Geriatric Assessment, Not ASA Physical Status, Is Associated With 6-Month Postoperative Survival in Patients With Cancer Aged ≥75 Years.
Academic Article
Overview
abstract
BACKGROUND: The American Society of Anesthesiologists physical status (ASA PS) classification system is the most common method of assessing preoperative functional status. Comprehensive geriatric assessment (CGA) has been proposed as a supplementary tool for preoperative assessment of older adults. The goal of this study was to assess the correlation between ASA classification and CGA deficits among oncogeriatric patients and to determine the association of each with 6-month survival. PATIENTS AND METHODS: Oncogeriatric patients (aged ≥75 years) who underwent preoperative CGA in an outpatient geriatric clinic at a single tertiary comprehensive cancer center were identified. All patients underwent surgery, with a hospital length of stay (LOS) ≥1 day and at least 6 months of follow-up. ASA classifications were obtained from preoperative anesthesiology notes. Preoperative CGA scores ranged from 0 to 13. Six-month survival was assessed using the Social Security Death Index. RESULTS: In total, 81 of the 980 patients (8.3%) included in the study cohort died within 6 months of surgery. Most patients were classified as ASA PS III (85.4%). The mean number of CGA deficits for patients with PS II was 4.03, PS III was 5.15, and PS IV was 6.95 (P<.001). ASA classification was significantly associated with age, preoperative albumin level, hospital LOS, and 30-day intensive care unit (ICU) admissions. On multivariable analysis, 6-month mortality was associated with number of CGA deficits (odds ratio [OR], 1.14 per each unit increase in CGA score; P=.01), 30-day ICU admissions (OR, 2.77; P=.003), hospital LOS (OR, 1.03; P=.02), and preoperative albumin level (OR, 0.36; P=.004). ASA classification was not associated with 6-month mortality. CONCLUSIONS: Number of CGA deficits was strongly associated with 6-month mortality; ASA classification was not. Preoperative CGA elicits critical information that can be used to enhance the prediction of postoperative outcomes among older patients with cancer.