Cost effectiveness of gene expression profiling for early stage breast cancer

Real-world use of multigene signatures in early breast cancer: differences to clinical trials

PURPOSE

In Italy, Lombardy was the first region to reimburse multigene assays (MGAs) for patients otherwise candidates for chemotherapy. This is a real-world experience of MGAs usage in six referral cancer centers in Lombardy.

METHODS

Among MGAs, Oncotype DX (RS) was used in 97% of cases. Consecutive patients tested with Oncotype DX from July 2020 to July 2022 were selected. The distribution of clinicopathologic features by RS groups (low RS: 0-25, high RS: 26-100) was assessed using chi-square and compared with those of the TAILORx and RxPONDER trials.

RESULTS

Out of 1,098 patients identified, 73% had low RS. Grade and Ki67 were associated with RS (p < 0.001). In patients with both G3 and Ki67 > 30%, 39% had low RS, while in patients with both G1 and Ki67 < 20%, 7% had high RS. The proportion of low RS in node-positive patients was similar to that in RxPONDER (82% vs 83%), while node-negative patients with low RS were significantly less than in TAILORx (66% vs 86%, p < 0.001). The distribution of Grade was different from registration trials, with more G3 and fewer G1 (38% and 3%) than in TAILORx (18% and 27%) and RxPONDER (10% and 24%) (p < 0.001). Patients ≤ 50 years were overrepresented in this series (41%) than in TAILORx and RxPONDER (31% and 24%, respectively) (p < 0.001) and, among them, 42% were node positive.

CONCLUSIONS

In this real-world series, Oncotype DX was the test almost exclusively used. Despite reimbursement being linked to pre-test chemotherapy recommendation, almost 3/4 patients resulted in the low-RS group. The significant proportion of node-positive patients ≤ 50 years tested indicates that oncologists considered Oncotype DX informative also in this population.

U.S. payer budget impact of using an AI-augmented cancer risk discrimination digital histopathology platform to identify high-risk of recurrence in women with early-stage invasive breast cancer

AIMS

Use of gene expression signatures to predict adjuvant chemotherapy benefit in women with early-stage breast cancer is increasing. However, high cost, limited access, and eligibility for these tests results in the adoption of less precise assessment approaches. This study evaluates the cost impact of PreciseDx Breast (PDxBr), an AI-augmented histopathology platform that assesses the 6-year risk of recurrence in early-stage invasive breast cancer patients to help improve informed use of adjuvant chemotherapy.

MATERIALS AND METHODS

A decision-tree Markov model was developed to compare the costs of treatment guided by standard of care (SOC) risk assessment (i.e. clinical diagnostic workup with or without Oncotype DX) versus PDxBr with SOC in a hypothetical cohort of U.S. women with early-stage invasive breast cancer. A commercial payer perspective compares costs of testing, adjuvant therapy, recurrence, adverse events, surveillance, and end-of-life care.

RESULTS

PDxBr use in prognostic evaluation resulted in savings of $4 million (M) in year one compared to current SOC in 1 M females members. Over 6-years, savings increased to $12.5 M. The per-treated patient costs in year one amounted to $19.5 thousand (K) for SOC and $16.9K for PDxBr.

LIMITATIONS

For simplicity, recurrence was not specified. We performed scenario analyses to account for variations in rates for local, regional, and distant recurrence. Second, a recurrent patient incurs the total cost of treated recurrence in the first year and goes back to remission or death. Third, CDK4/6i treatment is only incorporated in the recurrence costs but not in the first line of treatment for early-stage breast cancer due to limited data.

CONCLUSIONS

Sensitivity analyses demonstrated robust overall savings to changes in all variables in the model. The use of PDxBr to assess breast cancer recurrence risk has the potential to fill gaps in care and reduce costs when gene expression signatures are not available.

Cost-effectiveness of drug treatment for young and middle-aged stage 1 hypertensive patients with high risk

Background

Drug treatment was recommended for stage 1 hypertensive patients (blood pressure of 130-139 / 80-89 millimetres of mercury (mmHg)) with high cardiovascular disease (CVD) risk in the 2017 Hypertension Clinical Practice Guidelines, 2018 Chinese guidelines and 2021 World Health Organization guidelines, but not in other guidelines. However, evidence on the cost-effectiveness of drug treatment among young and middle-aged patients remains scarce. This study aimed to compare the cost-effectiveness of drug treatment vs. non-drug treatment for stage 1 hypertensive patients aged <60 years with high CVD risk.

Methods

A microsimulation model projected quality-adjusted life years (QALYs), health care costs, and incremental cost-effectiveness ratios for drug treatment from a societal perspective. Transition probabilities were estimated from the Kailuan study with a sample size of 34 093 patients aged <60 years with high CVD risk. Costs and health utilities were obtained from the Kailuan study, national statistics reports and published literature.

Results

Over a 15-year time horizon, the model predicted that drug treatment generated QALY of 9.36 and was associated with expected costs of 3735 US dollars ($) compared with 9.07 and $3923 produced by non-drug treatment among stage 1 hypertensive patients, resulting in a cost-saving for drug treatment. At a willingness-to-pay threshold of $10439/QALY (one gross domestic product (GDP) per capita in 2020), drug treatment had a 99.99% probability of being cost-effective for 10 000 samples of probabilistic sensitivity analysis. Sensitivity analyses by different values of transition probability, cost, utility and discount rate did not appreciably change the results. Shortening the time horizon to the average follow-up period of eight years resulted in ICER of $189/QALY for drug treatment (<1 × GDP/QALY).

