Randomized Trial of Low-Dose Morphine Versus Weak Opioids in Moderate Cancer Pain
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: The WHO guidelines on cancer pain management recommend a sequential three-step analgesic ladder. However, conclusive data are lacking as to whether moderate pain should be treated with either step II weak opioids or low-dose step III strong opioids. PATIENTS AND METHODS: In a multicenter, 28-day, open-label randomized controlled study, adults with moderate cancer pain were assigned to receive either a weak opioid or low-dose morphine. The primary outcome was the number of responder patients, defined as patients with a 20% reduction in pain intensity on the numerical rating scale. RESULTS: A total of 240 patients with cancer (118 in the low-dose morphine and 122 in the weak-opioid group) were included in the study. The primary outcome occurred in 88.2% of the low-dose morphine and in 57.7% of the weak-opioid group (odds risk, 6.18; 95% CI, 3.12 to 12.24; P < .001). The percentage of responder patients was higher in the low-dose morphine group, as early as at 1 week. Clinically meaningful (≥ 30%) and highly meaningful (≥ 50%) pain reduction from baseline was significantly higher in the low-dose morphine group (P < .001). A change in the assigned treatment occurred more frequently in the weak-opioid group, because of inadequate analgesia. The general condition of patients, which was based on the Edmonton Symptom Assessment System overall symptom score, was better in the morphine group. Adverse effects were similar in both groups. CONCLUSION: In patients with cancer and moderate pain, low-dose morphine reduced pain intensity significantly compared with weak opioids, with a similarly good tolerability and an earlier effect.
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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 | 0.027 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it