Background
Mortality disparities in sex, income, and race are unknown among patients with cancer who undergo percutaneous coronary intervention (PCI).
Methods
Propensity score adjusted multivariable regression for mortality was performed in this case-control study of the 2016 National Inpatient Sample. Regression models by PCI weighted by the complex survey design were adjusted for age, race, income, cancer metastases, NIS-calculated mortality risk by Diagnosis Related Group (DRG), acute coronary syndrome (ACS), and the likelihood of undergoing PCI. Model optimization was conducted with forward and backward stepwise regression, standard regression diagnostics, and performance comparison to backward propagation neural network machine learning (ML) according to root mean squared error (RMSE).
Results
Of 4,659,200 hospitalized adult cancer patients, females were less likely than males to have ACS (41.52% versus 58.48%), and less likely to undergo PCI during ACS (37.86% versus 62.14%). Multivariable regression in the subgroup of cancer patients who underwent PCI found significant disparities in mortality reduction according to sex, males (OR 0.56; 95%CI 0.50–0.62; p < 0.001) versus females (OR 0.61; 95%CI 0.53–0.69; p < 0.001), and race, whites (OR 0.50, 95%CI 0.46–0.55, p < 0.001) versus non-whites (OR 0.58, 95%CI 0.49–0.68, p < 0.001). However, there was no significant mortality disparity according to region, the interaction of income and region, nor the interaction of non-white race and region. There were significant regional disparities in PCI frequency among patients with cancer. RMSE confirmed comparable model performance to ML analysis.
Conclusion
Our nationally representative study suggests that females are less likely than males to undergo PCI and survive, among patients with cancer. Mortality disparities were observed according to race, but not income and region in PCI among patients with cancer.