Conclusions

Our results suggested that drug treatment was a dominant strategy for stage 1 hypertensive patients aged <60 years with high CVD risk in China, which may provide evidence for policymakers and clinicians when weighing the pros and cons of drug treatment for young and middle-aged stage 1 hypertensive patients.

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 current staging and classification systems of breast cancer and their pitfalls: Is it possible to integrate the complexity of this neoplasm into a unified staging system?

Breast cancer is one of the leading causes of cancer death in women worldwide due to its variable aggressiveness and high propensity to develop distant metastases. The staging can be performed clinically or pathologically, generating the stage stratification by the TNM (T - tumor size; N- lymph node metastasis; M - distant organ metastasis) system. However, cancers with virtually identical TNM characteristics can present highly contrasting behaviors due to the divergence of molecular profiles. This review focuses on the histopathological nuances and molecular understanding of breast cancer through the profiling of gene and protein expression, culminating in improvements promoted by the integration of this information into the traditional staging system. As a culminating point, it will highlight predictive statistical tools for genomic risks and decision algorithms as a possible solution to integrate the various systems because they have the potential to reduce the indications for such tests, serving as a funnel in association with staging and previous classification.

Practical Consensus Recommendations for Optimizing Risk versus Benefit of Chemotherapy in Patients with HR Positive Her2 Negative Early Breast Cancer in India

Breast cancer is a public health challenge globally as well as in India. Improving outcome and cure requires appropriate biomarker testing to assign risk and plan treatment. Because it is documented that significant ethnic and geographical variations in biological and genetic features exist worldwide, such biomarkers need to be validated and approved by authorities in the region where these are intended to be used. The use of western guidelines, appropriate for the Caucasian population, can lead to inappropriate overtreatment or undertreatment in Asia and India. A virtual meeting of domain experts discussed the published literature, real-world practical experience, and results of opinion poll involving 185 oncologists treating breast cancer across 58 cities of India. They arrived at a practical consensus recommendation statement to guide community oncologists in the management of hormone positive (HR-positive) Her2-negative early breast cancer (EBC). India has a majority (about 50%) of breast cancer patients who are diagnosed in the premenopausal stage (less than 50 years of age). The only currently available predictive test for HR-positive Her2-negative EBC that has been validated in Indian patients is CanAssist Breast. If this test gives a score indicative of low risk (< 15.5), adjuvant chemotherapy will not increase the chance of metastasis-free survival and should not be given. This is applicable even during the ongoing COVID-19 pandemic.

Practical consensus recommendations on management of HR + ve early breast cancer with specific reference to genomic profiling

Breast cancer is a heterogeneous disease and patients are managed clinically based on ER, PR, HER2 expression, and key risk factors. The use of gene expression assays for early stage disease is already common practice. These tests have found a place in risk stratifying the heterogeneous group of stage I–II breast cancers for recurrence, for predicting chemotherapy response, and for predicting breast cancer-related mortality. Most guidelines for hormone receptor (HR)–positive early breast cancer recommend addition of adjuvant chemotherapy for most women, leading to overtreatment, which causes considerable morbidity and cost. Expert oncologist discussed about strategies of gene expression assays and aid in chemotherapy recommendations for treatment of HR + ve EBC and the expert group used data from published literature, practical experience and opinion of a large group of academic oncologists to arrive at this practical consensus recommendations for the benefit of community oncologists.

Tumour profiling tests to guide adjuvant chemotherapy decisions in early breast cancer: a systematic review and economic analysis

BACKGROUND

Breast cancer and its treatment can have an impact on health-related quality of life and survival. Tumour profiling tests aim to identify whether or not women need chemotherapy owing to their risk of relapse.

OBJECTIVES

To conduct a systematic review of the effectiveness and cost-effectiveness of the tumour profiling tests oncotype DX^® (Genomic Health, Inc., Redwood City, CA, USA), MammaPrint^® (Agendia, Inc., Amsterdam, the Netherlands), Prosigna^® (NanoString Technologies, Inc., Seattle, WA, USA), EndoPredict^® (Myriad Genetics Ltd, London, UK) and immunohistochemistry 4 (IHC4). To develop a health economic model to assess the cost-effectiveness of these tests compared with clinical tools to guide the use of adjuvant chemotherapy in early-stage breast cancer from the perspective of the NHS and Personal Social Services.

DESIGN

A systematic review and health economic analysis were conducted.

REVIEW METHODS

The systematic review was partially an update of a 2013 review. Nine databases were searched in February 2017. The review included studies assessing clinical effectiveness in people with oestrogen receptor-positive, human epidermal growth factor receptor 2-negative, stage I or II cancer with zero to three positive lymph nodes. The economic analysis included a review of existing analyses and the development of a de novo model.

RESULTS

A total of 153 studies were identified. Only one completed randomised controlled trial (RCT) using a tumour profiling test in clinical practice was identified: Microarray In Node-negative Disease may Avoid ChemoTherapy (MINDACT) for MammaPrint. Other studies suggest that all the tests can provide information on the risk of relapse; however, results were more varied in lymph node-positive (LN+) patients than in lymph node-negative (LN0) patients. There is limited and varying evidence that oncotype DX and MammaPrint can predict benefit from chemotherapy. The net change in the percentage of patients with a chemotherapy recommendation or decision pre/post test ranged from an increase of 1% to a decrease of 23% among UK studies and a decrease of 0% to 64% across European studies. The health economic analysis suggests that the incremental cost-effectiveness ratios for the tests versus current practice are broadly favourable for the following scenarios: (1) oncotype DX, for the LN0 subgroup with a Nottingham Prognostic Index (NPI) of > 3.4 and the one to three positive lymph nodes (LN1-3) subgroup (if a predictive benefit is assumed); (2) IHC4 plus clinical factors (IHC4+C), for all patient subgroups; (3) Prosigna, for the LN0 subgroup with a NPI of > 3.4 and the LN1-3 subgroup; (4) EndoPredict Clinical, for the LN1-3 subgroup only; and (5) MammaPrint, for no subgroups.

