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Burden of Relapse Following Allogeneic Hematopoietic Stem Cell Transplantation on Health Care Resource Utilization in the Management of Acute Leukemia and Myelodysplastic Syndrome

2016· article· en· W2979416306 on OpenAlexaff
Silvy Lachance, J. Bibeau, Jean Lachaîne

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsMedicineHematopoietic stem cell transplantationTransplantationMedical recordInternal medicineDiseaseMyelodysplastic syndromesHealth careOncologyIntensive care medicineBone marrow

Abstract

fetched live from OpenAlex

Abstract Background: Allogeneic Hematopoietic Stem Cell Transplantation (aHSCT) represents the only curative modality for unfavorable acute leukemia (AL) and myelodysplastic syndrome (MDS). Despite its curative intent, a significant number of recipients relapse. There is no standardized approach for the management of relapse following transplants and therapeutic options vary among centers, which represent a major challenge. Post transplant relapse is usually associated with a poor outcome while the impact of the treatment choice on health care resource utilization and survival is unknown. The objective of this study was to measure the health care resource utilization for the management of relapse following AHSCT and how the treatment choice impacted on survival. Methods: A retrospective medical chart review was conducted at H™pital Maisonneuve-Rosemont (HMR) after research and ethic committee approval. Patients were selected using the Hematopoietic Stem Cell Transplant (HSCT) program database. Eligible patients were diagnosed with AL or MDS and relapsed following a HLA identical aHSCT between January 1st 2011 and December 31st 2014. Patients' and disease characteristics as well as relapse-related health care resource utilization were collected from the date of transplant relapse diagnosis until death or last follow-up. Results: During the study period, of the 645 HSCT performed at HMR, 303 were allogeneic. A total of 36 patients who relapsed met the inclusion criteria and were included in the survival analysis. Healthcare resource utilization analysis was conducted on the 25 patients for whom complete records were available. Patients' characteristics at relapse, mean health care resource utilization per patient and survival by treatment choice are presented in tables 1, 2 and 3 respectively. The mean time from relapse to death was 10.6 months (SD=13.2). Relapse-related hospitalization duration represented on average 20.3% of patients' follow-up period (SD=26.0). For a mean follow-up time of 9.5 months (ranged from 6 days to 4.8 years), the mean number of relapse-related hospitalization was 2.2 per patient (SD=2.6). The mean length of stay was 40.4 days per patient (SD=54.5). The mean hematologist consultation number was 32.4 per patient (SD=37.3 Conclusion: Relapse following AHSCT is associated with a poor prognosis and survival and significant use of health care resources. Aggressive treatment rarely leads to a second transplant. Innovative approaches should be developed to address this unmet medical need. Healthcare resources devoted to the care of patients in relapse post AHSCT provide a comparative basis for the development of cellular therapy. Disclosures No relevant conflicts of interest to declare.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.017
GPT teacher head0.274
Teacher spread0.257 · 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 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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