A Comparison of Change in the 0–10 Numeric Rating Scale to a Pain Relief Scale and Global Medication Performance Scale in a Short-term Clinical Trial of Breakthrough Pain Intensity
Bibliographic record
Abstract
BACKGROUND: Pain intensity is commonly reported using a 0-10 Numeric Rating Scale in pain clinical trials. Analysis of the change on the Pain Intensity Numerical Rating Scale as a proportion has most consistently correlated with clinically important differences reported on the patient's global impression of change. The correlation of data from patients with breakthrough pain with a Pain Relief Scale and a different global outcome measures will extend our understanding of these measures. METHODS: Data were obtained from the open titration phase of a multiple crossover, randomized, double-blind clinical trial comparing oral transmucosal fentanyl citrate with immediate-release oral morphine sulfate for the treatment of cancer-related breakthrough pain. Raw and percentage changes in the pain intensity scores from 1,307 episodes of pain in 134 oral transmucosal fentanyl citrate-naïve patients were correlated with the clinically relevant secondary outcomes of Pain Relief Verbal Response Scale and the global medication performance scale. The changes in raw and percentage change were assessed over time and compared with the ordinal Pain Relief Verbal Response Scale and Global Medication Performance Scale. RESULTS: The P value of the interaction between the raw pain intensity difference was significant (P = 0.034) for four 15-min time periods but not for the percentage pain intensity difference score (P = 0.26). We found similar results in comparison with the ordinal Pain Relief Verbal Response Scale (P = 0.0048 and P = 0.36 respectively) and global medication performance categories (P = 0.048 and P = 0.45, respectively). CONCLUSION: The change in pain intensity in breakthrough pain was more consistent over time and when compared with both the Pain Relief Verbal Response Scale and the Global Medication Performance Scale when the percentage change is used rather than raw pain intensity difference.
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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 | 0.031 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".