Application and accuracy of the EAPC/IASP diagnostic algorithm for neuropathic cancer pain and quantitative sensory testing profile in patients with pain due to cancer

Abstract

Abstract Introduction: Better diagnosis and treatment of neuropathic cancer pain (NcP) remains an unmet clinical need. The EAPC/IASP algorithm was specifically designed for NcP diagnosis; yet, to date, there is no information on its application and accuracy. Objectives: Our aim was to determine the accuracy of the EAPC/IASP algorithm compared with the Neuropathic Special Interest Group grading system (gold standard) and to describe patients' sensory profile with quantitative sensory testing (QST). Methods: This is a cross-sectional observational study conducted in a palliative care and pain outpatient clinic. Patients with cancer pain intensity ≥3 (numerical rating scale 0–10) were eligible. The palliative care physician applied the EAPC/IASP algorithm as a grading system to diagnose probable or definite NcP, and an independent investigator applied the gold standard and performed the QST. Sensitivity and specificity of the EAPC/IASP algorithm were measured in comparison with the gold standard results. Kruskal–Wallis and unequal variance independent-samples t tests were used to compare the QST parameters in patients with and without NcP. Results: Ninety-eight patients were enrolled from August 2020 to March 2023. Sensitivity and specificity for the EAPC/IASP algorithm were 85% (95% CI 70.2–94.3) and 98.3% (95% CI 90.8–100), respectively. Patients with NcP in contrast to patients without NcP showed cold hypoesthesia (P = 0.0032), warm hypoesthesia (P = 0.0018), pressure hyperalgesia (P = 0.02), and the presence of allodynia (P = 0.0001). Conclusion: The results indicate a good performance of the EAPC/IASP algorithm in diagnosing NcP and the QST discriminated well between patients with and without NcP.