RESUMO
Background: Research within the last decade highlights the patients' frailty status as an important predictor of esophageal cancer outcomes, but the literature evaluating frailty's role in these patients remains limited. We evaluated the role of frailty in patients undergoing resection of malignant esophageal neoplasms. Methods: We used the Nationwide Readmissions Database from 2016 and 2017 to identify patients who underwent excision of a malignant esophageal neoplasm. Patient frailty was queried using the Johns Hopkins Adjusted Clinical Groups frailty-defining diagnosis indicator. Propensity score matching identified 289 frail patients and 281 non-frail patients. Mann-Whitney U testing was performed and receiver operating characteristic (ROC) curves were created, following the creation of logistic regression models for predicting discharge disposition. The area under the curve (AUC) served as a proxy for model performance. Results: Frail patients had significantly more nonroutine discharges, longer inpatient lengths of stay, higher costs, more acute infections, posthemorrhagic anemia and deep vein thrombosis, and greater mortality (P<0.05). No significant differences were found between the 2 cohorts with respect to readmission rates, pulmonary embolism or dysphagia. Predictive models for patient discharge disposition demonstrated that frailty status in combination with age resulted in better ROC curves (AUC: 0.652) compared to models using age alone (AUC: 0.601). Conclusions: Frailty was found to be significantly correlated with higher rates of inpatient medical complications following esophagectomy. The inclusion of patient frailty status in predictive models for discharge disposition resulted in a better predictive capacity compared to those using age alone.
RESUMO
Background: Liver metastases arise frequently from primary colorectal, pancreatic, and breast cancers. Research has highlighted the patient's frailty status as an important predictor of outcomes, but the literature evaluating the role of frailty in patients with secondary metastatic disease of the liver remains limited. Using predictive analytics, we evaluated the role of frailty in patients who underwent hepatectomy for liver metastases. Methods: We used the Nationwide Readmissions Database from 2016-2017 to identify patients who underwent resection of a secondary malignant neoplasm of the liver. Patient frailty was evaluated using the Johns Hopkins Adjusted Clinical Groups (JHACG) frailty-defining diagnosis indicator. Propensity score matching was performed and Mann-Whitney U testing was used to analyze complication rates. Receiver operating characteristic (ROC) curves were created following creation of logistic regression models for predicting discharge disposition. Results: Frail patients reported significantly higher rates of nonroutine discharges, longer inpatient stays, greater costs, higher rates of acute infection, posthemorrhagic anemia, urinary tract infection (UTI), deep vein thrombosis (DVT), wound dehiscence and readmission, and greater mortality (P<0.05). Predictive models for patient discharge disposition, DVT and UTI demonstrated that the use of frailty status and age improved the area under the ROC curves significantly compared to models using age alone. Conclusions: Frailty was found to be significantly correlated with higher rates of medical complications during inpatient stay following hepatectomy in patients with liver metastasis. The inclusion of patient frailty status in predictive models improved their predictive capacity compared to those using age alone.