BACKGROUND Hepatocellular carcinoma(HCC)is the most common primary liver malignancy.Ablation therapy is one of the first-line treatments for early HCC.Accurately predicting early recurrence(ER)is crucial for making pr...BACKGROUND Hepatocellular carcinoma(HCC)is the most common primary liver malignancy.Ablation therapy is one of the first-line treatments for early HCC.Accurately predicting early recurrence(ER)is crucial for making precise treatment plans and improving patient prognosis.AIM To establish an intratumoral and peritumoral model for predicting ER in HCC patients following curative ablation.METHODS This study included a total of 288 patients from three Centers.The patients were divided into a primary cohort(n=222)and an external cohort(n=66).Radiomics and deep learning methods were combined for feature extraction,and models were constructed following a three-step feature selection process.Model performance was evaluated using the area under the receiver operating characteristic curve(AUC),while calibration curves and decision curve analysis(DCA)were used to assess calibration and clinical utility.Finally,Kaplan-Meier(K-M)analysis was used to stratify patients according to progression-free survival(PFS)and overall survival(OS).RESULTS The combined model,which utilizes the light gradient boosting machine learning algorithm and incorporates both intratumoral and peritumoral regions(5 mm and 10 mm),demonstrated the best predictive performance for ER following HCC ablation,achieving AUCs of 0.924 in the training set,0.899 in the internal validation set,and 0.839 in the external validation set.Calibration and DCA curves confirmed strong calibration and clinical utility,whereas K-M curves provided risk stratification for PFS and OS in HCC patients.CONCLUSION The most efficient model integrated the tumor region with the peritumoral 5 mm and 10 mm regions.This model provides a noninvasive,effective,and reliable method for predicting ER after curative ablation of HCC.展开更多
Early recurrence(ER)following surgery for rectal cancer is a significant factor impacting patient survival rates.Tsai et al identified age,preoperative neoadjuvant therapy,length of hospital stay,tumour location,and p...Early recurrence(ER)following surgery for rectal cancer is a significant factor impacting patient survival rates.Tsai et al identified age,preoperative neoadjuvant therapy,length of hospital stay,tumour location,and pathological stage as factors influencing the risk of ER.Postoperative monitoring for ER should encompass a thorough medical history review,physical examination,tumour marker testing,and imaging studies.Additionally,noninvasive circulating tumour cell DNA testing can be utilized to predict ER.Treatment strategies may involve radical surgery,radiation therapy,chemotherapy,and immunotherapy.Through a comprehensive analysis of risk factors,the optimization of monitoring methods,and the development of personalized treatment strategies,it is anticipated that both the efficacy of treatment and the quality of life for rectal cancer patients with postoperative recurrence can be significantly improved.展开更多
In a recent study by He et al,the nomogram integrates postoperative serum tumor markers such as carbohydrate antigen 19-9 and carcinoembryonic antigen,thereby improving the accuracy of identifying high-risk patients c...In a recent study by He et al,the nomogram integrates postoperative serum tumor markers such as carbohydrate antigen 19-9 and carcinoembryonic antigen,thereby improving the accuracy of identifying high-risk patients compared to relying solely on preoperative markers,which has significant implications for customizing adjuvant therapy and potentially improving outcomes for this aggressive form of cancer.However,the study’s single-center design and short follow-up period may limit the generalizability of its findings and potentially introduce reporting bias.Future studies could consider additional confounding factors,such as adjuvant chemotherapy and variations in surgical techniques,to improve the model’s accuracy.Furthermore,it would be valuable to validate the nomogram in broader,prospective cohorts and explore the inclusion of additional markers like circulating tumor DNA to refine further its predictive power and applicability across diverse patient populations.展开更多
We provide an editorial of recent findings on early recurrence(ER)in rectal cancer(RC),focusing on the study on ER of resectable RC by Tsai et al.The study established an 8-month recurrence-free survival cut-off for d...We provide an editorial of recent findings on early recurrence(ER)in rectal cancer(RC),focusing on the study on ER of resectable RC by Tsai et al.The study established an 8-month recurrence-free survival cut-off for differentiating ER from late recurrence,with implications for postrecurrence survival and overall survival.This offers not only a valuable timeframe for enhancing surveillance strategies in patients at higher risk,especially those who have undergone neoadjuvant chemoradiotherapy(CRT),but also raises questions about its applicability across different populations.Furthermore,the article suggests that while CRT is very effective in reducing locoregional recurrence,this treatment alone may not fully address the overall risk of ER.The authors advocate for personalized risk assessment and intensive surveillance during the postoperative period to improve outcomes,particularly in the first year.Future research should focus on larger,multicenter studies and incorporate advanced diagnostic techniques with genetic and molecular biomarkers to enhance prediction and management of ER.The ultimate goal is to refine treatment and surveillance strategies to improve survival and quality of life for patients with RC.展开更多
BACKGROUND Early recurrence is an important factor affecting the prognosis of hepatocellular carcinoma(HCC),but its preoperative prediction remains challenging.AIM To explore the value of a multimodal interpretable fu...BACKGROUND Early recurrence is an important factor affecting the prognosis of hepatocellular carcinoma(HCC),but its preoperative prediction remains challenging.AIM To explore the value of a multimodal interpretable fusion model combining computed tomography(CT)habitat imaging(HI),radiomics,and clinical features in predicting early recurrence of HCC and analyze its correlation with pathological indicators.METHODS The 191 HCC patients were categorized into early recurrence and non-early recurrence groups based on postoperative follow-up outcomes,and randomly divided into training and testing sets in a 7:3 ratio.Based on CT arterial phase and clinical data,the habitat model,radiomics model,clinical model,and fusion model were constructed and compared for their predictive ability in early recurrence of HCC.For the optimal model,SHapley Additive exPlanations(SHAP)analysis was performed to evaluate the contribution of different features in the model,and the correlation between HI and radiomics features with tumor microvascular invasion(MVI),Ki67 expression,GPC-3 expression,and pathological grading was analyzed.RESULTS The fusion model demonstrated the best performance in predicting early recurrence of HCC,achieving the area under the curve of 0.933 on the validation set.The decision curve analysis curve indicated that the fusion model yielded the highest clinical net benefit.SHAP analysis provided valuable insights into explaining the fusion model's prediction of early HCC recurrence.Correlation analysis revealed significant associations between certain radiomics and Habitat features and pathological indicators such as MVI and Ki-67 expression in HCC.CONCLUSION An interpretable fusion model integrating clinical,radiomic,and habitat features can assist clinicians in identifying early postoperative recurrence of HCC,offering significant potential for prognosis prediction and clinical management.展开更多
BACKGROUND Predicting early recurrence(ER),(≤12 months)after pancreatic ductal adenocar-cinoma(PDAC)resection remains challenging.Preoperative biomarkers such as carbohydrate antigen 19-9(CA19-9)and computed tomograp...BACKGROUND Predicting early recurrence(ER),(≤12 months)after pancreatic ductal adenocar-cinoma(PDAC)resection remains challenging.Preoperative biomarkers such as carbohydrate antigen 19-9(CA19-9)and computed tomography(CT)lack optimal specificity and reproducibility.Extracellular volume(ECV),measured on equi-librium-phase CT to quantify stromal fibrosis,correlates with PDAC progression but its utility for ER prediction is unknown.This study evaluates preoperative CT-ECV as a novel biomarker to predict ER following curative-intent PDAC resection.This retrospective study included 93 PDAC patients undergoing R0 resection and preoperative pancreatic CT from January 2020 to November 2023.Clinical and CT features were analyzed.ECV was calculated using unenhanced and equilibrium-phase CT.Univariable and multivariable Cox regression identified ER predictors,followed by receiver operating characteristic analysis.Recurrence-free survival(RFS)was assessed by the Kaplan-Meier method.RESULTS Multivariable analysis identified elevated CT-ECV[hazard ratio(HR)=1.05;95%confidence interval(CI):1.02-1.09;P=0.003],high preoperative CA19-9(HR=1.00;95%CI:1.00-1.00;P=0.002),and poor tumor grade(HR=2.51;95%CI:1.20-5.22;P=0.014)as independent ER predictors.CT-ECV demonstrated comparable predictive accuracy to tumor grade[areas under the curve(AUC):0.736 vs 0.650;P=0.202].Combining CT-ECV and CA19-9 achieved a higher AUC than tumor grade alone(0.759 vs 0.650;P<0.05).Kaplan-Meier analysis revealed sig-nificantly shorter RFS in patients with low CT-ECV(≤35.37%),elevated CA19-9(>55 U/mL),or poorly differen-tiated tumors compared to those with high CT-ECV(>35.37%),low CA19-9(≤55 U/mL),or moderately/well-differentiated tumors.CONCLUSION CT-derived ECV is a promising non-invasive biomarker for preoperative ER prediction in PDAC.Combined with CA19-9,it outperforms tumor grade in stratifying recurrence risk,offering a clinically actionable tool for opti-mizing postoperative management.展开更多
