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Record W2275130645 · doi:10.1016/j.bbmt.2015.11.360

Increasing Use of Allogeneic Hematopoietic Cell Transplantation (HCT) in Patients Age 70 Years and Older: A CIBMTR Study of Trends and Outcomes

2016· article· en· W2275130645 on OpenAlexaff
Lori Muffly, Marcelo C. Pasquini, Michael J. Martens, Ruta Brazauskas, Xiaochun Zhu, Kehinde Adekola, Mahmoud Aljurf, Andrew Artz, Ashish Bajel, Karen K. Ballen, Minoo Battiwalla, Amer Beitinjaneh, Jean‐Yves Cahn, Matthew Carabasi, Yi‐Bin Chen, Saurabh Chhabra, Stefan O. Ciurea, Edward A. Copelan, Anita D’Souza, John Edwards, César O. Freytes, Henry C. Fung, Robert Peter Gale, Sergio Giralt, Shahrukh K. Hashmi, Peiman Hematti, Gerhard Hildebrandt, Vincent T. Ho, Ann A. Jakubowski, Hillard M. Lazarus, Philip L. McCarthy, Rebecca L. Olin, Richard F. Olsson, Andrew R. Rezvani, David A. Rizzieri, Matthew D. Seftel, Sachiko Seo, Mohamed L. Sorror, Jeff Szer, William A. Wood

Bibliographic record

VenueBiology of Blood and Marrow Transplantation · 2016
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineHematopoietic cellTransplantationInternal medicinePopulationRelative survivalSiblingOncologyHematopoietic stem cell transplantationStem cellHaematopoiesisEpidemiologyCancer registry

Abstract

fetched live from OpenAlex

Limited data exist regarding the use and outcomes of allogeneic HCT in adults 70 years and older. We aimed to describe trends and outcomes of allogeneic HCT in this population utilizing data reported to the CIBMTR from 2000-2013 from US centers. 1106 allogeneic HCT recipients ≥70 years (89% 70-74, 10% 75-79, <1% ≥80) from 103 centers are included. The most common disease indications were AML (54%), MDS/MPN (22%), and NHL (10%). 82% had KPS ≥80% and 46% had HCT-CI ≥3 (HCT-CI capture began in 2008). Unrelated donor (URD), HLA-identical sibling (MRD), HLA-mismatched relative, and umbilical cord blood (UCB) were utilized in 61%, 26%, 7%, and 6%, respectively; the majority (87%) received reduced intensity conditioning. The absolute number and proportion of allografts for pts ≥70 years rose markedly over the past decade, from 62 (0.4% of all allogeneic HCT) in 2000-2003 to 471 (3.33% of all allogeneic HCT) in 2012-2013. HCT growth was seen mainly for AML and MDS (figure 1). Increase in HCT for MDS occurred after 2010 as transplants started to be covered by CMS. Table 1 and figure 1 display unadjusted 2-year outcomes. Among those transplanted in the recent era of 2008-2013, higher-risk disease (HR=1.25, P= 0.04 for advanced leukemia/MDS relative to early stage) and UCB relative to MRD (HR=2.1, P<0.01) were associated with higher mortality whereas HCT-CI, performance score and other donor sources were not associated with survival. Use of HCT in patients ≥70 years has increased and overall outcomes have improved significantly over the last decade. Research into methods to reduce TRM may further improve outcomes and encourage greater utilization in this age group.Table 1Univariate 2 year outcomes and 95% CI for each time period for patients 70 and older after allogeneic transplant2000-20032004-20072008-20112012-2013P across time periodTRM34 (23-47)35 (27-43)32 (28-37)34 (28-39)0.92Relapse/progr44 (32-57)43 (34-51)35 (30-40)36 (31-41)0.26PFS21 (12-33)22 (16-30)33 (29-37)30 (25-36)0.04OS28 (17-39)26 (19-34)40 (35-44)36 (30-42)0.008TRM, transplant-related mortality; PFS, progression-free survival; OS, overall survival. Open table in a new tab Figure 2OS for allogeneic HCT recipients 70 years and older transplanted between 2000-2007 and 2008-2013.View Large Image Figure ViewerDownload Hi-res image Download (PPT) TRM, transplant-related mortality; PFS, progression-free survival; OS, overall survival.

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 score0.170
Threshold uncertainty score0.317

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 head0.013
GPT teacher head0.259
Teacher spread0.245 · 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

Citations20
Published2016
Admission routes1
Has abstractyes

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