Association of high symptom burden with oral oncolytic agents.
Bibliographic record
Abstract
177 Background: Increasing numbers of cancer patients are being treated with oral oncolytics. This change represents a shift from frequent direct observation during intravenous therapy to periodic observation and increased necessity for improved monitoring and self-care management. Despite this shift, patients are at risk to develop many of the same chemotherapy-associated symptoms and toxicities. We sought to understand the symptom burden associated with use of oral oncolytics. Methods: Michigan Oncology Quality Consortium (MOQC) sponsored a quality improvement initiative focused on improving oral oncolytic care. Eight oncology practices participated. Patients were assessed with a modified Edmonton Symptom Assessment System (ESAS) prior to each outpatient visit. A total of 537 surveys were analyzed. 13 measures were categorized into mild (0 to 3), moderate (4 to 6), and severe (7 to 10) symptom burden. Results: Overall, the average ESAS symptom score was mild in 81% of patients, moderate in 13% of patients, and severe in 6% of patients. These average scores, however, obscure the significant burden in select ESAS domains. For example, 39% of patients categorized their overall well-being as being moderate/severely affected; 38% of patients felt they were moderate/severely fatigued, and 21% indicated moderate/severe neuropathy symptoms. Notably, 118/537 (24%) of the assessments had 4 or more symptoms rated moderate to severe. Conclusions: Patients taking oral oncolytics experience significant symptom burden that impacts quality of life. Intolerance of oral oncolytics may lead to adherence issues, potentially affecting expected outcomes. Given the prevalence of symptoms and potential for toxicity, self-care strategies to improve early recognition and treatment of symptoms by patients taking oral oncolytics are necessary. [Table: see text]
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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 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".