Pancreatic ductal adenocarcinoma(PDAC),a"silent killer"with elusive early symptoms and poor prognosis,sees nearly half of patients experience recurrence within a year post-curative-intent surgery.Very early ...Pancreatic ductal adenocarcinoma(PDAC),a"silent killer"with elusive early symptoms and poor prognosis,sees nearly half of patients experience recurrence within a year post-curative-intent surgery.Very early recurrence(VER),defined as recurrence within 12 weeks postoperatively and first termed"biological R^(2) resection"by Belfiori et al,remains a clinical puzzle.Martlıet al’s recent retrospective cohort study offers crucial insights into this understudied issue,identifies predictive factors that challenge long-held beliefs,and calls for a rethink of risk stratification and postoperative management for PDAC patients.Martlıet al studied 303 PDAC patients at a high-volume center from 2019 to 2024,with VER affecting 9.24%(28 patients)of the cohort.The study’s strength lies in combining traditional statistical analyses and machine learning(random forest modeling)to capture nonlinear relationships between clinicopathological factors and VER risk.Key findings include:(1)Poorly differentiated(G3)tumors are the strongest VER predictor(OR=2.43,P<0.001;random forest importance score=0.35),with 92.85%of VER patients having G3 tumors(vs 45.81%of non-VER patients);(2)Contrary to prior studies,pancreatic head tumors(89.28%of VER patients vs 83.66%of non-VER patients,P=0.031)were linked to VER;(3)Elevated red cell distribution width is a weaker predictor(random forest importance score=0.20,P=0.03 for group difference,P=0.079 in multivariate analysis);and(4)VER correlates with significantly higher 6-month mortality(32.44%vs 14.77%in non-VER patients,P=0.032).展开更多
BACKGROUND： Early recurrence （ER） after hepatic resection （HR） is a poor prognostic factor for patients with hepatocellular carcinoma （HCC）. This study aimed to identify the clinico- pathological features, outc...BACKGROUND： Early recurrence （ER） after hepatic resection （HR） is a poor prognostic factor for patients with hepatocellular carcinoma （HCC）. This study aimed to identify the clinico- pathological features, outcomes, and risk factors for ER after HR for small HCC in order to clarify the reasons why ER is a worse recurrence pattern. METHODS： We retrospectively examined 130 patients who underwent HR for small HCC （___30 mm）. Recurrence was clas- sifted into ER （〈2 years） and late recurrence （LR） （_〉2 years）. The clinicopathological features, outcomes, and risk factors for ER were analyzed by multivariate analysis. RESULTS： ER was observed in 39 patients （30.0%）. The sur- vival rate of the ER group was significantly lower than that of the LR group （P〈0.005）, and ER was an independent prognos- tic factor for poor survival （P=0.0001）. The ER group had a significantly higher frequency （P=0.0039） and shorter interval （P=0.027） of development to carcinoma beyond the Milan criteria （DBMC） compared with the LR group, and ER was an independent risk factor for DBMC （P〈0.0001）. Multi-nodularity, non-simple nodular type, and microvascular invasion were independent predictors for ER （P=0.012, 0.010, and 0.019, respectively）.CONCLUSIONS： ER was a highly malignant recurrence pattern associated with DBMC and subsequent poor survival after HR for small HCC. Multi-nodularity, non-simple nodular type, and microvascular invasion predict ER, and taking these factors into consideration may be useful for the decision of the treatment strategy for small HCC after HR.展开更多
BACKGROUND The prognosis for hepatocellular carcinoma(HCC)in the presence of cirrhosis is unfavourable,primarily attributable to the high incidence of recurrence.AIM To develop a machine learning model for predicting ...BACKGROUND The prognosis for hepatocellular carcinoma(HCC)in the presence of cirrhosis is unfavourable,primarily attributable to the high incidence of recurrence.AIM To develop a machine learning model for predicting early recurrence(ER)of posthepatectomy HCC in patients with cirrhosis and to stratify patients’overall survival(OS)based on the predicted risk of recurrence.METHODS In this retrospective study,214 HCC patients with cirrhosis who underwent curative hepatectomy were examined.Radiomics feature selection was conducted using the least absolute shrinkage and selection operator and recursive feature elimination methods.Clinical-radiologic features were selected through univariate and multivariate logistic regression analyses.Five machine learning methods were used for model comparison,aiming to identify the optimal model.The model’s performance was evaluated using the receiver operating characteristic curve[area under the curve(AUC)],calibration,and decision curve analysis.Additionally,the Kaplan-Meier(K-M)curve was used to evaluate the stratification effect of the model on patient OS.RESULTS Within this study,the most effective predictive performance for ER of post-hepatectomy HCC in the background of cirrhosis was demonstrated by a model that integrated radiomics features and clinical-radiologic features.In the training cohort,this model attained an AUC of 0.844,while in the validation cohort,it achieved a value of 0.790.The K-M curves illustrated that the combined model not only facilitated risk stratification but also exhibited significant discriminatory ability concerning patients’OS.CONCLUSION The combined model,integrating both radiomics and clinical-radiologic characteristics,exhibited excellent performance in HCC with cirrhosis.The K-M curves assessing OS revealed statistically significant differences.展开更多
BACKGROUND Radical resection remains an effective strategy for patients with hepatocellular carcinoma(HCC).Unfortunately,the postoperative early recurrence(recurrence within 2 years)rate is still high.AIM To develop a...BACKGROUND Radical resection remains an effective strategy for patients with hepatocellular carcinoma(HCC).Unfortunately,the postoperative early recurrence(recurrence within 2 years)rate is still high.AIM To develop a radiomics model based on preoperative contrast-enhanced computed tomography(CECT)to evaluate early recurrence in HCC patients with a single tumour.METHODS We enrolled a total of 402 HCC patients from two centres who were diagnosed with a single tumour and underwent radical resection.First,the features from the portal venous and arterial phases of CECT were extracted based on the region of interest,and the early recurrence-related radiomics features were selected via the least absolute shrinkage and selection operator proportional hazards model(LASSO Cox)to determine radiomics scores for each patient.Then,the clinicopathologic data were combined to develop a model to predict early recurrence by Cox regression.Finally,we evaluated the prediction performance of this model by multiple methods.RESULTS A total of 1915 radiomics features were extracted from CECT images,and 31 of them were used to determine the radiomics scores,which showed a significant difference between the early recurrence and nonearly recurrence groups.Univariate and multivariate Cox regression analyses showed that radiomics scores and serum alphafetoprotein were independent indicators,and they were used to develop a combined model to predict early recurrence.The area under the receiver operating characteristic curve values for the training and validation cohorts were 0.77 and 0.74,respectively,while the C-indices were 0.712 and 0.674,respectively.The calibration curves and decision curve analysis showed satisfactory accuracy and clinical utilities.Kaplan-Meier curves based on recurrence-free survival and overall survival showed significant differences.CONCLUSION The preoperative radiomics model was shown to be effective for predicting early recurrence among HCC patients with a single tumour.展开更多
