Amy F Campbell

Comparing Breast Cancer Multiparameter Tests in the OPTIMA Prelim Trial: No Test Is More Equal Than the Others

BACKGROUND Previous reports identifying discordance between multiparameter tests at the individual patient level have been largely attributed to methodological shortcomings of multiple in silico studies. Comparisons between tests, when performed using actual diagnostic assays, have been predicted to demonstrate high degrees of concordance. OPTIMA prelim compared predicted risk stratification and subtype classification of different multiparameter tests performed directly on the same population. METHODS Three hundred thirteen women with early breast cancer were randomized to standard (chemotherapy and endocrine therapy) or test-directed (chemotherapy if Oncotype DX recurrence score >25) treatment. Risk stratification was also determined with Prosigna (PAM50), MammaPrint, MammaTyper, NexCourse Breast (IHC4-AQUA), and conventional IHC4 (IHC4). Subtype classification was provided by Blueprint, MammaTyper, and Prosigna. RESULTS Oncotype DX predicted a higher proportion of tumors as low risk (82.1%, 95% confidence interval [CI] = 77.8% to 86.4%) than were predicted low/intermediate risk using Prosigna (65.5%, 95% CI = 60.1% to 70.9%), IHC4 (72.0%, 95% CI = 66.5% to 77.5%), MammaPrint (61.4%, 95% CI = 55.9% to 66.9%), or NexCourse Breast (61.6%, 95% CI = 55.8% to 67.4%). Strikingly, the five tests showed only modest agreement when dichotomizing results between high vs low/intermediate risk. Only 119 (39.4%) tumors were classified uniformly as either low/intermediate risk or high risk, and 183 (60.6%) were assigned to different risk categories by different tests, although 94 (31.1%) showed agreement between four of five tests. All three subtype tests assigned 59.5% to 62.4% of tumors to luminal A subtype, but only 121 (40.1%) were classified as luminal A by all three tests and only 58 (19.2%) were uniformly assigned as nonluminal A. Discordant subtyping was observed in 123 (40.7%) tumors. CONCLUSIONS Existing evidence on the comparative prognostic information provided by different tests suggests that current multiparameter tests provide broadly equivalent risk information for the population of women with estrogen receptor (ER)-positive breast cancers. However, for the individual patient, tests may provide differing risk categorization and subtype information.

Abstract P4-11-07: Comparison of multiparameter tests in the UK OPTIMA-Prelim trial

Introduction All published adjuvant chemotherapy trials in breast cancer have made the assumption that the proportional benefits of chemotherapy apply uniformly across molecular subgroups. However, it can be argued that chemotherapy effectiveness for luminal A breast cancer is low in comparison to other subtypes irrespective of tumour stage. A logical extension of this argument is that novel multiparametric tests that use biological features of breast cancers to assess risk may also inform chemotherapy benefit in luminal cancers. The OPTIMA trial is a multi-centre, partially blinded, randomised clinical trial with a non-inferiority endpoint, and an adaptive design, to compare standard treatment (chemotherapy followed by endocrine therapy) with multi-parameter test-guided treatment allocation to either chemotherapy followed by endocrine therapy or endocrine therapy alone. OPTIMA-prelim aimed to compare the predicted risk stratification, sub-type classification and cost effectiveness of different multiparameter tests performed on the same patient population. Methods Over 20 months of recruitment 285 patients were randomised to OPTIMA-prelim. Tissue was collected centrally, ER and HER2 status confirmed and samples provided for testing with Oncotype DX™, Prosigna™ (PAM50), Mammaprint™, Mammatyper™, IHC4-AQUA and IHC4 using conventional biomarkers. Sub-type classification was provided by Blueprint™, Mammatyper™ and Prosigna™. Each test was performed at central diagnostic laboratories (OncotypeDx, Mammaprint/Blueprint, Mammatyper) or in a central laboratory (Prosigna™/IHC4) strictly according to GLP practices. Results Samples from 181 patients randomised by January 2014 were tested and data analysed for this study. Patients were categorised as low/intermediate or high risk using predetermined cut-offs for each test. Oncotype DX predicted a proportion of low-risk tumours (79%; 95% CI 73-85%) similar to that predicted as either low or intermediate risk using Prosigna ROR_P (71%; 95% CI 64-78%) and IHC4 (69%; 95% CI 62-76%), whilst MammaPrint identified the fewest low-risk tumours (59%; 95% CI 52-66%). Strikingly, a comparison between tests showed modest agreement between tests when dichotomising results between high vs low/intermediate risk. Disagreement between different tests, in assigning individual tumours to risk categories, is not uncommon; for the four tests [Oncotype DX, MammaPrint, Prosigna ROR_P (low/int) and IHC4 (low/int)], only 71 (39%) tumours were classified as low/intermediate risk for all four tests and only 17 (9%) tumours were high risk for all four tests, 93 (52%) tumours were assigned to different risk categories by different tests. Similarly all three subtypes tests (Blueprint/Prosigna/Mammatyper) each assigned 59% of tumors to luminal A subtype but only 70% of these cases were classified as luminal A by all three assays. Conclusion Existing evidence on the comparative prognostic information provided by different tests suggests current multiparameter tests provide broadly equivalent risk information for the population of women with luminal breast cancers. However, for the individual patient, tests may provide differing risk categorisation or indeed subtype information. Acknowledgement This project was funded by the NIHR Health Technology Assessment (HTA) Programme (project 10/34/01). The opinions expressed therein are those of the authors and do not necessarily reflect those of the HTA programme, NIHR, NHS or Department of Health. Citation Format: John MS Bartlett, Robert C Stein, Jane Bayani, Andrea Marshall, Janet A Dunn, Amy F Campbell, Carrie Cunningham, Monika Sobol, Peter Hall, Leila Rooshenas, Adrienne Morgan, Christopher Poole, Sarah E Pinder, David A Cameron, Nigel Stallard, Jenny Donovan, Christopher McCabe, Luke Hughes-Davies, Andreas Makris, on Behalf of the OPTIMA Trial Management Group. Comparison of multiparameter tests in the UK OPTIMA-Prelim trial [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-11-07.