LIMITATIONS

There was only one completed RCT using a tumour profiling test in clinical practice. Except for oncotype DX in the LN0 group with a NPI score of > 3.4 (clinical intermediate risk), evidence surrounding pre- and post-test chemotherapy probabilities is subject to considerable uncertainty. There is uncertainty regarding whether or not oncotype DX and MammaPrint are predictive of chemotherapy benefit. The MammaPrint analysis uses a different data source to the other four tests. The Translational substudy of the Arimidex, Tamoxifen, Alone or in Combination (TransATAC) study (used in the economic modelling) has a number of limitations.

CONCLUSIONS

The review suggests that all the tests can provide prognostic information on the risk of relapse; results were more varied in LN+ patients than in LN0 patients. There is limited and varying evidence that oncotype DX and MammaPrint are predictive of chemotherapy benefit. Health economic analyses indicate that some tests may have a favourable cost-effectiveness profile for certain patient subgroups; all estimates are subject to uncertainty. More evidence is needed on the prediction of chemotherapy benefit, long-term impacts and changes in UK pre-/post-chemotherapy decisions.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42017059561.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Overview of Breast Cancer and Implications of Overtreatment of Early-Stage Breast Cancer: An Indian Perspective

The prevalence and mortality of breast cancer is increasing in Asian countries, including India. With advances in medical technology leading to better detection and characterization of the disease, it has been possible to classify breast cancer into various subtypes using markers, which helps predict the risk of distant recurrence, response to therapy, and prognosis using a combination of molecular and clinical parameters. Breast cancer and its therapy, mainly surgery, systemic therapy (anticancer chemotherapy, hormonal therapy, targeted therapy, and immunotherapy), and radiation therapy, are associated with significant adverse influences on physical and mental health, quality of life, and the economic status of the patient and her family. The fear of recurrence and its devastating effects often leads to overtreatment, with a toxic cost to the patient financially and physically in cases in which this is not required. This article discusses some aspects of a breast cancer diagnosis and its impact on the various facets of the life of the patient and her family. It further elucidates the role of prognostic factors, the currently available biomarkers and prognostic signatures, and the importance of ethnically validating biomarkers and prognostic signatures.

Mammaprint™: a comprehensive review

The number of breast cancer (BC) cases is growing worldwide, being most frequently diagnosed in the early-setting. Mammaprint™ is a 70-gene-expression signature, originally designed for selecting early BC patients with low risk of developing metastasis, so that they could be spared adjuvant chemotherapy. Its use as a prognostic biomarker has been extensively validated, both retrospectively and prospectively. However, its value as a predictive tool and as a clinically useful tool remains controversial. This review will describe how the test works, its application in the clinic and its limitations. Cost-effectiveness studies will be summarized. Finally, we will provide a perspective on the use of Mammaprint in the near future, as a valuable tool for personalizing the treatment of early BC patients.

Exploring the potential cost-effectiveness of precision medicine treatment strategies for diffuse large B-cell lymphoma

Activated B-cell-like (ABC) diffuse large B-cell lymphoma (DLBCL) is associated with worse survival after standard rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (RCHOP) chemoimmunotherapy compared to germinal center B-cell-like (GCB) subtype. Preliminary evidence suggests that benefits from novel agents may vary by subtype. Hypothesizing that treatment stratified by DLBCL subtype could be potentially cost-effective, we developed micro-simulation models to compare three first-line treatment strategies: (1) standard RCHOP for all patients (2) subtype testing followed by RCHOP for GCB and novel treatment for ABC DLBCL, and (3) novel treatment for all patients. Based on phase 2 evidence, we used lenalidomide + RCHOP as a surrogate novel treatment. The subtype-based approach showed a favorable incremental cost-effectiveness ratio of $15,015/quality-adjusted life year compared with RCHOP. Although our exploratory analyses demonstrated a wide range of conditions where subtype-based treatment remained cost-effective, data from phase 3 trials are needed to validate our models' findings and draw definitive conclusions.

Systematic review of the clinical and economic value of gene expression profiles for invasive early breast cancer available in Europe

Gene expression profiles with prognostic capacities have shown good performance in multiple clinical trials. However, with multiple assays available and numerous types of validation studies performed, the added value for daily clinical practice is still unclear. In Europe, the MammaPrint, OncotypeDX, PAM50/Prosigna and Endopredict assays are commercially available. In this systematic review, we aim to assess these assays on four important criteria: Assay development and methodology, clinical validation, clinical utility and economic value. We performed a literature search covering PubMed, Embase, Web of Science and Cochrane, for studies related to one or more of the four selected assays. We identified 147 papers for inclusion in this review. MammaPrint and OncotypeDX both have evidence available, including level IA clinical trial results for both assays. Both assays provide prognostic information. Predictive value has only been shown for OncotypeDX. In the clinical utility studies, a higher reduction in chemotherapy was achieved by OncotypeDX, although the number of available studies differ considerably between tests. On average, economic evaluations estimate that genomic testing results in a moderate increase in total costs, but that these costs are acceptable in relation to the expected improved patient outcome. PAM50/prosigna and EndoPredict showed comparable prognostic capacities, but with less economical and clinical utility studies. Furthermore, for these assays no level IA trial data are available yet. In summary, all assays have shown excellent prognostic capacities. The differences in the quantity and quality of evidence are discussed. Future studies shall focus on the selection of appropriate subgroups for testing and long-term outcome of validation trials, in order to determine the place of these assays in daily clinical practice.

