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Published on: February 12, 2017
Incidence and Predictors of Pulmonary Embolism Recurrence and Mortality in Patients With Lung Cancers
Reem F Almesfir1, Nada F Alqubaibi2, Ahmed Alkhelaifi3
1Medical Oncology, King Abdulaziz Medical City, Health Affairs, Ministry of National Guard, Riyadh, SAU.
Abstract:
Background Pulmonary embolism (PE) is a serious and potentially fatal complication in lung cancer patients. This study aims to identify predictors of recurrent PE and related mortality in this population. Methods A retrospective review was conducted using electronic medical records from King Abdulaziz Medical Cities in Riyadh and Jeddah, Saudi Arabia. Lung cancer patients with confirmed initial PE were included. Data on demographics, clinical features, and laboratory values-including Eastern Cooperative Oncology Group (ECOG) performance status, systemic infections, serum albumin, and D-dimer levels-were collected. PE and its recurrence were confirmed by standard imaging techniques. The statistical analyses comprised descriptive statistics, analysis of the receiver operating characteristic (ROC) curve to establish the optimum cutoff values of the biomarkers, and logistic regression to identify predictors of PE recurrence and mortality. Results A total of 98 adult lung cancer patients with initial PE were identified. Of these, 19 (19.4%) experienced recurrent PE, with a mortality rate of 73.7% in this group. Recurrent PE was significantly associated with poor ECOG performance status and systemic infections. Laboratory findings showed that recurrent cases had lower serum albumin (≤ 20.5 mg/L) and higher D-dimer (≥ 6.5 mg/L) levels. Logistic regression revealed that adenocarcinoma type, systemic infection, elevated D-dimer, and low albumin were significant predictors of PE recurrence. Mortality was higher in the recurrence group compared to non-recurrence (73.7% vs. 44.3%, p = 0.021). Conclusion Recurrent PE occurs in 19.4% of lung cancer patients with initial PE and carries high mortality. Identified predictors warrant validation in larger studies.
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