Objective. To analyze the relationship between hypercoagulable state and circulating tumor cells (CTCs) in peripheral blood, pathological characteristics, and prognosis of lung cancer patients. Method. A total of 148 patients with primary lung cancer diagnosed and treated in our hospital from January 2017 to January 2019 were selected as the research objects. According to the CTC test results, the patients were divided into CTC-positive group and CTC-negative group. Also, the coagulation index of patients was tested. According to the blood coagulation index test results, patients were divided into hypercoagulable group and non-hypercoagulable group. The relationship between hypercoagulable state and pathological characteristics of lung cancer patients was analyzed by single factor analysis and multiple logistic regression model. Kaplan–Meier survival curve was applied to analyze the relationship between hypercoagulable state and the prognosis of lung cancer patients. Results. The platelets (PLTs), fibrinogen (FIB), D-dimer (D-D), and prothrombin time (PT) in CTC-positive group were significantly higher than those in CTC-negative group. There was no significant relationship between the patient’s gender, smoking history, pathological type, and the hypercoagulable state of the patients. The proportion of patients aged 60 years or older, with TMN stage III or IV and lymph node metastasis, in the hypercoagulable group was significantly higher than that in the non-hypercoagulable group. Logistic regression analysis showed that there was an independent relationship between the patient’s age, lymph node metastasis, and hypercoagulable state. As of January 2020, among the 148 patients with lung cancer follow-up, 5 patients were lost and 52 died. The median survival time of patients in the hypercoagulable group was 82 weeks, which was significantly lower than the 104 weeks in the nonhypercoagulable group. Conclusion. There is a certain relationship between hypercoagulable state and CTC positive in lung cancer patients. There is an independent relationship between the patient’s age, lymph node metastasis, and the hypercoagulable state. The median survival time of patients in the hypercoagulable group was significantly lower than that in the non-hypercoagulable group.
Identification of periodicities in hydrological time series and evaluation of their statistical significance are not only important for water-related studies, but also challenging issues due to the complex variability of hydrological processes. In this article, we develop a “Moving Correlation Coefficient Analysis” (MCCA) method for identifying periodicities of a time series. In the method, the correlation between the original time series and the periodic fluctuation is used as a criterion, aiming to seek out the periodic fluctuation that fits the original time series best, and to evaluate its statistical significance. Consequently, we take periodic components consisting of simple sinusoidal variation as an example, and do statistical experiments to verify the applicability and reliability of the developed method by considering various parameters changing. Three other methods commonly used, harmonic analysis method (HAM), power spectrum method (PSM) and maximum entropy method (MEM) are also applied for comparison. The results indicate that the efficiency of each method is positively connected to the length and amplitude of samples, but negatively correlated with the mean value, variation coefficient and length of periodicity, without relationship with the initial phase of periodicity. For those time series with higher noise component, the developed MCCA method performs best among the four methods. Results from the hydrological case studies in the Yangtze River basin further verify the better performances of the MCCA method compared to other three methods for the identification of periodicities in hydrologic time series.
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