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Antidepressants for neuropathic pain

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Saarto, Tiina, Wiffen, Philip J·2007·Cochrane Database of Systematic Reviews

Abstract

BACKGROUND: This is an updated version of the original Cochrane review published in Issue 3, 2005 of The Cochrane Library. For many years antidepressant drugs have been used to manage neuropathic pain, and are often the first choice treatment. It is not clear, however, which antidepressant is more effective, what role the newer antidepressants can play in treating neuropathic pain, and what adverse effects are experienced by patients. OBJECTIVES: To determine the analgesic effectiveness and safety of antidepressant drugs in neuropathic pain. SEARCH STRATEGY: Randomised controlled trials (RCTs) of antidepressants in neuropathic pain were identified in MEDLINE (1966 to Oct 2005); EMBASE (1980 to Oct 2005); the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library, Issue 3, 2005; and the Cochrane Pain, Palliative and Supportive Care Trials Register (May 2002). Additional reports were identified from the reference list of the retrieved papers, and by contacting investigators. SELECTION CRITERIA: RCTs reporting the analgesic effects of antidepressant drugs in adult patients, with subjective assessment of pain of neuropathic origin. Studies that included patients with chronic headache and migraine were excluded. DATA COLLECTION AND ANALYSIS: Two review authors agreed the included studies, extracted data, and assessed methodological quality independently. Sixty one trials of 20 antidepressants were considered eligible (3293 participants) for inclusion. Relative Risk (RR) and Number-Needed-to-Treat (NNTs) were calculated from dichotomous data for effectiveness and adverse effects. This update includes 11 additional studies (778 participants). MAIN RESULTS: Sixty one RCTs were included in total. Tricyclic antidepressants (TCAs) are effective and have an NNT of 3.6 (95% CI 3 to 4.5) RR 2.1 (95% CI 1.8 to 2.5) for the achievement of at least moderate pain relief. There is limited evidence for the effectiveness of the newer SSRIs but no studies of SNRIs were found. Venlafaxine (three studies) has an NNT of 3.1 (95% CI 2.2 to 5.1) RR 2.2 (95% CI 1.5 to 3.1). There were insufficient data to assess effectiveness for other antidepressants such as St Johns Wort and L-tryptophan. For diabetic neuropathy the NNT for effectiveness was 1.3 (95% CI 1.2 to 1.5) RR 12.4 (95% CI 5.2 to 29.2) (five studies); for postherpetic neuralgia 2.7 (95% CI 2 to 4.1), RR 2.2 (95% CI 1.6 to 3.1) (four studies). There was evidence that TCAs are not effective in HIV-related neuropathies. The number needed to harm (NNH) for major adverse effects defined as an event leading to withdrawal from a study was 28 (95% CI 17.6 to 68.9) for amitriptyline and 16.2 (95% CI 8 to 436) for venlafaxine. The NNH for minor adverse effects was 6 (95% CI 4.2 to 10.7) for amitriptyline and 9.6 (95% CI 3.5 to 13) for venlafaxine. AUTHORS' CONCLUSIONS: This update has provided additional confirmation on the effectiveness of antidepressants for neuropathic pain and has provided new information on another antidepressant - venlafaxine. There is still limited evidence for the role of SSRIs. Whether antidepressants prevent the development of neuropathic pain (pre-emptive use) is still unclear. Both TCAs and venlafaxine have NNTs of approximately three. This means that for approximately every three patients with neuropathic pain who are treated with either of these antidepressants, one will get at least moderate pain relief. There is evidence to suggest that other antidepressants may be effective but numbers of participants are insufficient to calculate robust NNTs. SSRIs are generally better tolerated by patients and more high quality studies are required.

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Cited by

See all 764

Metadata

Authors
Saarto, T., & Wiffen, P. J.
Venue
Cochrane Database of Systematic Reviews
Publisher
Wiley
Published
2007-10-17
Volume
2014
Issue
1
Pages
CD005454-CD005454
ISSN
  • 1361-6137 (ISSN-L)
  • 1465-1858
OpenAlex
W1826161993
Cited by
764
References
3
FWCI
44.69
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.