Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Objective:To explore the value of salivary gland imaging based on deep learning and Delta radiomics in assessing salivary gland injury after 131I treatment in post-thyroidectomy thyroid cancer patients. Methods:A retrospective analysis on 223 patients (46 males, 177 females, age(47.7±14.0) years ) with papillary thyroid cancer, who underwent total thyroidectomy and 131I treatment in Affiliated Hospital of Guilin Medical University between December 2019 and January 2022, was conducted. All patients underwent salivary gland 99Tc mO 4- imaging before and after 131I therapy. The patients were categorized according to salivary gland function based on 99Tc mO 4- imaging results (normal salivary gland vs salivary gland injury), and divided into training and test sets in a ratio of 7∶3. A ResNet-34 neural network model was trained using images at the time of maximum salivary gland radioactivity and those based on background radioactivity counts for structured image feature data. The Delta radiomics approach was then used to subtract the image feature values of the two periods, followed by feature selection through t-test, correlation analysis, and the least absolute shrinkage and selection operator( LASSO) algorithm, to develop logistic regression (LR), support vector machine (SVM), and K-nearest neighbor (KNN) predictive models. The diagnostic performance of 3 models for salivary gland function on the test set was compared with that of the manual interpretation. The AUCs of the 3 models on the test set were compared (Delong test). Results:Among the 67 cases of the test set, the diagnostic accuracy of 3 physicians were 89.6%(60/67), 83.6%(56/67), and 82.1%(55/67) respectively, with the time required for diagnosis of 56, 74 and 55 min, respectively. The accuracies of LR, SVM, and KNN models were 91.0%(61/67), 86.6%(58/67), and 82.1%(55/67), with the required times of 12.5, 15.3 and 17.9 s, respectively. All 3 radiomics models demonstrated good classification and predictive capabilities, with AUC values for the training set of 0.972, 0.965, and 0.943, and for the test set of 0.954, 0.913, and 0.791, respectively. There were no significant differences among the AUC values for the test set ( z values: 0.72, 1.18, 1.82, all P>0.05). Conclusion:The models based on deep learning and Delta radiomics possess high predictive value in assessing salivary gland injury following 131I treatment after surgery in patients with thyroid cancer.

Objective:The National Central Cancer Registry estimates the number of new cancer cases and deaths in China in 2022, using incidence and mortality data collected by the National Cancer Center.Methods:According to the data of 700 cancer registries in 2018 and the data of 106 cancer registries from 2010 to 2018, the age-period-cohort model was used to estimate the incidence rate and mortality rate of all cancers and 23 types of cancer in 2022, stratified by gender and urban and rural areas. We estimated the number of new cancer cases and deaths in China in 2022 based on the estimated rate and population data in 2022.Results:The estimated results showed that in 2022, there were approximately 4 824 700 new cancer cases in China (2 533 900 in males and 2 290 800 in females), with an age-standardized incidence rate of Chinese population (ASIR) of 208.58 per 100 000 (212.67 per 100 000 for males and 208.08 per 100 000 for females). Approximately 2 903 900 new cancer cases occurred in urban areas, with an ASIR of 212.95 per 100 000. It was estimated about 1 920 800 new cancer cases in rural areas, and the ASIR was 199.65 per 100 000. The top five cancers (lung cancer 1 060 600, colorectal cancer 517 100, thyroid cancer 466 100, liver cancer 367 700 and female breast cancer 357 200) accounted for 57.4% of all new cases. The estimated number of deaths from cancer in China in 2022 was 2 574 200 (1 629 300 in males and 944 900 in females), with an age-standardized mortality rate of Chinese population (ASMR) of 97.08 per 100 000 (127.70 per 100 000 in males and 68.67 per 100 000 in females). The number of deaths from cancer in urban and rural areas was about 1 400 600 and 1 173 400, with the ASMR of 92.37 and 103.97 per 100 000 in urban and rural areas, respectively. The top five leading cause of cancers death (lung cancer 733 300, liver cancer 316 500, gastric cancer 260 400, colorectal cancer 240 000 and esophageal cancer 187 500) accounted for 67.5% of all cancer deaths. Lung cancer ranked first in the incidence and mortality in men and women. The incidence rate in urban areas was higher than that in rural areas, while the mortality rate was lower than that in rural areas.Conclusions:The burden of cancer in China is still relatively heavy, with significant differences in cancer patterns in gender, urban-rural, and regional. The burden of cancer presents a coexistence of developed and developing countries, and the situation of cancer prevention and control is still serious in China.

