to ensure the appropriate use of adjuvant chemotherapy may improve health outcomes and lower treatment-related costs.

Research on the Economics of Cancer-Related Health Care: An Overview of the Review Literature

We reviewed current literature reviews regarding economics of cancer-related health care to identify focus areas and gaps. We searched PubMed for systematic and other reviews with the Medical Subject Headings "neoplasms" and "economics" published between January 1, 2010, and April 1, 2020, identifying 164 reviews. Review characteristics were abstracted and described. The majority (70.7%) of reviews focused on cost-effectiveness or cost-utility analyses. Few reviews addressed other types of cancer health economic studies. More than two-thirds of the reviews examined cancer treatments, followed by screening (15.9%) and survivorship or end-of-life (13.4%). The plurality of reviews (28.7%) cut across cancer site, followed by breast (20.7%), colorectal (11.6%), and gynecologic (8.5%) cancers. Specific topics addressed cancer screening modalities, novel therapies, pain management, or exercise interventions during survivorship. The results indicate that reviews do not regularly cover other phases of care or topics including financial hardship, policy, and measurement and methods.

Nuances in the Surgical Management of Thyroid Cancer

The incidence of thyroid cancer is rapidly rising, primarily due to the increased use of imaging studies and incidentalomas. In the USA, the incidence has quadrupled. The last decades have seen remarkable advances in diagnosis and surgery for thyroid cancer. We will discuss the surgical advances in this manuscript. The American Thyroid Association and many other organizations around the world have been quite instrumental in developing the guidelines for the management of thyroid cancer, which have streamlined the treatment approaches. There have also been advances made in the management of medullary and anaplastic thyroid cancer, which will be a different subject not included in this manuscript. The major surgical advances include the following: impact of molecular markers, risk group stratifications, de-escalation in surgery, nerve monitoring, and endoscopic surgery. We will discuss some of these surgical nuances in this review article.

A Novel Prognostic Four-Gene Signature of Breast Cancer Identified by Integrated Bioinformatics Analysis

Molecular analysis facilitates the prediction of overall survival (OS) of breast cancer and decision-making of the treatment plan. The current study was designed to identify new prognostic genes for breast cancer and construct an effective prognostic signature with integrated bioinformatics analysis. Differentially expressed genes in breast cancer samples from The Cancer Genome Atlas (TCGA) dataset were filtered by univariate Cox regression analysis. The prognostic model was optimized by the Akaike information criterion and further validated using the TCGA dataset (n = 1014) and Gene Expression Omnibus (GEO) dataset (n = 307). The correlation between the risk score and clinical information was assessed by univariate and multivariate Cox regression analyses. Functional pathways in relation to high-risk and low-risk groups were analyzed using gene set enrichment analysis (GSEA). Four prognostic genes (EXOC6, GPC6, PCK2, and NFATC2) were screened and used to construct a prognostic model, which showed robust performance in classifying the high-risk and low-risk groups. The risk score was significantly related to clinical features and OS. We identified 19 functional pathways significantly associated with the risk score. This study constructed a new prognostic model with a high prediction performance for breast cancer. The four-gene prognostic signature could serve as an effective tool to predict prognosis and assist the management of breast cancer patients.

Cost-Effectiveness Analysis from a Societal Perspective of Recurrence Index for Distant Recurrence (RecurIndex) in Women with Hormone Receptor-Positive and HER2-Negative Early-Stage Breast Cancer

Purpose

A clinical-genomic prognostic multigene panel (RI-DR assay, RecurIndex^®), predicting the risk level of distant recurrence (DR) in early-stage breast cancer (EBC) patients with an Asian background, has been validated as a valuable tool for identifying high-risk patients to develop distant recurrence (metastasis). Although the clinical benefit of adjuvant chemotherapy from the assay’s prediction is already proved, its affordability remains uncertain. This study is the first time in which the long-term cost-effectiveness of the RI-DR assay is evaluated.

Patients and Methods

A lifetime Markov decision-analytic model was developed from a societal perspective to estimate the life-years gained (LYGs), quality-adjusted life-years (QALYs), medical costs, and incremental cost-effectiveness ratios (ICERs), comparing EBC women with and without RI-DR genomic testing. A decision tree was used to classify patients in one of the fifteen end nodes (by order, each arm was stratified by a patient being tested or not with the RI-DR assay, being treated or not with adjuvant chemotherapy and had no, minor, major, or fatal toxicity after adjuvant chemotherapy). Health utilities, costs, transition probabilities, and survival data were extracted from the scientific literature. Deterministic sensitivity analysis (DSA) and probabilistic sensitivity analysis (PSA) were performed on variables to assess the robustness of the model. A willingness-to-pay (WTP) threshold of 790,000 NT$ per QALY gained was considered as a cost-effectiveness criterion.

Results

The incremental cost per QALY gained under base-case assumptions of the model was 173,842 NT$. Findings on the variation in model input parameters were robust and confirmed that every key variable was cost-effective for the benefit of RI-DR testing.

Conclusion

The clinical-genomic RI-DR assay is cost-effective in guiding adjuvant chemotherapy decisions compared to current clinical practice guidelines.

Impact of TAILORx on chemotherapy prescribing and 21-gene recurrence score-guided treatment costs in a population-based cohort of patients with breast cancer

BACKGROUND

The trial assigning individualized options for treatment (Rx) (TAILORx) confirmed the predictive value of the 21-gene recurrence score (RS) assay in hormone receptor (HR)-positive, HER2-negative, node-negative breast cancer and established thresholds for chemotherapy benefit in younger and older patients. Real-world chemotherapy use and RS-guided treatment costs in British Columbia post-TAILORx were examined.