Discrepancies in central review re-testing of patients with ER-positive and HER2-negative breast cancer in the OPTIMA prelim randomised clinical trial

Background:There is limited data on results of central re-testing of samples from patients with invasive breast cancer categorised in their local hospital laboratories as oestrogen receptor (ER) positive and human epidermal growth factor receptor homologue 2 (HER2) negative.Methods:The Optimal Personalised Treatment of early breast cancer usIng Multiparameter Analysis preliminary study (OPTIMA prelim) was the feasibility phase of a randomised controlled trial to validate the use of multiparameter assay-directed chemotherapy decisions in the UK National Health Service (NHS). Eligibility criteria included ER positivity and HER2 negativity. Central re-testing of receptor status was mandatory.Results:Of the 431 patients tested centrally, discrepant results between central and local laboratory results were identified in only 19 (4.4%; 95% confidence interval 2.5–6.3%) patients (with 21 tumours). On central review, seven patients had cancers that were ER-negative (1.6%) and 13 (3.0%) patients with 15 tumours had HER2-positive disease, including one tumour discrepant for both biomarkers.Conclusions:Central re-testing of receptor status of invasive breast cancers in the UK NHS setting shows a high level of reproducibility in categorising tumours as ER-positive and HER2-negative, and raises questions regarding the cost effectiveness and clinical value of central re-testing in this sub-group of breast cancers in this setting.

Using adaptive designs for decision making within the optima trial: optimal personalized treatment of early breast cancer using multi-parameter tests

Methods OPTIMA prelim, the feasibility phase, aims to recruit 300 patients to evaluate performance and health-economics of a number of multi-parameter tests to identify test(s) to be used in the main trial and to establish the acceptability to patients and clinicians of randomisation. Patients are randomised to the standard arm or to the “test-directed treatment” arm according to the result of Oncotype DX test. The decision to roll forward into the main trial will be determined by the willingness of patients to be randomised, concordance and cost of the multi-parameter tests. Cost-effectiveness models will be based on the model developed in preparation for the OPTIMA trial, updated with contemporary evidence from the feasibility study and appropriate external data, e.g. the Ontario OncotypeDX field evaluation (prospective cohort study).

Value of Information Analysis of Multiparameter Tests for Chemotherapy in Early Breast Cancer: The OPTIMA Prelim Trial

BACKGROUND Precision medicine is heralded as offering more effective treatments to smaller targeted patient populations. In breast cancer, adjuvant chemotherapy is standard for patients considered as high-risk after surgery. Molecular tests may identify patients who can safely avoid chemotherapy. OBJECTIVES To use economic analysis before a large-scale clinical trial of molecular testing to confirm the value of the trial and help prioritize between candidate tests as randomized comparators. METHODS Women with surgically treated breast cancer (estrogen receptor-positive and lymph node-positive or tumor size ≥30 mm) were randomized to standard care (chemotherapy for all) or test-directed care using Oncotype DX™. Additional testing was undertaken using alternative tests: MammaPrintTM, PAM-50 (ProsignaTM), MammaTyperTM, IHC4, and IHC4-AQUA™ (NexCourse Breast™). A probabilistic decision model assessed the cost-effectiveness of all tests from a UK perspective. Value of information analysis determined the most efficient publicly funded ongoing trial design in the United Kingdom. RESULTS There was an 86% probability of molecular testing being cost-effective, with most tests producing cost savings (range -£1892 to £195) and quality-adjusted life-year gains (range 0.17-0.20). There were only small differences in costs and quality-adjusted life-years between tests. Uncertainty was driven by long-term outcomes. Value of information demonstrated value of further research into all tests, with Prosigna currently being the highest priority for further research. CONCLUSIONS Molecular tests are likely to be cost-effective, but an optimal test is yet to be identified. Health economics modeling to inform the design of a randomized controlled trial looking at diagnostic technology has been demonstrated to be feasible as a method for improving research efficiency.

