Objective:To construct a prediction model for postoperative poor in-hospital prognosis in patients with traumatic brain injury (TBI) and evaluate its predictive performance.Methods:A retrospective case control study was conducted to analyze the clinical data of 1 120 TBI patients admitted to Changde Hospital Affiliated to Xiangya Medical College of Central South University from May 2019 to December 2024. The patients were divided into the training set ( n=784) and verification set ( n=336) at a ratio of 7∶3. Based on the Glasgow outcome scale-extended (GOS-E) at discharge, the training set was stratified into favorable prognosis group ( n=335, GOS-E 5-8 points) and poor prognosis group ( n=449, GOS-E 1-4 points). The two groups in the training set were compared in terms of general baseline indicators, TBI-related clinical indicators, and admission laboratory blood test results. Univariate analysis and Lasso regression analysis were employed to screen risk factors associated with postoperative poor in-hospital prognosis in TBI patients. Multivariate Logistic regression analysis was used to determine independent risk factors and construct a regression equation. The regression equation was presented using R language to create a visual nomogram for predicting postoperative poor in-hospital prognosis in TBI patients. In both the training set and verification set, the predictive performance of the model was evaluated by calculating the area under the receiver operating characteristic (ROC) curve (AUC), plotting calibration curves, and performing decision curve analysis (DCA). Results:The results of the univariate analysis indicated that the age, Charlson complication index (CCI), time from trauma to admission, time from trauma to operation, cause of injury, abbreviated injury scale (AIS) (head and neck), injury severity score (ISS), admission Glasgow coma scale (GCS), admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraventricular hemorrhage, subarachnoid hemorrhage, decompressive craniotomy, intraoperative blood loss, intraoperative blood transfusion, traumatic cerebral infarction, postoperative delayed bleeding, epilepsy seizures, as well as the following admission tested results including red blood cell count, white blood cell count, platelet count, neutrophil percentage, percentage of lymphocytes, albumin, total bilirubin, urea nitrogen, thrombin time (TT), prothrombin time (PT), international standardized ratio (INR), glutamic aminotransferase, alanine aminotransferase, creatinine, and blood glucose were statistically different between the two groups in the training set ( P<0.05). Lasso regression analysis suggested 14 risk factors of age, CCI, cause of injury, head and neck AIS, ISS, admission GCS, admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraoperative blood loss, admission platelet count, admission albumin, admission blood glucose for postoperative poor in-hospital prognosis. The results of the multivariate Logistic regression analysis showed that age ( OR=1.02, 95% CI 1.00, 1.03, P<0.01), CCI ( OR=1.46, 95% CI 1.02, 2.09, P<0.05), head and neck AIS ( OR=1.43, 95% CI 1.11, 1.85, P<0.01), ISS ( OR=2.16, 95% CI 1.39, 3.35, P<0.01), admission GCS ( OR=1.59, 95% CI 1.19, 2.13, P<0.01), intracerebral hematoma ( OR=4.41, 95% CI 2.15, 9.44, P<0.01), intraoperative blood loss ( OR=1.05, 95% CI 1.00, 1.09, P<0.05), admission platelet count ( OR=0.98, 95% CI 0.97, 0.99, P<0.01), admission blood glucose ( OR=1.08, 95% CI 1.02, 1.15, P<0.05) could be the main risk factors to construct a prediction model for postoperative poor in-hospital prognosis in TBI patients. Meanwhile, a regression equation was constructed: Logit[ P/(1- P)]=-2.4+ 0.02×"age"+0.38×"CCI"+0.36×"head and neck AIS"+0.77×"ISS"+0.47×"admission GCS"+1.48×"intracerebral hematoma"+0.05×intraoperative blood loss-0.02×admission platelet count+0.08×admission blood glucose. In the training set, the predictive model for poor postoperative in-hospital prognosis in TBI patients achieved an AUC of 0.87 (95% CI 0.84, 0.89), with a Youden′s index of 0.57, sensitivity of 73.70%, and specificity of 83.00%. In the verification set, the model showed an AUC of 0.80 (95% CI 0.76, 0.85), with a Youden′s index of 0.63, sensitivity of 65.20%, and specificity of 77.90%. In the training set, the Brier score for the calibration curve was 0.14 (95% CI 0.13, 0.16). In the verification set, the Brier score for the calibration curve was 0.18 (95% CI 0.15, 0.20). The DCA diagram indicated that the nomogram prediction model provided high clinical net benefit for predicting postoperative poor in-hospital prognosis in TBI patients. Conclusion:The prediction model for postoperative poor in-hospital prognosis in TBI patients, constructed based on age, CCI, head and neck AIS, ISS, admission GCS, intracerebral hematoma, intraoperative blood loss, admission platelet count, and admission blood glucose, exhibits good predictive performance.