METHODS

The authors assembled 3 cohorts of HR-positive, HER2-negative, node-negative patients with breast cancer defined by diagnosis: before RS funding (cohort 1 [C1]: January 2013-December 2013), after introduction of public RS funding (cohort 2 [C2]: July 2015-June 2016), and after TAILORx results (cohort 3 [C3]: July 2018-June 2019). Chemotherapy use was compared between cohorts by age and RS. Budgetary impacts of RS testing on chemotherapy costs were evaluated pre- and post-TAILORx.

RESULTS

Among the 2066 patients included, chemotherapy use declined by 19% after RS funding was introduced and by an additional 23% after TAILORx publication (P = .001). Reduction in chemotherapy use was significant for RS 11-20 tumors (C3 vs C2, P = .004). There was no significant change in chemotherapy use in patients >50 years old (C2:12% vs C3:10%, P = .22). RS testing was associated with higher cost savings post-TAILORx, except in patients 70 to 80 years old, where testing led to excess costs when adjusting for the low rate of RS-concordant chemotherapy prescribed.

CONCLUSIONS

TAILORx has had population-based impacts on chemotherapy prescribing in intermediate RS tumors and patients ≤50 years old. The lower clinical use of RS and increased spending in patients 70-80 years old highlights the importance of careful selection of older candidates for high-cost genomic testing.

LAY SUMMARY

The 21-gene recurrence score (RS) test helps predict whether patients with hormone-positive, HER2-negative, lymph node-negative breast cancer are likely to benefit from chemotherapy. The recent trial assigning individualized options for treatment (Rx) (TAILORx) found that patients with intermediate RS tumors did not benefit from chemotherapy. The authors assessed whether TAILORx results translated to real-world changes in chemotherapy prescribing patterns. In this study, chemotherapy use decreased by 23% after TAILORx, with the greatest reductions seen among intermediate RS tumors and younger patients. In contrast, RS testing had lower clinical value and increased treatment costs in elderly patients, which requires further study to ensure optimal care for this age group.

Using Breast Cancer Gene Expression Signatures in Clinical Practice: Unsolved Issues, Ongoing Trials and Future Perspectives

The development of gene expression signatures since the early 2000's has offered standardized assays to evaluate the prognosis of early breast cancer. Five signatures are currently commercially available and recommended by several international guidelines to individualize adjuvant chemotherapy decisions in hormone receptors-positive/HER2-negative early breast cancer. However, many questions remain unanswered about their predictive ability, reproducibility and external validity in specific populations. They also represent a new hope to tailor (neo)adjuvant systemic treatment, adjuvant radiation therapy, hormone therapy duration and to identify a subset of patients who might benefit from CDK4/6 inhibitor adjuvant treatment. This review will highlight these particular issues, address the remaining questions and discuss the ongoing and future trials.

Uncovering the roles of microRNAs/lncRNAs in characterising breast cancer subtypes and prognosis

Background

Accurate prognosis and identification of cancer subtypes at molecular level are important steps towards effective and personalised treatments of breast cancer. To this end, many computational methods have been developed to use gene (mRNA) expression data for breast cancer subtyping and prognosis. Meanwhile, microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) have been extensively studied in the last 2 decades and their associations with breast cancer subtypes and prognosis have been evidenced. However, it is not clear whether using miRNA and/or lncRNA expression data helps improve the performance of gene expression based subtyping and prognosis methods, and this raises challenges as to how and when to use these data and methods in practice.

Results

In this paper, we conduct a comparative study of 35 methods, including 12 breast cancer subtyping methods and 23 breast cancer prognosis methods, on a collection of 19 independent breast cancer datasets. We aim to uncover the roles of miRNAs and lncRNAs in breast cancer subtyping and prognosis from the systematic comparison. In addition, we created an R package, CancerSubtypesPrognosis, including all the 35 methods to facilitate the reproducibility of the methods and streamline the evaluation.

Conclusions

The experimental results show that integrating miRNA expression data helps improve the performance of the mRNA-based cancer subtyping methods. However, miRNA signatures are not as good as mRNA signatures for breast cancer prognosis. In general, lncRNA expression data does not help improve the mRNA-based methods in both cancer subtyping and cancer prognosis. These results suggest that the prognostic roles of miRNA/lncRNA signatures in the improvement of breast cancer prognosis needs to be further verified.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04215-3.

Personalized Decision Making on Genomic Testing in Early Breast Cancer: Expanding the MINDACT Trial with Decision-Analytic Modeling

BACKGROUND

Genomic tests may improve upon clinical risk estimation with traditional prognostic factors. We aimed to explore how evidence on the prognostic strength of a genomic signature (clinical validity) can contribute to individualized decision making on starting chemotherapy for women with breast cancer (clinical utility).

METHODS

The MINDACT trial was a randomized trial that enrolled 6693 women with early-stage breast cancer. A 70-gene signature (Mammaprint) was used to estimate genomic risk, and clinical risk was estimated by a dichotomized version of the Adjuvant!Online risk calculator. Women with discordant risk results were randomized to the use of chemotherapy. We simulated the full risk distribution of these women and estimated individual benefit, assuming a constant relative effect of chemotherapy.

