Published in:
01-11-2008 | Thoracic Cancer
Severe Pericardial Effusion in Patients with Concurrent Malignancy: A Retrospective Analysis of Prognostic Factors Influencing Survival
Published in: Annals of Surgical Oncology | Issue 11/2008
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Background
The treatment of massive and/or symptomatic pericardial effusion in patients with cancer remains a subject of discussion. Medical and surgical management have been proposed. In the present study, we aimed to determine the prognostic factors influencing survival of cancer patients admitted in intensive care unit (ICU) with severe pericardial effusion to better select the treatment strategies.
Methods
All patients with cancer and massive or symptomatic pericardial effusion were retrospectively analyzed. Patients were followed up until death or last time known to be alive. Univariate and multivariate analyses were performed to determine prognostic factors influencing survival.
Results
Between January 1999 and August 2004, 55 eligible patients were admitted in the ICU for pericardial effusion, including 30 with lung cancer, 9 with breast cancer, 5 with hematological malignancies, and 11 patients with other types of solid tumors. Forty-three patients underwent a surgical drainage. No operative death occurred. Four patients presented with an asymptomatic recurrence. Median survival of the entire group was 112 days. Survival rates for 1, 2, and 3 years were 27%, 17%, and 12%, respectively. In univariate analysis, the following variables were significantly associated with a reduced survival: histopathological diagnosis of malignant pericardial effusion, age (>60 years), the volume of pericardial effusion (<550 cc), and the cancer status (complete or partial response). After multivariate analysis, the cancer status was the only statistically significant clinical factor influencing overall survival (P = .005).
Conclusion
In this series of patients presenting with severe pericardial effusion, the control of the underlying neoplasm was the only significant factor influencing survival and could be helpful in making decision to the optimal (invasive) treatment that should balance treatment efficacy with life expectancy.