The PD-PCS: A New Approach to Classifying Pain in Patients With Parkinson Disease

The Parkinson Disease-Pain Classification System (PD-PCS) is a valid, reliable tool to differentiate Parkinson disease-related pain from unrelated pain, with moderate inter- and intrarater reliability. This is according to research results published in Pain.

Researchers conducted an international, cross-sectional, multicenter study with a retest validation step to test a new mechanism-based classification system to differentiate Parkinson disease-related pain from unrelated pain. Participants included consecutive inpatients and outpatients with Parkinson disease, with or without pain.

In total, 159 patients and 37 healthy controls group participants were recruited across 4 clinical centers in Brazil and eastern Switzerland. Patients in the Parkinson disease group were more likely to be men, less frequently active, had higher Hospital Anxiety and Depression Scale (HADS) scores, and had higher clock-drawing test scores.

Full-scale assessment took less than 7 minutes in 85% of patients. Results of these assessments showed that 93% of patients with Parkinson disease were affected by pain, as assessed via the Brief Pain Inventory (BPI), compared with 6% of control group participants. Parkinson disease-related pain was seen in 77% of patients, 15% of whom experienced more than 1 syndrome at the same time.

Nociceptive, neuropathic, or nociplastic pain components were diagnosed in 55%, 16%, and 22% of patients, respectively. The most frequent mixed pain syndromes included nociceptive plus nociplastic pain (12.7%) or neuropathic pain (9.6%).

Pain unrelated to Parkinson disease — that is, neither caused nor aggravated by Parkinson disease — was present in 22% of patients and 5% of control group participants.

Nociceptive, neuropathic, and nociplastic pain affected 4.8 (±5.2), 8.5 (±5.8), and 10.1 (±8.9) body regions, respectively. Floor effects for these 3 types of pain, plus total scores, were present in 4%, 4%, 20%, and 32% of patients, respectively; ceiling effects were seen in 6% of patients with nociceptive pain and in no patients with the other types of pain.

Samples by geographic region (Brazil and Switzerland) were similar, although Brazilian patients were younger, had higher Unified Parkinson Disease Rating Scale Part III scores, and more frequently experienced levodopa-induced dyskinesia; and Swiss patients were more likely to experience nociplastic pain and had higher PD-PCS total scores.

The researchers evaluated inter- and intrarater reliability in patients who came to a second visit and did not exhibit relevant clinical changes in pain. The PD-PCS overall severity score demonstrated statistically significant intrarater and inter-rater reliability (ICC, 0.62 and 0.59, respectively).

Results of a multinomial logistic regression analysis showed that nociceptive pain was related to Wearing-Off Questionnaire-9 (WOQ-9) scores (odds ratio [OR], 1.43) and BPI pain score (OR, 1.27). Neuropathic pain was related to WOQ-9 score (OR, 1.83), HADS-A score (OR, 1.29), BPI score (OR, 1.51), and McGill Pain Questionnaire sensory score (OR, 1.19), whereas nociplastic pain was related to the WOQ-9 score (OR, 1.47).

When researchers stratified quality of life according to score (low, intermediate, high, or very high), pain unrelated to Parkinson disease had a “somewhat similar distribution across all strata,” while Parkinson disease-related pain was concentrated in the more affected strata.

“The PD-PCS is a valid and reliable tool for differentiating [Parkinson disease]-related pain from…unrelated pain,” the researchers wrote. “It detects and scores mechanistic pain subtypes in a pragmatic and treatment-oriented approach, unifying previous classifications of [Parkinson disease] pain.”

“The refinement of the characterization of pain in [Parkinson disease] should help improve pain in [Parkinson disease] patients in a more pragmatic and symptom-oriented manner,” they concluded.

Disclosure: This clinical trial was supported by Zambon and Mundipharma. Please see the original reference for a full list of authors’ disclosures.

Reference

Mylius V, Perez Lloret S, Cury RG, et al. The Parkinson disease pain classification system: results from an international mechanism-based classification approach. Pain. 2021;162(4):1201-1210. doi:10.1097/j.pain.0000000000002107