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.

Towards decision-making using individualized risk estimates for personalized medicine: A systematic review of genomic classifiers of solid tumors

Recent advances in the understanding of the genetic underpinnings of cancer offer the promise to customize cancer treatments to the individual through the use of genomic classifiers (GCs). At present, routine clinical utilization of GCs is uncommon and their current scope and status, in a broad sense, are unknown. As part of a registered review (PROSPERO 2014:CRD42014013371), we systematically reviewed the literature evaluating the utility of commercially available GCs by searching Ovid Medline (PubMed), EMBASE, the Cochrane Database of Systematic Reviews, and CINAHL on September 2, 2014. We excluded articles involving pediatric malignancies, non-solid or non-invasive cancers, hereditary risk of cancer, non-validated GCs, and GCs involving fewer than 3 biomarkers. A total of 3,625 studies were screened, but only 37 met the pre-specified inclusion criteria. Of these, 15 studies evaluated outcomes and clinical utility of GCs through clinical trials, and the remainder through the use of mathematical models. Most studies (29 of 37) were specific to hormone-receptor positive breast cancer, whereas only 4 studies evaluated GCs in non-breast cancer (prostate, colon, and lung cancers). GCs have spurred excitement across disciplines in recent decades. While there are several GCs that have been validated, the general quality of the data are weak. Further research, including prospective validation is needed, particularly in the non-breast cancer GCs.

Gene Expression Profiling for the Identification and Classification of Antibody-Mediated Heart Rejection

BACKGROUND

Antibody-mediated rejection (AMR) contributes to heart allograft loss. However, an important knowledge gap remains in terms of the pathophysiology of AMR and how detection of immune activity, injury degree, and stage could be improved by intragraft gene expression profiling.

METHODS

We prospectively monitored 617 heart transplant recipients referred from 4 French transplant centers (January 1, 2006-January 1, 2011) for AMR. We compared patients with AMR (n=55) with a matched control group of 55 patients without AMR. We characterized all patients using histopathology (ISHLT [International Society for Heart and Lung Transplantation] 2013 grades), immunostaining, and circulating anti-HLA donor-specific antibodies at the time of biopsy, together with systematic gene expression assessments of the allograft tissue, using microarrays. Effector cells were evaluated with in vitro human cell cultures. We studied a validation cohort of 98 heart recipients transplanted in Edmonton, AB, Canada, including 27 cases of AMR and 71 controls.

RESULTS

A total of 240 heart transplant endomyocardial biopsies were assessed. AMR showed a distinct pattern of injury characterized by endothelial activation with microcirculatory inflammation by monocytes/macrophages and natural killer (NK) cells. We also observed selective changes in endothelial/angiogenesis and NK cell transcripts, including CD16A signaling and interferon-γ-inducible genes. The AMR-selective gene sets accurately discriminated patients with AMR from those without and included NK transcripts (area under the curve=0.87), endothelial activation transcripts (area under the curve=0.80), macrophage transcripts (area under the curve=0.86), and interferon-γ transcripts (area under the curve=0.84; P<0.0001 for all comparisons). These 4 gene sets showed increased expression with increasing pathological AMR (pAMR) International Society for Heart and Lung Transplantation grade (P<0.001) and association with donor-specific antibody levels. The unsupervised principal components analysis demonstrated a high proportion of molecularly inactive pAMR1(I+), and there was significant molecular overlap between pAMR1(H⁺) and full-blown pAMR2/3 cases. Endothelial activation transcripts, interferon-γ, and NK transcripts showed association with chronic allograft vasculopathy. The molecular architecture and selective AMR transcripts, together with gene set discrimination capacity for AMR identified in the discovery set, were reproduced in the validation cohort.

CONCLUSIONS

Tissue-based measurements of specific pathogenesis-based transcripts reflecting NK burden, endothelial activation, macrophage burden, and interferon-γ effects accurately classify AMR and correlate with degree of injury and disease activity. This study illustrates the clinical potential of a tissue-based analysis of gene transcripts to refine diagnosis of heart transplant rejection.

[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.

A Framework for Prioritizing Research Investments in Precision Medicine

INTRODUCTION

The adoption of precision medicine (PM) has been limited in practice to date, and yet its promise has attracted research investments. Developing foundational economic approaches for directing proper use of PM and stimulating growth in this area from multiple perspectives is thus quite timely.

METHODS

Building on our previously developed expected value of individualized care (EVIC) framework, we conceptualize new decision-relevant metrics to better understand and forecast the expected value of PM. Several aspects of behavior at the patient, physician, and payer levels are considered that can inform the rate and manner in which PM innovations diffuse throughout the relevant population. We illustrate this framework and the methods using a retrospective evaluation of the use of OncotypeDx genomic test among breast cancer patients.

