Income and Rurality Impact Overall Survival but not Cause-Specific Survival in Patients With Chondrosarcoma: A Population-Based Study From the SEER Database.

BACKGROUND AND

OBJECTIVES

Previous studies evaluating socioeconomic status (SES) in bone malignancies such as chondrosarcoma used the Cox Proportional Hazards model, which might overestimate risk compared to cause-specific models like the Fine-Gray model. This study aims to evaluate the prognostic significance of income status in chondrosarcoma using both models.

METHODS

We performed a retrospective cohort study using the Surveillance, Epidemiology, and End Results (SEER) database for patients diagnosed with chondrosarcoma. Patients were stratified by SES indicators, including income levels (low: < $55 000, middle: $55 000-$70 000, high: > $70 000) and rurality (urban vs. rural). Survival analysis was conducted using Cox Proportional Hazards and Fine-Gray models.

RESULTS

The inclusion criteria were met by 3678 patients with income distributions as follows: 72.5% high-income, 18.3% middle-income, and 9.2% low-income. Cox analysis identified low-income (hazard ratio [HR] = 1.43, 95%-confidence interval [95%-CI]: 1.10-1.84, p = 0.006) and rurality (HR = 0.71, 95%-CI: 0.55-0.90, p = 0.006) as significant prognostic survival factors. Fine-Gray modeling attenuated the findings for low-income (sub-hazard ratio [SHR] = 1.36, 95%-CI: 0.95-1.94, p = 0.089) and rurality (SHR = 0.76, 95%-CI: 0.54-1.07, p = 0.122).

CONCLUSION

SES influences chondrosarcoma survival, but its effect on cause-specific mortality decreases when competing risks are considered. Fine-gray modeling reveals critical nuances in survival analysis, stressing the need for appropriate statistical methods to interpret SES-related disparities.