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Record W4405048799 · doi:10.1182/blood-2024-206125

Validation and Implementation of Flow Cytometry Based Minimal Residual Disease (MRD) Assay for Chronic Lymphocytic Leukemia (CLL) Clinical Studies

2024· article· en· W4405048799 on OpenAlexaff
Christèle Gonneau, Marc Brugarolas, Lotje Van Haecht, Marc Lenjou, Caitlyn Fritsche, Yevgeniy Linnik, Lucas Rifkin, Ting Yu, Simon Rule, Veerendra Munugalavadla, Yoav Peretz

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsAstraZeneca (Canada)
Fundersnot available
KeywordsChronic lymphocytic leukemiaMinimal residual diseaseFlow cytometryLeukemiaMedicineImmunologyCancer researchOncology

Abstract

fetched live from OpenAlex

Background: With the advances made in novel anti-cancer therapies, Chronic Lymphocytic Leukemia (CLL) patient remission rates have significantly improved over the years. Minimal or measurable residual disease (MRD) is emerging as an independent predictor of progression-free survival (PFS) and overall survival (OS) in several heme indications and has been proposed as a potential surrogate endpoint for long term CLL survival in clinical trials. While next generation sequencing (NGS) methods are emerging for establishing MRD measurements in CLL, flow cytometry remains as an option of choice for measuring MRD in CLL. Methods: In order to assess MRD in CLL patients using flow cytometry, Labcorp Biopharma Services validated a CLL MRD assay that was initially developed by the European Research Initiative on CLL (ERIC) (Rawstron et al, 2013). Assay validation was performed in several Labcorp central laboratories across the globe using bone marrow and whole blood samples from both healthy donors and CLL patients, characterizing precision performance, sample stability and B CLL cells assay sensitivity. This validated assay has been utilized in several clinical studies including ELEVATE- TN (NCT02475681; Sharman JP, 2020) as part of exploratory endpoints with 10-4 cut-off. Results: Validation of this assay demonstrated good performance for critical reportable measurement CLL B cells with a lower limit of quantitation (LLOQ) of 0.009%/of total nucleated cells (TNC) and 0.008% of TNC for whole blood and bone marrow respectively and when target total events is set at 2x106 cells in total. Using a similar setup, we also demonstrated an ambient specimen stability for CLL B cells of 72 hours for whole blood samples and 48 hours for bone marrow samples. Precision performance for repeatability and reproducibility for both matrices was below ≤10% CV, confirming high readout precision and suitability of the assay for implementation in multi-centric clinical trials. As part of the exploratory endpoints from the ELEVATE- TN study, peripheral blood samples were collected from patients in complete remission (CR) or complete remission with incomplete count recovery (CRi). Patients with CR or CRi in the acalabrutinib-obinutuzumab arm achieved higher rates of undetectable MRD (uMRD) in peripheral blood samples vs patients with CR or CRi receiving acalabrutinib monotherapy and chlorambucil-obinutuzumab (40.9% vs 8.8% and 8.3%, respectively). Conclusions: Validated six- color flow cytometry CLL- MRD assay is a robust test that has been successfully implemented (exploratory) and proven useful for global clinical studies, as demonstrated by clinical results obtained in ELEVATE-TN study. This flow cytometry assay is being implemented in several global clinical studies as an endpoint (secondary) including in an ongoing phase 3 study AMPLIFY (ACE-CL-311; NCT03836261).

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)0.040
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.209

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.057
GPT teacher head0.428
Teacher spread0.371 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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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