Abstract OT3-32-01: OPTIMA, a prospective randomized trial to validate the clinical utility and cost-effectiveness of gene expression test-directed chemotherapy decisions in high clinical risk early breast cancer
Bibliographic record
Abstract
Abstract Background: Multi-parameter tumor gene expression assays (MPAs) are used to estimate individual patient risk and guide chemotherapy use in hormone-sensitive, HER2-negative early breast cancer. The TAILORx trial supports MPA use in a node-negative population. Evidence for MPA use in postmenopausal node-positive breast cancer has been provided by the RxPONDER trial interim analysis but this relies on the absence of superiority in an analysis where >50% of events were unrelated to breast cancer. There is much uncertainty about MPA use for premenopausal patients. OPTIMA (Optimal Personalised Treatment of early breast cancer usIng Multi-parameter Analysis) (ISRCTN42400492) is a prospective international randomized controlled trial designed to validate MPAs as predictors of chemotherapy sensitivity in a largely node-positive breast cancer population. Methods: OPTIMA is a partially blinded study with an adaptive two-stage design. The trial recruits women and men age 40 or older with resected ER-positive, HER2-negative invasive breast cancer and up to 9 involved axillary lymph nodes. Randomization is to standard management (chemotherapy and endocrine therapy) or to MPA-directed treatment using the Prosigna (PAM50) test. Those with a Prosigna tumor Score (ROR_PT) >60 receive standard management whilst those with a low score (≤60) tumor are treated with endocrine therapy alone. Endocrine therapy for pre-menopausal women includes ovarian suppression for all participants unless they experience a chemotherapy-induced menopause. Adjuvant abemaciclib is permitted. The trial will be analyzed for (1) non-inferiority of recurrence according to randomization and (2) cost-effectiveness. The key secondary outcome is non-inferiority of recurrence for patients with low ROR_PT score tumors. The efficacy analyses will be performed Per Protocol using Invasive Breast Cancer Free Survival (IBCFS) as the primary outcome measure to limit the risk of a false non-inferiority conclusion. Recruitment of 4500 patients over 8 years will permit demonstration of up to 3% non-inferiority of test-directed treatment with at least 83% power, assuming 5-year IBCFS is 87% with standard management. An integrated qualitative recruitment study addresses challenges to consent and recruitment, building on experience from the feasibility study which found that a multidisciplinary approach is important for recruitment success. OPTIMA is strongly supported by a patient group which has helped design all patient documents and which is represented on the TMG. Results: The OPTIMA main trial opened in January 2017 and has continued to recruit throughout the COVID-19 pandemic. Overall recruitment as of 1 July 2022 was 2814 (2593 from UK, 221 from Norway). Patient characteristics are well balanced between the trial arms. Currently 95% of randomized participants are eligible for inclusion in the PP analysis. 66% of the MPA-directed arm participants have been allocated to endocrine therapy only. The test failure rate is < 1%. Conclusion: OPTIMA will provide robust unbiased evidence on test-directed chemotherapy safety for both postmenopausal and premenopausal women with 1-3 involved nodes as well as for patients with 4-9 involved nodes and for patients treated with abemaciclib. Funding: OPTIMA is funded by the UK NIHR HTA Programme (10/34/501) and in Norway by KLINBEFORSK and the Norwegian Cancer Society. Views expressed are those of the authors and not those of the HTA Programme, NIHR, NHS or the Department of Health. Trial Inquiries: OPTIMA@warwick.ac.uk Patient characteristics Citation Format: Robert Stein, Andreas Makris, Iain Macpherson, Luke Hughes-Davies, Andrea Marshall, Georgina Dotchin, David A. Cameron, Belinda E. Kiely, Caroline Wilson, Anne Armstrong, Helena M. Earl, Christopher J. Poole, Janice Tsang, Bjørn Naume, Daniel Rea, Hege Ohnstad, Peter S. Hall, Stuart A. McIntosh, Bethany Shinkins, Christopher McCabe, Adrienne Morgan, John MS Bartlett, Janet A. Dunn. OPTIMA, a prospective randomized trial to validate the clinical utility and cost-effectiveness of gene expression test-directed chemotherapy decisions in high clinical risk early breast cancer. [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr OT3-32-01.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".