Background:Lung cancer is the most commonly diagnosed cancer worldwide.Its survival rate can be significantly improved by early screening.Biomarkers based on radiomics features have been found to provide important phy...Background:Lung cancer is the most commonly diagnosed cancer worldwide.Its survival rate can be significantly improved by early screening.Biomarkers based on radiomics features have been found to provide important physiological information on tumors and considered as having the potential to be used in the early screening of lung cancer.In this study,we aim to establish a radiomics model and develop a tool to improve the discrimination between benign and malignant pulmonary nodules.Methods:A retrospective study was conducted on 875 patients with benign or malignant pulmonary nodules who underwent computed tomography(CT)examinations between June 2013 and June 2018.We assigned 612 patients to a training cohort and 263 patients to a validation cohort.Radiomics features were extracted from the CT images of each patient.Least absolute shrinkage and selection operator(LASSO)was used for radiomics feature selection and radiomics score calculation.Multivariate logistic regression analysis was used to develop a classification model and radiomics nomogram.Radiomics score and clinical variables were used to distinguish benign and malignant pulmonary nodules in logistic model.The performance of the radiomics nomogram was evaluated by the area under the curve(AUC),calibration curve and Hosmer-Lemeshow test in both the training and validation cohorts.Results:A radiomics score was built and consisted of 20 features selected by LASSO from 1288 radiomics features in the training cohort.The multivariate logistic model and radiomics nomogram were constructed using the radiomics score and patients’age.Good discrimination of benign and malignant pulmonary nodules was obtained from the training cohort(AUC,0.836;95%confidence interval[CI]:0.793-0.879)and validation cohort(AUC,0.809;95%CI:0.745-0.872).The Hosmer-Lemeshow test also showed good performance for the logistic regression model in the training cohort(P=0.765)and validation cohort(P=0.064).Good alignment with the calibration curve indicated the good performance of the nomogram.Conclusions:The established radiomics nomogram is a noninvasive preoperative prediction tool for malignant pulmonary nodule diagnosis.Validation revealed that this nomogram exhibited excellent discrimination and calibration capacities,suggesting its clinical utility in the early screening of lung cancer.展开更多
Dear Editor,Antipsychotics are a class of psychotropic medication pri-marily used for the treatment of schizophrenia and a range of other psychotic disorders.They are antagonists of multiple receptors,such as dopamine...Dear Editor,Antipsychotics are a class of psychotropic medication pri-marily used for the treatment of schizophrenia and a range of other psychotic disorders.They are antagonists of multiple receptors,such as dopamine D 1,dopamine D 2,serotonin 5HT 2A,and serotonin 5HT 1A receptors.Serotonin antagonists have been identified as growth-inhibiting agents in cancer cells,and they not only inhibit the growth of cancer cells but may also induce apoptosis in these cells[1].Several studies have examined the asso-ciation between antipsychotics and certain cancers,but the relationship between antipsychotics and lung cancer remains largely unknown.展开更多
Summary What is already known on this topic?COVID-19 has become a serious public health issue.A higher proportion of severe patients were senior patients with underlying diseases such as diabetes and hypertension and ...Summary What is already known on this topic?COVID-19 has become a serious public health issue.A higher proportion of severe patients were senior patients with underlying diseases such as diabetes and hypertension and had a lack of statistical evidence so far.What is added by this report?When severe illness was compared with non-severe illness,senior patients were at a greater risk(4.71)than young and middle-aged patients,as well as the odds ratio was about 2.99 patients with diabetes compared to patients without diabetes and hypertension.COVID-19-infectious senior patients with diabetes were inclined to suffer severe illness.展开更多
基金Key R&D project of Shandong Province,Grant/Award Number:2018GSF118152
文摘Background:Lung cancer is the most commonly diagnosed cancer worldwide.Its survival rate can be significantly improved by early screening.Biomarkers based on radiomics features have been found to provide important physiological information on tumors and considered as having the potential to be used in the early screening of lung cancer.In this study,we aim to establish a radiomics model and develop a tool to improve the discrimination between benign and malignant pulmonary nodules.Methods:A retrospective study was conducted on 875 patients with benign or malignant pulmonary nodules who underwent computed tomography(CT)examinations between June 2013 and June 2018.We assigned 612 patients to a training cohort and 263 patients to a validation cohort.Radiomics features were extracted from the CT images of each patient.Least absolute shrinkage and selection operator(LASSO)was used for radiomics feature selection and radiomics score calculation.Multivariate logistic regression analysis was used to develop a classification model and radiomics nomogram.Radiomics score and clinical variables were used to distinguish benign and malignant pulmonary nodules in logistic model.The performance of the radiomics nomogram was evaluated by the area under the curve(AUC),calibration curve and Hosmer-Lemeshow test in both the training and validation cohorts.Results:A radiomics score was built and consisted of 20 features selected by LASSO from 1288 radiomics features in the training cohort.The multivariate logistic model and radiomics nomogram were constructed using the radiomics score and patients’age.Good discrimination of benign and malignant pulmonary nodules was obtained from the training cohort(AUC,0.836;95%confidence interval[CI]:0.793-0.879)and validation cohort(AUC,0.809;95%CI:0.745-0.872).The Hosmer-Lemeshow test also showed good performance for the logistic regression model in the training cohort(P=0.765)and validation cohort(P=0.064).Good alignment with the calibration curve indicated the good performance of the nomogram.Conclusions:The established radiomics nomogram is a noninvasive preoperative prediction tool for malignant pulmonary nodule diagnosis.Validation revealed that this nomogram exhibited excellent discrimination and calibration capacities,suggesting its clinical utility in the early screening of lung cancer.
基金supported by the National Key Research and Development Program of China(2020YFC2003500),Shandong Province Major Science and Technology Innova-tion Project(2018CXGC1210),the Major Science and Tech-nology Projects of Shandong province(2018YFJH0506-2),and the National Natural Science Foundation of China(71804093).All authors report no conflicts of interest.
文摘Dear Editor,Antipsychotics are a class of psychotropic medication pri-marily used for the treatment of schizophrenia and a range of other psychotic disorders.They are antagonists of multiple receptors,such as dopamine D 1,dopamine D 2,serotonin 5HT 2A,and serotonin 5HT 1A receptors.Serotonin antagonists have been identified as growth-inhibiting agents in cancer cells,and they not only inhibit the growth of cancer cells but may also induce apoptosis in these cells[1].Several studies have examined the asso-ciation between antipsychotics and certain cancers,but the relationship between antipsychotics and lung cancer remains largely unknown.
文摘Summary What is already known on this topic?COVID-19 has become a serious public health issue.A higher proportion of severe patients were senior patients with underlying diseases such as diabetes and hypertension and had a lack of statistical evidence so far.What is added by this report?When severe illness was compared with non-severe illness,senior patients were at a greater risk(4.71)than young and middle-aged patients,as well as the odds ratio was about 2.99 patients with diabetes compared to patients without diabetes and hypertension.COVID-19-infectious senior patients with diabetes were inclined to suffer severe illness.