Practicalities of using an adaptive design for decision making within the optima trial: optimal personalized treatment of early breast cancer using multi-parameter tests

Multi-parameter gene expression assays (MPA) to aid selection of chemotherapy in hormone-sensitive early breast cancer have not been prospectively validated. This field of personalised medicine is rapidly evolving. There is currently no “best test”. OPTIMA is an adaptive trial of MPA-based chemotherapy assignment in a largely node-positive breast cancer population.

Abstract P6-08-11: UK OPTIMA-prelim study demonstrates economic value in more clinical evaluation of multi-parameter prognostic tests in early breast cancer

Background There is uncertainty about the benefit of chemotherapy for some patients with ER-positive HER2-negative early breast cancer. Multi-parameter assays of gene expression may enhance the value of chemotherapy through personalised treatment decisions. An economic evaluation was undertaken in the context of the feasibility phase of an RCT (OPTIMA prelim) designed to validate prospectively the use of such an assay as a treatment decision tool in the UK National Health Service (NHS). The aim of the economic evaluation was to confirm value in an ongoing RCT and optimise its design for economic endpoints. Comparators included (i) All patients treated with chemotherapy, (ii) Oncotype DX, (iii) MammaPrint/BluePrint and (iv) Prosigna. Methods A model-based cost-effectiveness analysis was conducted to the standards of the UK National Institute for Care Excellence (NICE) reference case. A Markov model was constructed to simulate the care pathway of a cohort of patients with characteristics identified in the OPTIMA prelim study or, where unavailable, from the published literature. The costs (GBP) and benefits (QALYs) were estimated over a time horizon of the patient life-time. Alternative scenarios of recurrence rates and chemotherapy effect were explored in patients identified high or low risk by the tests and treated with and without chemotherapy. Scenarios included estimates based on the SWOG-8814 trial, the EBCTCG and outcomes forecasted using Adjuvant! Online. Uncertainty introduced by discrepancy in patient selection between tests was modelled using a Bayesian decision analytic framework. Probabilistic sensitivity analysis and value of information analysis was conducted using Monte Carlo simulation. Results There were 285 randomised patients. Multi-parameter analyses were performed on tumour samples and baseline factors were included in the model. The cost-effectiveness of all tests was uncertain. Uncertainty was predominantly driven by assumptions about long term recurrence rates in test-selected groups and the ability of tests to predict benefit from chemotherapy. The relationship between recurrence-free survival and life expectancy in test-selected groups and in patients who did or did not receive adjuvant chemotherapy was also important. The incremental cost-effectiveness ratio (ICER) for Oncotype DX compared with chemotherapy for all was cost-effective in many scenarios, ranging from GBP26,000 per QALY to resulting in increased QALYs with cost savings (dominate), depending on assumptions. The value of information analysis placed high societal value in further research into recurrence-free survival for test-directed chemotherapy, irrespective of the test evaluated. Conclusion There is substantial value in prospective comparative research into all tests evaluated, including long term outcomes, to resolve uncertainties in the clinical and economic optimal choice of test. Acknowledgements This project was funded by the National Institute for Health Research Health Technology Assessment (NIHR HTA) Programme (project number 10/34/01). The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the HTA programme, NIHR, NHS or the Department of Health. Citation Format: Peter S Hall, Alison F Smith, Armando Vargas-Palacios, Robert C Stein, John Bartlett, Jane Bayani, Andrea Marshall, Janet A Dunn, Amy F Campbell, Carrie Cunningham, Leila Rooshenas, Monika Sobol, Adrienne Morgan, Christopher Poole, Sarah E Pinder, David A Cameron, Nigel Stallard, Jenny Donovan, Luke Hugh-Davies, Helena Earl, Andreas Makris, Claire Hulme, Christopher McCabe. UK OPTIMA-prelim study demonstrates economic value in more clinical evaluation of multi-parameter prognostic tests in early breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-08-11.