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International Validation of a Dithiothreitol (DTT)-Based Method to Resolve the Daratumumab Interference with Blood Compatibility Testing

2015· article· en· W2550682660 on OpenAlexaff
Claudia I. Chapuy, Maria Aguad, Rachel T. Nicholson, James P. AuBuchon, Claudia S. Cohn, Meghan Delaney, Joan Cid, Sunny Dzik, Mark Fung, Andreas Greinacher, Ai Leen Ang, Dana V. Devine, Nancy M. Dunbar, Henk Garritsen, Lawrence T. Goodnough, R. Herron, Tor Hervig, C. Michael Knudson, José Mauro Kutner, Frank Nizzi, Suchitra Pandey, Benjamin Rioux‐Massé, Kathleen Selleng, Joseph D. Sweeney, Minoko Takanashi, Aaron A.R. Tobian, Lorna Wall, Silvano Wendel, David Westerman, Meredith Unger, Parul Doshi, Michael Murphy, Larry J. Dumont, Richard M. Kaufman, The BEST Collaborative

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsCanadian Blood ServicesCentre Hospitalier de l’Université de MontréalUniversity of British Columbia
Fundersnot available
KeywordsDaratumumabDithiothreitolMedicineCD38AntibodyImmunologyChemistryMonoclonal antibodyBiologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract Introduction Daratumumab (DARA), an IgG1k human monoclonal antibody (Ab) against CD38, is a promising novel therapy for multiple myeloma. However, direct binding of DARA to endogenous CD38 on reagent red blood cells (RBCs) interferes with routine blood bank serologic testing. We recently showed that treating reagent RBCs with DTT eliminates the DARA interference by denaturing cell surface CD38, allowing the safe transfusion of patients on DARA.1 This multicenter international study was aimed at validating the DTT method for use by blood banks worldwide. Methods Participating blood banks received two plasma sample unknowns. Sample 1 was spiked with DARA alone (5 mcg/mL). Sample 2 was spiked with DARA plus a clinically significant RBC Ab (anti-D (Rh immune globulin) or monoclonal anti-Fya or anti-s). Sites were instructed to first perform an Ab screen using their usual method (tube, gel, or solid phase), then to repeat the Ab screen using DTT-treated RBCs (gel or tube). If the Ab screen remained positive with DTT-treated RBCs (Sample 2), sites were to identify the unknown Ab using a DTT-treated RBC panel (gel or tube.) The primary outcome measure was the proportion of sites able to successfully identify the unknown Ab in the presence of DARA. Qualitative data were collected by online survey. Results Paired plasma sample unknowns were shipped to 25 study sites in North America, South America, Europe, Asia, and Australia/New Zealand. Data were received from 23 sites to date (Table). For the initial Ab screen, 10 sites used tube testing, 7 sites used gel, and 6 sites used solid phase. All sites observed DARA interference with the Ab screen (false positive agglutination reactions). All sites reported no DARA interference using DTT-treated RBCs. For Ab identification (Sample 2), 13 sites used tube testing and 10 sites used gel. 23/23 sites (100%) were able to correctly identify the unknown Ab using the DTT method. The Abs identified were: anti-Fya (9/9), anti-s (8/8), and anti-D (6/6). Feedback on the DTT method was mainly positive, with 86% of sites that responded to the survey indicating that they planned to use the DTT method to manage clinical samples from DARA-treated patients. Conclusion DARA consistently interferes with all three Ab screening methods currently used by blood banks (tube, gel, and solid phase.) Using DTT-treated RBCs, 23/23 (100%) of blood bank laboratories from around the world were able to identify a clinically significant Ab initially masked by the presence of DARA. The DTT method is robust, reproducible, and can be implemented by blood banks globally to help provide safe blood products to patients on DARA. As DTT denatures Kell antigens, K- RBC units should be provided when using the DTT method. 1. Chapuy CI, Nicholson RT, Aguad MD, et al. Resolving the daratumumab interference with blood compatibility testing. Transfusion. 2015;55(6pt2):1545-1554. Disclosures Unger: Janssen: Employment. Doshi:Janssen: Employment. Kaufman:Janssen: Consultancy, Research Funding.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.090
GPT teacher head0.367
Teacher spread0.277 · 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 teacher head, 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

Citations3
Published2015
Admission routes1
Has abstractyes

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