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Widowed Status Predicts Poor Overall Survival of Chinese Patients with Prostate Cancer

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Specialty Oncology
Date 2022 Feb 4
PMID 35117404
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Abstract

Background: Little is known about the influence of marital status on Chinese prostate cancer (PCa) patients. Marital status may have an impact on overall survival in Chinese men with prostate cancer.

Methods: We identified 4,208 Chinese patients diagnosed with PCa between 2004 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox proportional hazard models were used to determine the impact of marital status on the overall survival (OS) of Chinese PCa patients. Survival analysis was performed using the Kaplan-Meier method. Smoothing function and threshold effect analysis were performed to determine the turning points of variables.

Results: Univariate analysis demonstrated that marital status, prostate-specific antigen (PSA) category, surgery status, T stage, N stage, and M stage were associated with OS. Multivariate analysis further indicated that marital status, PSA category, surgery status, T stage, and M stage were independent risk factors of OS. Survival analysis demonstrated that the nonwidowed group had a better OS than the widowed group. The risk of poor OS increased rapidly with the PSA level up to the turning point 15.6 and 45.4 ng/mL in the nonwidowed group (HR =1.089; 95% CI: 1.064-1.115; P<0.0001) and the widowed group (HR =1.056; 95% CI: 1.028-1.084; P<0.001), respectively.

Conclusions: In conclusion, this study demonstrated that widowed status greatly affects the OS of Chinese PCa patients. Altogether, this study highlights the importance of psychological intervention, especially for widowed Chinese PCa patients. Timely psychological intervention for widowed Chinese PCa patients might improve the survival outcomes of PCa.

Citing Articles

Marital Status, Living Arrangement, and Survival among Individuals with Advanced Prostate Cancer in the International Registry for Men with Advanced Prostate Cancer.

Chen N, McGrath C, Ericsson C, Vaselkiv J, Rencsok E, Stopsack K Cancer Epidemiol Biomarkers Prev. 2024; 33(3):419-425.

PMID: 38189661 PMC: 10922505. DOI: 10.1158/1055-9965.EPI-23-1207.

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