RESULTS

The trial showed a prognostic effect of the genomic signature (adjusted hazard ratio 2.4). A decision-analytic modeling approach identified far fewer women as candidates for genetic testing (4% rather than 50%) and fewer benefiting from chemotherapy (3% rather than 27%) as compared with the MINDACT trial report. The selection of women benefitting from genetic testing and chemotherapy depended strongly on the required benefit from treatment and the assumed therapeutic effect of chemotherapy.

CONCLUSIONS

A high-quality pragmatic trial was insufficient to directly inform clinical practice on the utility of a genomic test for individual women. The indication for genomic testing may be far more limited than suggested by the MINDACT trial.

Identification of novel cell glycolysis related gene signature predicting survival in patients with breast cancer

One of the most frequently identified tumors and a contributing cause of death in women is breast cancer (BC). Many biomarkers associated with survival and prognosis were identified in previous studies through database mining. Nevertheless, the predictive capabilities of single-gene biomarkers are not accurate enough. Genetic signatures can be an enhanced prediction method. This research analyzed data from The Cancer Genome Atlas (TCGA) for the detection of a new genetic signature to predict BC prognosis. Profiling of mRNA expression was carried out in samples of patients with TCGA BC (n = 1222). Gene set enrichment research has been undertaken to classify gene sets that vary greatly between BC tissues and normal tissues. Cox models for additive hazards regression were used to classify genes that were strongly linked to overall survival. A subsequent Cox regression multivariate analysis was used to construct a predictive risk parameter model. Kaplan–Meier survival predictions and log-rank validation have been used to verify the value of risk prediction parameters. Seven genes (PGK1, CACNA1H, IL13RA1, SDC1, AK3, NUP43, SDC3) correlated with glycolysis were shown to be strongly linked to overall survival. Depending on the 7-gene-signature, 1222 BC patients were classified into subgroups of high/low-risk. Certain variables have not impaired the prognostic potential of the seven-gene signature. A seven-gene signature correlated with cellular glycolysis was developed to predict the survival of BC patients. The results include insight into cellular glycolysis mechanisms and the detection of patients with poor BC prognosis.

Chemotherapy Costs and 21-Gene Recurrence Score Genomic Testing Among Medicare Beneficiaries With Early-Stage Breast Cancer, 2005 to 2011

BACKGROUND

This study examined whether associations between 21-gene recurrence score (RS) genomic testing and lower costs among patients with early-stage, estrogen receptor-positive breast cancer are observable in real-world data from the Medicare population.

METHODS

A retrospective cohort study was conducted using SEER-Medicare data for a nationally representative sample of Medicare beneficiaries diagnosed from 2005 through 2011. The main outcomes were associations between RS testing and overall and chemotherapy-specific costs. The primary analysis was restricted to patients aged 66 to 75 years.

RESULTS

The primary analysis comprised 30,058 patients. Mean costs 1 year after diagnosis were $35,940 [SD, $28,894] overall, $51,127 [33,386] for clinically high-risk disease, $33,225 [$27,711] for intermediate-risk disease, and $26,695 [$19,532] for low-risk disease. Chemotherapy-specific costs followed similar trends. In multivariable analyses, RS testing was associated with significantly lower costs among high-risk patients in terms of both relative costs (cost ratio, 0.88; 99% CI, 0.82-0.94) and absolute costs ($6,606; 99% CI, $39,223-$9,290). Higher costs among low-risk and intermediate-risk patients were mainly caused by higher noncancer costs. In sensitivity analyses that included all patients aged ≥66 years (N=64,996), associations between RS testing and costs among high-risk patients were similar but less pronounced because of lower overall use of chemotherapy.

CONCLUSIONS

RS testing was associated with lower overall and chemotherapy-related costs in patients with high-risk disease, consistent with lower chemotherapy use among these patients. Higher overall costs for patients with intermediate-risk and low-risk disease were driven largely by non-treatment-related costs.

The prognostic and predictive role of 21-gene recurrence scores in hormone receptor-positive early-stage breast cancer

Over the past two decades, gene expression profiling of breast cancer has emerged as an important tool in early-stage breast cancer management. The approach provides important information on underlying biological mechanisms, breast cancer classification, future risk potential of developing recurrent metastatic disease, and provides beneficial clues for adjuvant chemotherapy in hormone receptor (HR) positive breast cancer. Of the commercially available genomic tests for breast cancer, the prognostic and predictive value of 21-gene recurrence score tests have been validated using both retrospective data and prospective clinical trials. In this paper, we reviewed the current evidence on 21-gene expression profiles for HR-positive HER2-negative early-stage breast cancer management. We show that current evidence supports endocrine therapy alone as an appropriate adjuvant systemic therapy for approximately 70% of women with HR-positive, HER2-negative, node-negative breast cancer. Evolving evidence also suggests that 21-gene recurrence scores have predictive values for node-positive breast cancer and that chemotherapy can be avoided in more than half of women with nodes 1 to 3 positive HR-positive breast cancer. Furthermore, retrospective data also supports the predictive role of 21-gene recurrence scores for adjuvant radiation therapy. A prospective trial in this area is ongoing.

A Nomogram for Predicting the Oncotype DX Recurrence Score in Women with T1-3N0-1miM0 Hormone Receptor‒Positive, Human Epidermal Growth Factor 2 (HER2)‒Negative Breast Cancer

PURPOSE

This preliminary study was conducted to evaluate the association between Oncotype DX (ODX) recurrence score and traditional prognostic factors. We also developed a nomogram to predict subgroups with low ODX recurrence scores (less than 25) and to avoid additional chemotherapy treatments for those patients.

