Background: Suicide rate is much higher in cancer patients than in general population. This study examined the suicide risk in survivors of primary solid tumor across 19 cancer sites considering risk coincident patterns based on area-based SES indicators.
Methods: A retrospective search of the SEER database was conducted. Independent risk factors for suicide were identified using the Cox proportional-hazards model. Exploratory factor analysis and cluster analysis were used to create coincident patterns of SES factors.
Results: Suicide risk was higher for patients with a primary solid tumor who were older, male, white, unmarried, had no insurance, poorly differentiated, distant metastasis and did not undergo active treatment (especially surgery). The suicide risk was higher for patients living in areas with economic and education disadvantage, high levels of immigration and crowding, and high levels of residential instability. Concomitant presence of high economic and education disadvantage, high immigration and crowding levels and low residential instability, showed the highest risk of suicide.
Conclusion: In order to mitigate suicidal risk, clinicians should pay more attention to patients who are older, male, white, not married, high levels of cancer severity, not received active treatment (especially surgery), and having no insurance. Identifying coincident patterns of suicide help further screen high suicidal risk patients based on area-based socioeconomic status.
Keywords: socioeconomic status, suicide risk, solid tumor, exploratory factor analysis, cluster analysis, coincident patterns