Development and validation of the self-report symptom inventory of immune-related adverse events in patients with lung cancer
Year: 2024
Type: article
Abstract: Objective This study aims to develop and validate the Self-Report Symptom Inventory of immune-related Adverse Events in Patients with Lung Cancer (SRSI-irAEs-LC) to allow for systematic assessment of symptomatic irAEs in lung cancer patients treated with programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) immune checkpoint inhibitors (ICIs). Methods A sequential two-phase mixed-methods study was conducted. In phase Ⅰ, a draft version of the SRSI-irAEs-LC was constructed through item generation and draft inventory construction. Delphi expert consultation, cognitive interviews and a pilot study were conducted to evaluate the content validity and refine the scale. In phase Ⅱ, psychometric testing was performed on 512 lung cancer patients treated with PD-1/PD-L1 ICIs using item analysis, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), criterion validity, discriminant validity, and reliability evaluations. Results Through 5 sequential steps in phase Ⅰ, the preliminary version of the SRSI-irAEs-LC comprised 10 dimensions with 41 items. Through EFA, the final version of the SRSI-irAEs-LC included 8 dimensions and 26 items that explained 62.33% of the variance. The CFA model showed that the 8-factor model fitted the data well. Good criteria validity and known-groups discriminant validity were demonstrated. Cronbach's alpha , split-half reliability, and test-retest reliability of the scale were 0.824, 0.725, and 0.851, respectively. Conclusions Preliminarily, the SRSI-irAEs-LC is a valid and reliable instrument for assessing symptomatic irAEs in lung cancer patients treated with PD-1/PD-L1 ICIs. Further research is needed to confirm its generalizability to a broader population as well as its validity and reliability.
Authors: Tiantian Fan, Siying Zhu, Hong Wang, Yan Dong, Ying Zhou, Yalan Song, Shan Pan, Qiujuan Wu, Graeme Drummond Smith, Yumei Li, Yuan Han
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,980
Funder: Guangzhou Medical University
OpenAlex ID: W4403351660