RESULTS

The enriched metrics can help inform many facets of PM decision making, such as evaluating alternative reimbursement levels for PM tests, implementation and education programs for physicians and patients, and decisions around research investments by manufacturers and public entities. We replicated prior published results on evaluation of OncotypeDx among breast cancer patients but also illustrated that those results are based on assumptions that are often not met in practice. Instead, we show how incorporating more practical aspects of behavior around PM could lead to drastically different estimates of value.

CONCLUSION

We believe that the framework and the methods presented can provide decision makers with more decision-relevant tools to explore the value of PM. There is a growing recognition that data on adoption is important to decision makers. More research is needed to develop prediction models for potential diffusion of PM technologies.

Banff 2013 update: Pearls and pitfalls in transplant renal pathology

The pathological classification of rejection in renal allografts (Banff classification) has undergone substantial evolution for more than 20 years, and has been the diagnostic gold standard in clinical practice. The 2013 updated Banff classification encompasses a revised scheme of antibody-mediated rejection (ABMR) that consists of donor-specific antibody (DSA) positivity, characteristic histological manifestations for both acute and chronic ABMR, and DSA-induced endothelial cell injury which is represented by either C4d positivity, microvascular inflammation or expression of activated endothelial gene transcripts. Other modified criteria include a C4d positivity threshold, and histological definition of transplant glomerulitis and transplant glomerulopathy. Morphologically, glomerulonephritis, either recurrent or de novo, can be challenging to differentiate from ABMR-mediated transplant glomerulitis. Endothelial arteritis by itself does not warrant the diagnosis of acute T-cell mediated rejection; ABMR should also be considered based on the DSA test results. With regard to polyomavirus BK-associated nephropathy, immunohistochemical examination using anti-simian virus (SV) 40 antibody can be a promising method to assess the quantitative viral load of polyomavirus BK and graft survival. In summary, the 2013 updated Banff classification strictly defines ABMR with histopathological and serological criteria irrespective of C4d positivity. Inclusion of gene expression data relevant to ABMR highlights that the Banff criteria have entered the era of 'Seeing the Unseen' schemes, reflecting recent advances in understanding the molecular events in allograft injury.

Cost effectiveness of personalized treatment in women with early breast cancer: the application of OncotypeDX and Adjuvant! Online to guide adjuvant chemotherapy in Austria

A Breast Cancer Outcomes model was developed at the ONCOTYROL research center to evaluate personalized test-treatment strategies in Austria. The goal was to evaluate the cost-effectiveness of a new 21-gene assay (ODX) when used in conjunction with the Adjuvant! Online (AO) decision aid to support personalized decisions about use of adjuvant chemotherapy in early-stage breast cancer patients in Austria. We applied a validated discrete-event-simulation model to a hypothetical cohort of 50 years old women over a lifetime horizon. The test-treatment strategies of interest were defined using three-letter acronyms. The first (second, third) letter indicates whether patients with a low (intermediate, high) risk according to AO were tested using ODX (Y yes, N no). The main outcomes were life-years gained, quality-adjusted life-years (QALYs), costs and cost effectiveness. Robustness of the results was tested in sensitivity analyses. Results were compared to a Canadian analysis conducted by the Toronto Health Economics and Technology Assessment Collaborative (THETA). Five of eight strategies were dominated (i.e., more costly and less effective: NNY, NYN, YNN, YNY, YYN). The base-case analysis shows that YYY (ODX provided to all patients) is the most effective strategy and is cost effective with an incremental cost-effectiveness ratio of 15,700 EUR per QALY gained. These results are sensitive to changes in the probabilities of distant recurrence, age and costs of chemotherapy. The results of the base-case analysis were comparable to the THETA results. Based on our analyses, using ODX in addition to AO is effective and cost effective in all women in Austria. The development of future genetic tests may require alternative or additional test-treatment strategies to be evaluated.

Adjuvant Chemotherapy Use and Health Care Costs After Introduction of Genomic Testing in Breast Cancer

PURPOSE

We assessed the associations between the 21-gene recurrence score assay (RS) receipt, subsequent chemotherapy use, and medical expenditures among patients with early-stage breast cancer.

PATIENTS AND METHODS

Data from the Pennsylvania Cancer Registry were used to assemble a retrospective cohort of women with early-stage breast cancer from 2007 to 2010 who underwent initial surgical treatment. These data were merged with administrative claims from the 12-month periods before and after diagnosis to identify comorbidities, treatments, and expenditures (n = 7,287). Propensity score-weighted regression models were estimated to identify the effects of RS receipt on chemotherapy use and medical spending in the year after diagnosis.

RESULTS

The associations between RS receipt and outcomes varied markedly by patient age. RS use was associated with lower chemotherapy use among women younger than 55 (19.2% lower; 95% CI, 10.6 to 27.9). RS use was associated with higher chemotherapy use among women 75 to 84 years old (5.7% higher; 95% CI, 0.4 to 11.0). RS receipt was associated with lower adjusted 1-year medical spending among women younger than 55 ($15,333 lower; 95% CI, $2,841 to $27,824) and with higher spending among women who were 75 to 84 years old ($3,489 higher; 95% CI, $857 to $6,122).

CONCLUSION

RS receipt was associated with reduced use of adjuvant chemotherapy and lower health care spending among women with breast cancer who were younger than 55. Conversely, among women 75 and older, RS testing was associated with a modest increase in chemotherapy use and slightly higher spending. From a population perspective, the impact of RS testing on breast cancer treatment and health care costs is much greater in younger women.