The high rate of early recurrence in hepatocellular carcinoma(HCC)post curative surgical intervention poses a substantial clinical hurdle,impacting patient outcomes and complicating postoperative management.The advent...The high rate of early recurrence in hepatocellular carcinoma(HCC)post curative surgical intervention poses a substantial clinical hurdle,impacting patient outcomes and complicating postoperative management.The advent of machine learning provides a unique opportunity to harness vast datasets,identifying subtle patterns and factors that elude conventional prognostic methods.Machine learning models,equipped with the ability to analyse intricate relationships within datasets,have shown promise in predicting outcomes in various medical disciplines.In the context of HCC,the application of machine learning to predict early recurrence holds potential for personalized postoperative care strategies.This editorial comments on the study carried out exploring the merits and efficacy of random survival forests(RSF)in identifying significant risk factors for recurrence,stratifying patients at low and high risk of HCC recurrence and comparing this to traditional COX proportional hazard models(CPH).In doing so,the study demonstrated that the RSF models are superior to traditional CPH models in predicting recurrence of HCC and represent a giant leap towards precision medicine.展开更多
Background:Early recurrence results in poor prognosis of patients with hepatocellular carcinoma(HCC)after liver transplantation(LT).This study aimed to explore the value of computed tomography(CT)-based radiomics nomo...Background:Early recurrence results in poor prognosis of patients with hepatocellular carcinoma(HCC)after liver transplantation(LT).This study aimed to explore the value of computed tomography(CT)-based radiomics nomogram in predicting early recurrence of patients with HCC after LT.Methods:A cohort of 151 patients with HCC who underwent LT between December 2013 and July 2019 were retrospectively enrolled.A total of 1218 features were extracted from enhanced CT images.The least absolute shrinkage and selection operator algorithm(LASSO)logistic regression was used for dimension reduction and radiomics signature building.The clinical model was constructed after the analysis of clin-ical factors,and the nomogram was constructed by introducing the radiomics signature into the clinical model.The predictive performance and clinical usefulness of the three models were evaluated using re-ceiver operating characteristic(ROC)curve analysis and decision curve analysis(DCA),respectively.Cali-bration curves were plotted to assess the calibration of the nomogram.Results:There were significant differences in radiomics signature among early recurrence patients and non-early recurrence patients in the training cohort(P<0.001)and validation cohort(P<0.001).The nomogram showed the best predictive performance,with the largest area under the ROC curve in the training(0.882)and validation(0.917)cohorts.Hosmer-Lemeshow testing confirmed that the nomogram showed good calibration in the training(P=0.138)and validation(P=0.396)cohorts.DCA showed if the threshold probability is within 0.06-1,the nomogram had better clinical usefulness than the clinical model.Conclusions:Our CT-based radiomics nomogram can preoperatively predict the risk of early recurrence in patients with HCC after LT.展开更多
BACKGROUND Pancreatic ductal adenocarcinoma(PDAC)is a serious disease with a poor prognosis.Only a minority of patients undergo surgery due to the advanced stage of the disease,and patients with early-stage disease,wh...BACKGROUND Pancreatic ductal adenocarcinoma(PDAC)is a serious disease with a poor prognosis.Only a minority of patients undergo surgery due to the advanced stage of the disease,and patients with early-stage disease,who are expected to have a better prognosis,often experience recurrence.Thus,it is important to identify the risk factors for early recurrence and to develop an adequate treatment plan.AIM To evaluate the predictive factors associated with the early recurrence of earlystage PDAC.METHODS This study enrolled 407 patients with stage I PDAC undergoing upfront surgical resection between January 2000 and April 2016.Early recurrence was defined as a diagnosis of recurrence within 6 mo of surgery.The optimal cutoff values were determined by receiver operating characteristic(ROC)analyses.Univariate and multivariate analyses were performed to identify the risk factors for early recurrence.RESULTS Of the 407 patients,98 patients(24.1%)experienced early disease recurrence:26(26.5%)local and 72(73.5%)distant sites.In total,253(62.2%)patients received adjuvant chemotherapy.On ROC curve analysis,the optimal cutoff values for early recurrence were 70 U/mL and 2.85 cm for carbohydrate antigen 19-9(CA 19-9)levels and tumor size,respectively.Of the 181 patients with CA 19-9 level>70 U/mL,59(32.6%)had early recurrence,compared to 39(17.4%)of 226 patients with CA 19-9 level≤70 U/mL(P<0.001).Multivariate analysis revealed that CA 19-9 level>70 U/mL(P=0.006),tumor size>2.85 cm(P=0.004),poor differentiation(P=0.008),and non-adjuvant chemotherapy(P=0.025)were significant risk factors for early recurrence in early-stage PDAC.CONCLUSION Elevated CA 19-9 level(cutoff value>70 U/mL)can be a reliable predictive factor for early recurrence in early-stage PDAC.As adjuvant chemotherapy can prevent early recurrence,it should be recommended for patients susceptible to early recurrence.展开更多
BACKGROUND Hepatocellular carcinoma(HCC)is the most common primary liver malignancy.AIM To predict early recurrence(ER)and overall survival(OS)in patients with HCC after radical resection using deep learning-based rad...BACKGROUND Hepatocellular carcinoma(HCC)is the most common primary liver malignancy.AIM To predict early recurrence(ER)and overall survival(OS)in patients with HCC after radical resection using deep learning-based radiomics(DLR).METHODS A total of 414 consecutive patients with HCC who underwent surgical resection with available preoperative grayscale and contrast-enhanced ultrasound images were enrolled.The clinical,DLR,and clinical+DLR models were then designed to predict ER and OS.RESULTS The DLR model for predicting ER showed satisfactory clinical benefits[area under the curve(AUC=0.819 and 0.568 in the training and testing cohorts,respectively)],similar to the clinical model(AUC=0.580 and 0.520 in the training and testing cohorts,respectively;P>0.05).The C-index of the clinical+DLR model in the prediction of OS in the training and testing cohorts was 0.800 and 0.759,respectively.The clinical+DLR model and the DLR model outperformed the clinical model in the training and testing cohorts(P<0.001 for all).We divided patients into four categories by dichotomizing predicted ER and OS.For patients in class 1(high ER rate and low risk of OS),retreatment(microwave ablation)after recurrence was associated with improved survival(hazard ratio=7.895,P=0.005).CONCLUSION Compared to the clinical model,the clinical+DLR model significantly improves the accuracy of predicting OS in HCC patients after radical resection.展开更多
AIM:To investigate whether α-fetoprotein (AFP) and vascular endothelial growth factor receptor (VEGFR)-1 correlate with early recurrence of hepatoma/hepatocel-lular carcinoma (HCC).METHODS:From 2000 to 2005,114 conse...AIM:To investigate whether α-fetoprotein (AFP) and vascular endothelial growth factor receptor (VEGFR)-1 correlate with early recurrence of hepatoma/hepatocel-lular carcinoma (HCC).METHODS:From 2000 to 2005,114 consecutive pa-tients with HCC underwent primary curative hepatecto-my.The mean age was 60.7 (8.7) years and 94 patients were male.The median follow-up period was 71.2 mo (range:43-100 mo).Immediately prior to commencing laparotomy,5 mL bone marrow was aspirated from thesternum and collected in citrate-coated test tubes.The initial 2 mL of bone marrow aspirate was discarded in each case.AFP mRNA and VEGFR-1 mRNA in the bone marrow and peripheral blood (BM-and PH-AFP mRNA and BM-and PH-VEGFR-1 mRNA,respectively) were measured by real-time quantitative reverse transcription polymerase chain reaction.As normal controls,VEGFR-1 mRNA in the bone marrow and peripheral blood was also measured in 11 living liver donors.These data were evaluated for any correlation with early recurrence,comparing clinical and pathological outcomes.RESULTS:The cut-off value of the BM-AFP mRNA and PH-AFP mRNA level in patients with HCC was set at 1.92 × 10-7 and zero,respectively,based on data from the controls.A total of 34 (29.8%) and six (5.4%) patients were positive for BM-AFP mRNA and PH-AFP mRNA,respectively.The BM-VEGFR-1 mRNA levels in all HCC patients were higher than those in the normal con-trols,and this was the case also for PH-VEGFR-1mRNA.The 25-percentile values for the BM-and PH-VEGFR-1 mRNA in HCC patients were used as the cut-off values for assigning the patients into two groups based on these transcript levels.The High group for BM-VEG-FR-1 mRNA contained 81 (71.1%) HCC cases and the Low group was assigned 33 (28.9%) patients.These numbers for PH-VEGFR-1mRNA were 78 (75.0%) and 26 (25.0%),respectively.HCC recurred in 80 patients;in the remnant liver in 48 cases,in the remnant liver and remote tissue in 20,and in the remote tissue alone in 12.BM-AFP mRNA-positive cases showed a signifi-cantly higher rate of early recurrence (within 1 year of surgical treatment) compared with BM-AFP mRNA-negative patients (P=0.0091).Patients were classified into four groups according to the level/status of their BM-VEGFR-1 and BM-AFP mRNA as follows:group A (n=23),BM-VEGFR-1/BM-AFP mRNA=low/negative;group B (n=57) high/negative;group C (n=10) low/positive;group D (n=24),high/positive.This classifi-cation was found to correlate with a recurrence of thisdisease within 1 year (P=0.0228).The disease-free survival curve of group A was significantly better than that of groups B,C or D (P=0.0437,P=0.0325,P=0.0225).No other classification (i.e.,PH-VEGF-R1/BM-AFP,BM-VEGF-R1/PH-AFP,and PH-VEGF-R1/PH-AFP mRNA) showed such a correlation.CONCLUSION:The evaluation of BM-AFP and BM-VEG-FR-1 mRNA in patients with HCC may be a valuable pre-dictor of disease recurrence following curative resection.展开更多
