Prediction of hospitalizations in patients with cancer age 70 and older receiving chemotherapy.
Bibliographic record
Abstract
216 Background: Chemotherapy is one of the main treatments for cancer and is associated in many cancers with significant benefits in overall and disease-free survival. Nevertheless, it is also associated with adverse effects that may lead to hospitalizations in older patients with comorbidities or decreased general status. We aimed to identify factors associated with hospital admissions in this population. Methods: Records of cancer patients 70 years-old or older who received adjuvant chemotherapy or first line chemotherapy for a cancer in a single center were retrospectively reviewed. Demographic, disease and treatment data were extracted. Factors associated with hospitalizations during chemotherapy treatment were evaluated in a univariate analysis with the x2 or the Fisher’s exact test. Factors identified were fitted in a multivariate regression model. Results: Among the 276 patients included in the study, 117 (42.4%) were male and 159 (57.6%) were female. Most patients (53.6%) were 70 to 75 years-old, but there were also significant proportions of patients that were 76 to 80 years-old and above age 80 (29.0% and 17.4% respectively). Chemotherapy was given in the adjuvant setting in 51.1% of patients and in the first line metastatic setting in 48.9% of patients. Treatment was with single chemotherapy drug in 22.8% of patients and poly-chemotherapy was given in 77.2% of patients. One hundred and six patients (38.4%) had a hospital admission during or up to a month after their chemotherapy treatment. Factors associated with admission in the multivariate analysis included ECOG PS > 1 (p = 0.04, odds ratio 1.4, 95% CI: 1.0-1.9) and hypoalbuminemia (p = 0.03, odds ratio 0.94, 95% CI: 0.88-0.99). Among the 174 patients that had a good PS (ECOG PS = 0 or 1) and normal albumin, only 28.7% had been hospitalized during treatment, while 62.3% of the 77 patients with PS of 2 or 3, hypoalbuminemia or both were hospitalized during or within the month after completion of treatment. Conclusions: Good ECOG PS in combination with a normal albumin is predictive of lower hospitalization rate in cancer patients 70 years-old and older receiving chemotherapy.
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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 | 0.000 | 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 | 0.000 | 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) | 0.002 | 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".