Chronic non-cancer pain and the long-term efficacy and safety of opioids: Some blind men and an elephant?
Bibliographic record
Abstract
Background The use of opioids for chronic non-cancer pain (CNCP) remains very controversial. There are a number of randomized controlled trials (RCTs) showing efficacy and safety in the short-term, but long-term data are limited. Methods This article contains 10 case reports (followed to 2011) that were selected from a survey of 84 patients with intractable CNCP treated with opioids and followed every 3 months now for a median of 10 years. The previous published survey of this group reported outcomes of pain severity, adverse effects, pain relief, satisfaction, mood, problematic opioid use, tolerance, physical dependency, functional status, health-related quality of life (HRQL), immune status and sexual function. The outcome measures for that study included a numerical rating scale (NRS) for pain, Hospital Anxiety and Depression Scale (HADS), the Brief Pain Inventory Interference Scale (BPI-I), the Pain Disability Index (PDI), and for Health Related Quality of Life (HRQL) the Short Form Health Survey 12 version 2 (SF12v2). These selected patient reports were chosen to illustrate some important aspects of the diagnostic categories of CNCP, the opioids and doses used, particular issues (concurrent addiction history, bipolar disorder, and combination therapy), disease-specific and other outcomes (pain severity and relief, adverse effects, mood, function) and duration of follow-up with complex pain problems. Results Opioids were found to be safe and effective in the long-term for these particular patients, as well as in the larger group from which they originate. Most patients in the total sample reported 50% or greater relief and a moderate improvement in disability. Scores for functional status and HRQL were not severely affected (PDI and BPI-I ratings moderate or less and SF12v2 slightly below normative values for age). Problematic use, tolerance, and serious adverse effects including constipation were not major issues. Conclusion These 10 reports of patients with intractable CNCP treated with opioids with some success over many years put a face on some of the participants in the larger survey of 84 suggesting that this approach is effective and safe for some patients over many years. Implications These data may not be generalizable to a larger population of patients with CNCP because of the probable selection of patients who benefit and who do not have intolerable adverse effects.
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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 | 0.034 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".