Ellen M Lavoie Smith1, Noah Zanville2, Grace Kanzawa-Lee3, Clare Donohoe3, Celia Bridges3, Charles Loprinzi4, Jennifer Le-Rademacher5, James J Yang3. 1. University of Michigan School of Nursing, 400 North Ingalls, Ann Arbor, MI, 48109, USA. ellenls@med.umich.edu. 2. Indiana University School of Nursing, Indianapolis, IN, USA. 3. University of Michigan School of Nursing, 400 North Ingalls, Ann Arbor, MI, 48109, USA. 4. Mayo Clinic, Rochester, MN, USA. 5. Alliance Statistics and Data Center, Mayo Clinic, Rochester, MN, USA.
Abstract
PURPOSE: To 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. METHODS: A 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, item scaling based on response proportions, threshold ordering 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. RESULTS: A 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. CONCLUSIONS: Rasch 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.
PURPOSE: To 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. METHODS: A 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, item scaling based on response proportions, threshold ordering 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. RESULTS: A 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. CONCLUSIONS: Rasch 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.
Authors: Debra L Barton; Edward J Wos; Rui Qin; Bassam I Mattar; Nathan Benjamin Green; Keith S Lanier; James Dewitt Bearden; John W Kugler; Kay L Hoff; Pavan S Reddy; Kendrith M Rowland; Mike Riepl; Bradley Christensen; Charles L Loprinzi Journal: Support Care Cancer Date: 2010-05-25 Impact factor: 3.603
Authors: T J Postma; N K Aaronson; J J Heimans; M J Muller; J G Hildebrand; J Y Delattre; K Hoang-Xuan; M Lantéri-Minet; R Grant; R Huddart; C Moynihan; J Maher; R Lucey Journal: Eur J Cancer Date: 2005-04-14 Impact factor: 9.162
Authors: Ciao-Sin Chen; Ellen M Lavoie Smith; Kathleen A Stringer; N Lynn Henry; Daniel L Hertz Journal: Breast Cancer Res Treat Date: 2022-06-28 Impact factor: 4.624
Authors: Fiona Yeo; Chiu Chin Ng; Kiley W J Loh; Alex Molassiotis; Hui Lin Cheng; Joseph S K Au; Kwun To Leung; Yu Chung Li; Kam-Hung Wong; Lorna Suen; Choi Wan Chan; Janelle Yorke; Carole Farrell; Aishwarya Bandla; Emily Ang; Violeta Lopez; Raghav Sundar; Alexandre Chan Journal: Support Care Cancer Date: 2019-04-10 Impact factor: 3.603
Authors: Tiffany Li; Susanna B Park; Eva Battaglini; Madeleine T King; Matthew C Kiernan; David Goldstein; Claudia Rutherford Journal: Qual Life Res Date: 2022-05-21 Impact factor: 3.440
Authors: Hsing-Wei Hung; Chien-Ying Liu; Hsiu-Fang Chen; Chun-Chu Chang; Shu-Ching Chen Journal: Int J Environ Res Public Health Date: 2021-05-26 Impact factor: 3.390