Rasch model-based testing of the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-Chemotherapy-Induced Peripheral Neuropathy (QLQ-CIPN20) using Alliance for Clinical Trials in Oncology (Alliance) A151408 study data

PurposeTo test the psychometric properties of the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-Chemotherapy-Induced Peripheral Neuropathy (QLQ-CIPN20) using Rasch-based methods.MethodsA secondary data analysis was performed using pooled QLQ-CIPN20 data from patients (N=1008) who had participated in any of four multi-site chemotherapy-induced peripheral neuropathy (CIPN) treatment and prevention trials. QLQ-CIPN20 responses were evaluated using a polytomous Rasch partial credit model. Data were assessed for person-item fit using the chi-square statistic, itemscaling based on response proportions, thresholdordering using item characteristic curves and logit threshold locations, differential item response (DIF) (i.e., response bias) using likelihood ratio tests, and unidimensionality using cluster analysis.ResultsA statistically significant chi-square test indicated poor fit of the observed to the expected responses. More than 70% of the respondents reported a complete absence of six symptoms, reflecting significant floor effects and poor item scaling. Disordered/non-ordinal or narrow response thresholds were found for 11 of the 20 items. Item responses were significantly different by gender (p<0.0001) and chemotherapy type (p<0.0001). Cluster analysis findings suggest that the QLQ-CIPN20 is a unidimensional scale due to the absence of item clusters.ConclusionsRasch model testing revealed psychometric weaknesses that could be addressed by revising the QLQ-CIPN20's problematic items and response options. Alternatively, perhaps the new gold standard CIPN measurement approach in future intervention trials should involve use of only the best items, which would also allow comparisons across previous trials that utilized the QLQ-CIPN20.