MATERIALS AND METHODS

Clinicopathological and immunohistochemical variables were retrospectively retrieved and analyzed from a series of 485 T1-3N0-1miM0 hormone receptor-positive, human epidermal growth factor 2‒negative breast cancer patients with available ODX test results at Asan Medical Center from 2010 to 2016. One hundred twenty-seven patients (26%) had positive axillary lymph node micrometastases, and 408 (84%) had ODX recurrence scores of ≤25. Logistic regression was performed to build a nomogram for predicting a low-risk subgroup of the ODX assay.

RESULTS

Multivariate analysis revealed that estrogen receptor (ER) score, progesterone receptor (PR) score, histologic grade, lymphovascular invasion (LVI), and Ki-67 had a statistically significant association with the low-risk subgroup. With these variables, we developed a nomogram to predict the low-risk subgroup with ODX recurrence scores of ≤25. The area under the receiver operating characteristic curve was 0.90 (95% confidence interval [CI], 0.85 to 0.96). When applied to the validation group the nomogram was accurate with an area under the curve = 0.88 (95% CI, 0.83 to 0.95).

CONCLUSION

The low ODX recurrence score subgroup can be predicted by a nomogram incorporating five traditional prognostic factors: ER, PR, histologic grade, LVI, and Ki-67. Our nomogram, which predicts a low-risk ODX recurrence score, will be a useful tool to help select patients who may or may not need additional ODX testing.

The Oncotype Dx Assay in ER-Positive, HER2-Negative Breast Cancer Patients: A Real Life Experience from a Single Cancer Center

Objective

To determine the influence of the Oncotype Dx assay on the treatment of patients with Estrogen Receptor (ER)-positive, Human Epidermal Growth Factor Receptor 2 (HER2)-negative, axillary lymph node-negative or micrometastatic carcinoma of the breast in a single cancer center. In addition, patients with intermediate Oncotype Dx recurrence scores were analyzed to assess the factors influencing therapeutic decisions for adjuvant chemotherapy.

Materials and Methods

Data from medical records of women diagnosed with carcinoma of the breast and qualified for the Oncotype Dx assay were extracted (OncoDx cohort). Patient demographic and cancer characteristics, genomic report, and course of treatment data, including survival outcomes and treatment decision-making, were analyzed. A matched cohort of patients with similar tumor stage and biology (ER-positive, HER2-negative) from the era before the introduction of the Oncotype Dx assay was analyzed for comparison (pre-OncoDx cohort).

Results

Two hundred and one patients were included in the OncoDx cohort and one hundred and sixty patients were included in the pre-OncoDx cohort. Oncotype Dx recurrence score (RS) was low (<11) in fifty-six patients (28%), intermediate (11-25) in one hundred and twenty-three patients (61.5%) and high (>25) in twenty one patients (10.5%). Demographic and cancer clinicopathologic characteristics between OncoDx and pre-OncoDx cohorts were similar. Overall, 10.9% of the patients in the OncoDx cohort received adjuvant chemotherapy, versus 23.8% of the patients in the pre-OncoDx cohort (Fisher exact p=0.003). Fewer patients were recommended adjuvant chemotherapy in the OncoDx era compared to the pre-OncoDx era (17.9% vs 30.6%, respectively, Fisher exact p=0.006). The decision to recommend chemotherapy within the intermediate-risk cohort was influenced by the patient's RS. The mean RS of patients in the intermediate-risk cohort who did not receive chemotherapy was 21.5 while the score of those that received chemotherapy was 24.6 (p=0.000). The series confirmed excellent PFS and OS for both OncoDx and pre-OncoDx cohorts.

Conclusion

This single cancer center analysis confirms the avoidance of chemotherapy in the great majority of patients with early ER-positive, HER2-negative, lymph node-negative or micrometastatic carcinoma of the breast since the introduction of the Oncotype Dx assay. A higher recurrence risk score within the intermediate group may influence the decision for chemotherapy inclusion in the adjuvant treatment plan. A lower PR percentage by IHC and higher grade may predict higher Oncotype Dx scores.

Risk stratification of ER-positive breast cancer patients: A multi-institutional validation and outcome study of the Rochester Modified Magee algorithm (RoMMa) and prediction of an Oncotype DX® recurrence score <26

The skyrocketing cost of health-care demands that we question when to use multigene assay testing in the planning of treatment for breast cancer patients. A previously published algorithmic model gave recommendations for which cases to send out for Oncotype DX^® (ODX) testing. This study is a multi-institutional validation of that algorithmic model in 620 additional estrogen receptor positive breast cancer cases, with outcome data on 310 cases, named in this study as the Rochester Modified Magee algorithm (RoMMa). RoMMa correctly predicted 85% (140/164) and 100% (17/17) of cases to have a low- or high-risk ODX recurrence score, respectively, consistent with the original publication. Applying our own risk stratification criteria, in patients who received appropriate hormonal therapy, only one of the 45 (2.0%) patients classified as low risk by our original algorithm have been associated with a breast cancer recurrence over 5-10 years of follow-up. Eight of 116 (7.0%) patients classified as low risk by ODX have been associated with a breast cancer recurrence with up to 11 years of follow-up. In addition, 524 of 537 (98%) cases from our total population (n = 903) with an average modified Magee score ≤18 had an ODX recurrence score <26. Patients with an average modified Magee score ≤18 or >30 may not need to be sent out for ODX testing. By avoiding these cases sending out for ODX testing, the potential cost savings to the health-care system in 2018 are estimated to have been over $100,000,000.

