RESUMEN
Background and Purpose- Aneurysmal subarachnoid hemorrhage (aSAH) has a high healthcare cost burden. Methods- We performed a cross-sectional analysis of the costs of clipping and coiling of aSAH using the National Inpatient Sample and Vizient databases. We conducted multiple regression analyses to estimate national costs and study associations between patient demographic, clinical, and hospital factors and treatment costs. Results- We identified 23 324 ruptured aneurysm patients in the National Inpatient Sample (2002-2013) and found mean inflation-adjusted costs for clipping increased 41.0% ($66 358±1354-$93 597±2339), whereas costs for coiling increased 38.9% ($62 972±2657-$87 441±2382). Multivariate analysis showed that age, length of stay, insurance, comorbidities, risk of mortality, and urban teaching hospital status were associated with higher hospital costs for clipping and coiling (all P<0.05). In the Vizient database (2013-2015), costs for clipping and coiling increased 11% and 5%, respectively. Both databases demonstrated that the western United States had the highest health expenditures for aSAH (P<0.05). Conclusions- Findings show substantial cost increases and regional cost disparities for aSAH treatments. Patient and hospital factors copredict higher costs for aSAH procedures. Interhospital and regional cost variations open the door for cost-containment strategic development.
RESUMEN
Functional precision medicine aims to match individual cancer patients to optimal treatment through ex vivo drug susceptibility testing on patient-derived cells. However, few functional diagnostic assays have been validated against patient outcomes at scale because of limitations of such assays. Here, we describe a high-throughput assay that detects subtle changes in the mass of individual drug-treated cancer cells as a surrogate biomarker for patient treatment response. To validate this approach, we determined ex vivo response to temozolomide in a retrospective cohort of 69 glioblastoma patient-derived neurosphere models with matched patient survival and genomics. Temozolomide-induced changes in cell mass distributions predict patient overall survival similarly to O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation and may aid in predictions in gliomas with mismatch-repair variants of unknown significance, where MGMT is not predictive. Our findings suggest cell mass is a promising functional biomarker for cancers and drugs that lack genomic biomarkers.