MétaCan
Menu
Back to cohort
Record W2121399230 · doi:10.3324/haematol.11644

Thalidomide in induction treatment increases the very good partial response rate before and after high-dose therapy in previously untreated multiple myeloma

2007· article· en· W2121399230 on OpenAlexaff
H M Lokhorst, Ingo GH Schmidt-Wolf, Pieter Sonneveld, Bronno van der Holt, Hans Martin, Renée M. Y. Barge, Uta Bertsch, Jana Schlenzka, Gerard M.J. Bos, Sandra Croockewit, Sonja Zweegman, Iris Breitkreutz, Peter Joosten, Christof Scheid, Marinus van Marwijk-Kooy, H.-J. Salwender, Marinus H. J. van Oers, Ron Schaafsma, Ralph Naumann, Harm Sinnige, Igor Wolfgang Blau, Michel Delforge, Okke de Weerdt, P. Wijermans, S. Wittebol, U. Duersen, Edo Vellenga, Hartmut Goldschmidt

Bibliographic record

VenueHaematologica · 2007
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicineThalidomideDexamethasoneInternal medicineVincristineComplete responseAdverse effectMelphalanMultiple myelomaRandomized controlled trialGastroenterologyChemotherapyInduction chemotherapyUrologyCyclophosphamide

Abstract

fetched live from OpenAlex

In the prospective phase 3 HOVON-50/GMMG-HD3 trial, patients randomized to TAD (thalidomide, doxorubicin, dexamethasone) had a significantly higher response rate (at least PR) after induction compared with patients randomized to VAD (vincristine, adriamycin, dexamethasone, 72% vs. 54%, p<0.001). Complete remission (CR) and very good partial remission (VGPR) were also higher after TAD. After High Dose melphalan 200mg/m(2) response was comparable in both arms, 76% and 79% respectively. However, CR plus VGPR were significantly higher in the patients randomized to TAD (49% vs. 32%, p<0.001). CTC grade 3-4 adverse events were similar in both arms.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.029
GPT teacher head0.303
Teacher spread0.274 · 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 designNon-randomized trial
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

Citations142
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueHaematologicaSame topicMultiple Myeloma Research and TreatmentsFrench-language works237,207