Healthcare professionals' attitudes toward cancer precision medicine: A systematic review

Use of precision medicine in oncology is burgeoning and can provide patients with new treatment options. However, it is not clear how precision medicine is impacting healthcare professionals (HCPs), particularly with regards to their concerns about this new approach. We therefore synthesized the existing literature on HCPs' attitudes toward cancer precision medicine. We searched four databases for relevant articles. Two reviewers screened eligible articles and extracted data. We assessed the quality of each article using the QualSyst tool. We found 22 articles, representing 4,321 HCPs (63.7% cancer specialists). HCPs held largely positive attitudes toward cancer precision medicine, including their capacity to facilitate treatment decisions and provide prognostic information. However, they also had concerns regarding costs, insurance coverage, limited HCP knowledge about precision medicine, potential misuse, difficulties accessing the tests, and delays in receiving test results. Most HCPs felt that test-related decisions should be shared between families and HCPs. HCPs intended to disclose actionable results but were less inclined to disclose negative/secondary findings. HCPs had a strong preference for genetic counselor involvement when disclosing germline findings. Most HCPs intended to use somatic and germline tests in their future practice but the extent to which pharmacogenomic tests will be used is uncertain. HCPs indicated that additional evidence supporting test utility and increased availability of treatment guidelines could facilitate the use of testing. HCPs held generally positive attitudes toward cancer precision medicine, however there were some key concerns. Addressing concerns early, devising educational support for HCPs and developing guidelines may facilitate the successful implementation of precision medicine trials in the future.

Cancer registries - guardians of breast cancer biomarker information: A systematic review

BACKGROUND

Breast cancer is the most common cancer and the leading cause of cancer-related death in females, with a large societal and economic impact. Decisions regarding its treatment are largely affected by the categorization into different subtypes with hormone receptor status and HER2 status being the most important predictive factors. Other biological markers play an important role for prognostic and predictive reasons. The data collection and harmonization of cancer cases are performed by cancer registries whose collection of parameters largely differs, partially including results from biomarker testing.

METHODS

This systematic literature review consisting of a total of 729 reports determined whether information about biomarker testing in breast cancer cases is collected and published by cancer registries worldwide.

RESULTS

The number of publications using breast cancer biomarker data from registries steeply rose with the beginning of the 21st century and some hospital-based and population-based cancer registries reacted with immediate collection of biomarker data following the recommendation of clinical guidelines. For female breast cancer, biomarkers have achieved an essential clinical value and this review points to a steady increase in the collection of biomarker data by cancer registries during the last decade.

CONCLUSIONS

In the future, recommendations for biomarker data collection and coding by cancer registries may be required to ensure harmonization and comparability of the data.

Risk stratification in early breast cancer in premenopausal and postmenopausal women: integrating genomic assays with clinicopathological features

PURPOSE OF REVIEW

There is growing consensus that genomic assays provide useful complementary information to clinicopathological features in oestrogen receptor-positive breast cancers. Here, ongoing research with multigene tests used for postmenopausal breast cancer and new emerging prognostic and predictive markers for pre and postmenopausal women are summarised.

RECENT FINDINGS

Results of the TAILORx trial have shown that women with an intermediate risk score do not benefit from adjuvant chemotherapy. Prosgina has been further investigated in a contemporary patient population in postmenopausal women and its use has been extended for premenopausal women. The EndoPredict was extensively used in decision-impact studies showing that its use can potentially reduce the need for adjuvant chemotherapy. Several new genomic assays have been developed, with some of them showing promising use for women with early oestrogen receptor-positive breast cancer.

SUMMARY

New areas of research for prediction of recurrence and risk stratification involve the development of immune gene signatures that carry modest but significant prognostic value. The recent expansion of high-throughput technology platforms including circulating tumour DNA/RNA and microRNA offer new opportunities to improve prediction models, particularly in women with oestrogen receptor-negative disease and premenopausal women. Genomic assays have clearly improved prognostication of early oestrogen receptor-positive breast cancer but it is clear that standard clinicopathological parameters are still very important when identifying patient for adjuvant chemotherapy.

Biomarkers in breast cancer: A consensus statement by the Spanish Society of Medical Oncology and the Spanish Society of Pathology

This consensus statement revises and updates the recommendations for biomarkers use in the diagnosis and treatment of breast cancer, and is a joint initiative of the Spanish Society of Medical Oncology and the Spanish Society of Pathology. This expert group recommends determining in all cases of breast cancer the histologic grade and the alpha-estrogen receptor (ER), progesterone receptor, Ki-67 and HER2 status, in order to assist prognosis and establish therapeutic options, including hormone therapy, chemotherapy and anti-HER2 therapy. One of the four available genetic prognostic platforms (MammaPrint^®, Oncotype DX^®, Prosigna^® or EndoPredict^®) may be used in node-negative ER-positive patients to establish a prognostic category and decide with the patient whether adjuvant treatment may be limited to hormonal therapy. Newer technologies including next-generation sequencing, liquid biopsy, tumour-infiltrating lymphocytes or PD-1 determination are at this point investigational.

