Comprehensiveness of Quality of Life Instruments in Capturing Concerns Related to Chemotherapy-Induced Neutropenia
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".