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Abstract PO3-02-02: A prospective, international, observational, real-world evidence database, and collaborative platform for Investigator-Initiated Studies in Early-Stage Breast Cancer tested with MammaPrint and BluePrint– the FLEX Study

2024· article· en· W4396590792 on OpenAlexaboutno aff
JJ Alberty-Oller, Lee B. Riley, Laila Samiian, Sarah Thayer, Olexiy Aseyev, Karen L. Tedesco, Victoria Poillucci, William Audeh, Danijela Jelovac, Joyce O’Shaughnessy

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBlueprintFLEXObservational studyStage (stratigraphy)MedicineBreast cancerCancerMedical physicsInternal medicineComputer scienceEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Abstract TIPS SABCS 2023 A prospective, international, observational, real-world evidence database, and collaborative platform for Investigator-Initiated Studies in Early-Stage Breast Cancer tested with MammaPrint and BluePrint– the FLEX Study Background: Clinical trials have been an invaluable tool in providing improvements in the discovery, treatment, and quality of life for various diseases and disorders including breast cancer, which impacts millions of people each year. The MammaPrint 70-gene assay along with BluePrint 80-gene subtype analysis are tools to provide such improvements in treatment planning. Historically, patient trial populations have not been racially diverse. Current efforts are focused on improving diversity and inclusion to promote efficacy and health equity across all races/ethnicities. Given recent publications supporting the ability of MammaPrint and BluePrint to identify genomic differences in outcomes of black women with breast cancer, the ongoing multi-center FLEX trial (NCT03053193) has proven to be an unparalleled source for improvement in breast cancer care. With a target of 30,000 enrolled patients, the collaborative research network within FLEX will use MammaPrint, BluePrint, full transcriptome, and clinical data to explore clinical and genomic differences in (sub)populations of interest to promote and advance precision medicine for patients with early-stage breast cancer. Methods: FLEX is the first of its kind to link clinical data with full transcriptome data. It is a prospective, observational trial that enrolls patients who are ≥ 18 years old with histologically proven stage I-III breast cancer with up to 3 positive lymph nodes. Patient eligibility for study enrollment include standard of care MammaPrint testing with or without BluePrint and consent to clinically annotated full transcriptome data collection. The study’s infrastructure facilitates the generation of hypotheses for targeted sub-studies that are important for breast cancer management. The FLEX network fosters collaboration with 99 active sites, including Canada, Greece, and Israel. All proposed substudies are vetted and approved by both internal and external research and scientific review committees. Since launching in April 2017, 13,547 patients have been enrolled including those who have been historically underrepresented in trials (Black n =1032; Latin n= 373; AAPI n =276), 43 investigator initiated sub-studies have been approved and are in progress on a varied number of approaches like MammaPrint/Blueprint clinical utilities, racial disparities, neoadjuvant treatment planning in ER+, and or HER2+ breast cancer with 31 abstracts accepted in national and international congresses. Five ongoing sub-studies within FLEX address differences in underlying biology and treatment response/management among Black, Latina, and Asian American patients with early-stage breast cancer. These studies provide a broader understanding of how differential gene expression patterns, identified with MammaPrint and BluePrint, are unique to racial/ethnic groups and can impact treatment outcomes. Overall, the FLEX study strives to use MammaPrint, BluePrint, and newly developed immune signature, ImPrint, along with full transcriptome data to improve precision medicine in early-stage breast cancer. Citation Format: JJ Alberty-Oller, Lee Riley, Laila Samiian, Sarah Thayer, Olexiy Aseyev, Karen Tedesco, Victoria Poillucci, William Audeh, Danijela Jelovac, Joyce O'Shaughnessy. A prospective, international, observational, real-world evidence database, and collaborative platform for Investigator-Initiated Studies in Early-Stage Breast Cancer tested with MammaPrint and BluePrint– the FLEX Study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-02-02.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.045
metaresearch head score (Gemma)0.140
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.239

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.140
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0050.010
Science and technology studies0.0010.001
Scholarly communication0.0070.004
Open science0.0040.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0510.010

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.

Opus teacher head0.308
GPT teacher head0.489
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreMethods

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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