Abstract OT3-02-12: OPTIMA (optimal personalised treatment of early breast cancer usIng multi-parameter analysis), a prospective trial to validate the predictive utility and cost-effectiveness of gene expression test-directed chemotherapy decisions
Bibliographic record
Abstract
Abstract Background: Multi-parameter gene expression assays (MPAs) are widely used to estimate individual patient residual risk and to guide chemotherapy use in hormone-sensitive HER2-negative node-negative early breast cancer. These uses of MPAs have not yet been prospectively validated. OPTIMA aims to validate the use of MPA testing to predict chemotherapy sensitivity in a largely node-positive breast cancer population. Methods: OPTIMA is a partially blinded multi-center, phase 3 randomized controlled trial with an adaptive two-stage design. The preliminary phase (OPTIMA prelim) evaluated the performance of MPAs to identify a suitable test(s) to be used in the main efficacy trial and assessed the feasibility and acceptability of a large UK trial. Eligible patients are men or women aged 40 years or older who have surgically resected early stage breast cancer, which is ER-positive and HER2-negative and who have either 1-9 involved axillary lymph nodes or tumors of at least 30mm diameter. Randomization is to standard management (chemotherapy followed by endocrine therapy) or to MPA-directed treatment. Those with a tumor categorized as "high-risk" by the test will be assigned to standard management whilst those at "low-risk" will be treated with endocrine therapy alone. OPTIMA prelim used Oncotype DX as the primary discriminator; the main trial will use Prosigna (PAM50). The co-primary outcomes are (1) Invasive Disease Free Survival (IDFS) and (2) cost-effectiveness of test-directed therapy compared to standard practice. Secondary outcomes include IDFS in "low-risk" patients, distant disease free survival, breast cancer specific survival, overall survival and quality of life. An integrated qualitative recruitment study will identify and address challenges to recruitment and informed consent. Tumor blocks from all consenting participants will be banked allowing the performance of alternative MPA technologies to be evaluated. Recruitment of 4500 patients over 4 years will permit demonstration of 3% non-inferiority of test-directed treatment, with 5% significance and 85% power, assuming 3 years follow-up and a control arm 5-year IDFS of at least 85%. The addition of patients from OPTIMA prelim will allow non-inferiority to be assessed with 2.5% significance. Results: OPTIMA-prelim recruited 412 patients in 23 months from 35 sites. It confirmed the acceptability of randomization to patients with a 47% acceptance rate, and to clinicians and hence the feasibility of a large prospective trial of test-directed treatment running in 100-plus UK sites. It showed that investment into research on test-directed therapy, especially with Prosigna, should be of substantial value to the NHS. Conclusion: OPTIMA, as one of two large scale prospective trials validating the use of test-guided chemotherapy in node-positive hormone-sensitive early breast cancer will have a global impact on patient treatment. Recruitment into the main efficacy trial will commence in October 2015. Funding: Project funded by the UK NIHR HTA Programme (10/34/501). Views expressed are those of the authors and not those of the HTA Programme, NIHR, NHS or the DoH. Citation Format: Stein RC, Marshall A, Hall PS, Bartlett JMS, Rooshenas L, Campbell A, Cameron DA, Rea D, Macpherson I, Earl HM, Poole CJ, Francis A, Morgan A, Harmer V, Pinder SE, Stallard N, Donovan J, Hulme C, McCabe C, Hughes-Davies L, Makris A, Dunn JA. OPTIMA (optimal personalised treatment of early breast cancer usIng multi-parameter analysis), a prospective trial to validate the predictive utility and cost-effectiveness of gene expression test-directed chemotherapy decisions. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr OT3-02-12.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".