Assessing the causal influence of socioeconomic status on cervical cancer survival using the SEER database

Disparities in socioeconomic conditions particularly household income, have a major impact on health outcomes for many types of illnesses, including cervical cancer. This study aims to examine the causal effect between area-level income and survival outcomes in patients with cervical cancer using statistical and machine learning techniques. The study used a retrospective design utilizing data from the SEER database (2013 to 2015). The household income was divided into low, medium, and high. Vital status and survival months were among the variables that were examined after controlling for treatment-related, clinical, and demographic factors. Causal effects were estimated using Targeted Maximum Likelihood Estimation (TMLE) and Marginal Structural Models (MSM). Kaplan-Meier survival curves were created to illustrate survival differences after variables were balanced using stabilized inverse probability weights (IPWs). Sensitivity analyses were performed to validate results, which included computing E-values and reducing extreme weights. The study comprised 3810 individuals. Low and medium-income patients exhibited considerably lower survival months compared to the medium-income and high-income groups (63 months, p < 0.001). The MSM analysis revealed a mortality hazard ratio (HR) of 1.77 (95% CI 1.33–2.14) for low-income patients compared to high-income patients. TMLE supported similar findings, with low-income patients having 4.3 less survival months on average. Sensitivity analysis confirmed the validity of these findings. Low and medium Household income is substantially linked to shorter survival in cervical cancer patients. These findings show the need for targeted strategies for reducing socioeconomic gaps and improving cancer outcomes.