BACKGROUND Colorectal cancer is a common malignancy and various methods have been introduced to decrease the possibility of recurrence.Early recurrence(ER)is related to worse prognosis.To date,few observational studie...BACKGROUND Colorectal cancer is a common malignancy and various methods have been introduced to decrease the possibility of recurrence.Early recurrence(ER)is related to worse prognosis.To date,few observational studies have reported on the analysis of rectal cancer.Hence,we reported on the timing and risk factors for the ER of resectable rectal cancer at our institute.AIM To analyze a cohort of patients with local and/or distant recurrence following the radical resection of the primary tumor.METHODS Data were retrospectively collected from the institutional database from March 2011 to January 2021.Clinicopathological data at diagnosis,perioperative and postoperative data,and first recurrence were collected and analyzed.ER was defined via receiver operating characteristic curve.Prognostic factors were evaluated using the Kaplan–Meier method and Cox proportional hazards modeling.RESULTS We included 131 patients.The optimal cut off value of recurrence-free survival(RFS)to differentiate between ER(n=55,41.9%)and late recurrence(LR)(n=76,58.1%)was 8 mo.The median post-recurrence survival(PRS)of ER and LR was 1.4 mo and 2.9 mo,respectively(P=0.008)but PRS was not strongly associated with RFS(R^(2)=0.04).Risk factors included age≥70 years[hazard ratio(HR)=1.752,P=0.047],preoperative concurrent chemoradiotherapy(HR=3.683,P<0.001),colostomy creation(HR=2.221,P=0.036),and length of stay>9 d(HR=0.441,P=0.006).CONCLUSION RFS of 8 mo was the optimal cut-off value.Although ER was not associated with PRS,it was still related to prognosis;thus,intense surveillance is recommended.展开更多
BACKGROUND Early recurrence(ER)is associated with dismal outcomes in patients undergoing radical resection for pancreatic ductal adenocarcinoma(PDAC).Approaches for predicting ER will help clinicians in implementing i...BACKGROUND Early recurrence(ER)is associated with dismal outcomes in patients undergoing radical resection for pancreatic ductal adenocarcinoma(PDAC).Approaches for predicting ER will help clinicians in implementing individualized adjuvant therapies.Postoperative serum tumor markers(STMs)are indicators of tumor progression and may improve current systems for predicting ER.AIM To establish an improved nomogram based on postoperative STMs to predict ER in PDAC.METHODS We retrospectively enrolled 282 patients who underwent radical resection for PDAC at our institute between 2019 and 2021.Univariate and multivariate Cox regression analyses of variables with or without postoperative STMs,were performed to identify independent risk factors for ER.A nomogram was constructed based on the independent postoperative STMs.Receiver operating characteristic curve analysis was used to evaluate the area under the curve(AUC)of the nomogram.Survival analysis was performed using Kaplan-Meier survival plot and log-rank test.RESULTS Postoperative carbohydrate antigen 19-9 and carcinoembryonic antigen levels,preoperative carbohydrate antigen 125 levels,perineural invasion,and pTNM stage III were independent risk factors for ER in PDAC.The postoperative STMs-based nomogram(AUC:0.774,95%CI:0.713-0.835)had superior accuracy in predicting ER compared with the nomogram without postoperative STMs(AUC:0.688,95%CI:0.625-0.750)(P=0.016).Patients with a recurrence nomogram score(RNS)>1.56 were at high risk for ER,and had significantly poorer recurrence-free survival[median:3.08 months,interquartile range(IQR):1.80-8.15]than those with RNS≤1.56(14.00 months,IQR:6.67-24.80),P<0.001).CONCLUSION The postoperative STMs-based nomogram improves the predictive accuracy of ER in PDAC,stratifies the risk of ER,and identifies patients at high risk of ER for tailored adjuvant therapies.展开更多
Background: Postoperative early recurrence(ER) in patients with pancreatic ductal adenocarcinoma(PDAC) is frequently encountered after curative intent surgery. Nonetheless, clinical significance and risk factors of ER...Background: Postoperative early recurrence(ER) in patients with pancreatic ductal adenocarcinoma(PDAC) is frequently encountered after curative intent surgery. Nonetheless, clinical significance and risk factors of ER after surgery for PDAC have not been extensively investigated. The aim of this study was to determine preoperative risk predictors for ER in patients with PDAC after upfront surgery. Methods: Eighty-one consecutive patients with PDAC who underwent curative intent surgical resection at Kangbuk Samsung Hospital between January 2004 and May 2015 were enrolled. ER was defined as tumor relapse within 6 months after surgery. Results: ER occurred in 26 patients(32.1%), whereas 49 patients(60.5%) had late recurrence( ≥ 6 months after surgery), and 6 patients had no recurrence(7.4%). Univariate analysis showed that C-reactive protein(CRP) > 3.0 mg/dL, modified Glasgow prognostic score(mGPS) = 2, decrease of total lymphocyte count by > 50% of baseline value in the preoperative period, prognostic nutritional index(PNI) < 45, neutrophilto-lymphocyte ratio(NLR) ≥ 3, and preoperative maximum standardized uptake value(SUVmax) were significantly associated with ER. Multivariate logistic regression analysis revealed that CRP > 3.0 mg/dL, decrease of total lymphocyte count by > 50% of baseline value, and preoperative SUVmax were significant and independent contributors of ER in patients with resectable PDAC who underwent curative intent surgery. Conclusions: Postoperative ER for resectable PDAC was frequent with poor prognosis after curative intent upfront surgery. It is reasonable to suggest that there is a subgroup of resectable PDAC patients at highrisk of ER and neoadjuvant therapy should be considered in these patients in a clinical trial setting.展开更多
BACKGROUND Pancreatectomy with concomitant portomesenteric vein resection(PVR)enables patients with portomesenteric vein(PV)involvement to achieve radical resection of pancreatic ductal adenocarcinoma,however,early re...BACKGROUND Pancreatectomy with concomitant portomesenteric vein resection(PVR)enables patients with portomesenteric vein(PV)involvement to achieve radical resection of pancreatic ductal adenocarcinoma,however,early recurrence(ER)is frequently observed.AIM To predict ER and identify patients at high risk of ER for individualized therapy.METHODS Totally 238 patients undergoing pancreatectomy and PVR were retrospectively enrolled and were allocated to the training or validating cohort.Univariate Cox and LASSO regression analyses were performed to construct serum recurrence score(SRS)based on 26 serum-derived parameters.Uni-and multivariate Cox regression analyses of SRS and 18 clinicopathological variables were performed to establish a Nomogram.Receiver operating characteristic curve analysis was used to evaluate the predictive accuracy.Survival analysis was performed using Kaplan-Meier method and log-rank test.RESULTS Independent serum-derived recurrence-relevant factors of LASSO regression model,including postoperative carbohydrate antigen 19-9,postoperative carcinoembryonic antigen,postoperative carbohydrate antigen 125,preoperative albumin(ALB),preoperative platelet to ALB ratio,and postoperative platelets to lymphocytes ratio,were used to construct SRS[area under the curve(AUC):0.855,95%CI:0.786–0.924].Independent risk factors of recurrence,including SRS[hazard ratio(HR):1.688,95%CI:1.075-2.652],pain(HR:1.653,95%CI:1.052-2.598),perineural invasion(HR:2.070,95%CI:0.827-5.182),and PV invasion(HR:1.603,95%CI:1.063-2.417),were used to establish the recurrence nomogram(AUC:0.869,95%CI:0.803-0.934).Patients with either SRS>0.53 or recurrence nomogram score>4.23 were considered at high risk for ER,and had poor long-term outcomes.CONCLUSION The recurrence scoring system unique for pancreatectomy and PVR,will help clinicians in predicting recurrence efficiently and identifying patients at high risk of ER for individualized therapy.展开更多
Malignant fibrous histiocytoma (MFH) is a rare tumor of the heart and the patients with these tumors usually have a poor prognosis. We report a case of MFH with an origin from the left superior pulmonary vein, involvi...Malignant fibrous histiocytoma (MFH) is a rare tumor of the heart and the patients with these tumors usually have a poor prognosis. We report a case of MFH with an origin from the left superior pulmonary vein, involving the left atrium and protruding through the mitral valve, which needed urgent surgery. Complete resection was performed but local recurrence was detected one month later.展开更多
基金Supported by Anhui Provincial Key Research and Development Plan,No.202104j07020048.