AIM To observe the effects of Hugan Tablets on high-fat diet induced non-alcoholic fatty liver disease(NAFLD)in a mouse model,and the autophagy,pyroptosis and the PI3K/Akt/mTOR signaling pathway as well.METHODS The C57BL/6 mice were randomly divided into the normal group,the model group,the Hugan Tablets group(0.7 g/kg)and the Yishanfu group(0.23 g/kg),with 10 mice in each group.The NAFLD mouse model was established by 16 weeks feeding of high-fat diet.From the 13th week,the mice started their corresponding dosing of the drug by gavage followed by killing of the mice at the end of 16th week and collection of their serum and liver tissue samples.The mice had their serum ALT,AST,TG,TC,LDL levels,liver TG,TC,NEFA,MDA levels and activities of SOD and GSH-Px detected;their serum levels of IL-1β,IL-6 and TNF-αdetected by ELISA;their hepatic pathological changes observed using HE staining and oil red O staining;and their hepatic protein expressions of ACC,CPT1A,FAS,p-PI3K,p-Akt,p-mTOR,P62,LC3,NLRP3,GSDMD and Caspase1 detected by Western blot.RESULTS Compared with the model group,the Hugan Tablets group displayed decreased body weight and hepatosmatic index level(P＜0.01);decreased levels of serum ALT,AST,TG,TC,LDL,IL-6,IL-1β and TNF-α(P＜0.05,P＜0.01);increased hepatic levels of TG,TC,NEFA and MDA(P＜0.05);decreased activities of SOD and GSH-Px(P＜0.05);improved pathological changes of hepatic lipid deposition and hepatocytic ballooning and decreased NAS score and oil red O staining area(P＜0.01);decreased hepatic protein expressions of ACC1,FAS,NLRP3,Caspase1,GSDMD,P62,p-PI3K,p-Akt and p-mTOR(P＜0.05,P＜0.01);and increased protein expressions of CPT1A and LC3(P＜0.01).CONCLUSION Hugan Tablets can effectively prevent and control the development of high-fat diet induced NAFLD in mice,and the mechanism may be associated with the promotion of autophagy in hepatocytes and the inhibition of pyroptosis via the inhibition of PI3K/Akt/mTOR signaling pathway.

Objective:To investigate the completion rate of tumor evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients in the national multicenter real-world database.Methods:The prospective real-world study was conducted. The clinicopathological data of 1 074 patients who underwent surgical treatment for mid and low rectal cancer in 47 national medical institutions, including Peking Union Medical College Hospital et al, from May 12,2023 to May 11,2024 were collected. Observation indicators: (1) clinical characteristics of patients with mid and low rectal cancer; (2) initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer; (3) initial imaging evaluation of patients with mid and low rectal cancer; (4) imaging evaluation after neoadjuvant therapy for patients with mid and low rectal cancer. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( Q1, Q3). Count data were described as absoluter numbers and/or percentages. Results:(1) Clinical characteristics of patients with mid and low rectal cancer. Of the 1 074 patients, there were 713 males and 361 females, aged 63(56,70)years. The body mass index of 1 074 patients was 24(21,26)kg/m 2.For American Society of Anesthesiologists classification, there were 147 cases of stage Ⅰ, 641 cases of stage Ⅱ, 157 cases of stage Ⅲ, 2 cases of stage Ⅳ, and there were 127 cases missing data. (2) Initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer. Of the 1 074 patients, there were 787 cases (73.28%) undergoing complete colonoscopy, and there were only 197 cases (18.34%) undergoing immunohistochemical evaluation of all four mismatch repair proteins. (3) Initial imaging evaluation of patients with mid and low rectal cancer. Of the 1 074 patients, there were 842(78.40%) patients completing magnetic resonance imaging (MRI) or ultrasound evaluation, and there were 914(85.10%) patients completing chest, abdomen, and pelvis enhanced computed tomography (CT) evaluation. In the 149 patients completing rectal ultrasound evaluation, there were 122 cases (81.88%) comple-ting T staging evaluation, and there were 81 cases (54.36%) completing N staging evaluation. In the 808 patients completing rectal MRI evaluation, there were 708 cases (87.62%) completing T staging evaluation, and there were 590 cases (73.02%) completing N staging evaluation. (4) Imaging evalua-tion after neoadjuvant therapy for patients with mid and low rectal cancer. Of the 388 patients with neoadjuvant therapy, there were 332 patients (85.57%) completing MRI or ultrasound evaluation, and there were 327 patients (84.28%) completing chest, abdomen, and pelvis enhanced CT evalua-tion. In the 70 patients completing rectal ultrasound evaluation, there were 65 cases (92.86%) com-pleting T staging evaluation, and there were 49 cases (70.00%) completing N staging evaluation. In the 327 patients completing rectal MRI evaluation, there were 246 cases (75.23%) completing T staging, and there were 228 cases (69.72%) completing N staging evaluation. Conclusion:The com-pletion rate of tumor imaging evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients on a national scale is relatively good.