Cost-Effectiveness Analyses of the 21-Gene Assay in Breast Cancer: Systematic Review and Critical Appraisal

Purpose Prior studies examining cost effectiveness of the 21-gene assay (Oncotype DX [ODX]) for women with hormone receptor-positive, early-stage breast cancer have yielded disparate results. We aimed to explore why these analyses may have yielded different conclusions. Methods We conducted a systematic literature review of cost-effectiveness analyses (CEAs) of ODX. We examined the extent to which the structure of CEA modeling, the assumptions of the models, and the selection of input parameters influenced cost-effectiveness estimates. We also explored the prevalence of industry funding and whether industry funding was associated with study designs favoring ODX. Results We identified 27 analyses, 15 of which received industry funding. In 18 studies, the clinical characteristics (eg, tumor size and grade) commonly used to make chemotherapy decisions were not incorporated into simulation modeling; thus, these studies would favor ODX being cost effective and might not reflect clinical practice. Most studies ignored the heterogeneous effect of ODX on chemotherapy use; only five studies assumed that ODX would increase chemotherapy use for clinically low-risk patients but decrease chemotherapy use for clinically high-risk patients. No study used population-based joint distributions of ODX recurrence score and tumor characteristics, and 12 studies inappropriately assumed that chemotherapy would increase distant recurrence for the low recurrence score group; both approaches overestimated the benefits of ODX. Industry-funded studies tended to favor ODX; all five studies that reported ODX as being cost saving were industry funded. In contrast, two studies that reported an incremental cost-effectiveness ratio > $50,000 per quality-adjusted life-year were not funded by industry. Conclusion Although a majority of published analyses indicated that ODX is cost effective, they incorporated study designs that can increase the risk of bias.

Clinical and economic impact of the 21-gene recurrence score assay in adjuvant therapy decision making in patients with early-stage breast cancer: pooled analysis in 4 Basque Country university hospitals

Purpose

The 21-gene recurrence score (RS) is a genomic test developed as a prognostic and predictive tool to improve the treatment decision making in cases of estrogen receptor-positive and human epidermal growth factor receptor 2-negative early-stage breast cancer. This study examined the clinical and economic impact of its use in 4 Basque Country university hospitals.

Methods

Taking into consideration the RS result, we recorded the recommended initial systemic adjuvant therapy (endocrine therapy with or without chemotherapy) according to standard clinicopathologic factors and the final decision about chemotherapy. Then, if the RS was high, chemotherapy was recommended; it was not recommended if the RS was low; for those with an intermediate RS, clinicopathologic factors were considered, and the initial recommendation based on those factors was maintained. In addition, the probability of switching treatment was calculated. Then, we developed an economic evaluation by measuring the treatment’s incremental short-term budget impact from both the societal perspective and that of the Basque Health System. Patients’ characteristics and chemotherapy use were analyzed using logistic regressions and receiver operating characteristic curves.

Results

Without an RS, chemotherapy would have been prescribed to 56% of 401 patients, but, with RS use, that percentage decreased to 25. The overall rate of decision change was 35.4%. Test inclusion led to a reduction in chemotherapy costs of €922 per patient in the total population. Although this reduction did not entirely offset the cost of the test, the productivity loss per patient was reduced by €1,977.

Conclusion

The 21-gene RS test significantly changed the indication for chemotherapy. As chemotherapy treatments with no benefit were avoided, patients’ quality of life was improved. The short-term economic impact was negative for the Basque Health Service, but savings resulted when sick-leave costs were included.

[Consensus statement on biomarkers in breast cancer by the Spanish Society of Pathology and the Spanish Society of Medical Oncology]

This consensus statement is a joint initiative of the Spanish Society of Pathology (SEAP) and the Spanish Society of Medical Oncology (SEOM). It revises and updates the recommendations for the use of biomarkers in the diagnosis and treatment of breast cancer. The group of experts recommends that, in all cases of breast cancer, the histologic grade and the alpha-estrogen receptor (ER), progesterone receptor, Ki-67 and HER2 status should be determined, in order to assist prognosis and establish therapeutic options, including hormone therapy, chemotherapy and anti-HER2 therapy. One of the four available genetic prognostic platforms (MammaPrint^®, Oncotype DX^®, Prosigna^® or EndoPredict^®) may be used in node-negative ER-positive patients to establish a prognostic category and decide, together with the patient, whether adjuvant treatment be limited to hormonal therapy. Newer technologies, including next generation sequencing, liquid biopsy, tumour infiltrating lymphocytes or PD-1 determination, are still investigational.

Do online prognostication tools represent a valid alternative to genomic profiling in the context of adjuvant treatment of early breast cancer? A systematic review of the literature

INTRODUCTION

Decision-making regarding adjuvant chemotherapy has been based on clinical and pathological features. However, such decisions are seldom consistent. Web-based predictive models have been developed using data from cancer registries to help determine the need for adjuvant therapy. More recently, with the recognition of the heterogenous nature of breast cancer, genomic assays have been developed to aid in the therapeutic decision-making.

METHODS

We have carried out a comprehensive literature review regarding online prognostication tools and genomic assays to assess whether online tools could be used as valid alternatives to genomic profiling in decision-making regarding adjuvant therapy in early breast cancer.

RESULTS AND CONCLUSIONS

Breast cancer has been recently recognized as a heterogenous disease based on variations in molecular characteristics. Online tools are valuable in guiding adjuvant treatment, especially in resource constrained countries. However, in the era of personalized therapy, molecular profiling appears to be superior in predicting clinical outcome and guiding therapy.

