Correlation of clinical, radiologic and pathologic manifestations with prognosis in lung cancer patients

Abstract

Many different factors that are extremely variable for each individual affect the survival of lung cancer patients. Prognosis in lung cancer depends upon tumor type, patient immunity and treatment modalities. The objective of our study was to determine the infl uence of clinical manifestations including the patient symptoms, laboratory findings, imaging modalities and histopathologic tumor features on the prognosis in lung cancer. Another aim was to evaluate whether the collaboration of these data predicted a more accurate prognostic assessment. A total of 1800 lung cancer patients evaluated at our clinic between 1984 and 2005 years were included in the study. The patients had blood chemistry, chest x-ray, pulmonary function tests, chest computed tomography and histopathology. Prognosis of the patients was evaluated in regard to initial clinical symptoms, performance status, laboratory findings, pulmonary function test results, radiologic, CT and histopathologic manifestations. For patient performance BODE and Karnofsky index were used. Statistical analysis was performed by using Pearson correlation and chi-square tests. Patient performance status and symptoms had a weak correlation with prognosis. The routine laboratory and the pulmonary function test results were incoherent predictors of survival. Chest x-ray and computed tomography findings displayed a noteworthy correlation for the prognostic outcome. Histopathologic features including tumor type, differentiation profile and microscopic invasive features of the airways, nerves, blood or lymphatic vessels were the hallmark of prognostic evaluation along with immunohistochemistry findings. The above criteria other than the pathologic manifestations showed a poor or a moderate correlation by themselves for an accurate prognostic outcome. Collaboration of the clinical manifestations revealed a significantly high correlation for the prognostic evaluation of lung cancer. The most accurate prognostic determination was achieved in advanced stage cases. The results of our study indicate that the more specific the clinical criteria are considered in a lung cancer patient, the more accurate the prognostic assessment will be since cancer pathogenesis is associated with many different complex mechanisms.