文摘BACKGROUND Hepatocellular carcinoma(HCC)is the most common primary liver malignancy.Ablation therapy is one of the first-line treatments for early HCC.Accurately predicting early recurrence(ER)is crucial for making precise treatment plans and improving patient prognosis.AIM To establish an intratumoral and peritumoral model for predicting ER in HCC patients following curative ablation.METHODS This study included a total of 288 patients from three Centers.The patients were divided into a primary cohort(n=222)and an external cohort(n=66).Radiomics and deep learning methods were combined for feature extraction,and models were constructed following a three-step feature selection process.Model performance was evaluated using the area under the receiver operating characteristic curve(AUC),while calibration curves and decision curve analysis(DCA)were used to assess calibration and clinical utility.Finally,Kaplan-Meier(K-M)analysis was used to stratify patients according to progression-free survival(PFS)and overall survival(OS).RESULTS The combined model,which utilizes the light gradient boosting machine learning algorithm and incorporates both intratumoral and peritumoral regions(5 mm and 10 mm),demonstrated the best predictive performance for ER following HCC ablation,achieving AUCs of 0.924 in the training set,0.899 in the internal validation set,and 0.839 in the external validation set.Calibration and DCA curves confirmed strong calibration and clinical utility,whereas K-M curves provided risk stratification for PFS and OS in HCC patients.CONCLUSION The most efficient model integrated the tumor region with the peritumoral 5 mm and 10 mm regions.This model provides a noninvasive,effective,and reliable method for predicting ER after curative ablation of HCC.
基金Supported by the Key Clinical Specialty Discipline Construction Program of Fujian,Fujian Health Medicine and Politics,No.[2022]884.
文摘Early recurrence(ER)following surgery for rectal cancer is a significant factor impacting patient survival rates.Tsai et al identified age,preoperative neoadjuvant therapy,length of hospital stay,tumour location,and pathological stage as factors influencing the risk of ER.Postoperative monitoring for ER should encompass a thorough medical history review,physical examination,tumour marker testing,and imaging studies.Additionally,noninvasive circulating tumour cell DNA testing can be utilized to predict ER.Treatment strategies may involve radical surgery,radiation therapy,chemotherapy,and immunotherapy.Through a comprehensive analysis of risk factors,the optimization of monitoring methods,and the development of personalized treatment strategies,it is anticipated that both the efficacy of treatment and the quality of life for rectal cancer patients with postoperative recurrence can be significantly improved.
文摘In a recent study by He et al,the nomogram integrates postoperative serum tumor markers such as carbohydrate antigen 19-9 and carcinoembryonic antigen,thereby improving the accuracy of identifying high-risk patients compared to relying solely on preoperative markers,which has significant implications for customizing adjuvant therapy and potentially improving outcomes for this aggressive form of cancer.However,the study’s single-center design and short follow-up period may limit the generalizability of its findings and potentially introduce reporting bias.Future studies could consider additional confounding factors,such as adjuvant chemotherapy and variations in surgical techniques,to improve the model’s accuracy.Furthermore,it would be valuable to validate the nomogram in broader,prospective cohorts and explore the inclusion of additional markers like circulating tumor DNA to refine further its predictive power and applicability across diverse patient populations.
文摘We provide an editorial of recent findings on early recurrence(ER)in rectal cancer(RC),focusing on the study on ER of resectable RC by Tsai et al.The study established an 8-month recurrence-free survival cut-off for differentiating ER from late recurrence,with implications for postrecurrence survival and overall survival.This offers not only a valuable timeframe for enhancing surveillance strategies in patients at higher risk,especially those who have undergone neoadjuvant chemoradiotherapy(CRT),but also raises questions about its applicability across different populations.Furthermore,the article suggests that while CRT is very effective in reducing locoregional recurrence,this treatment alone may not fully address the overall risk of ER.The authors advocate for personalized risk assessment and intensive surveillance during the postoperative period to improve outcomes,particularly in the first year.Future research should focus on larger,multicenter studies and incorporate advanced diagnostic techniques with genetic and molecular biomarkers to enhance prediction and management of ER.The ultimate goal is to refine treatment and surveillance strategies to improve survival and quality of life for patients with RC.
基金Supported by the"Summit Plan(New Departure)"Project for the Development of Doctoral Degree Authorization Points and Professional Disciplines at the Affiliated Hospital of Youjiang Medical University for Nationalities,No.DF20244433Self-funded Research Projects by the Guangxi Health and Wellness Committee,No.Z-L20240824and the Project to Enhance the Research Foundations of Young and Mid-career Faculty in Guangxi Universities,No.2024KY0562.
文摘BACKGROUND Early recurrence is an important factor affecting the prognosis of hepatocellular carcinoma(HCC),but its preoperative prediction remains challenging.AIM To explore the value of a multimodal interpretable fusion model combining computed tomography(CT)habitat imaging(HI),radiomics,and clinical features in predicting early recurrence of HCC and analyze its correlation with pathological indicators.METHODS The 191 HCC patients were categorized into early recurrence and non-early recurrence groups based on postoperative follow-up outcomes,and randomly divided into training and testing sets in a 7:3 ratio.Based on CT arterial phase and clinical data,the habitat model,radiomics model,clinical model,and fusion model were constructed and compared for their predictive ability in early recurrence of HCC.For the optimal model,SHapley Additive exPlanations(SHAP)analysis was performed to evaluate the contribution of different features in the model,and the correlation between HI and radiomics features with tumor microvascular invasion(MVI),Ki67 expression,GPC-3 expression,and pathological grading was analyzed.RESULTS The fusion model demonstrated the best performance in predicting early recurrence of HCC,achieving the area under the curve of 0.933 on the validation set.The decision curve analysis curve indicated that the fusion model yielded the highest clinical net benefit.SHAP analysis provided valuable insights into explaining the fusion model's prediction of early HCC recurrence.Correlation analysis revealed significant associations between certain radiomics and Habitat features and pathological indicators such as MVI and Ki-67 expression in HCC.CONCLUSION An interpretable fusion model integrating clinical,radiomic,and habitat features can assist clinicians in identifying early postoperative recurrence of HCC,offering significant potential for prognosis prediction and clinical management.