Objective:The National Central Cancer Registry estimates the number of new cancer cases and deaths in China in 2022, using incidence and mortality data collected by the National Cancer Center.Methods:According to the data of 700 cancer registries in 2018 and the data of 106 cancer registries from 2010 to 2018, the age-period-cohort model was used to estimate the incidence rate and mortality rate of all cancers and 23 types of cancer in 2022, stratified by gender and urban and rural areas. We estimated the number of new cancer cases and deaths in China in 2022 based on the estimated rate and population data in 2022.Results:The estimated results showed that in 2022, there were approximately 4 824 700 new cancer cases in China (2 533 900 in males and 2 290 800 in females), with an age-standardized incidence rate of Chinese population (ASIR) of 208.58 per 100 000 (212.67 per 100 000 for males and 208.08 per 100 000 for females). Approximately 2 903 900 new cancer cases occurred in urban areas, with an ASIR of 212.95 per 100 000. It was estimated about 1 920 800 new cancer cases in rural areas, and the ASIR was 199.65 per 100 000. The top five cancers (lung cancer 1 060 600, colorectal cancer 517 100, thyroid cancer 466 100, liver cancer 367 700 and female breast cancer 357 200) accounted for 57.4% of all new cases. The estimated number of deaths from cancer in China in 2022 was 2 574 200 (1 629 300 in males and 944 900 in females), with an age-standardized mortality rate of Chinese population (ASMR) of 97.08 per 100 000 (127.70 per 100 000 in males and 68.67 per 100 000 in females). The number of deaths from cancer in urban and rural areas was about 1 400 600 and 1 173 400, with the ASMR of 92.37 and 103.97 per 100 000 in urban and rural areas, respectively. The top five leading cause of cancers death (lung cancer 733 300, liver cancer 316 500, gastric cancer 260 400, colorectal cancer 240 000 and esophageal cancer 187 500) accounted for 67.5% of all cancer deaths. Lung cancer ranked first in the incidence and mortality in men and women. The incidence rate in urban areas was higher than that in rural areas, while the mortality rate was lower than that in rural areas.Conclusions:The burden of cancer in China is still relatively heavy, with significant differences in cancer patterns in gender, urban-rural, and regional. The burden of cancer presents a coexistence of developed and developing countries, and the situation of cancer prevention and control is still serious in China.

Objective To investigate the distribution patterns of traditional Chinese medicine(TCM)constitution in 959 patients with endometriosis(EMs).Methods From January 2019 to November 2019,959 EMs patients were selected from Guang'anmen Hospital of China Academy of Chinese Medical Sciences,Beijing Obstetrics and Gynecology Hospital Affiliated to Capital Medical University,Beijing Hospital,Dongfang Hospital of Beijing University of Chinese Medicine,Beijing Friendship Hospital Affiliated to Capital Medical University,and Fuxing Hospital Affiliated to Capital Medical University.The general clinical information of the patients was recorded and then the TCM constitution was identified.After that,the correlation of TCM constitution distribution with concurrent constitution and the relationship of TCM constitution distribution with age and the complication of dysmenorrhea were analyzed.Results(1)The constitution types of EMs patients listed in descending order of the proportion were yang deficiency constitution(65.1％,624/959),qi stagnation constitution(58.4％,560/959),qi deficiency constitution(52.8％,506/959),blood stasis constitution(44.2％,424/959),phlegm-damp constitution(42.5％,408/959),damp-heat constitution(41.9％,402/959),yin deficiency constitution(39.6％,380/959),balanced constitution(26.8％,257/959),and inherited special constitution(16.6％,159/959).Among the patients,there were fewer patients with single constitution,accounting for 20.2％(194/959),and most of them had concurrent constitution types,accounting for 79.8％(765/959).(2)The association rule mining based on Apriori algorithm obtained 33 related rules.The concurrent constitution types of qi deficiency-yang deficiency,blood stasis-yang deficiency,and blood stasis-qi stagnation were the association rules with high confidence.(3)Compared with patients aged 35 years and below,the patients over 35 years old were predominated by high proportion of blood stasis constitution(P＜0.05).Compared with patients without dysmenorrhea,the patients with dysmenorrhea had the increased proportion of biased constitutions and the decreased proportion of balanced constitution(P＜0.05 or P＜0.01).Conclusion Yang deficiency constitution,qi stagnation constitution,qi deficiency constitution and blood stasis constitution are the high-risk constitution types of EMs patients.The concurrent constitution types are commonly seen in EMs patients,which are more common than single biased constitution.Management of EMs patients with the methods of warming yang,relieving stagnation,benefiting qi and activating blood will be helpful for correcting the biased constitutions in time and preventing disease progression,which will achieve the preventive treatment efficacy through TCM constitution correction.