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Quality of Life Scores Improve with Increasing Hemoglobin but Optimal Thresholds Vary According to Transfusion Dependence and Clinical Risk Scores: A Canadian Cross Sectional Study of 689 Patients with 2969 Measurements

2016· article· en· W2623919964 on OpenAlexaffabout
Rena Buckstein, Richard A. Wells, Nancy Zhu, Michelle Geddes, Mitchell Sabloff, Brian Leber, Mary‐Margaret Keating, John M. Storring, Karen Yee, Heather A. Leitch, Ève St‐Hilaire, Thomas J. Nevill, April Shamy, Rajat Kumar, Mohamed Elemary, Robert Delage, Martha Lenis, Alexandre Mamedov, Jessica Ivo, Shabbir M.H. Alibhai

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsUniversity of GuelphUniversité LavalUniversity of SaskatchewanUniversity of British ColumbiaCancerCare ManitobaHealth Sciences CentreOttawa HospitalUniversity Health NetworkDr. Georges-L.-Dumont University Hospital CentreSt. Paul's HospitalMcMaster UniversityPrincess Margaret Cancer CentreFoothills Medical CentreUniversity of AlbertaMcGill UniversityMcGill University Health CentreJewish General HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineQuality of life (healthcare)ComorbidityCohortInternal medicinePhysical therapy

Abstract

fetched live from OpenAlex

Abstract Background : We previously presented that selected quality of life (QOL) domains in MDS patients are impaired compared with age-matched controls and most impacted by hemoglobin (Hgb) level, transfusion dependence, frailty and comorbidity in an initial cohort of 236 patients from a Canadian MDS registry (Buckstein R. et al, Abstract 699, ASH 2012 and Abstract 2500, ASH 2009). The optimal Hgb threshold associated with improved QOL may vary according to health states that may fluctuate for any given patient. With longer follow up and greater sample size, we now examine the impact of Hgb levels on QOL in transfusion dependent (TD) versus independent (TI) patients and according to IPSS-R risk scores. Methods:Since 2008, we have prospectively assessed QOL in all patients registered in the Canadian national MDS registry using the instruments EORTC QLQ-C30, FACT-F, global fatigue scale (GFS) and EQ-5D, at enrollment and every 4-6 months. These QOL data are paired with disease specific and laboratory information at the same time intervals. Each patient could provide multiple QOL measurements at different time points. Clinically significant score differences were considered 10 points for the EORTC, 0.08 for the EQ-5D and 4 for the FACT F. General linear regression analysis was applied to search for a significant relationship between physical and social functioning, dyspnea, fatigue and QOL with Hgb, according to transfusion dependence, IPSS and IPSS-R measured categorically. To account for multiple comparisons among 5 Hgb categories, Bonferroni adjusted p-value < .01 was considered statistically significant. Results: 689 patients from 15 Canadian sites completed their first QOL assessment at a median time of 7.8 (IQR 2.7-23) months from MDS diagnosis. The median time from MDS diagnosis to death or last follow-up was 2.5 years (IQR 1.2-4.9). The median Hgb at enrollment was 100 g/L (IQR 86-113) and the distribution of risk scores included: very low (13%); low (35%); intermediate (28%); high (15%); and very high (10%). 27% of patients were TD at enrollment and 54% were TD at any time. The median number of QOL assessments per patient completed was 3 (IQR 2-6) with 547 patients completing at least 2, 424 at least 3 and 335 at least 4 serial QOL measurements at a median time interval of 17 weeks (IQR 13-25). When examined by Hgb thresholds, mean physical functioning, dyspnea, fatigue (QLQ-C30 and GFS) and global QOL improved with increasing Hgb. QOL symptom and function scores were clinically and statistically significantly superior in TI versus TD patients (table 1). The optimal discriminating Hgb threshold for improved symptom and function scores was 100 g/L for patients that were TI or with IPSS-R very low, low and intermediate risk MDS; and 90 g/L for high and very high risk disease (table 2). No discriminating threshold was found in TD patients. Conclusions: In the largest reported serial cross sectional population based assessment of QOL in MDS patients, we confirm that higher Hgb and transfusion independence have significant impact on QOL, symptoms and self-reported function and should be considered important surrogate endpoints for clinical improvement. Disclosures Buckstein: Novartis: Honoraria; Celgene: Honoraria, Research Funding. Wells:Janssen: Honoraria, Other: Advisory Board; Celgene: Honoraria, Other: advisory board; Novartis: Honoraria, Other: advisory board; Alexion: Honoraria, Other: Advisory board. Zhu:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees. Geddes:Celgene: Other: Advisory Board, Research Funding. Sabloff:Gilead: Research Funding; Novartis Canada: Membership on an entity's Board of Directors or advisory committees; Alexion: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Lundbeck: Research Funding. Leber:BMS Canada: Honoraria, Research Funding, Speakers Bureau; Celgene: Honoraria, 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. Storring:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees. Yee:Novartis Canada: Membership on an entity's Board of Directors or advisory committees, Research Funding. Leitch:Alexion: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. St-Hilaire:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis Canada: Membership on an entity's Board of Directors or advisory committees. Nevill:Alexion: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Shamy:Celgene: Honoraria, Other: Advisory board; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees. Kumar:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees. Delage:Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: 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)0.001
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 score0.112
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.054
GPT teacher head0.344
Teacher spread0.290 · 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
Published2016
Admission routes2
Has abstractyes

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