基金Supported by the Chongqing Medical Scientific Research Project(Joint Project of Chongqing Health Commission and Science and Technology Bureau),No.2025MSXM043。
文摘BACKGROUND Predicting early recurrence(ER),(≤12 months)after pancreatic ductal adenocar-cinoma(PDAC)resection remains challenging.Preoperative biomarkers such as carbohydrate antigen 19-9(CA19-9)and computed tomography(CT)lack optimal specificity and reproducibility.Extracellular volume(ECV),measured on equi-librium-phase CT to quantify stromal fibrosis,correlates with PDAC progression but its utility for ER prediction is unknown.This study evaluates preoperative CT-ECV as a novel biomarker to predict ER following curative-intent PDAC resection.This retrospective study included 93 PDAC patients undergoing R0 resection and preoperative pancreatic CT from January 2020 to November 2023.Clinical and CT features were analyzed.ECV was calculated using unenhanced and equilibrium-phase CT.Univariable and multivariable Cox regression identified ER predictors,followed by receiver operating characteristic analysis.Recurrence-free survival(RFS)was assessed by the Kaplan-Meier method.RESULTS Multivariable analysis identified elevated CT-ECV[hazard ratio(HR)=1.05;95%confidence interval(CI):1.02-1.09;P=0.003],high preoperative CA19-9(HR=1.00;95%CI:1.00-1.00;P=0.002),and poor tumor grade(HR=2.51;95%CI:1.20-5.22;P=0.014)as independent ER predictors.CT-ECV demonstrated comparable predictive accuracy to tumor grade[areas under the curve(AUC):0.736 vs 0.650;P=0.202].Combining CT-ECV and CA19-9 achieved a higher AUC than tumor grade alone(0.759 vs 0.650;P<0.05).Kaplan-Meier analysis revealed sig-nificantly shorter RFS in patients with low CT-ECV(≤35.37%),elevated CA19-9(>55 U/mL),or poorly differen-tiated tumors compared to those with high CT-ECV(>35.37%),low CA19-9(≤55 U/mL),or moderately/well-differentiated tumors.CONCLUSION CT-derived ECV is a promising non-invasive biomarker for preoperative ER prediction in PDAC.Combined with CA19-9,it outperforms tumor grade in stratifying recurrence risk,offering a clinically actionable tool for opti-mizing postoperative management.
文摘Pancreatic ductal adenocarcinoma(PDAC),a"silent killer"with elusive early symptoms and poor prognosis,sees nearly half of patients experience recurrence within a year post-curative-intent surgery.Very early recurrence(VER),defined as recurrence within 12 weeks postoperatively and first termed"biological R^(2) resection"by Belfiori et al,remains a clinical puzzle.Martlıet al’s recent retrospective cohort study offers crucial insights into this understudied issue,identifies predictive factors that challenge long-held beliefs,and calls for a rethink of risk stratification and postoperative management for PDAC patients.Martlıet al studied 303 PDAC patients at a high-volume center from 2019 to 2024,with VER affecting 9.24%(28 patients)of the cohort.The study’s strength lies in combining traditional statistical analyses and machine learning(random forest modeling)to capture nonlinear relationships between clinicopathological factors and VER risk.Key findings include:(1)Poorly differentiated(G3)tumors are the strongest VER predictor(OR=2.43,P<0.001;random forest importance score=0.35),with 92.85%of VER patients having G3 tumors(vs 45.81%of non-VER patients);(2)Contrary to prior studies,pancreatic head tumors(89.28%of VER patients vs 83.66%of non-VER patients,P=0.031)were linked to VER;(3)Elevated red cell distribution width is a weaker predictor(random forest importance score=0.20,P=0.03 for group difference,P=0.079 in multivariate analysis);and(4)VER correlates with significantly higher 6-month mortality(32.44%vs 14.77%in non-VER patients,P=0.032).
文摘BACKGROUND： Early recurrence （ER） after hepatic resection （HR） is a poor prognostic factor for patients with hepatocellular carcinoma （HCC）. This study aimed to identify the clinico- pathological features, outcomes, and risk factors for ER after HR for small HCC in order to clarify the reasons why ER is a worse recurrence pattern. METHODS： We retrospectively examined 130 patients who underwent HR for small HCC （___30 mm）. Recurrence was clas- sifted into ER （〈2 years） and late recurrence （LR） （_〉2 years）. The clinicopathological features, outcomes, and risk factors for ER were analyzed by multivariate analysis. RESULTS： ER was observed in 39 patients （30.0%）. The sur- vival rate of the ER group was significantly lower than that of the LR group （P〈0.005）, and ER was an independent prognos- tic factor for poor survival （P=0.0001）. The ER group had a significantly higher frequency （P=0.0039） and shorter interval （P=0.027） of development to carcinoma beyond the Milan criteria （DBMC） compared with the LR group, and ER was an independent risk factor for DBMC （P〈0.0001）. Multi-nodularity, non-simple nodular type, and microvascular invasion were independent predictors for ER （P=0.012, 0.010, and 0.019, respectively）.CONCLUSIONS： ER was a highly malignant recurrence pattern associated with DBMC and subsequent poor survival after HR for small HCC. Multi-nodularity, non-simple nodular type, and microvascular invasion predict ER, and taking these factors into consideration may be useful for the decision of the treatment strategy for small HCC after HR.
基金Supported by Anhui Provincial Key Research and Development Plan,No.202104j07020048.
文摘BACKGROUND The prognosis for hepatocellular carcinoma(HCC)in the presence of cirrhosis is unfavourable,primarily attributable to the high incidence of recurrence.AIM To develop a machine learning model for predicting early recurrence(ER)of posthepatectomy HCC in patients with cirrhosis and to stratify patients’overall survival(OS)based on the predicted risk of recurrence.METHODS In this retrospective study,214 HCC patients with cirrhosis who underwent curative hepatectomy were examined.Radiomics feature selection was conducted using the least absolute shrinkage and selection operator and recursive feature elimination methods.Clinical-radiologic features were selected through univariate and multivariate logistic regression analyses.Five machine learning methods were used for model comparison,aiming to identify the optimal model.The model’s performance was evaluated using the receiver operating characteristic curve[area under the curve(AUC)],calibration,and decision curve analysis.Additionally,the Kaplan-Meier(K-M)curve was used to evaluate the stratification effect of the model on patient OS.RESULTS Within this study,the most effective predictive performance for ER of post-hepatectomy HCC in the background of cirrhosis was demonstrated by a model that integrated radiomics features and clinical-radiologic features.In the training cohort,this model attained an AUC of 0.844,while in the validation cohort,it achieved a value of 0.790.The K-M curves illustrated that the combined model not only facilitated risk stratification but also exhibited significant discriminatory ability concerning patients’OS.CONCLUSION The combined model,integrating both radiomics and clinical-radiologic characteristics,exhibited excellent performance in HCC with cirrhosis.The K-M curves assessing OS revealed statistically significant differences.
基金National Natural Science Foundation of China,No.81773148Natural Science Foundation of Guangxi,No.2018GXNSFDA138001+3 种基金Program of Guangxi Zhuang Autonomous Region Health and Family Planning Commission,No.Z20210706Guangxi Medical and Healthcare Appropriate Technology Development and Promotion and Application Projects,No.S2022132Guangxi Natural Science Foundation,No.2022JJA140009Guangxi Zhuang Autonomous Region Health and Family Planning Commission Self-funded of Scientific Research Project,No.Z20170812.
文摘BACKGROUND Radical resection remains an effective strategy for patients with hepatocellular carcinoma(HCC).Unfortunately,the postoperative early recurrence(recurrence within 2 years)rate is still high.AIM To develop a radiomics model based on preoperative contrast-enhanced computed tomography(CECT)to evaluate early recurrence in HCC patients with a single tumour.METHODS We enrolled a total of 402 HCC patients from two centres who were diagnosed with a single tumour and underwent radical resection.First,the features from the portal venous and arterial phases of CECT were extracted based on the region of interest,and the early recurrence-related radiomics features were selected via the least absolute shrinkage and selection operator proportional hazards model(LASSO Cox)to determine radiomics scores for each patient.Then,the clinicopathologic data were combined to develop a model to predict early recurrence by Cox regression.Finally,we evaluated the prediction performance of this model by multiple methods.RESULTS A total of 1915 radiomics features were extracted from CECT images,and 31 of them were used to determine the radiomics scores,which showed a significant difference between the early recurrence and nonearly recurrence groups.Univariate and multivariate Cox regression analyses showed that radiomics scores and serum alphafetoprotein were independent indicators,and they were used to develop a combined model to predict early recurrence.The area under the receiver operating characteristic curve values for the training and validation cohorts were 0.77 and 0.74,respectively,while the C-indices were 0.712 and 0.674,respectively.The calibration curves and decision curve analysis showed satisfactory accuracy and clinical utilities.Kaplan-Meier curves based on recurrence-free survival and overall survival showed significant differences.CONCLUSION The preoperative radiomics model was shown to be effective for predicting early recurrence among HCC patients with a single tumour.