Transcriptomics in cancer diagnostics: developments in technology, clinical research and commercialization

Transcriptomic technologies are evolving to diagnose cancer earlier and more accurately to provide greater predictive and prognostic utility to oncologists and patients. Digital techniques such as RNA sequencing are replacing still-imaging techniques to provide more detailed analysis of the transcriptome and aberrant expression that causes oncogenesis, while companion diagnostics are developing to determine the likely effectiveness of targeted treatments. This article examines recent advancements in molecular profiling research and technology as applied to cancer diagnosis, clinical applications and predictions for the future of personalized medicine in oncology.

Personalised and Precision Medicine in Cancer Clinical Trials: Panacea for Progress or Pandora's Box?

Cancer clinical trials have been one of the key foundations for significant advances in oncology. However, there is a clear recognition within the academic, care delivery and pharmaceutical/biotech communities that our current model of clinical trial discovery and development is no longer fit for purpose. Delivering transformative cancer care should increasingly be our mantra, rather than maintaining the status quo of, at best, the often miniscule incremental benefits that are observed with many current clinical trials. As we enter the era of precision medicine for personalised cancer care (precision and personalised medicine), it is important that we capture and utilise our greater understanding of the biology of disease to drive innovative approaches in clinical trial design and implementation that can lead to a step change in cancer care delivery. A number of advances have been practice changing (e.g. imatinib mesylate in chronic myeloid leukaemia, Herceptin in erb-B2-positive breast cancer), and increasingly we are seeing the promise of a number of newer approaches, particularly in diseases like lung cancer and melanoma. Targeting immune checkpoints has recently yielded some highly promising results. New algorithms that maximise the effectiveness of clinical trials, through for example a multi-stage, multi-arm type design are increasingly gaining traction. However, our enthusiasm for the undoubted advances that have been achieved are being tempered by a realisation that these new approaches may have significant cost implications. This article will address these competing issues, mainly from a European perspective, highlight the problems and challenges to healthcare systems and suggest potential solutions that will ensure that the cost/value rubicon is addressed in a way that allows stakeholders to work together to deliver optimal cost-effective cancer care, the benefits of which can be transferred directly to our patients.

The importance of test accuracy in economic evaluations of companion diagnostics

BACKGROUND

Economic evaluations of companion diagnostics often fail to include the impact that tests have on the overall economic value of test-drug combinations. 

METHODS

To illustrate the importance of test accuracy on the cost-effectiveness of companion diagnostics by means of examples. Data were extracted from the literature.

RESULTS

The accuracy of a test and in particularly its specificity, is often more influential on the overall cost-effectiveness results than the price of the test. Specificity becomes more crucial when prevalence of the biomarker is low. Multiple, simultaneous testing faces specific challenges regarding its overall specificity.

CONCLUSION

This article opens a discussion on some fundamental points linked to economic evaluations of test-therapy combinations.

Lessons Learned from a Cross-Model Validation between a Discrete Event Simulation Model and a Cohort State-Transition Model for Personalized Breast Cancer Treatment

OBJECTIVES

Breast cancer is the most common malignancy among women in developed countries. We developed a model (the Oncotyrol breast cancer outcomes model) to evaluate the cost-effectiveness of a 21-gene assay when used in combination with Adjuvant! Online to support personalized decisions about the use of adjuvant chemotherapy. The goal of this study was to perform a cross-model validation.

METHODS

The Oncotyrol model evaluates the 21-gene assay by simulating a hypothetical cohort of 50-year-old women over a lifetime horizon using discrete event simulation. Primary model outcomes were life-years, quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs). We followed the International Society for Pharmacoeconomics and Outcomes Research-Society for Medical Decision Making (ISPOR-SMDM) best practice recommendations for validation and compared modeling results of the Oncotyrol model with the state-transition model developed by the Toronto Health Economics and Technology Assessment (THETA) Collaborative. Both models were populated with Canadian THETA model parameters, and outputs were compared.

RESULTS

The differences between the models varied among the different validation end points. The smallest relative differences were in costs, and the greatest were in QALYs. All relative differences were less than 1.2%. The cost-effectiveness plane showed that small differences in the model structure can lead to different sets of nondominated test-treatment strategies with different efficiency frontiers. We faced several challenges: distinguishing between differences in outcomes due to different modeling techniques and initial coding errors, defining meaningful differences, and selecting measures and statistics for comparison (means, distributions, multivariate outcomes).

CONCLUSIONS

Cross-model validation was crucial to identify and correct coding errors and to explain differences in model outcomes. In our comparison, small differences in either QALYs or costs led to changes in ICERs because of changes in the set of dominated and nondominated strategies.

A retrospective study of the impact of 21-gene recurrence score assay on treatment choice in node positive micrometastatic breast cancer

To assess clinical utility of the 21-gene assay (Oncotype DX^® Recurrence Score^®), we determined whether women with HER2(−)/ER+ pN1mi breast cancer with low (<18) Recurrence Scores results are given adjuvant chemotherapy in a lower proportion than those with high scores (≥31). This was a multicenter chart review of ≥18 year old women with pN1mi breast cancer, HER2(−)/ER+ tumors, ductal/lobular/mixed histology, with the assay ordered on or after 1 January 2007. One hundred and eighty one patients had a mean age of 60.7 years; 82.9% had ECOG performance status 0; 33.7% had hypertension, 22.7% had osteoporosis, 18.8% had osteoarthritis, and 8.8% had type-2 diabetes. Mean Recurrence Score was 17.8 (range: 0–50). 48.6% had a mastectomy; 55.8% had a lumpectomy. 19.8% of low-risk group patients were recommended chemotherapy vs. 57.9% in the intermediate-risk group and 100% in the high-risk group (p < 0.001). A total of 80.2% of the low-risk group were recommended endocrine therapy alone, while 77.8% of the high-risk group were recommended both endocrine and chemotherapy (p < 0.001). The Oncotype DX Recurrence Score result provides actionable information that can be incorporated into treatment planning for women with HER2(−)/ER+ pN1mi breast cancer. The Recurrence Score result has clinical utility in treatment planning for HER2(−)/ER+ pN1mi breast cancer patients.

