Role of different peripheral components in the expression of neuropathic pain syndrome

A treatment algorithm for neuropathic pain: an update

OBJECTIVE

The purpose of this review is to provide an update of the neuropathic pain treatment algorithm previously published by Namaka et al. in 2004. This algorithm focuses on the strategic incorporation of the latest pain therapies while providing an update of any recent developments involving medications previously listed in the algorithm.

DATA SOURCES

PubMed, MEDLINE, Cochrane, and Toxnet databases were used to conduct all literature searches on neuropathic pain and targeted treatment strategies. Comprehensive search efforts in the identified databases included studies published between 1980 and 2009. The search term "neuropathic pain" was used along with each of the agents outlined in this review: pregabalin, paroxetine CR, duloxetine, tramadol XL, Tramacet, Sativex, and nabilone.

STUDY SELECTION

A total of 90 studies were reviewed and selected based on level 1, 2, and 3 search strategies.

DATA EXTRACTION

Level 1 search strategies were initially aimed at evidence-based trials of large sample size (N > 100), with a randomized, double-blind, placebo-controlled design conducted by investigators well versed in the specialty area of interest. A level 2 search was conducted for additional trials that had many, but not all, of the desirable traits of evidence-based trials. In addition, a level 3 search strategy was conducted to compare key findings stated in anecdotal reports of very small (N < 15), poorly designed trials with the results of well-designed, evidence-based trials identified in level 1 and/or level 2 searches.

DATA SYNTHESIS

Based on a thorough evaluation of the literature, pregabalin, paroxetine CR, and duloxetine have been placed in the updated algorithm as first-line agents, while tramadol XL, Tramacet, Sativex, and nabilone function primarily as adjunctive agents.

CONCLUSION

The updated algorithm provides a baseline framework from which clinicians can justify the medication they prescribe.

Behavioral characteristics of a mouse model of cancer pain

Pain is a major symptom in cancer patients, and most cancer patients with advanced or terminal cancers suffer from chronic pain related to treatment failure and/or tumor progression. In the present study, we examined the development of cancer pain in mice. Murine hepatocarcinoma cells, HCa-1, were inoculated unilaterally into the thigh or the dorsum of the foot of male C3H/HeJ mice. Four weeks after inoculation, behavioral signs were observed for mechanical allodynia, cold allodynia, and hyperalgesia using a von Frey filament, acetone, and radiant heat, respectively. Bone invasion by the tumor commenced from 7 days after inoculation of tumor cells and was evident from 14 days after inoculation. Cold allodynia but neither mechanical allodynia nor hyperalgesia was observed in mice that received an inoculation into the thigh. On the contrary, mechanical allodynia and cold allodynia, but not hyperalgesia, were developed in mice with an inoculation into the foot. Sometimes, mirror-image pain was developed in these animals. These results suggest that carcinoma cells injected into the foot of mice may develop severe chronic pain related to cancer. This animal model of pain would be useful to elucidate the mechanisms of cancer pain in humans.

A treatment algorithm for neuropathic pain

BACKGROUND

Neuropathic pain is a chronic pain syndrome caused by drug-, disease-, or injury-induced damage or destruction of sensory neurons within the dorsal root ganglia of the peripheral nervous system. Characteristic clinical symptoms include the feeling of pins and needles; burning, shooting, and/or stabbing pain with or without throbbing; and numbness. Neuronal hyperexcitability represents the hallmark cellular mechanism involved in the underlying pathophysiology of neuropathic pain. Although the primary goal is to alleviate pain, clinicians recognize that even the most appropriate treatment strategy may be, at best, only able to reduce pain to a more tolerable level.

OBJECTIVE

The purpose of this review is to propose a treatment algorithm for neuropathic pain that health care professionals can logically follow and adapt to the specific needs of each patient. The algorithm is intended to serve as a general guide to assist clinicians in optimizing available therapeutic options.

METHODS

A comprehensive review of the literature using the PubMed, MEDLINE, Cochrane, and Toxnet databases was conducted to design and develop a novel treatment algorithm for neuropathic pain that encompasses agents from several drug classes, including antidepressants, antiepileptic drugs, topical antineuralgic agents, narcotics, and analgesics, as well as various treatment options for refractory cases.

RESULTS

Any of the agents in the first-line drug classes (tricyclic antidepressants, antiepileptic drugs, topical antineuralgics, analgesics) may be used as a starting point in the treatment of neuropathic pain. If a patient does not respond to treatment with at least 3 different agents within a drug class, agents from a second drug class may be tried. When all first-line options have been exhausted, narcotic analgesics or refractory treatment options may provide some benefit. Patients who do not respond to monotherapy with any of the first- or second-line agents may respond to combination therapy or may be candidates for referral to a pain clinic. Because the techniques used at pain clinics tend to be invasive, referrals to these clinics should be reserved for patients who are truly refractory to all forms of pharmacotherapy.

CONCLUSIONS

Neuropathic pain continues to be one of the most difficult pain conditions to treat. With the proposed algorithm, clinicians will have a framework from which to design a pain treatment protocol appropriate for each patient. The algorithm will also help streamline referrals to specialized pain clinics, thereby reducing waiting list times for patients who are truly refractory to traditional pharmacotherapy.