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Comprehensiveness of Quality of Life Instruments in Capturing Concerns Related to Chemotherapy-Induced Neutropenia

2008· article· en· W2549713075 on OpenAlexaffabout
Lathi A Nina, Pierre K. Isogai, Nicole Mittmann, Carlo DeAngelis, Matthew C. Cheung, Knowles Sandra, Eugenia Piliotis, Neil H. Shear, Scott E. Walker

Bibliographic record

VenueBlood · 2008
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsNeutropeniaMedicineQuality of life (healthcare)AnxietyVisual analogue scalePhysical therapyCancerFebrile neutropeniaInternal medicineIntensive care medicineChemotherapyPsychiatryNursing

Abstract

fetched live from OpenAlex

Abstract Neutropenia is a serious hematologic consequence of cancer chemotherapy that can lead to further complications such as febrile neutropenia (FN). FN is potentially life threatening and often requires hospitalization. Few studies have evaluated the impact of neutropenia on quality of life (QoL). This study quantified QoL using two nonneutropenia-specific instruments, the EQ-5D questionnaire, a generic tool used to measure health-related QoL, and the Functional Assessment of Cancer Therapy - General (FACT-G) questionnaire, and a neutropenia-specific instrument, the Functional Assessment of Cancer Therapy - Neutropenia (FACT-N) questionnaire. The FACT-G is a 27-item questionnaire that examines QoL in patients with cancer using four subscales. A neutropenia-specific subscale (NSS) has been developed for use with the FACT-G; this combined questionnaire is the FACT-N. Data were collected from patients, who provided informed consent, and who were admitted to Sunnybrook Health Sciences Centre, Toronto, Canada, for the treatment of chemotherapy-induced FN. Linear regression models were fitted to examine the relationship of scores from the neutropenia-specific instrument with those obtained from the other instruments. Two models were fitted using the NSS as the response variable. Predictors for the regression models were the FACT-G scores for each of the subscales (physical, emotional, social and functional wellbeing) and the five domains of the EQ-5D (mobility, self-care, usual activity, pain/discomfort and anxiety/depression) along with the visual analog scale (VAS) component of this tool. The physical and emotional wellbeing subscales of the FACT-G had a strong relationship to the NSS (p < 0.05); the social and functional well-being subscales had a much weaker relationship (p > 0.5). For the EQ-5D, the pain/discomfort domain had the strongest relationship to the NSS (p=0.18); the remaining domains, with or without the VAS, all demonstrated a weaker relationship (p > 0.5). Model fit was assessed by the adjusted R2 statistic; it was 0.54 when FACT-G subscales were used as the predictors compared to −0.04 for the EQ-5D domains indicating that the FACT-G was a better predictor of neutropenia-related concerns. Neutropenia concerns appear to be more closely related to cancer specific QoL compared to general quality of life as demonstrated by the stronger relationship of the NSS to the FACT-G than to the EQ-5D. This may be due to the comprehensiveness of the FACT-G questionnaire where a possible score anywhere from 0 to 24 or 28 can be obtained in each of the subscales, compared to three-point descriptive system for each of the domains of the EQ-5D.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.165
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.060
GPT teacher head0.326
Teacher spread0.266 · 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.

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

Citations2
Published2008
Admission routes2
Has abstractyes

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