AIM To observe the effects of Hugan Tablets on high-fat diet induced non-alcoholic fatty liver disease(NAFLD)in a mouse model,and the autophagy,pyroptosis and the PI3K/Akt/mTOR signaling pathway as well.METHODS The C57BL/6 mice were randomly divided into the normal group,the model group,the Hugan Tablets group(0.7 g/kg)and the Yishanfu group(0.23 g/kg),with 10 mice in each group.The NAFLD mouse model was established by 16 weeks feeding of high-fat diet.From the 13th week,the mice started their corresponding dosing of the drug by gavage followed by killing of the mice at the end of 16th week and collection of their serum and liver tissue samples.The mice had their serum ALT,AST,TG,TC,LDL levels,liver TG,TC,NEFA,MDA levels and activities of SOD and GSH-Px detected;their serum levels of IL-1β,IL-6 and TNF-αdetected by ELISA;their hepatic pathological changes observed using HE staining and oil red O staining;and their hepatic protein expressions of ACC,CPT1A,FAS,p-PI3K,p-Akt,p-mTOR,P62,LC3,NLRP3,GSDMD and Caspase1 detected by Western blot.RESULTS Compared with the model group,the Hugan Tablets group displayed decreased body weight and hepatosmatic index level(P＜0.01);decreased levels of serum ALT,AST,TG,TC,LDL,IL-6,IL-1β and TNF-α(P＜0.05,P＜0.01);increased hepatic levels of TG,TC,NEFA and MDA(P＜0.05);decreased activities of SOD and GSH-Px(P＜0.05);improved pathological changes of hepatic lipid deposition and hepatocytic ballooning and decreased NAS score and oil red O staining area(P＜0.01);decreased hepatic protein expressions of ACC1,FAS,NLRP3,Caspase1,GSDMD,P62,p-PI3K,p-Akt and p-mTOR(P＜0.05,P＜0.01);and increased protein expressions of CPT1A and LC3(P＜0.01).CONCLUSION Hugan Tablets can effectively prevent and control the development of high-fat diet induced NAFLD in mice,and the mechanism may be associated with the promotion of autophagy in hepatocytes and the inhibition of pyroptosis via the inhibition of PI3K/Akt/mTOR signaling pathway.

