BACKGROUND Gastric cancer is one of the most common malignant tumors in the digestive system,ranking sixth in incidence and fourth in mortality worldwide.Since 42.5%of metastatic lymph nodes in gastric cancer belong t...BACKGROUND Gastric cancer is one of the most common malignant tumors in the digestive system,ranking sixth in incidence and fourth in mortality worldwide.Since 42.5%of metastatic lymph nodes in gastric cancer belong to nodule type and peripheral type,the application of imaging diagnosis is restricted.AIM To establish models for predicting the risk of lymph node metastasis in gastric cancer patients using machine learning(ML)algorithms and to evaluate their pre-dictive performance in clinical practice.METHODS Data of a total of 369 patients who underwent radical gastrectomy at the Depart-ment of General Surgery of Affiliated Hospital of Xuzhou Medical University(Xuzhou,China)from March 2016 to November 2019 were collected and retro-spectively analyzed as the training group.In addition,data of 123 patients who underwent radical gastrectomy at the Department of General Surgery of Jining First People’s Hospital(Jining,China)were collected and analyzed as the verifi-cation group.Seven ML models,including decision tree,random forest,support vector machine(SVM),gradient boosting machine,naive Bayes,neural network,and logistic regression,were developed to evaluate the occurrence of lymph node metastasis in patients with gastric cancer.The ML models were established fo-llowing ten cross-validation iterations using the training dataset,and subsequently,each model was assessed using the test dataset.The models’performance was evaluated by comparing the area under the receiver operating characteristic curve of each model.RESULTS Among the seven ML models,except for SVM,the other ones exhibited higher accuracy and reliability,and the influences of various risk factors on the models are intuitive.CONCLUSION The ML models developed exhibit strong predictive capabilities for lymph node metastasis in gastric cancer,which can aid in personalized clinical diagnosis and treatment.展开更多
BACKGROUND Signet-ring cell carcinoma(SRCC)was previously thought to have a worse prognosis than other differentiated gastric cancer(GC),however,recent studies have shown that the prognosis of SRCC is related to patho...BACKGROUND Signet-ring cell carcinoma(SRCC)was previously thought to have a worse prognosis than other differentiated gastric cancer(GC),however,recent studies have shown that the prognosis of SRCC is related to pathological type.We hypothesize that patients with SRCC and with different SRCC pathological components have different probability of lymph node metastasis(LNM).AIM To establish models to predict LNM in early GC(EGC),including early gastric SRCC.METHODS Clinical data from EGC patients who had undergone gastrectomy at the First Affiliated Hospital of Nanjing Medical University from January 2012 to March 2022 were reviewed.The patients were divided into three groups based on type:Pure SRCC,mixed SRCC,and non-signet ring cell carcinoma(NSRC).The risk factors were identified through statistical tests using SPSS 23.0,R,and EmpowerStats software.RESULTS A total of 1922 subjects with EGC were enrolled in this study,and included 249 SRCC patients and 1673 NSRC patients,while 278 of the patients(14.46%)presented with LNM.Multivariable analysis showed that gender,tumor size,depth of invasion,lymphovascular invasion,ulceration,and histological subtype were independent risk factors for LNM in EGC.Establishment and analysis using prediction models of EGC showed that the artificial neural network model was better than the logistic regression model in terms of sensitivity and accuracy(98.0%vs 58.1%,P=0.034;88.4%vs 86.8%,P<0.001,respectively).Among the 249 SRCC patients,LNM was more common in mixed(35.06%)rather than in pure SRCC(8.42%,P<0.001).The area under the ROC curve of the logistic regression model for LNM in SRCC was 0.760(95%CI:0.682-0.843),while the area under the operating characteristic curve of the internal validation set was 0.734(95%CI:0.643-0.826).The subgroups analysis of pure types showed that LNM was more common in patients with a tumor size>2 cm(OR=5.422,P=0.038).CONCLUSION A validated prediction model was developed to recognize the risk of LNM in EGC and early gastric SRCC,which can aid in pre-surgical decision making of the best method of treatment for patients.展开更多
BACKGROUND Superficial esophageal squamous cell carcinoma(ESCC)is defined as cancer infiltrating the mucosa and submucosa,regardless of regional lymph node metastasis(LNM).Endoscopic resection of superficial ESCC is s...BACKGROUND Superficial esophageal squamous cell carcinoma(ESCC)is defined as cancer infiltrating the mucosa and submucosa,regardless of regional lymph node metastasis(LNM).Endoscopic resection of superficial ESCC is suitable for lesions that have no or low risk of LNM.Patients with a high risk of LNM always need further treatment after endoscopic resection.Therefore,accurately assessing the risk of LNM is critical for additional treatment options.AIM To analyze risk factors for LNM and develop a nomogram to predict LNM risk in superficial ESCC patients.METHODS Clinical and pathological data of superficial ESCC patients undergoing esophagectomy from January 1,2009 to January 31,2016 were collected.Logistic regression analysis was