A cross-sectional study on the prediction model of fear of cancer recurrence in individuals with non-small cell lung cancer

Abstract

Abstract Objective To study the fear of cancer recurrence (FCR) of individuals with non-small cell lung cancer (NSCLC); this research focused on developing and validating a prediction model to identify which individuals with NSCLC were at high risk of relapse fear. Methods The sociodemographic and clinical variable data of 347 NSCLC patients from the Department of Thoracic Surgery, Cancer Hospital of Chinese Academy of Medical Sciences from December 2020 to September 2022 were collected by convenience sampling. The t-test, ANOVA, and nonparametric test were used to test the difference of a single factor in the disease fear scores of patients with NSCLC with different demographic characteristics and disease-related conditions. After the disease fear scores were converted into binary data (fear and no fear), the univariate logistic regression analysis was conducted according to the univariate analysis. Multivariate logistic regression analysis was conducted by adjusting the relevant covariates to establish a risk prediction model for NSCLC patients to fear disease progression. Results Gender, ethnicity, family per capita monthly income, and hope level were independent predictors of cancer recurrence fear in patients with non-small cell lung cancer. The model established by these predictors showed that the area under the curve was 0.891,95% confidence interval:0.858–0.924. Conclusion This study developed a validated and easy-to-use prediction algorithm that can be used to identify patients at high risk of recurrence fear with moderate accuracy.