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Record W3080882593 · doi:10.1080/10428194.2020.1791846

Primary prophylaxis with G-CSF may improve outcomes in patients with newly diagnosed stage III/IV Hodgkin lymphoma treated with brentuximab vedotin plus chemotherapy

2020· article· en· W3080882593 on OpenAlexaff
David J. Straus, Graham P. Collins, Jan Walewski, Pier Luigi Zinzani, Andrew Grigg, Anna Sureda, Árpád Illés, Tae Min Kim, Sergey Alekseev, Lena Specht, Valéria Buccheri, Anas Younes, Joseph M. Connors, Andres Forero‐Torres, Keenan Fenton, Ashish Gautam, Indra Purevjal, Rachael Liu, Andrea Gallamini

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2020
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsSpinal Cord Injury BC
Fundersnot available
KeywordsMedicineNeutropeniaBrentuximab vedotinInternal medicineFebrile neutropeniaDacarbazineVinblastineAdverse effectLymphomaChemotherapyGastroenterologySurgeryOncologyHodgkin lymphoma

Abstract

fetched live from OpenAlex

= 579) on safety and efficacy of brentuximab vedotin plus doxorubicin, vinblastine, and dacarbazine (A + AVD) in the ECHELON-1 study of previously untreated stage III/IV classical Hodgkin lymphoma. G-PP was associated with lower incidence of ≥ grade 3 neutropenia (29% versus 70%) and febrile neutropenia (11% versus 21%). Fewer dose delays (35% versus 49%), reductions (20% versus 26%), and hospitalizations (29% versus 38%) were observed. Seven neutropenia-associated deaths occurred in the A + AVD arm; none received G-PP. A + AVD with G-PP was associated with decreased risk of a modified progression-free survival event by 26% compared with A + AVD alone (95% CI: 0.40-1.37). G-PP reduced the rate and severity of adverse events, including febrile neutropenia, reduced treatment delays, dose reductions, and discontinuations, and may thus improve efficacy outcomes. These data support G-PP for all patients treated with A + AVD.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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
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

Citations19
Published2020
Admission routes1
Has abstractyes

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