The Research On Zinc-finger Protein X-linked Expression Of Serum In Small Cell Lung Cancer And Non-small Cell Lung Cancer Patients And Clinical Application

ObjectiveIn this study,the level of serum X chromosome-coupled zinc finger protein in small cell lung cancer,non-small cell lung cancer patients,and healthy people was measured to determine the difference in levels of ZFX in various lung cancer pathological types.Establishing a Logistic regression-assisted diagnostic model.Discuss the differences between serum ZFX levels of small cell lung cancer and non-small cell lung cancer and healthy people.Provide scientific basis for clinical diagnosis and related treatment of lung cancer.MethodsThe experimental group was 30 patients with small cell lung cancer and 40 patients with non-small cell lung cancer who were newly diagnosed and treated in Baotou Central Hospital of Inner Mongolia from December 2018 to December 2019.Another40 healthy people were collected as the control group.Enzyme-linked immunosorbent assay（ELISA）was used to determine the level of serum ZFX in the experimental group and the control group.Count data（gender,smoking）were tested by chi-square test,measurement data（age,ZFX value）and analysis of variance were used to verify the correlation between the experimental group and the control group.Finally,the different indicators were substituted into the Logistic regression equation to analyze the correlation between the serum ZFX level and the pathological classification of lung cancer.The difference was considered statistically significant at P<0.05.Results1.The result of single factor analysis shows:The small cell lung cancer group had a lower ZFX value than the non-small cell lung cancer group,and the difference was statistically significant（P<0.05）,but there were no significant differences in age,gender,and smoking（P>0.05）.The small cell lung cancer group compared with the control group and the non-small cell lung cancer group compared with the control group had significant differences in ZFX value,age,and smoking（P<0.05）,but there was no significant difference in gender differences（P>0.05）.2.Analysis of multi-factor results revealed:Significant differences were substituted into the logistic regression equation to obtain the modeling equation.The formula for the diagnosis model of small cell lung cancer was:Logit(P_A/C)=-6.728+0.741*X₁+0.006*X₂+1.851*X₃.The formula for the diagnosis model of non-small cell lung cancer was:Logit(P_B/C)=-6.867+1.049*X₁+0.064*X₂+1.589*X₃.3.The model sample prediction results are calculated based on these two models:Small cell lung cancer has been diagnosed and the correctly predicted sample size is 7,the accuracy rate is 23.3%;The sample size that has been diagnosed with non-small cell lung cancer and is correctly predicted is 28,with an accuracy rate of 70%;the sample size that is correctly predicted by healthy people is 32,with an accuracy rate of 80%;the overall prediction accuracy of the model is 60.9%.Conclusions1.Non-small cell lung cancer has a higher ZFX value than small cell lung cancer.ZFX can also be measured in healthy human serum,but it is lower than small cell lung cancer and non-small cell lung cancer.2.The small cell lung cancer group and the non-small cell lung cancer group have significant differences in age and smoking compared with the healthy group.The two lung cancer groups were older and more smokers than the healthy group.There was no significant difference between the small cell lung cancer group and the non-small cell lung cancer group in age,sex,and smoking.3.High serum ZFX concentration,older age,and smoking history are risk factors for small cell lung cancer and non-small cell lung cancer.The lung cancer risk assessment model constructed is not ideal,but it still has some significance for the diagnosis and differentiation of lung cancer,which needs to be further studied after improvement.The next step should be to use larger samples and include more risk factors to introduce research,and develop a diagnostic model with better predictive effects for the diagnosis and differentiation of lung cancer.