Objective:To investigate the completion rate of tumor evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients in the national multicenter real-world database.Methods:The prospective real-world study was conducted. The clinicopathological data of 1 074 patients who underwent surgical treatment for mid and low rectal cancer in 47 national medical institutions, including Peking Union Medical College Hospital et al, from May 12,2023 to May 11,2024 were collected. Observation indicators: (1) clinical characteristics of patients with mid and low rectal cancer; (2) initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer; (3) initial imaging evaluation of patients with mid and low rectal cancer; (4) imaging evaluation after neoadjuvant therapy for patients with mid and low rectal cancer. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( Q1, Q3). Count data were described as absoluter numbers and/or percentages. Results:(1) Clinical characteristics of patients with mid and low rectal cancer. Of the 1 074 patients, there were 713 males and 361 females, aged 63(56,70)years. The body mass index of 1 074 patients was 24(21,26)kg/m 2.For American Society of Anesthesiologists classification, there were 147 cases of stage Ⅰ, 641 cases of stage Ⅱ, 157 cases of stage Ⅲ, 2 cases of stage Ⅳ, and there were 127 cases missing data. (2) Initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer. Of the 1 074 patients, there were 787 cases (73.28%) undergoing complete colonoscopy, and there were only 197 cases (18.34%) undergoing immunohistochemical evaluation of all four mismatch repair proteins. (3) Initial imaging evaluation of patients with mid and low rectal cancer. Of the 1 074 patients, there were 842(78.40%) patients completing magnetic resonance imaging (MRI) or ultrasound evaluation, and there were 914(85.10%) patients completing chest, abdomen, and pelvis enhanced computed tomography (CT) evaluation. In the 149 patients completing rectal ultrasound evaluation, there were 122 cases (81.88%) comple-ting T staging evaluation, and there were 81 cases (54.36%) completing N staging evaluation. In the 808 patients completing rectal MRI evaluation, there were 708 cases (87.62%) completing T staging evaluation, and there were 590 cases (73.02%) completing N staging evaluation. (4) Imaging evalua-tion after neoadjuvant therapy for patients with mid and low rectal cancer. Of the 388 patients with neoadjuvant therapy, there were 332 patients (85.57%) completing MRI or ultrasound evaluation, and there were 327 patients (84.28%) completing chest, abdomen, and pelvis enhanced CT evalua-tion. In the 70 patients completing rectal ultrasound evaluation, there were 65 cases (92.86%) com-pleting T staging evaluation, and there were 49 cases (70.00%) completing N staging evaluation. In the 327 patients completing rectal MRI evaluation, there were 246 cases (75.23%) completing T staging, and there were 228 cases (69.72%) completing N staging evaluation. Conclusion:The com-pletion rate of tumor imaging evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients on a national scale is relatively good.

Objective:To construct a prediction model for postoperative poor in-hospital prognosis in patients with traumatic brain injury (TBI) and evaluate its predictive performance.Methods:A retrospective case control study was conducted to analyze the clinical data of 1 120 TBI patients admitted to Changde Hospital Affiliated to Xiangya Medical College of Central South University from May 2019 to December 2024. The patients were divided into the training set ( n=784) and verification set ( n=336) at a ratio of 7∶3. Based on the Glasgow outcome scale-extended (GOS-E) at discharge, the training set was stratified into favorable prognosis group ( n=335, GOS-E 5-8 points) and poor prognosis group ( n=449, GOS-E 1-4 points). The two groups in the training set were compared in terms of general baseline indicators, TBI-related clinical indicators, and admission laboratory blood test results. Univariate analysis and Lasso regression analysis were employed to screen risk factors associated with postoperative poor in-hospital prognosis in TBI patients. Multivariate Logistic regression analysis was used to determine independent risk factors and construct a regression equation. The regression equation was presented using R language to create a visual nomogram for predicting postoperative poor in-hospital prognosis in TBI patients. In both the training set and verification set, the predictive performance of the model was evaluated by calculating the area under the receiver operating characteristic (ROC) curve (AUC), plotting calibration curves, and