Retrospective cohort examining the relationship between changes in nutritional status, as measured by the abridged Patient Generated Subjective Global Assessment, and changes in quality of life in people with cancer
Bibliographic record
Abstract
Malnutrition, present in approximately 40% of the general cancer population, negatively impacts quality of life (QOL) and treatment outcomes. Most nutrition screening and/or assessment tools are of limited clinical use as they omit nutrition impacting symptoms and physical performance known to be associated both with malnutrition and QOL. The purpose of this thesis was to evaluate whether differences in nutritional status, as measured by the abridged patient-generated subjective global assessment (aPGSGA), were able to predict differences in QOL, physical performance and short-term survival (< 3 y) in cancer patients. The Edmonton Symptom Assessment System (ESAS) was used to measure QOL and the 6-minute walk test (6MWT) to measure physical performance. Two-hundred and seven adult patients attending the cancer rehabilitation and cachexia clinic at the McGill University Health Centre between November 2013 and September 2015 were included. One-hundred and thirteen patients with information over four clinic visits formed a subgroup for repeated measures analysis of ESAS and aPGSGA score. Cross-sectional analyses (n = 207) included Pearson's correlations, multiple regression, one-way ANOVA and Kaplan-Meier survival analysis. Repeated measures analyses (n = 113) included repeated measures ANOVA and mixed models. Significance was accepted at p < 0.05. Total aPGSGA score was 9.6 ± 6.3 at the first visit with nutrition impact symptoms comprising 61% of the total score. A moderate strength correlation between total aPGSGA and ESAS scores (r = 0.478, p < 0.001) was observed at baseline. Baseline aPGSGA score predicted baseline ESAS score (p < 0.001) while controlling for age, diagnosis, ethnicity and sex. There was a difference of 71 m in 6MWT between highest and lowest aPGSGA scores (p = 0.011). In the 113 patients with full data total aPGSGA scores improved from 9.4 ± 5.8 to 5.3 ± 3.8 by the fourth visit (p < 0.001). Total aPGSGA score predicted changes in total ESAS score (p < 0.001), with every 1 point change in aPGSGA score resulting in a corresponding change of 0.972 in total ESAS score over the study period. There were no significant differences in survival according to aPGSGA categories. Nutrition status, as measured by the aPGSGA, is able to detect differences in physical performance and QOL at baseline and predicts changes in QOL over time. Future studies are needed to further explore the impact of nutrition on both survival and cancer treatment outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".