MétaCan
Menu
Back to cohort
Record W2972329330 · doi:10.1016/j.bbmt.2019.09.007

Evaluation of the Impact of Autologous Hematopoietic Stem Cell Transplantation on the Quality of Life of Older Patients with Lymphoma

2019· article· en· W2972329330 on OpenAlexafffund
Christopher Lemieux, Imran Ahmad, Nadia M. Bambace, Léa Bernard, Sandra Cohen, Jean‐Sébastien Delisle, Isabelle Fleury, Thomas Kiss, Luigina Mollica, Denis-Claude Roy, Guy Sauvageau, Jean Roy, Silvy Lachance

Bibliographic record

VenueBiology of Blood and Marrow Transplantation · 2019
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
FundersUniversité de MontréalHoechst Marion Roussel
KeywordsMedicineLymphomaHematopoietic stem cell transplantationStem cellTransplantationHaematopoiesisOncologyQuality of life (healthcare)Hematopoietic cellInternal medicineNursingGenetics

Abstract

fetched live from OpenAlex

High-dose chemotherapy (HDT) followed by autologous hematopoietic stem cell transplantation (AHSCT) improves survival in patients with chemosensitive non-Hodgkin lymphoma (NHL). Determination of the Hematopoietic Cell Transplantation Comorbidity Index (HCT-CI) has contributed to improve patient selection while allowing for prediction of nonrelapse mortality. We previously demonstrated the efficacy and safety of AHSCT in a cohort of older patients with chemosensitive NHL. Quality of life following AHSCT still has not been widely evaluated. The goal of this study was to assess the long-term quality of life of elderly patients surviving AHSCT. This single-center, Research and Ethics Committee-approved study investigated QoL in survivors of AHSCT for the treatment of NHL in a cohort of older patients. Inclusion criteria were defined as patients age ≥60 years who underwent AHSCT for NHL between January 1, 2008, and January 1, 2015, at our center. Fifty-nine patients from the original cohort of 90 survived at a median of 50 months post-AHSCT. Forty-seven (79.7%) of those patients agreed to complete the QoL assessment questionnaires after the transplantation and are included in this report. All patients provided signed informed consent. We used the EQ-5D instrument to assess mobility, self-care, usual activities, pain/discomfort, and anxiety/depression and the Functional Assessment of Cancer Therapy-Bone Marrow Transplant (FACT-BMT) questionnaire to assess physical, social/family, emotional, and functional well-being and BMT-specific concerns. With both tools, a higher score indicates better QoL. Fifteen percent of patients were in relapse at the time of the QoL assessment. In the EQ-5D, few patients (9%) reported severe impairment, which requires significant negative effects in 4 or 5 domains. Lower Karnofsky Performance Status (KPS) score at the time of transplantation was negatively correlated with mobility (P= .001), self-care (P= .001), and usual activities (P= .007) dysfunction. Anxiety was significant for patients in relapsed after transplantation (P= .002). FACT-BMT questionnaire results demonstrated that physical, social, and emotional well-being were all well preserved after the transplantation, whereas functional well-being was more variable among patients. Relapse was associated with impaired functional well-being (P= .007) and lower total FACT-BMT score (P= .014). Other comparators, including the conditioning regimen, sex, age subgroups (<65 or ≥65 years), HCT-CI score, and disease status at transplantation, did not impact any of these outcomes. This study demonstrates that physical, social, and functional well-being are preserved in older patients following AHSCT. Low KPS score before AHSCT is a predictor of disability at distance from AHSCT. Relapse following AHSCT remains the most significant impediment to maintaining a good QoL. Innovative interventions to improve performance status before transplantation and measures to prevent relapse thereafter should be investigated to improve survival and QoL.

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 score0.001
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.274
Teacher spread0.256 · 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

Citations20
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueBiology of Blood and Marrow TransplantationSame topicLymphoma Diagnosis and TreatmentFrench-language works237,207