performing decision curve analysis (DCA). Results:The results of the univariate analysis indicated that the age, Charlson complication index (CCI), time from trauma to admission, time from trauma to operation, cause of injury, abbreviated injury scale (AIS) (head and neck), injury severity score (ISS), admission Glasgow coma scale (GCS), admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraventricular hemorrhage, subarachnoid hemorrhage, decompressive craniotomy, intraoperative blood loss, intraoperative blood transfusion, traumatic cerebral infarction, postoperative delayed bleeding, epilepsy seizures, as well as the following admission tested results including red blood cell count, white blood cell count, platelet count, neutrophil percentage, percentage of lymphocytes, albumin, total bilirubin, urea nitrogen, thrombin time (TT), prothrombin time (PT), international standardized ratio (INR), glutamic aminotransferase, alanine aminotransferase, creatinine, and blood glucose were statistically different between the two groups in the training set ( P<0.05). Lasso regression analysis suggested 14 risk factors of age, CCI, cause of injury, head and neck AIS, ISS, admission GCS, admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraoperative blood loss, admission platelet count, admission albumin, admission blood glucose for postoperative poor in-hospital prognosis. The results of the multivariate Logistic regression analysis showed that age ( OR=1.02, 95% CI 1.00, 1.03, P<0.01), CCI ( OR=1.46, 95% CI 1.02, 2.09, P<0.05), head and neck AIS ( OR=1.43, 95% CI 1.11, 1.85, P<0.01), ISS ( OR=2.16, 95% CI 1.39, 3.35, P<0.01), admission GCS ( OR=1.59, 95% CI 1.19, 2.13, P<0.01), intracerebral hematoma ( OR=4.41, 95% CI 2.15, 9.44, P<0.01), intraoperative blood loss ( OR=1.05, 95% CI 1.00, 1.09, P<0.05), admission platelet count ( OR=0.98, 95% CI 0.97, 0.99, P<0.01), admission blood glucose ( OR=1.08, 95% CI 1.02, 1.15, P<0.05) could be the main risk factors to construct a prediction model for postoperative poor in-hospital prognosis in TBI patients. Meanwhile, a regression equation was constructed: Logit[ P/(1- P)]=-2.4+ 0.02×"age"+0.38×"CCI"+0.36×"head and neck AIS"+0.77×"ISS"+0.47×"admission GCS"+1.48×"intracerebral hematoma"+0.05×intraoperative blood loss-0.02×admission platelet count+0.08×admission blood glucose. In the training set, the predictive model for poor postoperative in-hospital prognosis in TBI patients achieved an AUC of 0.87 (95% CI 0.84, 0.89), with a Youden′s index of 0.57, sensitivity of 73.70%, and specificity of 83.00%. In the verification set, the model showed an AUC of 0.80 (95% CI 0.76, 0.85), with a Youden′s index of 0.63, sensitivity of 65.20%, and specificity of 77.90%. In the training set, the Brier score for the calibration curve was 0.14 (95% CI 0.13, 0.16). In the verification set, the Brier score for the calibration curve was 0.18 (95% CI 0.15, 0.20). The DCA diagram indicated that the nomogram prediction model provided high clinical net benefit for predicting postoperative poor in-hospital prognosis in TBI patients. Conclusion:The prediction model for postoperative poor in-hospital prognosis in TBI patients, constructed based on age, CCI, head and neck AIS, ISS, admission GCS, intracerebral hematoma, intraoperative blood loss, admission platelet count, and admission blood glucose, exhibits good predictive performance.

The comparison between traditional Chinese medicine Jinzhen oral liquid (JZOL) and Western medicine in treating children with acute bronchitis (AB) showed encouraging outcomes. This trial evaluated the efficacy and safety of the JZOL for improving cough and expectoration in children with AB. 480 children were randomly assigned to take JZOL or ambroxol hydrochloride and clenbuterol hydrochloride oral solution for 7 days. The primary outcome was time-to-cough resolution. The median time-to-cough resolution in both groups was 5.0 days and the antitussive onset median time was only 1 day. This randomized controlled trial showed that JZOL was not inferior to cough suppressant and phlegm resolving western medicine in treating cough and sputum and could comprehensively treat respiratory and systemic discomfort symptoms. Combined with clinical trials, the mechanism of JZOL against AB was uncovered by network target analysis, it was found that the pathways in TRP channels like IL-1β/IL1R/TRPV1/TRPA1, NGF/TrkA/TRPV1/TRPA1, and PGE2/EP/PKA/TRPV1/TRPA1 might play important roles. Animal experiments further confirmed that inflammation and the immune regulatory effect of JZOL in the treatment of AB were of vital importance and TRP channels were the key mechanism of action.

