The utility/futility of medications for neuropathic pain – an observational study
Bibliographic record
Abstract
Background and aims The RELIEF (Real Life) study by AstraZeneca was designed as an observational study to validate a series of Patient Reported Outcome (PRO) questionnaires in a mixed population of subjects with neuropathic pain (NP) coming from diabetes, neurology and primary care clinics. This article is an analysis of a subset of the information to include the medications used and the effects of pharmacological treatment over 6 months. The RELIEF study was performed during 2010-2013. Methods Subjects were recruited from various specialty clinics and one general practice clinic across Canada. The subjects were followed for a total of 2 years with repeated documentation of their status using 10 PROs. A total of 210 of the recruited subjects were entered into the data base and analyzed. Of these, 123 had examination-verified painful diabetic neuropathy (PDN) and 87 had examination-verified post-traumatic neuropathy (PTN). To evaluate the responsiveness of the PROs to change, several time points were included and this study focusses primarily on the first 6 months. Subjects also maintained a diary to document all medications, both for pain and other medical conditions, including all doses, start dates and stop dates, that could be correlated to changes in the PRO parameters. Results RELIEF was successful in being able to correlate the validity of the PROs and this data was used for further AstraZeneca Phase 1, 2, and 3 clinical trials of NP. To our surprise, there was very little change in pain and low levels of patient satisfaction with treatment during the trial. Approximately 15% of the subjects reported improvement, 8% worsening of pain, the remainder reported pain unchanged despite the use of multiple medications at multiple doses, alone or in combination with frequent changes of medications and doses over the study. Those taking predominantly NSAIDs (COX-inhibitors) did no worse than those taking the standard recommended medications against NP. Conclusions Since this is a real-life study, it reflects the clinical utility of a variety of internationally recommended medications for the treatment of NP. In positive clinical trials of these medications in selected "ideal" subjects, the effects are not overwhelming - 30% are 50% improved on average. This study shows that in the real world the results are not nearly as positive and reflects information from non-published negative clinical trials. Implications We still do not have very successful medications for NP. Patients probably differ in many respects from those subjects in clinical trials. This is not to negate the use of recommended medications for NP but an indication that success rates of treatment are likely to be worse than the data coming from those trials published by the pharmaceutical industry.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".