Implementing a Method for Evaluating Patient-Reported Outcomes Associated With Oral Oncolytic Therapy
Bibliographic record
Abstract
INTRODUCTION: The paradigm shift in health care toward value-based reimbursement has brought emphasis to providing better quality of care to patients with chronic diseases, including patients with cancer. In accordance with providing better quality of care to patients, there has been a growing interest in evaluating quality of life through patient-reported outcomes (PROs). The revised Edmonton Symptom Assessment Scale (ESAS-r) is a tool that can be used to assess PROs and has been validated for use in patients with cancer. This initiative sought to use this standard assessment tool to acquire PROs concerning symptom burden from patients prescribed oral oncolytics. PATIENTS AND METHODS: Eight oncology practices in the state of Michigan used a modified ESAS-r to evaluate symptom burden of patients prescribed oral oncolytics before each outpatient visit. Thirteen symptoms were categorized as mild (0 to 3), moderate (4 to 6), or severe (7 to 10). RESULTS: A total of 1,235 modified ESAS-r surveys were collected and analyzed; 82.5% of symptoms were categorized as mild, 11.9% of symptoms were categorized as moderate, and 5.6% of symptoms were categorized as severe. CONCLUSION: PROs can be evaluated through the use of a standardized tool, such as the ESAS-r, in oncology patients receiving oral oncolytic therapy. Implementing such a tool in both community and academic practices is feasible and may facilitate improvements in the quality of care.
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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 | 0.039 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".