Hepatocellular carcinoma(HCC)is a serious neoplastic disease with increasing incidence and mortality,accounting for 90%of all liver cancers.Hepatitis viruses are the major causative agents in the development of HCC.Hepatitis A virus(HAV)primarily causes acute infections,which is associated with HCC to a certain extent,as shown by clinicopathological studies.Chronic hepatitis B virus(HBV)or hepatitis C virus(HCV)infections lead to persistent liver inflammation and cirrhosis,disrupt multiple pathways associated with cellular apoptosis and proliferation,and are the most common viral precursors of HCC.Mutations in the HBV X protein(HBx)gene are closely associated with the incidence of HCC,while the expression of HCV core proteins contributes to hepatocellular lipid accumulation,thereby promoting tumorigenesis.In the clinical setting,hepatitis D virus(HDV)frequently co-infects with HBV,increasing the risk of chronic hepatitis.Hepatitis E virus(HEV)usually causes acute infections.However,chronic infections of HEV have been increasing recently,particularly in immuno-compromised patients and organ transplant recipients,which may increase the risk of progression to cirrhosis and the occurrence of HCC.Early detection,effective intervention and vaccination against these viruses may significantly reduce the incidence of liver cancer,while mechanistic insights into the interplay between hepatitis viruses and HCC may facilitate the development of more effective intervention strategies.This article provides a comprehensive overview of hepatitis viruses and reviews recent advances in research on aberrant hepatic immune responses and the pathogenesis of HCC due to viral infection.

OBJECTIVE: To investigate the correlation between ¹⁸Fluoro-deoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) metabolic parameters and peripheral blood circulating tumour DNA (ctDNA) in patients with diffuse large B-cell lymphoma (DLBCL), and the prognostic value of these two types of parameters in predicting progression-free survival (PFS). METHODS: Clinical, PET/CT and ctDNA data of DLBCL patients who underwent peripheral blood ctDNA testing and corresponding PET/CT scans during the same period were retrospectively analyzed. At the time of ctDNA sampling and PET scan, patients were divided into baseline and relapsed/refractory (R/R) groups according to different disease conditions. CtDNA mutation abundance was expressed as variant allele frequency (VAF), including maximum VAF (maxVAF) and mean VAF (meanVAF). Total metabolic tumour volume (TMTV) and total lesion glycolysis (TLG) were obtained by the 41% maximum normalized uptake value method, and the distance between the two farthest lesions (Dmax) was used to assess the correlation between PET parameters and ctDNA mutation abundance using Spearman correlation analysis. The receiver operating characteristic (ROC) curves were used to obtain the optical cut-off values of those parameters in predicting PFS in the baseline and R/R groups, respectively. Survival curves were outlined using the Kaplan-Meier method and log-rank test was performed to compare survival differences. RESULTS: A total of 67 DLBCL patients ［28 males and 39 females, median age 56.0(46.0, 67.0) years］ were included and divided into baseline group (29 cases) and R/R group (38 cases). Among these PET parameters, baseline TMTV, TLG, and Dmax were significantly correlated with baseline ctDNA mutation abundance, except for maximum standardized uptake value (SUVmax) (maxVAF vs TMTV: r=0.711; maxVAF vs TLG: r=0.709; maxVAF vs Dmax: r=0.672; meanVAF vs TMTV: r=0.682; meanVAF vs TLG: r=0.677; meanVAF vs Dmax: r=0.646). While in all patients, these correlations became weaker significantly. Among R/R patients, only TMTV had a weak correlation with meanVAF (r=0.376). ROC analysis showed that, the specificity of TMTV, TLG and Dmax in predicting PFS was better than mutation abundance, while the sensitivity of ctDNA mutation abundance was better. Except R/R patients, TMTV, TLG, Dmax, and VAF were significantly different at normal/elevated lactate dehydrogenase in baseline group and all patients (all P<0.05). Survival curves indicated that high TMTV (>109.5 cm³), high TLG (>2 141.3), high Dmax (>33.1 cm) and high VAF (maxVAF>7.74%, meanVAF>4.39%) were risk factors for poor PFS in baseline patients, while only high VAF in R/R patients (both maxVAF and meanVAF >0.61%) was a risk factor for PFS. CONCLUSION PET-derived parameters correlate well with ctDNA mutation abundance, especially in baseline patients. VAF of ctDNA predicts PFS more sensitively than PET metabolic parameters, while PET metabolic tumour burden with better specificity. TMTV, TLG and VAF all have good prognostic value for PFS. PET/CT combined with ctDNA has potential for further studies in prognostic assessment and personalized treatment.
Male ; Female ; Humans ; Middle Aged ; Positron Emission Tomography Computed Tomography ; Fluorodeoxyglucose F18 ; Circulating Tumor DNA/genetics* ; Retrospective Studies ; Positron-Emission Tomography ; Survival Analysis ; Lymphoma, Large B-Cell, Diffuse/metabolism* ; Prognosis