Clinical utility of gene-expression signatures in early stage breast cancer

Breast cancer is a heterogeneous disease, with different subtypes having a distinct biological, molecular, and clinical course. Assessments of standard clinical and pathological features have traditionally been used to determine the use of adjuvant systemic therapy in patients with early stage breast cancer; however, the ability to identify those who will benefit from adjuvant chemotherapy remains a challenge, leading to the overtreatment of some patients. Advances in molecular medicine have substantially improved the accuracy of gene-expression profiling of breast tumours, resulting in improvements in the ability to predict a patient's risk of breast cancer recurrence and likely response to endocrine therapy and/or chemotherapy. These genomic assays, several of which are commercially available, have aided physicians in tailoring treatment decisions for patients at the individual level. Herein, we describe the available data on the clinical validity of the most widely available assays in patients with early stage breast cancer, with a focus on the development, validation, and clinical application of these assays, in addition to the anticipated outcomes of ongoing prospective trials. We also review data from comparative studies of these assays and from cost-effectiveness analyses relating to their clinical use.

The MAGIC survey in hormone receptor positive (HR+), HER2-negative (HER2-) breast cancer: When might multigene assays be of value?

BACKGROUND

A modest proportion of patients with early stage hormone receptor-positive (HR+), HER2-negative (HER2-) breast cancer benefit from adjuvant chemotherapy. Traditionally, treatment recommendations are based on clinical/pathologic criteria that are not predictive of chemotherapy benefit. Multigene assays provide prognostic and predictive information that can help to make more informed treatment decisions. The MAGIC survey evaluated international differences in treatment recommendations, how traditional parameters are used for making treatment choices, and for which patients treating physicians feel most uncertain about their decisions.

METHODS

The MAGIC survey captured respondents' demographics, practice patterns, relevance of traditional parameters for treatment decisions, and use of or interest in using multigene assays. Using this information, a predictive model was created to simulate treatment recommendations for 672 patient profiles.

RESULTS

The survey was completed by 911 respondents (879 clinicians, 32 pathologists) from 52 countries. Chemo-endocrine therapy was recommended more often than endocrine therapy alone, but there was substantial heterogeneity in treatment recommendations in 52% of the patient profiles; approximately every fourth physician provided a different treatment recommendation. The majority of physicians indicated they wanted to use multigene assays clinically. Lack of reimbursement/availability were the main reasons for non-usage.

CONCLUSIONS

The survey reveals substantial heterogeneity in treatment recommendations. Physicians have uncertainty in treatment recommendations in a high proportion of patients with intermediate risk features using traditional parameters. In HR+, HER2- patients with early disease the findings highlight the need for additional markers that are both prognostic and predictive of chemotherapy benefit that may support more-informed treatment decisions.

Pathologic diagnosis of breast cancer patients: evolution of the traditional clinical-pathologic paradigm toward "precision" cancer therapy

We present an updated account of breast cancer treatment and of progress toward "precision" cancer therapy; we focus on new developments in diagnostic molecular pathology and breast cancer that have emerged during the past 2 years. Increasing awareness of new prognostic and predictive methodologies, and introduction of next generation sequencing has increased understanding of both tumor biology and clinical behavior, which offers the possibility of more appropriate therapeutic choices. It remains unclear which of these testing methodologies provides the most informative and cost-effective actionable results for predictive and prognostic pathology. It is likely, however, that an integrated "step-wise" approach that uses the traditional clinical-pathologic paradigms coordinated with molecular characterization of breast tumor tissue, will offer the most comprehensive and cost-effective options for individualized, "precision" therapy for patients with breast cancer.

[Validation and clinical application of MammaPrint® in patients with breast cancer]

BACKGROUND

In recent years, advances in molecular biology have resulted in innovations in breast cancer diagnostics and therapeutics. The development of genomics has revolutionized our understanding of this disease. MammaPrint^® was developed as a diagnostic tool to predict risk of breast cancer recurrence using the expression of 70 genes altering the clinicopathologic paradigm of selection of patients for adjuvant cytotoxic chemotherapy.

MATERIALS AND METHODS

A study of stage i-ii breast cancer patients on whom the MammaPrint^® genomic assay was performed.

RESULTS

The use of the MammaPrint^® assay was a decisive factor for the recommendation of adjuvant treatment with chemotherapy and/or hormone therapy in patients with high risk for relapse. In our group, the patients with low-risk have not presented local or systemic recurrences DISCUSSION: The determination of the genetic characteristics and its alterations in breast cancer, is fundamentally important for a better identification of risk, as well as a better selection of cancer therapy.

CONCLUSION

MammaPrint^® is an effective study to determine risk of recurrence of in early stage breast cancer.