used to predict LNM risk factors,and a nomogram was developed based on risk factors derived from multivariate logistic regression analysis.The receiver operating characteristic(ROC)curve was used to obtain the accuracy of the nomogram model.RESULTSA total of 4660 patients with esophageal cancer underwent esophagectomy.Of these,474 superficial ESCC patientswere enrolled in the final analysis,with 322 patients in the training set and 142 patients in the validation set.Theprevalence of LNM was 3.29%(5/152)for intramucosal cancer and increased to 26.40%(85/322)for submucosalcancer.Multivariate logistic analysis showed that tumor size,invasive depth,tumor differentiation,infiltrativegrowth pattern,tumor budding,and lymphovascular invasion were significantly correlated with LNM.Anomogram using these six variables showed good discrimination with an area under the ROC curve of 0.789(95%CI:0.737-0.841)in the training set and 0.827(95%CI:0.755-0.899)in the validation set.CONCLUSIONWe developed a useful nomogram model to predict LNM risk for superficial ESCC patients which will facilitateadditional decision-making in treating patients who undergo endoscopic resection.展开更多
BACKGROUND For the prognosis of patients with early gastric cancer(EGC),lymph node metastasis(LNM)plays a crucial role.A thorough and precise evaluation of the patient for LNM is now required.AIM To determine the fact...BACKGROUND For the prognosis of patients with early gastric cancer(EGC),lymph node metastasis(LNM)plays a crucial role.A thorough and precise evaluation of the patient for LNM is now required.AIM To determine the factors influencing LNM and to construct a prediction model of LNM for EGC patients.METHODS Clinical information and pathology data of 2217 EGC patients downloaded from the Surveillance,Epidemiology,and End Results database were collected and analyzed.Based on a 7:3 ratio,1550 people were categorized into training sets and 667 people were assigned to testing sets,randomly.Based on the factors influencing LNM determined by the training sets,the nomogram was drawn and verified.RESULTS Based on multivariate analysis,age at diagnosis,histology type,grade,T-stage,and size were risk factors of LNM for EGC.Besides,nomogram was drawn to predict the risk of LNM for EGC patients.Among the categorical variables,the effect of grade(well,moderate,and poor)was the most significant prognosis factor.For training sets and testing sets,respectively,area under the receiver-operating characteristic curve of nomograms were 0.751[95%confidence interval(CI):0.721-0.782]and 0.786(95%CI:0.742-0.830).In addition,the calibration curves showed that the prediction model of LNM had good consistency.CONCLUSION Age at diagnosis,histology type,grade,T-stage,and tumor size were independent variables for LNM in EGC.Based on the above risk factors,prediction model may offer some guiding implications for the choice of subsequent therapeutic approaches for EGC.展开更多
BACKGROUND Colorectal cancer(CRC)is a significant global health issue,and lymph node metastasis(LNM)is a crucial prognostic factor.Accurate prediction of LNM is essential for developing individualized treatment strate...BACKGROUND Colorectal cancer(CRC)is a significant global health issue,and lymph node metastasis(LNM)is a crucial prognostic factor.Accurate prediction of LNM is essential for developing individualized treatment strategies for patients with CRC.However,the prediction of LNM is challenging and depends on various factors such as tumor histology,clinicopathological features,and molecular characteristics.The most reliable method to detect LNM is the histopathological examination of surgically resected specimens;however,this method is invasive,time-consuming,and subject to sampling errors and interobserver variability.AIM To analyze influencing factors and develop and validate a risk prediction model for LNM in CRC based on a large patient queue.METHODS This study retrospectively analyzed 300 patients who underwent CRC surgery at two Peking University Shenzhen hospitals between January and December 2021.A deep learning approach was used to extract features potentially associated with LNM from primary tumor histological images while a logistic regression model was employed to predict LNM in CRC using machine-learning-derived features and clinicopathological variables as predictors.RESULTS The prediction model constructed for LNM in CRC was based on a logistic regression framework that incorporated machine learning-extracted features and clinicopathological variables.The model achieved high accuracy(0.86),sensitivity(0.81),specificity(0.87),positive predictive value(0.66),negative predictive value(0.94),area under the curve for the receiver operating characteristic(0.91),and a low Brier score(0.10).The model showed good agreement between the observed and predicted probabilities of LNM across a range of risk thresholds,indicating good calibration and clinical utility.CONCLUSION The present study successfully developed and validated a potent and effective risk-prediction model for LNM in patients with CRC.This model utilizes machine-learning-derived features extracted from primary tumor histology and clinicopathological variables,demonstrating superior performance and clinical applicability compared to existing models.The study provides new insights into the potential of deep learning to extract valuable information from tumor histology,in turn,improving the prediction of LNM in CRC and facilitate risk stratification and decision-making in clinical practice.展开更多
