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Record W7116365831 · doi:10.1016/j.jtct.2025.12.993

Quality of Life and Comorbidities of Long-Term Survivors of Allogeneic Hematopoietic Cell Transplant Versus Their Siblings

2025· article· en· W7116365831 on OpenAlexafffund
Dylan E. O’Sullivan, Nikki Blosser, Nicole Crisp, Baljit Randhawa, Sanjeev Bista, Grace Beda, Mona Shafey, Kevin A. Hay, Robert Puckrin, Andrew Daly, Jan Storek, Kareem Jamani

Bibliographic record

VenueTransplantation and Cellular Therapy · 2025
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsNorthern Alberta Institute of TechnologyAlberta Cancer FoundationUniversity of Calgary
FundersArnie Charbonneau Cancer Institute, University of Calgary
KeywordsComorbidityQuality of life (healthcare)Survivorship curveIncidence (geometry)SiblingTransplantationHematopoietic cellMental health

Abstract

fetched live from OpenAlex

Survivors of allogeneic hematopoietic cell transplantation (allo-HCT) are known to be at risk of late toxicities. The spectrum of late toxicities may be impacted by changing allo-HCT practices: In contemporary allo-HCT practice, conditioning with high-dose total body irradiation is infrequent, the incidence of chronic GVHD is declining, and older adults receive allo-HCT more frequently. Few studies have examined the burden of comorbidities and the quality of life (QoL) of recent long-term survivors of allo-HCT, and even fewer have included a biological sibling control group for comparison. We set out to quantify and compare the burden of comorbidities and the QoL of a largely contemporary group of survivors of allo-HCT versus their biological siblings. We further aimed to understand the association of transplant-related variables, demographic variables, and comorbidities, with QoL amongst recipients. We conducted a cross-sectional study comparing QoL and comorbidity burden between allo-HCT recipients and their biological siblings. In addition, we built multivariable models to understand predictors of physical health (PH) and mental health (MH)-related QoL amongst recipients. Recipients without active chronic GVHD or relapse were enrolled at 1 of 2 survivorship clinics alongside their siblings. We used PROMIS Global Health to assess QoL and the post-transplant multimorbidity index to evaluate comorbidities. In total, 391 recipients were enrolled. Of these, 106 recipients had a total of 154 siblings enrolled for comparison. The 106 recipients experienced significantly more comorbidities versus their siblings: 3 or more comorbidities were observed in 51.9% of recipients versus 33.1% of siblings (P = .002), while at least 1 severe comorbidity was observed in 24.5% versus 13.0%, respectively (P = .02). In spite of this, PH and MH-related QoL of recipients was similar to that of siblings: PH QoL median T-score 49.9 (IQR 45.8 to 57.4) versus 50.7 (IQR 46.3 to 54.4), respectively (P = .77), and MH QoL median T-score 50.9 (IQR 44.8 to 54.6) versus 51.6 (IQR 45.3 to 55.1), respectively (P = .58). Social functioning was rated as very good or excellent by 65.1% of recipients versus 68.6% of siblings (P = .33). Amongst the entire cohort of 391 recipients, the number of comorbidities was strongly associated with MH and PH-related QoL as well as social functioning, whereas transplant-related variables such as prior cGVHD, receipt of low dose TBI, graft and donor type, were not. Survivors of allo-HCT continue to experience excess comorbidities versus their biological siblings. Despite this, survivors enjoy QoL and social functioning that are comparable to their siblings and general population norms. Amongst survivors, the number of comorbidities is strongly associated with QoL and social functioning while transplant-related variables are not.

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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.001
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 head0.040
GPT teacher head0.294
Teacher spread0.254 · 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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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