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Record W2003656303 · doi:10.1016/j.bbmt.2013.01.004

Salvage Second Hematopoietic Cell Transplantation in Myeloma

2013· article· en· W2003656303 on OpenAlexaff
Laura C. Michaelis, Ayman Saad, Xiaobo Zhong, Jennifer Le‐Rademacher, César O. Freytes, David I. Marks, Hillard M. Lazarus, Jennifer M. Bird, Leona Holmberg, Rammurti T. Kamble, Shaji Kumar, Michael Lill, Kenneth R. Meehan, Wael Saber, Jeffrey Schriber, Jason Tay, Dan T. Vogl, Baldeep Wirk, Bipin N. Savani, Robert Peter Gale, David H. Vesole, Gary J. Schiller, Muneer H. Abidi, Kenneth C. Anderson, Taiga Nishihori, Matt Kalaycio, Julie M. Vose, Jan S. Moreb, William R. Drobyski, Reinhold Munker, Vivek Roy, Armin Ghobadi, H. Kent Holland, Rajneesh Nath, L. Bik To, Ângelo Maiolino, Adetola A. Kassim, Sergio Giralt, Heather Landau, Harry C. Schouten, Richard T. Maziarz, Joseph Mıkhael, Tamila L. Kindwall‐Keller, Patrick J. Stiff, John Gibson, Sagar Lonial, Amrita Krishnan, Angela Dispenzieri, Parameswaran Hari

Bibliographic record

VenueBiology of Blood and Marrow Transplantation · 2013
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of Ottawa
FundersNational Institute of Allergy and Infectious DiseasesNational Cancer InstituteOffice of Naval ResearchNational Heart, Lung, and Blood InstituteTakeda OncologyTerumo BCTHealth Resources and Services AdministrationNational Institutes of HealthSwedish Orphan BiovitrumOtsuka AmericaKiadis PharmaTherakosSigma-Tau PharmaceuticalsMedical College of WisconsinTarix PharmaceuticalsStemCyteBlue Cross and Blue Shield AssociationU.S. NavyOsiris TherapeuticsCelgeneHistoGeneticsTeva Pharmaceutical IndustriesWellPointMerckGlaxoSmithKlineLeukemia and Lymphoma SocietyBe The Match FoundationAriad PharmaceuticalsOtsuka America PharmaceuticalAmgenSanofiU.S. Department of DefenseGenentechCellGenixSeattle GeneticsU.S. Department of Health and Human ServicesNational Marrow Donor Program
KeywordsMedicineMultiple myelomaTransplantationSurgerySalvage therapyProgression-free survivalHematopoietic stem cell transplantationProgressive diseaseHematopoietic cellRetrospective cohort studyInternal medicineOverall survivalHaematopoiesisChemotherapyStem cell

Abstract

fetched live from OpenAlex

Autologous hematopoietic cell transplantation (AHCT) as initial therapy of patients with multiple myeloma (MM) improves survival. However, data to support this approach for relapsed/progressive disease after initial AHCT (AHCT1) are limited. Using Center for International Blood and Marrow Transplant Research data, we report the outcomes of 187 patients who underwent a second AHCT (AHCT2) for the treatment of relapsed/progressive MM. Planned tandem AHCT was excluded. Median age at AHCT2 was 59 years (range, 28 to 72), and median patient follow-up was 47 months (range, 3 to 97). Nonrelapse mortality after AHCT2 was 2% at 1 year and 4% at 3 years. Median interval from AHCT1 to relapse/progression was 18 months, and median interval between transplantations was 32 months. After AHCT2, the incidence of relapse/progression at 1 and 3 years was 51% and 82%, respectively. At 3 years after AHCT2, progression-free survival was 13%, and overall survival was 46%. In multivariate analyses, those relapsing ≥36 months after AHCT1 had superior progression-free (P = .045) and overall survival (P = .019). Patients who underwent AHCT2 after 2004 had superior survival (P = .026). AHCT2 is safe and feasible for disease progression after AHCT1. In this retrospective study, individuals relapsing ≥36 months from AHCT1 derived greater benefit from AHCT2 compared with those with a shorter disease-free interval. Storage of an adequate graft before AHCT1 will ensure that the option of a second autologous transplantation is retained for patients with relapsed/progressive MM.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.253
Teacher spread0.242 · 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

Citations110
Published2013
Admission routes1
Has abstractyes

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