Genome-based risk prediction for early stage breast cancer

Tests to better characterize tumor genomic architecture are quickly becoming a standard of care in oncology. For breast cancer, the use of gene expression assays for early stage disease is already common practice. These tests have found a place in risk stratifying the heterogeneous group of stage I-II breast cancers for recurrence, for predicting chemotherapy response, and for predicting breast cancer-related mortality. In the last 5 years, more assays have become available to the practicing oncologist. Given the rapidity with which this field has evolved, it is prudent to review the tests, their indications, and the studies from which they have been validated. We present a comprehensive review of the available gene expression assays for early stage breast cancer. We review data for several individual tests and comparative studies looking at risk prediction and cost-effectiveness.

The multigene signature MammaPrint impacts on multidisciplinary team decisions in ER+, HER2- early breast cancer

Background:

Validated multigene signatures (MGS) provide additional prognostic information when evaluating clinical features of ER⁺, HER2⁻ early breast cancer. We have studied the quantitative and qualitative impact of MGS on multidisciplinary team (MDT) recommendations.

Methods:

We prospectively recruited 75 ER⁺, HER2⁻ breast cancer patients. Inclusion was based on biopsy assessment of grade, hormone receptor status, HER2, clinical tumour and nodal status. A fresh tissue sample was sent for MammaPrint (MP), TargetPrint analysis at surgery. Clinical risk was decided by the MDT in the absence of MP results and repeated following the collection of MP results. Decision changes were recorded and a health technology assessment was undertaken to compare cost effectiveness.

Results:

The majority of patients were assigned low to intermediate clinical risk by the MDT. According to MP, 76% were low risk. A very high correlation between local IHC and the TargetPrint assessment was shown. In over a third of patients, discordance between clinical and molecular risk was observed. Decision changes were recorded in half of these cases (18.6%) and resulted in two out of three patients not requiring chemotherapy. The use of MP was also found to be more cost effective.

Conclusions:

The multigene signature MP revealed clinical and molecular risk discordance in a third of patients. The impact of this on MDT recommendations was most profound in cases where few clinical risk factors were observed and enabled some women to forgo chemotherapy. The use of MGS is unlikely to have an impact in either clinically low-risk women or in patients with more than one relative indication for chemotherapy.

Clinical validation of the EndoPredict test in node-positive, chemotherapy-treated ER+/HER2- breast cancer patients: results from the GEICAM 9906 trial

Introduction

EndoPredict (EP) is an RNA-based multigene test that predicts the likelihood of distant recurrence in patients with estrogen receptor-positive (ER+), human epidermal growth factor receptor 2–negative (HER2−) breast cancer (BC) who are being treated with adjuvant endocrine therapy. Herein we report the prospective-retrospective clinical validation of EP in the node-positive, chemotherapy-treated, ER+/HER2− BC patients in the GEICAM 9906 trial.

Methods

The patients (N = 1,246) were treated either with six cycles of fluorouracil, epirubicin and cyclophosphamide (FEC) or with four cycles of FEC followed by eight weekly courses of paclitaxel (FEC-P), as well as with endocrine therapy if they had hormone receptor–positive disease. The patients were assigned to EP risk categories (low or high) according to prespecified cutoff levels. The primary endpoint in the clinical validation of EP was distant metastasis-free survival (MFS). Metastasis rates were estimated using the Kaplan-Meier method, and multivariate analysis was performed using Cox regression.

Results

The molecular EP score and the combined molecular and clinical EPclin score were successfully determined in 555 ER+/HER2− tumors from the 800 available samples in the GEICAM 9906 trial. On the basis of the EP, 25% of patients (n = 141) were classified as low risk. MFS was 93% in the low-risk group and 70% in the high-risk group (absolute risk reduction = 23%, hazard ratio (HR) = 4.8, 95% confidence interval (CI) = 2.5 to 9.5; P < 0.0001). Multivariate analysis showed that, in this ER+/HER2− cohort, EP results are an independent prognostic parameter after adjustment for age, grade, lymph node status, tumor size, treatment arm, ER and progesterone receptor (PR) status and proliferation index (Ki67). Using the predefined EPclin score, 13% of patients (n = 74) were assigned to the low-risk group, who had excellent outcomes and no distant recurrence events (absolute risk reduction vs high-risk group = 28%; P < 0.0001). Furthermore, EP was prognostic in premenopausal patients (HR = 6.7, 95% CI = 2.4 to 18.3; P = 0.0002) and postmenopausal patients (HR = 3.3, 95% CI = 1.3 to 8.5; P = 0.0109). There were no statistically significant differences in MFS between treatment arms (FEC vs FEC-P) in either the high- or low-risk groups. The interaction test results between the chemotherapy arm and the EP score were not significant.