BACKGROUND Malignant proliferating trichilemmal tumor(MPTT)is an infrequent malignant neoplasm originating from cutaneous appendages,with only a handful of documented cases.This report delineates a unique instance of ...BACKGROUND Malignant proliferating trichilemmal tumor(MPTT)is an infrequent malignant neoplasm originating from cutaneous appendages,with only a handful of documented cases.This report delineates a unique instance of MPTT situated in the neck,accompanied by lymph node metastasis.A comprehensive exposition of its clinical trajectory and imaging manifestation is presented,aiming to enhance comprehension and management of this atypical ailment.CASE SUMMARY Patient concerns:A 79-year-old male presented with a longstanding right neck mass persisting for over six decades,exhibiting recent enlargement over the past year.Diagnoses:Enhanced magnetic resonance imaging of the neck unveiled an elliptical mass on the right neck side,characterized by an ill-defined border and a heterogeneous signal pattern.The mass exhibited subdued signal intensity on T1-weighted imaging(T1WI)and a heterogeneous high signal on T2-weighted imaging(T2WI),interspersed with a lengthy T1 and T2 cystic signal motif.Close anatomical association with the submandibular gland joint was noted,and intravenous gadolinium diethylene triamine pentaacetic acid administration facilitated conspicuous enhancement.Substantial enhancement of the solid segment prompted an initial preoperative diagnosis of malignant nerve sheath tumor.However,post-surgery histopathological and immunohistochemical analysis conclusively confirmed the diagnosis as malignant hyperplastic external hair root sheath tumor.Intervention:Complete excision of the tumor was successfully executed.Outcomes:The patient experienced a favorable postoperative recovery.CONCLUSION Malignant proliferative trichilemmal tumor external hair root sheath tumor is a cystic-solid lesion,appearing as low signal on T1WI images or high signal on T2WI with enhancement of the solid component.Suspicions of malignancy are heightened when the tumor border is indistinct,tissue planes are breached,or when linear or patchy high signals are observed in the subcutaneous tissue on T1 liver acquisition with volume acceleration enhanced images along with intermediate signal on T2WI and restricted diffusion on diffusion-weighted imaging images.Strong consideration for malignancy should arise if there are signs of compromised adjacent tissue relationships or direct invasion evident on imaging.We have incorporated the above-mentioned content into the entire manuscript.展开更多
BACKGROUND Given the poor prognosis of patients with lymph node metastasis,estimating the lymph node status in patients with early esophageal cancer is crucial.Indicators that could be used to predict lymph node metas...BACKGROUND Given the poor prognosis of patients with lymph node metastasis,estimating the lymph node status in patients with early esophageal cancer is crucial.Indicators that could be used to predict lymph node metastasis in early esophageal cancer have been reported in many recent studies,but no recent studies have included a review of this subject.AIM To review indicators predicting lymph node metastasis in early esophageal squamous cell carcinoma(ESCC)and early esophageal adenocarcinoma(EAC).METHODS We searched PubMed with“[early esophageal cancer(Title/Abstract)]and[lymph node(Title/Abstract)]”or“[early esophageal carcinoma(Title/Abstract)]and[lymph node(Title/Abstract)]”or“[superficial esophageal cancer(Title/Abstract)]and[lymph node(Title/Abstract)].”A total of 29 studies were eligible for analysis.RESULTS Preoperative imaging(size),serum markers(microRNA-218),postoperative pathology and immunohistochemical analysis(depth of invasion,tumor size,differentiation grade,lymphovascular invasion,neural invasion,expression of PIM-1<30%)were predictive factors for lymph node metastasis in both early ESCC and EAC.Serum markers(thymidine kinase 1≥3.38 pmol/L;cytokeratin 19 fragment antigen 21-1>3.30 ng/mL;stathmin-1)and postoperative pathology and immunohistochemical analysis(overexpression of cortactin,mixed-lineage leukaemia 2,and stanniocalcin-1)were predictive for lymph node metastasis in early ESCC.Transcription of CD69,myeloid differentiation protein 88 and toll-like receptor 4 and low expression of olfactomedin 4 were predictive of lymph node metastasis in early EAC.A total of 6 comprehensive models for early ESCC,including logistic regression model,nomogram,and artificial neural network(ANN),were reviewed.The areas under the receiver operating characteristic curve of these models reached 0.789-0.938,and the ANN performed best.As all these models relied on postoperative pathology,further models focusing on serum markers,imaging and immunohistochemical indicators are still needed.CONCLUSION Various factors were predictive of lymph node metastasis in early esophageal cancer,and present comprehensive models predicting lymph node metastasis in early ESCC mainly relied on postoperative pathology.Further studies focusing on serum markers,imaging and immunohistochemical indicators are still in need.展开更多
