First comprehensive tool for screening pain in Parkinson's disease: the King's Parkinson's Disease Pain Questionnaire

Eur J Neurol. 2018 Oct;25(10):1255-1261. doi: 10.1111/ene.13691. Epub 2018 Jun 22.

Abstract

Background and purpose: Pain is highly prevalent in Parkinson's disease (PD), impacting patients' ability, mood and quality of life. Detecting the presence of pain in its multiple modalities is necessary for adequate personalized management of PD. A 14-item, PD-specific, patient-based questionnaire (the King's Parkinson's Disease Pain Questionnaire, KPPQ) was designed corresponding to the rater-based KPP Scale (KPPS). The present multicentre study was aimed at testing the validity of this screening tool.

Methods: First, a comparison between the KPPQ scores of patients and matched controls was performed. Next, convergent validity, reproducibility (test-retest) and diagnostic performance of the questionnaire were analysed.

Results: Data from 300 patients and 150 controls are reported. PD patients declared significantly more pain symptoms than controls (3.96 ± 2.56 vs. 2.17 ± 1.39; P < 0.0001). The KPPQ convergent validity was high with KPPS total score (rS = 0.80) but weak or moderate with other pain assessments. Test-retest reliability was satisfactory with kappa values ≥0.65 except for item 5, Dyskinetic pains (κ = 0.44), and the intraclass correlation coefficient (ICC) for the KPPQ total score was 0.98. After the scores of the KPPS were adapted for screening (0, no symptom; ≥1, symptom present), a good agreement was found between the KPPQ and the KPPS (ICC = 0.88). A strong correlation (rS = 0.80) between the two instruments was found. The diagnostic parameters of the KPPQ were very satisfactory as a whole, with a global accuracy of 78.3%-98.3%.

Conclusions: These results suggest that the KPPQ is a useful, reliable and valid screening instrument for pain in PD to advance patient-related outcomes.

Keywords: King's Parkinson's Disease Pain Questionnaire; Parkinson's disease; assessment; pain; screening; validation.

Publication types

  • Multicenter Study
  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Cross-Sectional Studies
  • Female
  • Humans
  • Male
  • Middle Aged
  • Pain / complications
  • Pain / diagnosis*
  • Pain Measurement
  • Parkinson Disease / complications*
  • Parkinson Disease / physiopathology
  • Quality of Life*
  • Reproducibility of Results
  • Surveys and Questionnaires*