Abstract
Cancer patients have historically had a very poor outcome following ICU admission. Outcome has however improved over the last decade. We aim to identify factors that predict survival for critically ill patients with hematological malignancy and which can be readily identified prior to admission. This would improve selection of patients suitable for ICU admission, which represents a limited resource. We also assessed the ability of the APACHE II score to predict prognosis in these patients. Since the ICU admission case mix will vary between hospitals, one non-surgical admission within +/− 1 week of each hematological admission acted as a control group. Factors which might affect outcome were assessed by multivariate regression analysis. Factors included were age, hematological diagnosis (acute or chronic leukemia, myeloma, lymphoma), time from hematological diagnosis to ICU admission (0–6 months, 6–12 months, >12 months), degree of prior treatment (admission prior to diagnosis, during first line therapy, after first line), remission status, prior stem cell transplant, documented infection and length of neutropenia (none, 1–10 days, >10 days). For hematology patients, predicted hospital mortality was calculated from the APACHE II score by the formula of Knaus et al (Critical Care Medicine 1985). The APACHE scores of hematology patients were compared to controls by a two-sample t test. Predicted and actual mortalities were compared using a one sample test of proportion. The impact of mechanical ventilation (MV) on mortality was assessed by risk ratios. We identified 111 patients with hematological malignancy (acute leukemia n=42, chronic leukemia n=11, myeloma n=19 and lymphoma n=39) admitted to ICU in one teaching and three district general hospitals (November 2000 - January 2006). Median age of hematological patients was 59 years (range 17–84) and M: F ratio 1.22:1. Control patients (n=111) were similar with median age 63 years (range 17–86) and M: F ratio 1.09:1. For control patients, overall ICU and hospital survival rates were 70% and 55% respectively while survival for hematology patients was approximately half at 44% and 24% respectively. In multivariate regression analysis, only increasing age predicted poor outcome (p=0.016). There was a trend to poor outcome if patients were not in complete remission (p=0.066) or had documented infection (p=0.06). All other variables were not significant. APACHE scores were significantly higher in hematology patients (median 27) compared to controls (median 19) p<0.001. Predicted hospital mortality for hematology patients was 56%, significantly lower than actual mortality (77%) p<0.001. For controls, hospital survival was slightly reduced for MV v’s not receiving MV (risk ratio = 1.37; 95% C.I. = 0.91, 2.05). Hematology patients hospital survival was significantly worse for MV - 5/55, 9% v’s no MV 20/44, 45% (risk ratio = 5.00; 95% CI = 2.04, 12.50). The pre-admission variables assessed did not predict mortality and should not be used for this. Despite high APACHE scores, predicted hospital mortality underestimated mortality for patients with hematological malignancy. Need for MV still predicts poor outcome in this group but without MV nearly half survive to hospital discharge.
Disclosure: No relevant conflicts of interest to declare.
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