Conclusions

EP is an independent prognostic parameter in node-positive, ER+/HER2− BC patients treated with adjuvant chemotherapy followed by hormone therapy. EP did not predict a greater efficacy of FEC-P compared to FEC alone.

Performance characteristics of the MammaPrint® breast cancer diagnostic gene signature

BACKGROUND

The analytical performance of multigene signatures depends on many parameters, including precision, repeatability, reproducibility and intratumor heterogeneity. Indicators such as sensitivity, specificity, positive predictive value and negative predictive value are typically used to define the clinical performance of a diagnostic test.

AIM

Here we study these performance characteristics of the MammaPrint^® (Agendia NV, Amsterdam, The Netherlands) 70-gene signature using the US FDA-recommended guidelines, as well as predetermined acceptance criteria.

RESULTS

The clinical and analytical performance characteristics show that MammaPrint is a robust, reproducible, precise test, with a maximum variation of 5% in multiple samplings of the same tissue.

CONCLUSION

MammaPrint is a reliable indicator of distant metastasis in early-stage breast cancer patients of all ages and is well suited for personalized medical care.

Microarray diagnosis of antibody-mediated rejection in kidney transplant biopsies: an international prospective study (INTERCOM)

In a reference set of 403 kidney transplant biopsies, we recently developed a microarray-based test that diagnoses antibody-mediated rejection (ABMR) by assigning an ABMR score. To validate the ABMR score and assess its potential impact on practice, we performed the present prospective INTERCOM study (clinicaltrials.gov NCT01299168) in 300 new biopsies (264 patients) from six centers: Baltimore, Barcelona, Edmonton, Hannover, Manchester and Minneapolis. We assigned ABMR scores using the classifier created in the reference set and compared it to conventional assessment as documented in the pathology reports. INTERCOM documented uncertainty in conventional assessment: In 41% of biopsies where ABMR features were noted, the recorded diagnoses did not mention ABMR. The ABMR score correlated with ABMR histologic lesions and donor-specific antibodies, but not with T cell-mediated rejection lesions. The agreement between ABMR scores and conventional assessment was identical to that in the reference set (accuracy 85%). The ABMR score was more strongly associated with failure than conventional assessment, and when the ABMR score and conventional assessment disagreed, only the ABMR score was associated with early progression to failure. INTERCOM confirms the need to reduce uncertainty in the diagnosis of ABMR, and demonstrates the potential of the ABMR score to impact practice.

The faces of personalized medicine: a framework for understanding its meaning and scope

The objective of this article was to provide a framework for understanding the different definitions of the term "personalized medicine." The term personalized medicine is used regularly but interpreted in different ways. This article approaches the term by starting with a broad view of clinical medicine, where three components can be distinguished: the questions (e.g., what is the diagnosis?), the methods used to answer them (e.g., a test), and the available actions (e.g., to give or not give a particular drug). Existing definitions of personalized medicine disagree about which questions, methods, and actions fall within its domain. Some define the term narrowly, referring to the use of a diagnostic test to predict drug response, thereby clarifying whether or not a patient will benefit from that drug. An example of this combination is the HER2/neu test to predict the effectiveness of trastuzumab in breast cancer. Many who adopt this definition associate the concept of personalized medicine with fields such as genetics, genomics, and other types of "-omics." In contrast, others view personalized medicine as a concept that has always existed, because medicine has always considered the needs of the individual. One definition of personalized medicine that accommodates both interpretations is "the use of combined knowledge (genetic or otherwise) about a person to predict disease susceptibility, disease prognosis, or treatment response and thereby improve that person's health." This predictive ability can increase over time through innovations in various technologies, resulting in further improvements in health outcomes. Moreover, these developments can lead to a better understanding of the underlying causes of disease, which can eventually lead to breakthroughs in the treatment of individual patients. In that sense, a truly personalized form of medicine can also be seen as an ideal, a goal that will be achieved only after multiple advances in science. Although the term personalized medicine was rechristened somewhat recently, our ability to personalize medicine will continue to advance in unimaginable ways as we come to learn more about the heterogeneity that exists among individuals and diseases.

Potential impact of microarray diagnosis of T cell-mediated rejection in kidney transplants: The INTERCOM study

We previously developed a microarray-based test for T cell-mediated rejection (TCMR) in a reference set of 403 biopsies. To determine the potential impact of this test in clinical practice, we undertook INTERCOM, a prospective international study of 300 indication biopsies from 264 patients (ClinicalTrials.gov NCT01299168). Biopsies from six centers-Baltimore, Barcelona, Edmonton, Hannover, Manchester and Minneapolis-were analyzed by microarrays, assigning TCMR scores by an algorithm developed in the reference set and comparing TCMR scores to local histology assessment. The TCMR score correlated with histologic TCMR lesions-tubulitis and interstitial infiltration. The accuracy for primary histologic diagnoses (0.87) was similar to the reference set (0.89). The TCMR scores reclassified 77/300 biopsies (26%): 16 histologic TCMR were molecularly non-TCMR; 15 histologic non-TCMR were molecularly TCMR, including 6 with polyoma virus nephropathy; and all 46 "borderline" biopsies were reclassified as TCMR (8) or non-TCMR (38). Like the reference set, discrepancies were primarily in situations where histology has known limitations, for example, in biopsies with scarring and inflammation/tubulitis potentially from other diseases. Neither the TCMR score nor histologic TCMR was associated with graft loss. Thus the molecular TCMR score has potential to add new insight, particularly in situations where histology is ambiguous or potentially misleading.