Objective: To predict the risk factors of lymph node metastasis in cervical cancer by using large sample clinical data, and to construct and verify the nomogram for predicting lymph node metastasis. Methods: A total o...Objective: To predict the risk factors of lymph node metastasis in cervical cancer by using large sample clinical data, and to construct and verify the nomogram for predicting lymph node metastasis. Methods: A total of 5940 patients with cervical cancer from 2004 to 2015 in the National Cancer Institute Surveillance Epidemiology and End Results database were retrospectively screened and randomly assigned to training group (n = 4172) and validation group (n = 1768). Multivariate Logistic regression analysis was used, and the optimal model was selected according to AIC or BIC and likelihood ratio test, and a nomogram was drawn. The accuracy and robustness of the prediction model were evaluated in three aspects: discrimination, calibration and clinical net benefit. Results: The prediction model based on race, tumor tissue differentiation degree, tumor histopathological type, distant metastasis of tumor, tumor diameter and other risk factors was successfully established and a nomogram was constructed. The AUCs of training group and validation group were: 0.736 and 0.714, respectively. And the p-values of the Hosmer-Lemeshow test were 0.28 and 0.11, respectively. The calibration curve was in good agreement with the ideal curve. It had high accuracy and applicability after internal verification. Conclusion: A prediction model is constructed based on the risk factors of lymph node metastasis of cervical cancer. The nomogram has a good effective prediction and can provide a theoretical basis for clinicians to assess the disease quickly before surgery.展开更多
AIM:To investigate the correlation between gastric cancer growth and signal transducer and activator of transcription-3(STAT3) expression.METHODS:We assessed the expressions of STAT3,phosphor-STAT3(pSTAT3),suppressor ...AIM:To investigate the correlation between gastric cancer growth and signal transducer and activator of transcription-3(STAT3) expression.METHODS:We assessed the expressions of STAT3,phosphor-STAT3(pSTAT3),suppressor of cytokine signaling-1(SOCS-1),survivin and Bcl-2 in gastric cancer patients after gastrectomy by immunohistochemical method.In addition,in situ hybridization was used to further demonstrate the mRNA expression of STAT3 in gastric cancer.RESULTS:With the univariate analysis,expressions of STAT3,pSTAT3,SOCS-1,survivin and Bcl-2,the size of primary tumor and the lymph node metastasis were found to be associated with the overall survival(OS) of gastric cancer patients.However,only pSTAT3 expression and the lymph node metastasis were identified as the independent factors of OS of gastric cancer with multivariate analysis.STAT3 expression was correlated with the lymph node metastasis.There were positive correlations between expressions of STAT3,survivin,Bcl-2 and pSTAT3 in gastric cancer,whereas there was negative correlation between STAT3 expression and SOCS-1 expression in gastric cancer.CONCLUSION:STAT3 can transform into pSTAT3 to promote the survival and inhibit the apoptosis of gastric cancer cells.SOCS-1 might be the valid molecular antagonist to inhibit the STAT3 expression in gastric cancer.展开更多
The aim of the present study was to examine the relationship between the protein expression of vascular endothelial growth factor(VEGF) and lymph node metastasis(LNM) in papillary thyroid cancer(PTC). VEGF-related art...The aim of the present study was to examine the relationship between the protein expression of vascular endothelial growth factor(VEGF) and lymph node metastasis(LNM) in papillary thyroid cancer(PTC). VEGF-related articles that had been published until August 2016 were searched from the Pub Med, EMBASE, and MEDLINE to identify the risk factors of LNM in PTC. Rev Man 5.3 software was used for the meta-analysis. Finally, 9 articles met the inclusion criteria and were included in our meta-analysis. LNM was found to be present in 176 of 318 patients(57.8%) with high VEGF expression and in 71 of 159 patients(47.0%) with low VEGF expression. The overall OR was 2.81(95% confidence interval, 1.49–5.29). LNM occurred more frequently in patients with high VEGF expression than in those with low VEGF expression(P=0.001). Heterogeneity was markedly decreased in the subgroup analyses of LNM in terms of the patients' country of origin and the detection methods. Our meta-analysis concluded that the VEGF protein expression is associated with LNM in PTC.展开更多
The purpose of this study was to assess the differences in clinical and sonographic features of papillary thyroid carcinoma(PTC) between cervical lymph node metastatic(CLNM) and nonmetastatic groups.Clinical data of P...The purpose of this study was to assess the differences in clinical and sonographic features of papillary thyroid carcinoma(PTC) between cervical lymph node metastatic(CLNM) and nonmetastatic groups.Clinical data of PTC patients(414 patients with 624 malignant nodules) who underwent a preoperative ultrasonography and surgery between June 2010 and March 2015 at Renmin Hospital of Wuhan University were retrospectively analyzed.Clinical factors,preoperative ultrasound features and the final pathological findings were obtained.The differences in the sonographic features of PTC between the CLNM group and the non-CLNM group were