文摘The high rate of early recurrence in hepatocellular carcinoma(HCC)post curative surgical intervention poses a substantial clinical hurdle,impacting patient outcomes and complicating postoperative management.The advent of machine learning provides a unique opportunity to harness vast datasets,identifying subtle patterns and factors that elude conventional prognostic methods.Machine learning models,equipped with the ability to analyse intricate relationships within datasets,have shown promise in predicting outcomes in various medical disciplines.In the context of HCC,the application of machine learning to predict early recurrence holds potential for personalized postoperative care strategies.This editorial comments on the study carried out exploring the merits and efficacy of random survival forests(RSF)in identifying significant risk factors for recurrence,stratifying patients at low and high risk of HCC recurrence and comparing this to traditional COX proportional hazard models(CPH).In doing so,the study demonstrated that the RSF models are superior to traditional CPH models in predicting recurrence of HCC and represent a giant leap towards precision medicine.
基金the National Key Research and Development Program of China(2019YFC0118104)the National Natural Science Foundation of China(82001808)+2 种基金the Beijing Natural Science Foundation(7222319)the Beijing Munici-pal Science&Technology Commission(Z21100002921047)the Capital’s Clinical Applied Research Project(Z181100001718013).
文摘Background:Early recurrence results in poor prognosis of patients with hepatocellular carcinoma(HCC)after liver transplantation(LT).This study aimed to explore the value of computed tomography(CT)-based radiomics nomogram in predicting early recurrence of patients with HCC after LT.Methods:A cohort of 151 patients with HCC who underwent LT between December 2013 and July 2019 were retrospectively enrolled.A total of 1218 features were extracted from enhanced CT images.The least absolute shrinkage and selection operator algorithm(LASSO)logistic regression was used for dimension reduction and radiomics signature building.The clinical model was constructed after the analysis of clin-ical factors,and the nomogram was constructed by introducing the radiomics signature into the clinical model.The predictive performance and clinical usefulness of the three models were evaluated using re-ceiver operating characteristic(ROC)curve analysis and decision curve analysis(DCA),respectively.Cali-bration curves were plotted to assess the calibration of the nomogram.Results:There were significant differences in radiomics signature among early recurrence patients and non-early recurrence patients in the training cohort(P<0.001)and validation cohort(P<0.001).The nomogram showed the best predictive performance,with the largest area under the ROC curve in the training(0.882)and validation(0.917)cohorts.Hosmer-Lemeshow testing confirmed that the nomogram showed good calibration in the training(P=0.138)and validation(P=0.396)cohorts.DCA showed if the threshold probability is within 0.06-1,the nomogram had better clinical usefulness than the clinical model.Conclusions:Our CT-based radiomics nomogram can preoperatively predict the risk of early recurrence in patients with HCC after LT.
文摘BACKGROUND Pancreatic ductal adenocarcinoma(PDAC)is a serious disease with a poor prognosis.Only a minority of patients undergo surgery due to the advanced stage of the disease,and patients with early-stage disease,who are expected to have a better prognosis,often experience recurrence.Thus,it is important to identify the risk factors for early recurrence and to develop an adequate treatment plan.AIM To evaluate the predictive factors associated with the early recurrence of earlystage PDAC.METHODS This study enrolled 407 patients with stage I PDAC undergoing upfront surgical resection between January 2000 and April 2016.Early recurrence was defined as a diagnosis of recurrence within 6 mo of surgery.The optimal cutoff values were determined by receiver operating characteristic(ROC)analyses.Univariate and multivariate analyses were performed to identify the risk factors for early recurrence.RESULTS Of the 407 patients,98 patients(24.1%)experienced early disease recurrence:26(26.5%)local and 72(73.5%)distant sites.In total,253(62.2%)patients received adjuvant chemotherapy.On ROC curve analysis,the optimal cutoff values for early recurrence were 70 U/mL and 2.85 cm for carbohydrate antigen 19-9(CA 19-9)levels and tumor size,respectively.Of the 181 patients with CA 19-9 level>70 U/mL,59(32.6%)had early recurrence,compared to 39(17.4%)of 226 patients with CA 19-9 level≤70 U/mL(P<0.001).Multivariate analysis revealed that CA 19-9 level>70 U/mL(P=0.006),tumor size>2.85 cm(P=0.004),poor differentiation(P=0.008),and non-adjuvant chemotherapy(P=0.025)were significant risk factors for early recurrence in early-stage PDAC.CONCLUSION Elevated CA 19-9 level(cutoff value>70 U/mL)can be a reliable predictive factor for early recurrence in early-stage PDAC.As adjuvant chemotherapy can prevent early recurrence,it should be recommended for patients susceptible to early recurrence.
文摘BACKGROUND Hepatocellular carcinoma(HCC)is the most common primary liver malignancy.AIM To predict early recurrence(ER)and overall survival(OS)in patients with HCC after radical resection using deep learning-based radiomics(DLR).METHODS A total of 414 consecutive patients with HCC who underwent surgical resection with available preoperative grayscale and contrast-enhanced ultrasound images were enrolled.The clinical,DLR,and clinical+DLR models were then designed to predict ER and OS.RESULTS The DLR model for predicting ER showed satisfactory clinical benefits[area under the curve(AUC=0.819 and 0.568 in the training and testing cohorts,respectively)],similar to the clinical model(AUC=0.580 and 0.520 in the training and testing cohorts,respectively;P>0.05).The C-index of the clinical+DLR model in the prediction of OS in the training and testing cohorts was 0.800 and 0.759,respectively.The clinical+DLR model and the DLR model outperformed the clinical model in the training and testing cohorts(P<0.001 for all).We divided patients into four categories by dichotomizing predicted ER and OS.For patients in class 1(high ER rate and low risk of OS),retreatment(microwave ablation)after recurrence was associated with improved survival(hazard ratio=7.895,P=0.005).CONCLUSION Compared to the clinical model,the clinical+DLR model significantly improves the accuracy of predicting OS in HCC patients after radical resection.
基金Supported by Japan Society for the Promotion of Science KAKENHI 21390369[Grant-in-Aid for Science Research(B)]
文摘AIM:To investigate whether α-fetoprotein (AFP) and vascular endothelial growth factor receptor (VEGFR)-1 correlate with early recurrence of hepatoma/hepatocel-lular carcinoma (HCC).METHODS:From 2000 to 2005,114 consecutive pa-tients with HCC underwent primary curative hepatecto-my.The mean age was 60.7 (8.7) years and 94 patients were male.The median follow-up period was 71.2 mo (range:43-100 mo).Immediately prior to commencing laparotomy,5 mL bone marrow was aspirated from thesternum and collected in citrate-coated test tubes.The initial 2 mL of bone marrow aspirate was discarded in each case.AFP mRNA and VEGFR-1 mRNA in the bone marrow and peripheral blood (BM-and PH-AFP mRNA and BM-and PH-VEGFR-1 mRNA,respectively) were measured by real-time quantitative reverse transcription polymerase chain reaction.As normal controls,VEGFR-1 mRNA in the bone marrow and peripheral blood was also measured in 11 living liver donors.These data were evaluated for any correlation with early recurrence,comparing clinical and pathological outcomes.RESULTS:The cut-off value of the BM-AFP mRNA and PH-AFP mRNA level in patients with HCC was set at 1.92 × 10-7 and zero,respectively,based on data from the controls.A total of 34 (29.8%) and six (5.4%) patients were positive for BM-AFP mRNA and PH-AFP mRNA,respectively.The BM-VEGFR-1 mRNA levels in all HCC patients were higher than those in the normal con-trols,and this was the case also for PH-VEGFR-1mRNA.The 25-percentile values for the BM-and PH-VEGFR-1 mRNA in HCC patients were used as the cut-off values for assigning the patients into two groups based on these transcript levels.The High group for BM-VEG-FR-1 mRNA contained 81 (71.1%) HCC cases and the Low group was assigned 33 (28.9%) patients.These numbers for PH-VEGFR-1mRNA were 78 (75.0%) and 26 (25.0%),respectively.HCC recurred in 80 patients;in the remnant liver in 48 cases,in the remnant liver and remote tissue in 20,and in the remote tissue alone in 12.BM-AFP mRNA-positive cases showed a signifi-cantly higher rate of early recurrence (within 1 year of surgical treatment) compared with BM-AFP mRNA-negative patients (P=0.0091).Patients were classified into four groups according to the level/status of their BM-VEGFR-1 and BM-AFP mRNA as follows:group A (n=23),BM-VEGFR-1/BM-AFP mRNA=low/negative;group B (n=57) high/negative;group C (n=10) low/positive;group D (n=24),high/positive.This classifi-cation was found to correlate with a recurrence of thisdisease within 1 year (P=0.0228).The disease-free survival curve of group A was significantly better than that of groups B,C or D (P=0.0437,P=0.0325,P=0.0225).No other classification (i.e.,PH-VEGF-R1/BM-AFP,BM-VEGF-R1/PH-AFP,and PH-VEGF-R1/PH-AFP mRNA) showed such a correlation.CONCLUSION:The evaluation of BM-AFP and BM-VEG-FR-1 mRNA in patients with HCC may be a valuable pre-dictor of disease recurrence following curative resection.
