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Record W2005090809 · doi:10.1016/j.bbmt.2014.07.013

Older Patients with Myeloma Derive Similar Benefit from Autologous Transplantation

2014· article· en· W2005090809 on OpenAlexaff
Manish Sharma, Mei‐Jie Zhang, Xiaobo Zhong, Muneer H. Abidi, Görgün Akpek, Ulrike Bacher, Natalie S. Callander, Angela Dispenzieri, César O. Freytes, Henry C. Fung, Robert Peter Gale, Cristina Gasparetto, John Gibson, Leona Holmberg, Tamila L. Kindwall‐Keller, Thomas R. Klumpp, Amrita Krishnan, Heather Landau, Hillard M. Lazarus, Sagar Lonial, Ângelo Maiolino, David I. Marks, Paulette Mehta, Joseph Mıkhael, Taiga Nishihori, Richard F. Olsson, Muthalagu Ramanathan, Vivek Roy, Bipin N. Savani, Harry C. Schouten, Emma C. Scott, Jason Tay, Luen Bik To, David H. Vesole, Dan T. Vogl, Parameswaran Hari

Bibliographic record

VenueBiology of Blood and Marrow Transplantation · 2014
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of Ottawa
FundersNational Cancer InstituteOffice of Naval ResearchNational Heart, Lung, and Blood InstituteTerumo BCTHealth Resources and Services AdministrationMedacSwedish Orphan BiovitrumIncyteGenentechSeattle GeneticsUniversity of UtahBlue Cross and Blue Shield AssociationKiadis PharmaSigma-Tau PharmaceuticalsMedical College of WisconsinTarix PharmaceuticalsStemCyteTakeda OncologyUniversity of MinnesotaNational Marrow Donor ProgramSt. Baldrick's FoundationHealth ResearchU.S. NavyOsiris TherapeuticsMerckGlaxoSmithKlineTexas InstrumentsLeukemia and Lymphoma SocietyBe The Match FoundationAllos TherapeuticsActinium PharmaceuticalsAriad PharmaceuticalsOtsuka America PharmaceuticalAmgenWellPointNational Institute of Allergy and Infectious DiseasesRoswell Park Cancer InstituteOnyx PharmaceuticalsU.S. Department of DefenseSanofi
KeywordsMedicineMultiple myelomaCohortHematopoietic cellInternal medicineTransplantationHematopoietic stem cell transplantationMultivariate analysisOncologyDemographyGerontologyHaematopoiesisStem cell

Abstract

fetched live from OpenAlex

Autologous hematopoietic cell transplantation (AHCT) for plasma cell myeloma is performed less often in people >70 years old than in people ≤70 years old. We analyzed 11,430 AHCT recipients for plasma cell myeloma prospectively reported to the Center for International Blood and Marrow Transplant Research between 2008 and 2011, representing the majority of US AHCT activity during this period. Survival (OS) was compared in 3 cohorts: ages 18 to 59 years (n = 5818), 60 to 69 years (n = 4666), and >70 years (n = 946). Median OS was not reached for any cohort. In multivariate analysis, increasing age was associated with mortality (P = .0006). Myeloma-specific mortality was similar among cohorts at 12%, indicating an age-related effect on nonmyeloma mortality. Analyses were performed in a representative subgroup comparing relapse rate, progression-free survival (PFS), and nonrelapse mortality (NRM). One-year NRM was 0% for age >70 years and 2% for other ages (P = not significant). The three-year relapse rate was 56% in age 18 to 59 years, 61% in age 60 to 69 years, and 63% age >70 (P = not significant). Three-year PFS was similar at 42% in age 18 to 59 years, 38% in age 60 to 69 years, and 33% in age >70 years (P = not significant). Postrelapse survival was significantly worse for the older cohort (P = .03). Older subjects selected for AHCT derived similar antimyeloma benefit without worse NRM, relapse rate, or PFS.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.460

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 head0.007
GPT teacher head0.233
Teacher spread0.226 · 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".

Quick stats

Citations84
Published2014
Admission routes1
Has abstractyes

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