analyzed.There were 187 CLNM and 227 non-CLNM patients.The median age at the diagnosis of this cohort was 45.4 years old(ranging from 18 to 77 years).Ultrasonographic parameters that were significantly associated with CLNM [OR=2.569(1.502,4.393),P<0.001)] were as follows:the mulifocality of the nodules,size over 2 cm,the presence of microcalcifications,the distance ratio(DR) pattern showing the contact of the nodules with the thyroid capsule,and the extracapsular spread of the nodules.No significant differences in age,gender,thyroid stimulating hormone(TSH) levels and other ultrasonography parameters were found between the CLNM and the non-CLNM groups.Therefore,our results suggest that a larger size,microcalcifications,mulifocality,and the DR pattern showing the contact of the nodules with the thyroid capsule and extracapsular spread are significantly more indicative of CLNM in PTC.展开更多
The study aimed to examine the applicability of carbon nanoparticles as a tracer for lymph node mapping and the related factors of lymph node and No.8p subgroup metastasis in patients with gastric cancer.Clinical data...The study aimed to examine the applicability of carbon nanoparticles as a tracer for lymph node mapping and the related factors of lymph node and No.8p subgroup metastasis in patients with gastric cancer.Clinical data of 50 patients with gastric cancer,who had not received treatment preoperatively and underwent gastrectomy in Department of Gastrointestinal Surgery,Wuhan Union Hospital,between October 2014 and August 2015,were retrospectively analyzed.These patients were found to have no distant metastasis preoperatively.Thirty-five out of 50 patients were subjected to lymphatic mapping technique using carbon nanoparticles as the tracer,and the rest 15 cases did not experience the lymphatic mapping and served as controls.The sensitivity,specificity,false positive rate and false negative rate were calculated according to the number of lymph nodes,and the staining and metastasis condition of lymph nodes.The diagnostic value of carbon nanoparticles on metastatic lymph nodes was evaluated.The relationship between the metastasis of lymph nodes or subgroup No.8p lymph nodes and clinicopathologic features was analyzed by χ2-test or Fisher's exact test.All patients underwent D2 surgery(lymph node dissection including all the group 1 and group 2 nodes) plus the dissection of the subgroup No.8p lymph nodes.It was found that the average number of harvested lymph nodes in lymphatic mapping technique group(45.7±14.5) was greater than that in control group(39.2±11.7),but the difference was not significantly different(P=0.138>0.05).The success rate,the accuracy,sensitivity,specificity and false negative rate was 97%,57%,28%,62% and 72% respectively.The metastasis of lymph nodes was correlated to the depth of cancer invasion(T stage)(P=0.004<0.05),and the metastasis of No.8p lymph nodes was correlated to the extent of lymph node involvement(N stage)(P=0.007<0.05).Six cases had lymph node metastasis in subgroup No.8p,and their TNM stages and clinical stages were as follows:T1N2M0 ⅡA,T3N3M0 ⅢB,T4 a N3M0 ⅢC,T4 a N3M0 ⅢC,T4 a N3M0 ⅢC,and T4 b N3M0 ⅢC.In conclusion,our study indicated that carbon nanoparticles failed to show good selectivity for metastatic lymph nodes;the result of lymphatic mapping does not achieve a satisfactory performance;the incidence of lymph node metastasis may increase,accompanying with the increase of the depth of cancer invasion;No.8p lymph node metastasis tends to occur for gastric carcinoma patients with the extent of lymph node metastasis over N2 stage.展开更多
Objective:The current standard D2 lymphadenectomy for gastric cancer(GC)includes dissection of lymph nodes(LNs)along the proper hepatic artery(No.12 a),however,the survival benefit remains controversial.The purpose of...Objective:The current standard D2 lymphadenectomy for gastric cancer(GC)includes dissection of lymph nodes(LNs)along the proper hepatic artery(No.12 a),however,the survival benefit remains controversial.The purpose of this study was to evaluate the pattern of No.12 a LN metastasis(LNM)in GC and explore the indications for No.12 a LN dissection.Methods:Medical records of 413 consecutive GC patients who underwent curative surgery in Zhongshan Hospital,Fudan University between January 2015 and December 2018 were enrolled and reviewed retrospectively.The correlation between No.12 a LNM and clinicopathologic characteristics of patients was analyzed.Results:The overall incidence of No.12 a LNM was 2.67%(11/413).Tumor location(P=0.012),depth of tumor infiltration(P<0.01)and N stage(P=0.018)were significant factors associated with No.12 a LNM.All the tumors with No.12 a LNM involved the lower third of the stomach and were in T3-4 stages.Patients with No.12 a LNM had extensive LNM than those without(20.91±4.25 vs.5.0±0.54,P<0.001).For advanced GC patients(stage III/IV)with tumors involving the lower third of the stomach,the incidence of No.12 a LNM increased to 10.7%(11/103).Patients with No.12 a LNM had a significantly poorer recurrence-free survival(RFS)(P=0.005)and overall survival(OS)(P=0.017).According to the result of multivariable Cox regression,No.12 a LNM was not an independent impact factor on RFS and OS.Conclusions:The overall incidence of No.12 a LNM was low but it was much higher in GC patients who had very advanced tumors involving the lower third of the stomach.No.12 a LN dissection should be considered for these patients to improve the survival outcomes.展开更多
