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Timeliness is an important factor when treating patients with inflammatory sensory neuronopathy (SNN), according to a study published in the February issue of the Journal of the Neurological Sciences.
SNNs are characterized by primary involvement of sensory neurons in the dorsal root ganglion (DRG), and follow an acute, subacute, or chronic course, depending on disease etiology. Acute and subacute courses involve dysregulation of the immune system, as demonstrated by an inflammatory cell reaction in the DRG, and involvement of specific autoantibodies.
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Using sensory nerve action potentials (SNAPs) as a surrogate marker for DRG neuron loss, Jean-Christophe Antoine, MD, and colleagues from the French Neuromuscular Network found that the therapeutic window for SNN stabilization was 8 months from disease onset. Improvement of disease required treatment within 2 months.
“This means that the main endpoint for future clinical trials should aim at stabilizing the neuropathy rather than improving it within this period. Treatments within two months, the period in which SNAPs undergo maximal reduction, might improve the disease process but needs an early [electromyography] testing of the ulnar and radial nerves, which are the most sensitive to the neuropathic process in the upper limbs,” the authors write.
Evolution of Neuronal Loss
Although patients with inflammatory SNN may benefit from immunomodulatory or immunosuppressive therapies, prior studies have not demonstrated a strong response in this patient population, Arun Varadhachary, MD, PhD, an assistant professor of neurology from the division of neuromuscular disease at Washington University in St. Louis, Missouri, told Clinical Pain Advisor.
Postulating that treatment had to be administered before the occurrence of irreversible damage, researchers used SNAPs to determine the evolution of neuronal loss in 86 patients with all types of acute/subacute inflammatory SNN. SNAPs were recorded in the median, ulnar, radial, sural, and peroneal nerves, and monthly reductions were normalized with the lower limit of normal (LLN).
