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Record W2951482915 · doi:10.1002/hon.99_2630

EXPLORATORY BIOMARKER ANALYSIS IN THE PH 3 ECHELON‐1 STUDY: WORSE OUTCOME WITH ABVD IN PATIENTS WITH ELEVATED BASELINE LEVELS OF SCD30 AND TARC

2019· article· en· W2951482915 on OpenAlexaff
John Radford, Joseph M. Connors, Anas Younes, Andrea Gallamini, Stephen M. Ansell, W.S. Kim, June‐Won Cheong, Ian W. Flinn, Nagesh Kalakonda, Mark Kaminski, Ruth Pettengell, Matthew Onsum, Neil C. Josephson, Shingo Kuroda, R. Liu, Harry Miao, Ashish Gautam, William L. Trepicchio, Anna Sureda

Bibliographic record

VenueHematological Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsSpinal Cord Injury BC
Fundersnot available
KeywordsMedicineBrentuximab vedotinInternal medicineDacarbazineOncologyABVDBiomarkerPost-hoc analysisProgression-free survivalGastroenterologyLymphomaOverall survivalCD30VincristineChemotherapyCyclophosphamide

Abstract

fetched live from OpenAlex

Introduction: Soluble (s)CD30 and thymus and activation-regulated chemokine (TARC) are established prognostic biomarkers in Hodgkin lymphoma (HL): higher baseline serum levels are associated with poorer survival outcomes. Elevated sCD30 and TARC levels are also associated with established poor prognostic factors in HL, e.g. Stage IV disease, higher International Prognostic Score (IPS), and extranodal involvement (ENI). The phase 3 ECHELON-1 study compared frontline brentuximab vedotin (a CD30-directed antibody-drug conjugate) plus doxorubicin, vinblastine, and dacarbazine (A+AVD) vs ABVD in patients (pts) with advanced classical HL (cHL). A+AVD demonstrated superior modified progression-free survival (modified PFS) vs ABVD (HR = 0.77 [95% CI 0.60–0.98]; p = 0.035; 2-yr mPFS 82.1% vs 77.2%. An exploratory ad-hoc biomarker analysis evaluated mPFS according to baseline sCD30 and TARC levels. Methods: Serum samples were collected from 1334 pts with Stage III (36%) or IV (64%) cHL during the screening period and analyzed using validated assays for sCD30 (Covance Labs) and TARC (ICON Labs). mPFS (defined as time to progression, death, or evidence of noncomplete response followed by subsequent anticancer therapy) per independent review facility (IRF) was analyzed according to baseline sCD30 and TARC levels; the association of biomarker levels with treatment outcomes along with other potential predictive factors was explored in a multivariate Cox model. Results: For the ad-hoc sCD30 analysis, pts were dichotomized around the median sCD30 baseline level (207.9 ng/mL). Pts in the A+AVD arm performed similarly regardless of baseline sCD30 level, with a 2-yr mPFS of 80.7% (sCD30 >median) and 82.7% (sCD30 ≤median). However, a decrease in effectiveness of ABVD was observed in pts with sCD30 >median with a 2-yr mPFS of 68.9% [sCD30 >median] and 85.7% [sCD30 ≤median]). A mPFS benefit in favor of A+AVD vs ABVD was observed in pts with sCD30 >median (HR (95% CI) = 0.600 (0.428-0.841)) . Multivariate Cox analysis with the interaction between treatment group and sCD30 level showed an increased risk of experiencing an mPFS event with ABVD and sCD30 >median (interaction p = 0.025) when adjusted by other prognostic factors (Ann Arbor stage, IPS and ENI). Similar trends were observed with the exploratory ad-hoc TARC analysis. No new safety signals were reported in subgroups with elevated sCD30 or TARC levels. Conclusions: Preliminary adhoc analysis indicates that ABVD treated patients do not perform as well with elevated baseline sCD30 and TARC levels. A+AVD treated patients perform well regardless of levels of these poor prognostic markers. Prospective studies need to be conducted in order to further validate these findings. If validated, these biomarkers may help identify patient populations that could benefit from more effectively targeted therapy. Keywords: ABVD; brentuximab vedotin; classical Hodgkin lymphoma (cHL). Disclosures: Radford, J: Consultant Advisory Role: Millennium Pharmaceuticals Inc, ADC Therapeutics, BMS, Novartis; Stock Ownership: GSK, AstraZeneca (spouse); Honoraria: Millennium Pharmaceuticals Inc, Seattle Genetics, Novartis, BMS; Research Funding: Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. Connors, J: Consultant Advisory Role: Seattle Genetics, Millennium Pharmaceuticals Inc; Honoraria: Seattle Genetics, Millennium Pharmaceuticals Inc; Research Funding: Seattle Genetics. Younes, A: Consultant Advisory Role: BMS, Incyte, Janssen, Genentech, Merck; Honoraria: Genentech, Merck, Millennium Pharmaceuticals Inc, Incyte, BMS, AbbVie; Research Funding: Novartis, J&J, Curis, Roche, BMS. Ansell, S: Research Funding: BMS, Seattle Genetics, Trillium, Affimed, Pfizer, LAM Therapeutics, Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. Kim, W: Research Funding: Roche, Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited, J&J, Mundupharma, Kyowa-kirin, Celltrion, DongaN. Flinn, I: Consultant Advisory Role: Abbvie, Seattle Genetics, TG Therapeutics, Verastem; Research Funding: Abbvie, Acerta Pharma, Agios, ArQule, AstraZeneca, BeiGene, Calithera Biosciences, Celgene, Constellation Pharmaceuticals, Curis, FORMA Therapeutics, Forty Seven, Genentech, Gilead Sciences, Incyte, Infinity Pharmaceuticals, Janssen, Juno Therapeutics, Karyopharm Therapeutics, Kite Pharma, Merck, MorphoSys AG, Novartis, Pfizer, Pharmacyclics, Portola Pharmaceuticals, Roche, Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited, Teva, TG Therapeutics, Trillium Therapeutics, Unum Therapeutics, Verastem. Pettengell, R: Consultant Advisory Role: CTI Life Sciences Ltd, Immune Design, Pfizer, Roche Ltd, Servier, Millennium Pharmaceuticals Inc, TEVA; Honoraria: CTI Life Sciences Ltd, Immune Design, Pfizer, Roche Ltd, Servier, Millennium Pharmaceuticals Inc, TEVA. Onsum, M: Employment Leadership Position: Seattle Genetics; Stock Ownership: Seattle Genetics. Josephson, N: Employment Leadership Position: Seattle Genetics, Inc.; Stock Ownership: Seattle Genetics, Inc.. Kuroda, S: Employment Leadership Position: Takeda Pharmaceutical Company Limited. Liu, R: Employment Leadership Position: Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. Miao, H: Employment Leadership Position: Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. Gautam, A: Employment Leadership Position: Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited; Stock Ownership: Takeda Pharmaceutical Company Limited. Trepicchio, W: Employment Leadership Position: Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. Sureda, A: Consultant Advisory Role: Millennium Pharmaceuticals Inc, BMS, Gilead, Novartis; Honoraria: Millennium Pharmaceuticals Inc, BMS, MSD, Gilead, Novartis, Jannssen, Celgene, Sanofi, Roche.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.046
GPT teacher head0.320
Teacher spread0.275 · 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 designObservational
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".

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Citations1
Published2019
Admission routes1
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