BACKGROUND Lymph node metastasis(LNM)affects the application and outcomes of endoscopic resection in T1 esophageal squamous cell carcinoma(ESCC).However,reports of the risk factors for LNM have been controversial.AIM ...BACKGROUND Lymph node metastasis(LNM)affects the application and outcomes of endoscopic resection in T1 esophageal squamous cell carcinoma(ESCC).However,reports of the risk factors for LNM have been controversial.AIM To evaluate risk factors for LNM in T1 ESCC.METHODS We searched Embase,PubMed and Cochrane Library to select studies related to LNM in patients with T1 ESCC.Included studies were divided into LNM and non-LNM groups.We performed a meta-analysis to examine the relationship between LNM and clinicopathologic features.Odds ratio(OR),mean differences and 95%confidence interval(CI)were assessed using a fixed-effects or randomeffects model.RESULTS Seventeen studies involving a total of 3775 patients with T1 ESCC met the inclusion criteria.After excluding studies with heterogeneity based on influence analysis,tumor size(OR=1.93,95%CI=1.49-2.50,P<0.001),tumor location(OR=1.46,95%CI=1.17-1.82,P<0.001),macroscopic type(OR=3.17,95%CI=2.33-4.31,P<0.001),T1 substage(OR=6.28,95%CI=4.93-8.00,P<0.001),differentiation(OR=2.11,95%CI=1.64-2.72,P<0.001)and lymphovascular invasion(OR=5.86,95%CI=4.60-7.48,P<0.001)were found to be significantly associated with LNM.Conversely,sex,age and infiltrative growth pattern were not identified as risk factors for LNM.CONCLUSION A tumor size>2 cm,lower location,nonflat macroscopic type,T1b stage,poor differentiation and lymphovascular invasion were associated with LNM in patients with T1 ESCC.展开更多
Superficial esophageal squamous cell carcinoma(SESCC)is defined as carcinoma with mucosal or submucosal invasion,regardless of regional lymph node metastasis(LNM).The lymph node status is not only a key factor to dete...Superficial esophageal squamous cell carcinoma(SESCC)is defined as carcinoma with mucosal or submucosal invasion,regardless of regional lymph node metastasis(LNM).The lymph node status is not only a key factor to determine the training strategy,but also the most important prognostic factor in esophageal cancer.In this study,we establish a clinical nomogram for predicting LNM in patients with SESCC.A predictive model was established based on the training cohort composed of 711 patients who underwent esophagectomy for SESCC from December 2009 to June 2018.A prospective cohort of 203 patients from June 2018 to January 2019 was used for validation.Favorable calibration and well-fitted decision curve analysis were conducted and good discrimination was observed(concordance index[C-index],0.860;95%confidence interval[CI],0.825-0.894)through internal validation.The external validation cohort presented good discrimination(C-index,0.916;95%CI,0.860-0.971).This model may facilitate the prediction of LNM in patients with SESCCs.展开更多
BACKGROUND Primary pancreatic paragangliomas are extremely rare tumors.Limited by the diagnostic efficacy of histopathological examination,their malignant behavior is thought to be associated with local invasion or me...BACKGROUND Primary pancreatic paragangliomas are extremely rare tumors.Limited by the diagnostic efficacy of histopathological examination,their malignant behavior is thought to be associated with local invasion or metastasis,with only four malignant cases reported in the literature to date.As pancreatic paragangliomas share similar imaging features with other types of pancreatic neuroendocrine neoplasms,they are difficult to diagnose accurately without the support of pathological evidence.As primary pancreatic paragangliomas are rare,especially those accompanied by lymph node metastasis,there is currently no consensus on treatment.Herein,we report a case of primary pancreatic paraganglioma with lymph node metastasis.CASE SUMMARY A mass located in the pancreatic body was incidentally discovered on computed tomography in a 41-year-old Tibetan man.Distal pancreatectomy was subsequently performed and a 4.1 cm×4.2 cm tumor was found embedded in the body of the pancreas during surgery.Histological examination confirmed the characteristics of paraganglioma in which the neoplastic chief cells were arranged in a classic Zellballen pattern under hematoxylin-eosin staining.Further,immunohistochemistry demonstrated that the sustentacular cells in the tumor tissue were positive for S-100 protein,and neoplastic cells and pancreatic draining lymph nodes were positive for chromogranin A and synaptophysin;thus,the presence of lymph node metastasis(two of the eight resected pancreatic draining lymph nodes)was also confirmed.A diagnosis of primary pancreatic paraganglioma with lymph node metastasis was finally established.The patient remained disease-free for 1 year after the surgery.CONCLUSION A definite diagnosis of pancreatic paraganglioma mainly depends on postoperative histopathological and immunohistochemical examinations.Surgical resection may be the first treatment of choice for patients with primary pancreatic paraganglioma that has metastasized to the lymph nodes.展开更多
