Factors Affecting Opioid Treatment in Cancer Patients
Bibliographic record
Abstract
PURPOSE: Pain is prevalent in cancer patients, appearing to be moderate to severe in more than one third of them. Despite the fact that fentanyl is widely used with effective analgesic results, some patients do not correspond to treatment, resulting in opioid change. METHODS: This is a cohort study, performed in Greek patients with cancer. Its scope was to identify potential reasons responsible for opioid change, due to transdermal-fentanyl intolerance, resulting from inadequate analgesia (pain relief<33% in 1week) and/or unacceptable adverse-events (grade≥3 at Common Terminology Criteria-v4.0). The final sample included 289 participants. To investigate responsible reasons for transdermal-fentanyl intolerance we studied its relation with patients' history, haematology, biochemistry, body-mass-index, demographic and disease related characteristics. The Eastern Cooperative Oncology Group performance status scale, the Mini Mental State Examination questionnaire, the M.D.Anderson Symptom Inventory and the Greek Brief Pain Inventory were also used to measure performance status and quality-of-life for the same reason. RESULTS: Almost one third of the patients had to change to an alternative opioid oral-morphine in order to achieve adequate analgesia or/and avoid adverse-events. The most common adverse-events observed were nausea/vomiting and sleepiness. Statistical analysis demonstrated that younger age (OR=0.976) and obesity (OR=0.29 against underweight, OR=0.39 against normal, OR=0.48 against pre-obese) had a higher possibility to contribute to modification of the analgesic treatment. Furthermore, a higher impact of symptoms in patient's life (OR=1.184) and chemotherapy (OR=2.109) could also contribute to the need of change of the opioid analgesic medication. CONCLUSION: This study found significant variables for transdermal-fentanyl intolerance. This knowledge may help person-center care in moderate to severe cancer pain. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 teacher head, 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".