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Measuring quality of life in chronic hematologic malignancy: The QUALMS-1.

2014· article· en· W2590194247 on OpenAlexaffabout
Yolanda Martins, Robert J. Klaassen, Fabio Efficace, Rena Buckstein, Sara Tinsley, Corey D. Watts, Joseph G. Jurcic, Gregory A. Abel

Bibliographic record

VenueJournal of Clinical Oncology · 2014
Typearticle
Languageen
FieldMedicine
TopicMultiple and Secondary Primary Cancers
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of Ottawa
Fundersnot available
KeywordsQuality of life (healthcare)MedicineDiseaseHematologic malignancyCancerGerontologyInternal medicine

Abstract

fetched live from OpenAlex

263 Background: Disease-specific measures of quality of life (QoL) allow for assessment of disease-specific symptoms and psycho-social factors, an especially important endeavor for patients with chronic hematologic malignancies. We aimed to determine if disease-specific QoL could be measured for patients with myelodysplastic syndromes, and what underlying constructs would inform such a measure. Methods: We previously reported on the development of the QUALMS-1, a 33-item QoL tool for MDS patients. 124 MDS patients completed the QUALMS-1 and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30). Chart review was conducted to collect disease characteristics, lab tests, treatments, transfusions, and use of growth factors. Participants were recruited from MDS centers across the USA, Canada and Italy. QUALMS-1 items were scored on a scale ranging from 1 “Never” to 5 “Always”, with 4 reverse-scored items. Items were averaged to create a preliminary total scale score, with higher scores indicating poorer MDS-specific QoL. Results: Mean total scores on the QUALMS-1 ranged from 1.0 - 3.9. The measure had excellent internal consistency reliability (α=.92) and was moderately correlated with the QLQ-C30’s global health, physical functioning, role functioning, emotional health, cognitive functioning, social functioning, fatigue, nausea and pain measures (r range from 0.34 – 0.65, all p <.01). Patients with Hg <= 10 showed a small but consistent higher QUALMS-1 score (M = 2.5; SD =.59) than those with Hg >10 (M = 2.1; SD =.54; p =.03). Preliminary analyses suggested that four latent factors underlie the QUALMS-1, corresponding to the following subscales: physical burden, disease information and uncertainty, emotional burden, and disease-related positives. Conclusions: Our data suggest that the QUALMS-1 is internally consistent and has construct validity in patients with MDS. The measure provides a unique assessment of disease information and uncertainty, as well as disease-related positives. These are psychosocial constructs that may be particular to chronic hematologic malignancies such as MDS and are not well-assessed by generic or cancer-related measures.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.348
GPT teacher head0.495
Teacher spread0.147 · 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 teacher head, not a consensus.

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
Published2014
Admission routes2
Has abstractyes

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