Predictors of In-Hospital Mortality in Patients With Metastatic Cancer Receiving Specific Critical Care Therapies

Background: In-hospital mortality is high for critically ill patients with metastatic cancer. To help patients, families, and clinicians make an informed decision about invasive medical treatments, we examined predictors of in-hospital mortality among patients with metastatic cancer who received critical care therapies (CCTs). Patients and Methods: We used the 2010 California Healthcare Cost and Utilization Project: State Inpatient Databases to identify admissions of patients with metastatic cancer (age ≥18 years) who received CCTs, including invasive mechanical ventilation (IMV), tracheostomy, percutaneous endoscopic gastrostomy (PEG) tube, acute use of dialysis, and total parenteral nutrition (TPN). We first described the characteristics and outcomes of patients who received any CCTs. We then used multivariable logistic regression models with generalized estimating equations (to account for clustering within hospitals) to identify predictors of in-hospital mortality among patients who received any CCTs. Results: For 2010, we identified 99,085 admissions among patients with metastatic cancer. Of these, 9,348 (9.4%) received any CCT during hospitalization; 50% received IMV, 15% PEG tube, 8% tracheostomy, 40% TPN, and 8% acute dialysis. Inpatient mortality was 30%. Of patients who received any CCT and survived to discharge, 27% were discharged to a skilled nursing facility. Compared with patients who died, costs of care were $3,019 higher for admissions in which patients survived the hospitalization. Predictors of in-hospital mortality included non-white race (vs whites), lack of insurance (vs Medicare), unscheduled admissions, principal diagnosis of infections (vs cancer-related), greater burden of comorbidities, end-stage renal disease, liver disease and lung cancer (vs other cancers). Conclusions: Although more studies are needed to better understand risks and benefits of specific treatments in the setting of specific cancer types, these data will help to inform decision-making for patients with metastatic cancer who become critically ill.

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