BACKGROUND Tumor deposits(TDs)are not equivalent to lymph node(LN)metastasis(LNM)but have become independent adverse prognostic factors in patients with rectal cancer(RC).Although preoperatively differentiating TDs an...BACKGROUND Tumor deposits(TDs)are not equivalent to lymph node(LN)metastasis(LNM)but have become independent adverse prognostic factors in patients with rectal cancer(RC).Although preoperatively differentiating TDs and LNMs is helpful in designing individualized treatment strategies and achieving improved prognoses,it is a challenging task.AIM To establish a computed tomography(CT)-based radiomics model for preoperatively differentiating TDs from LNM in patients with RC.METHODS This study retrospectively enrolled 219 patients with RC[TDs+LNM-(n=89);LNM+TDs-(n=115);TDs+LNM+(n=15)]from a single center between September 2016 and September 2021.Single-positive patients(i.e.,TDs+LNM-and LNM+TDs-)were classified into the training(n=163)and validation(n=41)sets.We extracted numerous features from the enhanced CT(region 1:The main tumor;region 2:The largest peritumoral nodule).After deleting redundant features,three feature selection methods and three machine learning methods were used to select the best-performing classifier as the radiomics model(Rad-score).After validating Rad-score,its performance was further evaluated in the field of diagnosing double-positive patients(i.e.,TDs+LNM+)by outlining all peritumoral nodules with diameter(short-axis)>3 mm.RESULTS Rad-score 1(radiomics signature of the main tumor)had an area under the curve(AUC)of 0.768 on the training dataset and 0.700 on the validation dataset.Rad-score 2(radiomics signature of the largest peritumoral nodule)had a higher AUC(training set:0.940;validation set:0.918)than Radscore 1.Clinical factors,including age,gender,location of RC,tumor markers,and radiological features of the largest peritumoral nodule,were excluded by logistic regression.Thus,the combined model was comprised of Rad-scores of 1 and 2.Considering that the combined model had similar AUCs with Rad-score 2(P=0.134 in the training set and 0.594 in the validation set),Rad-score 2 was used as the final model.For the diagnosis of double-positive patients in the mixed group[TDs+LNM+(n=15);single-positive(n=15)],Rad-score 2 demonstrated moderate performance(sensitivity,73.3%;specificity,66.6%;and accuracy,70.0%).CONCLUSION Radiomics analysis based on the largest peritumoral nodule can be helpful in preoperatively differentiating between TDs and LNM.展开更多
Tumor lymph node(LN)metastasis seriously affects the treatment prognosis.Studies have shown that nanoparticles with size of sub-50 nm can directly penetrate into LN metastases after intravenous administration.Here,we ...Tumor lymph node(LN)metastasis seriously affects the treatment prognosis.Studies have shown that nanoparticles with size of sub-50 nm can directly penetrate into LN metastases after intravenous administration.Here,we speculate through introducing targeting capacity,the nanoparticle accumulation in LN metastases would be further enhanced for improved local treatment such as photothermal therapy.Trastuzumabtargeted micelles(<50 nm)were formulated using a unique surfactantstripping approach that yielded concentrated phthalocyanines with strong near-infrared absorption.Targeted micellar phthalocyanine(T-MP)was an effective photothermal transducer and ablated HT-29 cells in vitro.A HER2-expressing colorectal cancer cell line(HT-29)was used to establish an orthotopic mouse model that developed metastatic disease in mesenteric sentinel LN.T-MP accumulated more in the LN metastases compared to the micelles conjugated with control IgG.Following surgical resection of the primary tumor,minimally invasive photothermal treatment of the metastatic LN with T-MP,but not the control micelles,extended mouse survival.Our findings demonstrate for the first time that targeted small-sized nanoparticles have potential to enable superior paradigms for dealing with LN metastases.展开更多
BACKGROUND The most important consideration in determining treatment strategies for undifferentiated early gastric cancer(UEGC)is the risk of lymph node metastasis(LNM).Therefore,identifying a potential biomarker that...BACKGROUND The most important consideration in determining treatment strategies for undifferentiated early gastric cancer(UEGC)is the risk of lymph node metastasis(LNM).Therefore,identifying a potential biomarker that predicts LNM is quite useful in determining treatment.AIM To develop a machine learning(ML)-based integral procedure to construct the LNM gray-level co-occurrence matrix(GLCM)prediction model.METHODS We retrospectively selected 526 cases of UEGC confirmed through pathological examination after radical gastrectomy without endoscopic treatment in four tertiary hospitals between January 2015 to December 2021.We extracted GLCM-based features from grayscale images and applied ML to the classification of candidate predictive variables.The robustness and clinical utility of each model were evaluated based on the following factors:Receiver operating characteristic curve(ROC),decision curve analysis,and clinical impact curve.RESULTS GLCM-based feature extraction significantly correlated with LNM.The top 7 GLCM-based factors included inertia value 0°(IV_0),inertia value 45°(IV_45),inverse gap 0°(IG_0),inverse gap 45°(IG_45),inverse gap full angle(IG_all),Haralick 30°(Haralick_30),Haralick full angle(Haralick_all),and Entropy.The areas under the ROC curve(AUCs)of the random forest