Determining the optimal cut-off scores for the Chinese version of the Memorial Anxiety Scale for Prostate Cancer (MAX-PC)

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Abstract

Purpose: Anxiety is a common emotion experienced by patients with prostate cancer (PCa), and can be exacerbated by testing the prostate-specific antigen (PSA) index. The Memorial Anxiety Scale for Prostate Cancer (MAX-PC) was developed to assess the cancer-specific anxiety of these patients, but lack of appropriate thresholds for this scale limits its use. This study aimed to utilize ROC curve analysis to identify the best cut-off values for the Chinese version of the MAX-PC scale. Methods: A cross-sectional survey was conducted using the Chinese version of the MAX-PC scale and the Generalized Anxiety Disorder Scale (GAD). ROC curve analysis, Youden index, Kappa consistency test and McNemar test were used for the optimal cutoff points for screening mild, moderate, and severe cancer-specific anxiety levels in patients with PCa, on the Chinese version of the MAX-PC scale. Results: Two hundred eighty-seven patients with PCa completed the survey. The appropriate cut-off values for the MAX-PC scale for screening patients with PCa for cancer-specific anxiety were 20, 28, and 38 for mild, moderate, and severe anxiety, respectively with the highest Youden indices. The Kappa and McNemar’s test showed the best level of consistency with values of 0.627, 0.580, and 0.606 for screening mild, moderate, and severe anxiety, respectively. Conclusions: The scores 20, 28, and 38 are the best cut-off values for the Chinese version of the MAX-PC scale. This scale should be used for screening cancer-specific anxiety for patients with PCa to assess and evaluate their anxiety levels and provide targeted interventions.

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Huang, Q., Jiang, P., Ding, Y., Zheng, Y., Zheng, L., Luo, J., … Wang, W. (2023). Determining the optimal cut-off scores for the Chinese version of the Memorial Anxiety Scale for Prostate Cancer (MAX-PC). Health and Quality of Life Outcomes, 21(1). https://doi.org/10.1186/s12955-023-02210-1

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