Cost-utility analyses of drug therapies in breast cancer: a systematic review

The economic evaluation (EE) of health care products has become a necessity. Their quality must be high in order to trust the results and make informed decisions. While cost-utility analyses (CUAs) should be preferred to cost-effectiveness analyses in the oncology area, the quality of breast cancer (BC)-related CUA has been given little attention so far. Thus, firstly, a systematic review of published CUA related to drug therapies for BC, gene expression profiling, and HER2 status testing was performed. Secondly, the quality of selected CUA was assessed and the factors associated with a high-quality CUA identified. The systematic literature search was conducted in PubMed, MEDLINE/EMBASE, and Cochrane to identify published CUA between 2000 and 2014. After screening and data extraction, the quality of each selected CUA was assessed by two independent reviewers, using the checklist proposed by Drummond et al. The analysis of factors associated with a high-quality CUA (defined as a Drummond score ≥7) was performed using a two-step approach. Our systematic review was based on 140 CUAs and showed a wide variety of methodological approaches, including differences in the perspective adopted, the time horizon, measurement of cost and effectiveness, and more specially health-state utility values (HSUVs). The median Drummond score was 7 [range 3-10]. Only one in two of the CUA (n = 74) had a Drummond score ≥7, synonymous of "high quality." The statistically significant predictors of a high-quality CUA were article with "gene expression profiling" topic (p = 0.001), consulting or pharmaceutical company as main location of first author (p = 0.004), and articles with both incremental cost-utility ratio and incremental cost-effectiveness ratio as outcomes of EE (p = 0.02). Our systematic review identified only 140 CUAs published over the past 15 years with one in two of high quality. It showed a wide variety of methodological approaches, especially focused on HSUVs. A critical appraisal of utility values is necessary to better understand one of the main difficulties encountered by authors and propose areas for improvement to increase the quality of CUA. Since the last 5 years, there is a tendency toward an improvement in the quality of these studies, probably coupled with economic context, a better and widely spreading of recommendations and thus appropriation by medical practitioners. That being said, there is an urgent need for mandatory use of European and international recommendations to ensure quality of such approaches and to allow easy comparison.

Clinical Outcomes of Patients with Rare and Heavily Pretreated Solid Tumors Treated according to the Results of Tumor Molecular Profiling

Patients with heavily pretreated advanced cancer or with rare tumors are difficult to treat. Molecular profiling (MP) of tumors to identify biomarkers that predict potential outcomes with individual therapies is an emerging strategy to guide treatment decisions. Patients with rare tumors for which standard-of-care therapy was unavailable or more common tumors for which standard-of-care options had been exhausted underwent MP at a single Australian center. Data regarding treating physicians' choice of therapy, MP results and recommendations, and patient outcomes were collected. Seven patients had received prior standard first-line therapy (PST), 16 had rare tumors, and 31 had been heavily pretreated (HPT; ≥2 prior lines). Most treatments suggested by MP (541/594; 91.1%) were common chemotherapy drugs available in generic formulations. MP-guided therapy recommendations differed from physician's recommendations in 48 patients (88.9%). MP-guided therapy produced clinical benefit (improved QOL and/or performance status, symptoms, bodyweight, or RECIST) in 19/31 (61.3%), 11/16 (68.8%), and 3/7 (42.9%) patients with HPTs, rare tumors, and PSTs, respectively, and had a PFS ratio ≥1.3 in 22/37 evaluable patients (59.5%; 95% confidence interval 44–76%). The null hypothesis that ≤15% of these patients would have a PFS ratio ≥1.3 was rejected (one-sided p < 0.0001). In conclusion, using MP to guide therapy selection is feasible in clinical practice and may improve patient outcomes.

Investigation of potential molecular biomarkers and small molecule drugs for hepatocellular carcinoma transformed from cirrhosis

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in China and the third leading cause of cancer-associated morality. The aim of the present study was to investigate and analyze differentially-expressed genes (DEGs) between cirrhosis and HCC, in order to screen the key genes involved in the transformation from cirrhosis to HCC and provide novel targets for the diagnosis and treatment of HCC in patients with cirrhosis. The gene expression profile, GSE17548, was obtained from Gene Expression Omnibus database and the DEGs were identified by LIMMA package in R language. Kyoto Encyclopedia of Genes and Genomes and gene ontology biology process analysis were performed for the DEGs. Differential co-expression network (DEN) analysis was conducted and the network was visualized using Cytoscape. Small molecule drugs were also screened from the Comparative Toxicogenomics Database for higher degree DEGs. A total of 95 DEGs were obtained, including 46 upregulated and 49 downregulated genes. The upregulated DEGs were primarily involved in biological processes and pathways associated with the cell cycle, while the downregulated DEGs were primarily involved in immune-associated biological processes. A total of 22 key DEGs were identified by DEN analysis, which distinguished HCC from cirrhosis samples. Furthermore, estradiol, benzo(a)pyrene, acetaminophen, copper sulfate and bisphenol A were identified as the five most associated chemicals to these 22 DEGs. In conclusion, the hub genes and chemicals identified by the present study may provide a theoretical basis for additional research on diagnosis and treatment of HCC transformed from cirrhosis.

Enabling Equal Access to Molecular Diagnostics: What Are the Implications for Policy and Health Technology Assessment?

Molecular diagnostics can offer important benefits to patients and are a key enabler of the integration of personalised medicine into health care systems. However, despite their promise, few molecular diagnostics are embedded into clinical practice (especially in Europe) and access to these technologies remains unequal across countries and sometimes even within individual countries. If research translation and the regulatory environments have proven to be more challenging than expected, reimbursement and value assessment remain the main barriers to providing patients with equal access to molecular diagnostics. Unclear or non-existent reimbursement pathways, together with the lack of clear evidence requirements, have led to significant delays in the assessment of molecular diagnostics technologies in certain countries. Additionally, the lack of dedicated diagnostics budgets and the siloed nature of resource allocation within certain health care systems have significantly delayed diagnostics commissioning. This article will consider the perspectives of different stakeholders (patients, health care payers, health care professionals, and manufacturers) on the provision of a research-enabled, patient-focused molecular diagnostics platform that supports optimal patient care. Through the discussion of specific case studies, and building on the experience from countries that have successfully integrated molecular diagnostics into clinical practice, this article will discuss the necessary evolutions in policy and health technology assessment to ensure that patients can have equal access to appropriate molecular diagnostics.