Background Brain metastasis are frequently associated with lung cancer. However, there are few epidemiological data on patients concerned.
Purpose The aim of this retrospective and descriptive epidemiological study was to compare diagnostical, therapeutical and survival data for symptomatic and asymptomatic patients.
Materials and methods This study reviews 55 records of patients hospitalised in 2008, previously diagnosed with lung cancer and brain metastasis. The studied parameters were sex ratio, proportion of death, mean time from primitive cancer diagnosis to brain metastasis diagnosis, from cancer and brain metastasis diagnosis to death, lung cancer type, histological type, TNM (tumour node metastasis) stage, number and anatomic situation of brain metastasis, treatment and neurological symptoms.
Results 48 out of 55 patients died. Median survival times for lung cancer and brain metastasis diagnosis were respectively 8 and 4 months. Mean times from lung cancer and brain metastasis diagnosis to death were statistically different (11 months vs 5.4 months, p<0.003). 33 patients (60.0%) were neurologically symptomatic and 22 (40.0%) were asymptomatic. For each of the studied parameters, no statistical difference was found between these 2 groups (t-test or χ2 test α=0.05). The 3 most frequent symptoms at metastasis diagnosis were motor deficiency (45.5%), confusion (18.2%) and headache (18.2%). The median survival time of asymptomatic patients was 4 months and 3.5 months for patients with symptoms (Kaplan-Meier method). The log-rank test of survival rates between symptomatic and asymptomatic patients had no significant outcome (p=0.2).
Conclusions These results are consistent with previous study on non-small cell lung cancer and brain metastasis (J. Sanchez de Cos – 2009) which shows the same order of magnitude for patient characteristics and median survival time for asymptomatic and patients with symptoms. However, it would be interesting to consolidate this study by including more patients in order to improve the statistical relevance and identify new prognostic factors.
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