文摘BACKGROUND Colorectal cancer is a common malignancy and various methods have been introduced to decrease the possibility of recurrence.Early recurrence(ER)is related to worse prognosis.To date,few observational studies have reported on the analysis of rectal cancer.Hence,we reported on the timing and risk factors for the ER of resectable rectal cancer at our institute.AIM To analyze a cohort of patients with local and/or distant recurrence following the radical resection of the primary tumor.METHODS Data were retrospectively collected from the institutional database from March 2011 to January 2021.Clinicopathological data at diagnosis,perioperative and postoperative data,and first recurrence were collected and analyzed.ER was defined via receiver operating characteristic curve.Prognostic factors were evaluated using the Kaplan–Meier method and Cox proportional hazards modeling.RESULTS We included 131 patients.The optimal cut off value of recurrence-free survival(RFS)to differentiate between ER(n=55,41.9%)and late recurrence(LR)(n=76,58.1%)was 8 mo.The median post-recurrence survival(PRS)of ER and LR was 1.4 mo and 2.9 mo,respectively(P=0.008)but PRS was not strongly associated with RFS(R^(2)=0.04).Risk factors included age≥70 years[hazard ratio(HR)=1.752,P=0.047],preoperative concurrent chemoradiotherapy(HR=3.683,P<0.001),colostomy creation(HR=2.221,P=0.036),and length of stay>9 d(HR=0.441,P=0.006).CONCLUSION RFS of 8 mo was the optimal cut-off value.Although ER was not associated with PRS,it was still related to prognosis;thus,intense surveillance is recommended.
基金Supported by National Natural Science Foundation of China,No.82373012.
文摘BACKGROUND Early recurrence(ER)is associated with dismal outcomes in patients undergoing radical resection for pancreatic ductal adenocarcinoma(PDAC).Approaches for predicting ER will help clinicians in implementing individualized adjuvant therapies.Postoperative serum tumor markers(STMs)are indicators of tumor progression and may improve current systems for predicting ER.AIM To establish an improved nomogram based on postoperative STMs to predict ER in PDAC.METHODS We retrospectively enrolled 282 patients who underwent radical resection for PDAC at our institute between 2019 and 2021.Univariate and multivariate Cox regression analyses of variables with or without postoperative STMs,were performed to identify independent risk factors for ER.A nomogram was constructed based on the independent postoperative STMs.Receiver operating characteristic curve analysis was used to evaluate the area under the curve(AUC)of the nomogram.Survival analysis was performed using Kaplan-Meier survival plot and log-rank test.RESULTS Postoperative carbohydrate antigen 19-9 and carcinoembryonic antigen levels,preoperative carbohydrate antigen 125 levels,perineural invasion,and pTNM stage III were independent risk factors for ER in PDAC.The postoperative STMs-based nomogram(AUC:0.774,95%CI:0.713-0.835)had superior accuracy in predicting ER compared with the nomogram without postoperative STMs(AUC:0.688,95%CI:0.625-0.750)(P=0.016).Patients with a recurrence nomogram score(RNS)>1.56 were at high risk for ER,and had significantly poorer recurrence-free survival[median:3.08 months,interquartile range(IQR):1.80-8.15]than those with RNS≤1.56(14.00 months,IQR:6.67-24.80),P<0.001).CONCLUSION The postoperative STMs-based nomogram improves the predictive accuracy of ER in PDAC,stratifies the risk of ER,and identifies patients at high risk of ER for tailored adjuvant therapies.
文摘Background: Postoperative early recurrence(ER) in patients with pancreatic ductal adenocarcinoma(PDAC) is frequently encountered after curative intent surgery. Nonetheless, clinical significance and risk factors of ER after surgery for PDAC have not been extensively investigated. The aim of this study was to determine preoperative risk predictors for ER in patients with PDAC after upfront surgery. Methods: Eighty-one consecutive patients with PDAC who underwent curative intent surgical resection at Kangbuk Samsung Hospital between January 2004 and May 2015 were enrolled. ER was defined as tumor relapse within 6 months after surgery. Results: ER occurred in 26 patients(32.1%), whereas 49 patients(60.5%) had late recurrence( ≥ 6 months after surgery), and 6 patients had no recurrence(7.4%). Univariate analysis showed that C-reactive protein(CRP) > 3.0 mg/dL, modified Glasgow prognostic score(mGPS) = 2, decrease of total lymphocyte count by > 50% of baseline value in the preoperative period, prognostic nutritional index(PNI) < 45, neutrophilto-lymphocyte ratio(NLR) ≥ 3, and preoperative maximum standardized uptake value(SUVmax) were significantly associated with ER. Multivariate logistic regression analysis revealed that CRP > 3.0 mg/dL, decrease of total lymphocyte count by > 50% of baseline value, and preoperative SUVmax were significant and independent contributors of ER in patients with resectable PDAC who underwent curative intent surgery. Conclusions: Postoperative ER for resectable PDAC was frequent with poor prognosis after curative intent upfront surgery. It is reasonable to suggest that there is a subgroup of resectable PDAC patients at highrisk of ER and neoadjuvant therapy should be considered in these patients in a clinical trial setting.
基金Supported by National Natural Science Foundation of China,No.82373012.
文摘BACKGROUND Pancreatectomy with concomitant portomesenteric vein resection(PVR)enables patients with portomesenteric vein(PV)involvement to achieve radical resection of pancreatic ductal adenocarcinoma,however,early recurrence(ER)is frequently observed.AIM To predict ER and identify patients at high risk of ER for individualized therapy.METHODS Totally 238 patients undergoing pancreatectomy and PVR were retrospectively enrolled and were allocated to the training or validating cohort.Univariate Cox and LASSO regression analyses were performed to construct serum recurrence score(SRS)based on 26 serum-derived parameters.Uni-and multivariate Cox regression analyses of SRS and 18 clinicopathological variables were performed to establish a Nomogram.Receiver operating characteristic curve analysis was used to evaluate the predictive accuracy.Survival analysis was performed using Kaplan-Meier method and log-rank test.RESULTS Independent serum-derived recurrence-relevant factors of LASSO regression model,including postoperative carbohydrate antigen 19-9,postoperative carcinoembryonic antigen,postoperative carbohydrate antigen 125,preoperative albumin(ALB),preoperative platelet to ALB ratio,and postoperative platelets to lymphocytes ratio,were used to construct SRS[area under the curve(AUC):0.855,95%CI:0.786–0.924].Independent risk factors of recurrence,including SRS[hazard ratio(HR):1.688,95%CI:1.075-2.652],pain(HR:1.653,95%CI:1.052-2.598),perineural invasion(HR:2.070,95%CI:0.827-5.182),and PV invasion(HR:1.603,95%CI:1.063-2.417),were used to establish the recurrence nomogram(AUC:0.869,95%CI:0.803-0.934).Patients with either SRS>0.53 or recurrence nomogram score>4.23 were considered at high risk for ER,and had poor long-term outcomes.CONCLUSION The recurrence scoring system unique for pancreatectomy and PVR,will help clinicians in predicting recurrence efficiently and identifying patients at high risk of ER for individualized therapy.
文摘Malignant fibrous histiocytoma (MFH) is a rare tumor of the heart and the patients with these tumors usually have a poor prognosis. We report a case of MFH with an origin from the left superior pulmonary vein, involving the left atrium and protruding through the mitral valve, which needed urgent surgery. Complete resection was performed but local recurrence was detected one month later.
