Does anti-nerve growth factor monoclonal antibody treatment have the potential to replace nonsteroidal anti-inflammatory drugs and opioids in treating hip or knee osteoarthritis? A systematic review of randomized controlled trials
Bibliographic record
Abstract
Purpose: Considering the adverse effects of nonsteroidal anti-inflammatory drugs (NSAIDs) and opioids for treating osteoarthritis (OA), development of drugs that are more effective and better tolerated than existing treatments is urgently needed. This systematic review aimed to evaluate the efficacy and safety of anti-nerve growth factor (NGF) monoclonal antibodies vs active comparator therapy, such as NSAIDs and oxycodone, in treating hip or knee OA. Methods: Databases were comprehensively searched for randomized controlled trials (RCTs) published before January 2022. Efficacy and safety outcomes were assessed. Results: Six RCTs that included 4325 patients were identified. Almost all the RCTs indicated that moderate doses of anti-NGF monoclonal antibody treatment significantly improved efficacy outcomes based on the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain score, the WOMAC physical function score and the Patient's Global Assessment compared with those of the active comparator. At least half of the RCTs indicated that the incidence of severe adverse events, withdrawals due to adverse events (AEs) and total joint replacement were not significantly different between anti-NGF monoclonal antibody treatment and active comparator therapy, but the outcomes of some studies may have been limited by a short duration of follow-up. Most RCTs suggested that anti-NGF monoclonal antibody treatment had a lower incidence of gastrointestinal and cardiovascular AEs. However, the majority of RCTs reported a higher incidence of abnormal peripheral sensation with anti-NGF monoclonal antibody treatment. Furthermore, the higher incidence of rapidly progressive osteoarthritis (RPOA) with anti-NGF monoclonal antibody treatment should also not be overlooked, and the identification of patient characteristics that increase the risk of RPOA is critical in further studies. Conclusion: Based on the current research evidence, anti-NGF monoclonal antibodies are not yet a replacement for analgesic drugs such as NSAIDs but might be a new treatment option for hip or knee OA patients who are intolerant or unresponsive to nonopioid or opioid treatment. Notably, however, considering the inconsistency and inconclusive evidence on the safety outcomes of recent studies, more research is needed, and long-term follow-up is required.
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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 | 0.012 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.012 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".