The Impact of Frailty on Chemotherapy Outcomes in Patients With Digestive System Tumors
Bibliographic record
Abstract
BACKGROUND: The prevalence of patients with digestive system tumors has been high. In recent years, frailty has been considered to be associated with poor prognosis of digestive system tumors, but there are conflicting research results. A better understanding of the relationship between frailty and outcomes after chemotherapy can help advance the development of oncology care. OBJECTIVE: The aim of this study was to evaluate the effects of prechemotherapy frailty on chemotherapy toxicity, overall mortality, unplanned hospitalization, and overall survival in patients with digestive system tumors. METHODS: Up to April 2023, observational studies assessing the impact of frailty on chemotherapy outcomes in patients with digestive system tumors were collected through searching 10 online research databases. Two evaluators independently extracted literature based on the inclusion and exclusion criteria and evaluated the quality of the studies using the Newcastle-Ottawa Scale. RESULTS: Eventually, 11 cohort studies encompassing 2380 patients were included. The meta-analysis revealed that the frail group exhibited an increased risk of overall mortality, with poorer overall survival than the nonfrail group. CONCLUSION: Frailty increases the risk of chemotherapy-induced toxic effects, unplanned hospitalization, and death in patients. However, because of this study's limited number of participants, large-sample, multicenter studies to verify these findings are required. IMPLICATIONS FOR PRACTICE: This study provides theoretical support for incorporating frailty assessment into the nursing evaluation of patients with digestive system tumors before chemotherapy. This integration aids in predicting patients at a high risk of chemotherapy toxicity, mortality, and unplanned hospitalization, therefore providing corresponding interventions in advance to reduce adverse 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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".