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Record W2913936095 · doi:10.1182/blood-2018-99-114327

Health Related Quality of Life Remains Stable over Time in Myelodysplastic Syndrome: An MDS-CAN Prospective Study

2018· article· en· W2913936095 on OpenAlexaffabout
Danielle Blunt, Richard A. Wells, Martha Lenis, Lisa Chodirker, Michelle Geddes, Nancy Zhu, Jill Fulcher, Mitchell Sabloff, Mary‐Margaret Keating, Brian Leber, Heather A. Leitch, Karen Yee, Ève St‐Hilaire, Nicholas Finn, April Shamy, Mohamed Elemary, Robert Delage, K. Rockwood, Versha Banerji, Alexandre Mamedov, Liying Zhang, Rena Buckstein

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsUniversity of ManitobaPrincess Margaret Cancer CentreCentre hospitalier de l'Université LavalUniversity of British ColumbiaDr. Georges-L.-Dumont University Hospital CentreSt. Paul's HospitalMcMaster UniversityQueen Elizabeth II Health Sciences CentreUniversity of AlbertaCancerCare ManitobaSaskatchewan Cancer AgencyHealth Sciences CentreOttawa HospitalUniversity Health NetworkDalhousie UniversityUniversity of TorontoJewish General HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineQuality of life (healthcare)International Prognostic Scoring SystemMyelodysplastic syndromesInternal medicineAzacitidineProspective cohort studyDecitabinePhysical therapyPediatrics

Abstract

fetched live from OpenAlex

Abstract Background: Health-Related Quality of life (HRQoL) is diminished in patients with myelodysplastic syndrome (MDS). We have previously shown that HRQoL remains stable over time and low hemoglobin, transfusion dependence (TD) and age > 65 years impact QoL1. Here, we present an updated larger data set with longer follow up and consider the impact of baseline characteristics and treatments received on patient-related outcomes. Methods: MDS-CAN is a prospective database active in 15 centers across Canada, enrolling patients since April 2012. In addition to disease and patient-related characteristics, we measure HRQoL at baseline and every 6 months using the EORTC-QLQ-C30, EQ-5D, and a global fatigue scale (GFS). We examined the impact of disease related factors (IPSS, IPSS-R, karyotype, TD), patient factors (ECOG, age, gender, co-morbidity (Charlson index), frailty (Rockwood scale), disability (Lawton-Brody Independent Activities of Daily Living), and treatments received at any time (azacitidine (AZA), lenalidomide, erythropoietin-stimulating agents (ESA), iron chelation) on QoL scores. AZA-treated patients were divided into responders (where documented) or deriving benefit (if > 6 cycles) vs. non-responders. Wilcoxon rank-sum or Kruskal-Wallis nonparametric tests were used to compare scores among subgroups. Changes in QoL were assessed with a linear mixed model to account for time- dependent covariates such as TD, risk scores and treatment. Results: 594 patients were enrolled a median of 2.2 months post diagnosis (IQR: 0.8, 4.8) with a median age of 73 years , 63% male gender and performance status (ECOG) of 0-1 in 90%. IPSS scores were low/int-1 in 73% and IPSS-R scores were very low (9%), low (30%), intermediate (27%), high (20%) and very high (14% of patients). 31% were transfusion dependent at enrolment. Treatments received at any time included AZA (38%), lenalidomide (9.8%), ESA (35%) and iron chelation (12%). At a median follow up of 17 months, 329 patients (55%) died with cause of death reported as AML in 22%. Baseline assessment: Mean EQ-5D global score for the cohort was 0.75 ± 0.25 and did not significantly change over time (Figure 1). Patients with high IPSS, high/very high IPSS-R, TD, lower hemoglobin, higher ECOG, increased comorbidity, frailty and disability were more likely to have lower EQ-5D/QLQ C30 scores (inferior QoL) and higher fatigue (GFS). Age was not significantly related to QoL. Interestingly, female gender was associated with inferior QoL by EQ-5D and GFS (Figure 2). Patients scoring in the lowest quartiles for physical performance tests (grip, 4 metre walk and 10x chair sit-stand tests) also had inferior QoL scores. QoL over time: By linear mixed modelling, we did not find significant differences in QoL over time in patients treated with or without AZA, lenalidomide, or ESAs measured by the EQ-5D instrument. Iron chelation was associated with lower scores (p=0.003) although this may simply be a surrogate for transfusion dependence which is associated with inferior QoL. AZA responding/deriving benefit patients had higher QoL scores from baseline and decreased fatigue compared with those not responding or not deriving benefit (Figure 3) measured by the QLQ-C30 and GFS instruments. Patients with the highest IPSS/IPSS-R risk groups had significantly inferior QoL over time. In conclusion, this study demonstrates that HRQoL remains fairly stable over time in MDS and implementation of treatment is not at the detriment of patient related outcomes. Patients treated with AZA who respond or remain on drug for > 6 months maintain higher QoL scores over time. Disease (IPSS, IPSS-R, hemoglobin, transfusion dependence) and patient-related factors (ECOG, gender, comorbidities, disability, frailty) are associated with reduced HRQoL. The prospective assessment of QoL using a validated MDS-specific QoL instrument (QUALMS) and disease course is underway. 1 Buckstein, R., Alibhai, S.M., Lam, A., et al. The health-related quality of life of MDS patients is impaired and most predicted by transfusion dependence, hemoglobin and age. Leukemia Research. May 2011 Vol 35, Supplement 1, Pages S55-56. Disclosures Wells: Alexion Pharmaceuticals, Inc.: Honoraria, Other: Travel Support , Research Funding; Novartis: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Geddes:Alexion: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Zhu:Janssen: Consultancy; Novartis: Consultancy; Celgene: Consultancy, Research Funding. Sabloff:Celgene: Membership on an entity's Board of Directors or advisory committees. Keating:Bayer: Honoraria, Membership on an entity's Board of Directors or advisory committees. Leber:Novartis Canada: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis Canada: Honoraria, Membership on an entity's Board of Directors or advisory committees. Leitch:Novartis: Honoraria, Research Funding, Speakers Bureau; Celgene: Honoraria, Research Funding; Alexion: Honoraria, Research Funding; AbbVie: Research Funding. Yee:Celgene, Novartis, Otsuka: Membership on an entity's Board of Directors or advisory committees; Agensys, Astex, GSK, Onconova, Genentech/Roche: Research Funding. St-Hilaire:Novartis: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Shamy:Amgen: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Elemary:Roche: Membership on an entity's Board of Directors or advisory committees; Lundbeck: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Delage:Celgene: Membership on an entity's Board of Directors or advisory committees; AbbVie: Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding. Rockwood:Pfizer: Research Funding; Lundbeck: Membership on an entity's Board of Directors or advisory committees; CHIR: Research Funding; Nova Scotia Health research foundation: Research Funding; Sanofi: Research Funding; Capital Health research support: Research Funding; Canadian consortium on neurodegeneration in aging and nutricia: Membership on an entity's Board of Directors or advisory committees; Alzheimer Society of Canada: Research Funding; Foundation Family Fund: Research Funding. Banerji:Teva: Other: Unrestricted grant received in the past; Gilead: Other: Unrestricted grant received in the past; Abbvie: Other: Unrestricted grant received in the past; Roche: Other: Unrestricted grant received in the past; Janssen: Other: Unrestricted grant received in the past. Buckstein:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.071
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.028
GPT teacher head0.336
Teacher spread0.308 · 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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Citations2
Published2018
Admission routes2
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