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P108 Anti-nerve growth factor (anti-NGF) antibodies as analgesia in the management of osteoarthritis

2021· article· en· W3159933909 on OpenAlexaboutno aff
Jashmitha Rammanohar, James P. Sutton, K.T. Matthew Seah, Wasim Khan, Kendrick To

Bibliographic record

VenueLara D. Veeken · 2021
Typearticle
Languageen
FieldMedicine
TopicIntramuscular injections and effects
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisContext (archaeology)Nerve growth factorJadad scaleKnee painInternal medicineCochrane LibraryPhysical therapyMeta-analysisAlternative medicinePathology

Abstract

fetched live from OpenAlex

Abstract Background/Aims Osteoarthritis is a major cause of morbidity and disability. Much of this comes from joint pain, which is exacerbated by movement and exercise. Pharmacological analgesia therefore not only has the obvious benefit of alleviating pain, but in doing so, it also facilitates exercise (a pillar of conservative management). Non-steroidal anti-inflammatory drugs (NSAIDs) and opioids are currently the main analgesics used in this context. However, these agents can cause unwanted side effects and are contraindicated in some patients. We thus conducted a systematic review and meta-analysis using the Cochrane collaboration criteria to evaluate the efficacy of anti-nerve growth factor (anti-NGF) antibodies as potential alternative analgesics in osteoarthritis of the hip and/or knee. Whilst tanezumab has been studied extensively and monoclonal anti-NGF antibodies have been reviewed in other pain states, this is the first systematic review of three key anti-NGF antibodies: tanezumab, fulranumab and fasinumab in symptomatic hip and/or knee osteoarthritis. Methods An interdisciplinary work group conducted a literature search across seven electronic databases for the use of anti-NGF antibodies in osteoarthritis. All hip/knee osteoarthritis studies investigating anti-NGF antibodies regardless of dose regimen or phase of trial were included. Studies in which participants received NSAIDs or analgesics other than anti-NGF antibodies, or studies in which the only intervention was the administration of anti-NGF antibodies in combination with NSAIDs or other analgesics were excluded. The Jadad Scale score was used to assess the quality of each study. Results Thirteen studies involving 8,145 patients with a diagnosis of hip and/or knee osteoarthritis were analysed. Demographic information including duration of disease and Kellgren-Lawrence grades were also extracted. Anti-NGF antibodies showed significant improvements compared to placebo as rated on the Western Ontario and McMaster Universities Arthritis Index (WOMAC) scales for pain (SMD= -0.50, 95% CI -0.71 to -0.28, P < 0.00001; I2 = 88%), physical function (SMD= -0.82, 95% CI -1.09 to -0.55, P < 0.00001; I2 = 94%) and stiffness (SMD= -0.88, 95% CI -1.22 to -0.54, P < 0.00001; I2 = 95%). These agents were not associated with a significant increase in serious adverse events but were associated with a significant increase in discontinuation due to adverse events, abnormal peripheral sensations and peripheral neuropathy. Conclusion Anti-NGF antibodies appear very promising with regard to alleviating osteoarthritic hip/knee pain but more studies are needed to determine the optimal dosage and the overall risk-to benefit ratio, particularly with long-term use. Disclosure J. Rammanohar: None. J. Sutton: None. K. Seah: None. W.S. Khan: None. K. To: None.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.266
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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