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Record W4366607243 · doi:10.1016/j.jtct.2023.04.011

Transplantation Referral Patterns for Patients with Newly Diagnosed Higher-Risk Myelodysplastic Syndromes and Acute Myeloid Leukemia at Academic and Community Sites in the Connect® Myeloid Disease Registry: Potential Barriers to Care

2023· article· en· W4366607243 on OpenAlexfundno aff
Benjamin Tomlinson, Marcos de Lima, Christopher R. Cogle, Michael A. Thompson, David L. Grinblatt, Daniel A. Pollyea, Rami S. Komrokji, Gail J. Roboz, Michael R. Savona, Mikkael A. Sekeres, Mehrdad Abedi, Guillermo Garcia‐Manero, Sandra Kurtin, Jaroslaw P. Maciejewski, Jay Patel, Dennis A. Revicki, Tracy I. George, E. Dawn Flick, Pavel Kiselev, Chrystal U. Louis, Irene S. DeGutis, Melissa Nifenecker, Harry P. Erba, David P. Steensma, Bart L. Scott

Bibliographic record

VenueTransplantation and Cellular Therapy · 2023
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteSierra OncologyIncyteAstex PharmaceuticalsAstellas PharmaTG TherapeuticsKaryopharm TherapeuticsAlexion PharmaceuticalsSunesisTeva Pharmaceutical IndustriesBristol-Myers SquibbAstraZenecaAgios Pharmaceuticals
KeywordsMedicineMyeloid leukemiaTransplantationMyelodysplastic syndromesInternal medicineDisease registryComorbidityReferralHematopoietic stem cell transplantationDiseaseCancer registryMyeloidCancerFamily medicineBone marrow

Abstract

fetched live from OpenAlex

Hematopoietic stem cell transplantation (HCT) is indicated for patients with higher-risk (HR) myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML). Age, performance status, patient frailty, comorbidities, and nonclinical factors (eg, cost, distance to site) are all recognized as important clinical factors that can influence HCT referral patterns and patient outcomes; however, the proportion of eligible patients referred for HCT in routine clinical practice is largely unknown. This study aimed to assess patterns of consideration for HCT among patients with HR-MDS and AML enrolled in the Connect® Myeloid Disease Registry at community/government (CO/GOV)- or academic (AC)-based sites, as well as to identify factors associated with rates of transplantation referral. We assessed patterns of consideration for and completion of HCT in patients with HR-MDS and AML enrolled between December 12, 2013, and March 6, 2020, in the Connect Myeloid Disease Registry at 164 CO/GOV and AC sites. Registry sites recorded whether patients were considered for transplantation at baseline and at each follow-up visit. The following answers were possible: "considered potentially eligible," "not considered potentially eligible," or "not assessed." Sites also recorded whether patients subsequently underwent HCT at each follow-up visit. Rates of consideration for HCT between CO/GOV and AC sites were compared using multivariable logistic regression analysis with covariates for age and comorbidity. Among the 778 patients with HR-MDS or AML enrolled in the Connect Myeloid Disease Registry, patients at CO/GOV sites were less likely to be considered potentially eligible for HCT than patients at AC sites (27.9% versus 43.9%; P < .0001). Multivariable logistic regression analysis with factors for age (<65 versus ≥65 years) and ACE-27 comorbidity grade (<2 versus ≥2) showed that patients at CO/GOV sites were significantly less likely than those at AC sites to be considered potentially eligible for HCT (odds ratio, 1.6, 95% confidence interval, 1.1 to 2.4; P = .0155). Among patients considered eligible for HCT, 45.1% (65 of 144) of those at CO/GOV sites and 35.7% (41 of 115) of those at AC sites underwent transplantation (P = .12). Approximately one-half of all patients at CO/GOV (50.1%) and AC (45.4%) sites were not considered potentially eligible for HCT; the most common reasons were age at CO/GOV sites (71.5%) and comorbidities at AC sites (52.1%). Across all sites, 17.4% of patients were reported as not assessed (and thus not considered) for HCT by their treating physician (20.7% at CO/GOV sites and 10.7% at AC sites; P = .0005). These findings suggest that many patients with HR-MDS and AML who may be candidates for HCT are not receiving assessment or consideration for transplantation in clinical practice. In addition, treatment at CO/GOV sites and age remain significant barriers to ensuring that all potentially eligible patients are assessed for HCT.

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 score0.133
Threshold uncertainty score0.915

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.275
Teacher spread0.255 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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