Classification of neuropathic pain in cancer patients: a Delphi expert survey report and EAPC/IASP proposal of an algorithm for diagnostic criteria

Summary: A Delphi expert consensus was used to adapt the IASP special interest group for neuropathic pain (NeuPSIG) criteria for neuropathic pain diagnosis in cancer patients and to propose a clinical diagnostic algorithm. Abstract: Neuropathic pain (NP) in cancer patients lacks standards for diagnosis. This study is aimed at reaching consensus on the application of the International Association for the Study of Pain (IASP) special interest group for neuropathic pain (NeuPSIG) criteria to the diagnosis of NP in cancer patients and on the relevance of patient-reported outcome (PRO) descriptors for the screening of NP in this population. An international group of 42 experts was invited to participate in a consensus process through a modified 2-round Internet-based Delphi survey. Relevant topics investigated were: peculiarities of NP in patients with cancer, IASP NeuPSIG diagnostic criteria adaptation and assessment, and standardized PRO assessment for NP screening. Median consensus scores (MED) and interquartile ranges (IQR) were calculated to measure expert consensus after both rounds. Twenty-nine experts answered, and good agreement was found on the statement “the pathophysiology of NP due to cancer can be different from non-cancer NP” (MED = 9, IQR = 2). Satisfactory consensus was reached for the first 3 NeuPSIG criteria (pain distribution, history, and sensory findings; MEDs >= 8, IQRs <= 3), but not for the fourth one (diagnostic test/imaging; MED = 6, IQR = 3). Agreement was also reached on clinical examination by soft brush or pin stimulation (MEDs >= 7 and IQRs <= 3) and on the use of PRO descriptors for NP screening (MED = 8, IQR = 3). Based on the study results, a clinical algorithm for NP diagnostic criteria in cancer patients with pain was proposed. Clinical research on PRO in the screening phase and on the application of the algorithm will be needed to examine their effectiveness in classifying NP in cancer patients.