Thrombocytosis and coagulation systems activation are commonly associated with disease progression and are suggested poor prognostic factors in patients with malignancies. This study aimed to investigate the prevalence and prognostic significance of thrombocytosis and elevated fibrinogen levels in patients with advanced non-small cell lung cancer (NSCLC). Initial platelet counts and fibrinogen levels were reviewed in 854 patients with histologically proven NSCLC. Thrombocytosis was defined as platelet counts > 450 x 10(9)/L. A serum fibrinogen level > 4.5 g/L was considered high. At the time of diagnosis, initial platelet counts and serum fibrinogen levels were evaluated before treatment. Clinicopathologic data including histological type, tumor, node, metastasis (TNM) stage, performance status, treatment method, and survival time were evaluated. Initial thrombocytosis was found in 6.9% of patients, and elevated fibrinogen levels were found in 55.1% of patients. Patients with thrombocytosis had a significantly poorer prognosis than patients with normal platelet counts (P < 0.001). In multivariate survival analysis, thrombocytosis was an independent prognostic factor (P < 0.001). An elevated serum fibrinogen level was associated with poor prognosis (P < 0.001). In conclusion, initial thrombocytosis and a high fibrinogen level are independent factors for predicting poor prognosis in patients with advanced NSCLC.
Aged ; Blood Platelets/*cytology ; Carcinoma, Non-Small-Cell Lung/*diagnosis/mortality/pathology ; Female ; Fibrinogen/*analysis ; Humans ; Lung Neoplasms/*diagnosis/mortality/pathology ; Male ; Middle Aged ; Neoplasm Staging ; Platelet Count ; Prognosis ; Retrospective Studies ; Survival Rate ; Thrombocytosis/complications/diagnosis

Hypoxia-inducible factor-1 alpha (HIF-1α) plays a vital role in the initiation, evaluation and prognosis in lung cancer. The prognostic value of HIF-1α reported in diverse study remains disputable. Accordingly, a meta-analysis was implemented to further understand the prognostic role of HIF-1α in lung cancer. The relationship between HIF-1α and the clinicopathological characteristics and prognosis of lung cancer were investigated by a meta-analysis. PubMed and Embase were searched from their inception to January 2015 for observational studies. Fixed-effects or random-effects meta-analyses were used to calculate odds ratios and 95% confidence intervals of different comparisons. A total of 20 studies met the criteria. The results showed that HIF-1α expression in lung cancer tissues was significantly higher than that in normal lung tissues. Expression of HIF-1α in patients with squamous cell carcinoma was significantly higher than that of patients with adenocarcinomas. Similarly, non-small cell lung cancer (NSCLC) patients had higher HIF-1α expression than small cell lung cancer (SCLC) patients. Moreover, lymph node metastasized tissues had higher HIF-1α expression than non-lymph node metastasized tissues. A high level HIF-1α expression was well correlated with the expression of vascular endothelial growth factor and epidermal growth factor receptor in the NSCLC. Notably, NSCLC or SCLC patients with positive HIF-1α expression in tumor tissues had lower overall survival rate than patients with negative HIF-1α expression. It was suggested that HIF-1α expression may be a prognostic biomarker and a potential therapeutic target for lung cancer.
Adenocarcinoma ; diagnosis ; genetics ; mortality ; pathology ; Biomarkers, Tumor ; genetics ; metabolism ; Carcinoma, Non-Small-Cell Lung ; diagnosis ; genetics ; mortality ; pathology ; Carcinoma, Squamous Cell ; diagnosis ; genetics ; mortality ; pathology ; Humans ; Hypoxia-Inducible Factor 1, alpha Subunit ; genetics ; metabolism ; Lung Neoplasms ; diagnosis ; genetics ; mortality ; pathology ; Lymphatic Metastasis ; Neoplasm Grading ; Neoplasm Staging ; Odds Ratio ; Prognosis ; Receptor, Epidermal Growth Factor ; genetics ; metabolism ; Survival Analysis ; Vascular Endothelial Growth Factor A ; genetics ; metabolism

OBJECTIVETo study the survival and prognostic factors of stage III N2 non-small cell lung cancer (NSCLC) after surgical treatment.

METHODS266 patients with stage III N2 NSCLC underwent operation from 1982 to 1996, with the 5-year survival rate compared with those of stage N0 and N1 patients who received operation in the same period. Histological classification, number of positive nodes, location and extent of mediastinal lymph node involvement, T primary tumor status, complete or incomplete operation, the procedure of operation were univariately and multivariately analyzed to determine their impact on the 5-year survival.

RESULTSThe 5-year survival rate of patients with stage III N2 non-small lung cancer after surgical treatment was 17.3%, which was significant lower than those with N0 (51.4%) and N1 (30.4%). Four prognostic factors significantly influenced the outcome: number of positive nodes, location and extent of mediastinal lymph node involvement, T primary tumor status and complete resection of the tumor.

CONCLUSIONPatients with stage III N2 NSCLC are candidates for surgical treatment if they have evidence of limited mediastinal lymph node metastasis and prospects of complete resection.

Aged ; Carcinoma, Non-Small-Cell Lung ; diagnosis ; mortality ; secondary ; surgery ; Female ; Humans ; Lung Neoplasms ; diagnosis ; mortality ; pathology ; surgery ; Lymph Nodes ; Lymphatic Metastasis ; Male ; Middle Aged ; Neoplasm Staging ; Prognosis ; Survival Rate

We present a recurrence prediction model using multiple clinical parameters in patients surgically treated for non-small cell lung cancer. Among 1,578 lung cancer patients who underwent complete resection, we compared the early-recurrence group with the 3-yr non-recurrence group for evaluating those factors that influence early recurrence within one year after surgery. Adenocarcinoma and squamous cell carcinoma were analyzed independently. We used multiple logistic regression analysis to identify the independent clinical predictors of recurrence and Cox's proportional hazard regression method to develop a clinical prediction model. We randomly divided our patients into the training and test subsets. The pathologic stages, tumor cell type, differentiation of tumor, neoadjuvant therapy and age were significant factors on the multivariable analysis. We constructed the model for the training set with adenocarcinoma (n=236) and squamous cell carcinoma (n=305), and we applied it to the test set with adenocarcinoma (n=110) and squamous cell carcinoma (n=154). It was predictive for the in adenocarcinoma (P<0.001) and the squamous cell carcinoma (P=0.037), respectively. Our results showed that our recurrence prediction model based on the clinical parameters could significantly predict the individual patients who were at high risk or low risk for recurrence.
Adenocarcinoma/mortality/pathology/surgery ; Adolescent ; Adult ; Aged ; Aged, 80 and over ; Carcinoma, Non-Small-Cell Lung/mortality/pathology/*surgery ; Carcinoma, Squamous Cell/mortality/pathology/surgery ; Disease-Free Survival ; Female ; Humans ; Lung Neoplasms/mortality/pathology/*surgery ; Male ; Middle Aged ; Neoplasm Recurrence, Local/*diagnosis ; Neoplasm Staging ; Predictive Value of Tests ; Prognosis ; Regression Analysis ; Risk Factors ; Survival Rate