classifier(RFC)model,support vector machine,eXtreme gradient boosting,artificial neural network,and decision tree ranged from 0.805[95%confidence interval(CI):0.258-1.352]to 0.925(95%CI:0.378-1.472)in the training set and from 0.794(95%CI:0.237-1.351)to 0.912(95%CI:0.355-1.469)in the testing set,respectively.The RFC(training set:AUC:0.925,95%CI:0.378-1.472;testing set:AUC:0.912,95%CI:0.355-1.469)model that incorporates Entropy,Haralick_all,Haralick_30,IG_all,IG_45,IG_0,and IV_45 had the highest predictive accuracy.CONCLUSION The evaluation results indicate that the method of selecting radiological and textural features becomes more effective in the LNM discrimination against UEGC patients.Additionally,the MLbased prediction model developed using the RFC can be used to derive treatment options and identify LNM,which can hence improve clinical outcomes.展开更多
BACKGROUND Although PNENs generally have a better prognosis than pancreatic cancers,some PNENs display malignant behavior including lymph node(LN)metastasis.Complete tumor resection can be the only potentially curativ...BACKGROUND Although PNENs generally have a better prognosis than pancreatic cancers,some PNENs display malignant behavior including lymph node(LN)metastasis.Complete tumor resection can be the only potentially curative treatment for patients with resectable PNENs.However,the indications for LN dissection are still controversial.Over the last decade,minimally invasive surgery such as laparoscopic pancreatic surgery(LPS)has been increasingly performed for pancreatic tumors including PNENs.AIM To investigate the risk factors for LN metastasis in PNENs and to select appropriate patients for limited surgery by LPS.METHODS From April 2001 to December 2019,92 patients underwent pancreatic resection for PNENs at Kumamoto University Hospital.Finally,82 patients were enrolled in this study.Using perioperative factors,we examined the predictive factors for LN metastasis in PNENs.RESULTS Among the 82 patients,the percentage of LN metastasis according to the pathological findings was 12%(10/82 cases).The median tumor size was 12 mm(range:5-90 mm).The median tumor size in the LN-positive group(37 mm)was significantly larger than that in the LN-negative group(12 mm)(P=0.0001).Multivariate analyses revealed that larger tumor size(≥20 mm)was an independent risk factor for LN metastasis(odds ratio 16.8,P=0.0062).In patients with small tumors(≤10 mm),LN metastasis was not found.CONCLUSION Larger tumor size(≥20 mm)is an independent risk factor for LN metastasis in PNENs.In smaller PNENs(≤10 mm),we may be able to choose limited surgery without LN dissection.展开更多
文摘BACKGROUND Gastric cancer is one of the most common malignant tumors in the digestive system,ranking sixth in incidence and fourth in mortality worldwide.Since 42.5%of metastatic lymph nodes in gastric cancer belong to nodule type and peripheral type,the application of imaging diagnosis is restricted.AIM To establish models for predicting the risk of lymph node metastasis in gastric cancer patients using machine learning(ML)algorithms and to evaluate their pre-dictive performance in clinical practice.METHODS Data of a total of 369 patients who underwent radical gastrectomy at the Depart-ment of General Surgery of Affiliated Hospital of Xuzhou Medical University(Xuzhou,China)from March 2016 to November 2019 were collected and retro-spectively analyzed as the training group.In addition,data of 123 patients who underwent radical gastrectomy at the Department of General Surgery of Jining First People’s Hospital(Jining,China)were collected and analyzed as the verifi-cation group.Seven ML models,including decision tree,random forest,support vector machine(SVM),gradient boosting machine,naive Bayes,neural network,and logistic regression,were developed to evaluate the occurrence of lymph node metastasis in patients with gastric cancer.The ML models were established fo-llowing ten cross-validation iterations using the training dataset,and subsequently,each model was assessed using the test dataset.The models’performance was evaluated by comparing the area under the receiver operating characteristic curve of each model.RESULTS Among the seven ML models,except for SVM,the other ones exhibited higher accuracy and reliability,and the influences of various risk factors on the models are intuitive.CONCLUSION The ML models developed exhibit strong predictive capabilities for lymph node metastasis in gastric cancer,which can aid in personalized clinical diagnosis and treatment.
基金National Natural Science Foundation of China,No.82200625 and No.82100595Youth Talent Development Program,No.YNRCQN0313+2 种基金Young Scholar Fostering Fund of the First Affiliated Hospital of Nanjing Medical University,No.PY2021023Top Talent of Changzhou“The 14th Five-Year Plan”High-Level Health Talents Training Project,No.2022CZBJ051Natural Science Foundation of Jiangsu Province,China,No.BK20210958.
文摘BACKGROUND Signet-ring cell carcinoma(SRCC)was previously thought to have a worse prognosis than other differentiated gastric cancer(GC),however,recent studies have shown that the prognosis of SRCC is related to pathological type.We hypothesize that patients with SRCC and with different SRCC pathological components have different probability of lymph node metastasis(LNM).AIM To establish models to predict LNM in early GC(EGC),including early gastric SRCC.METHODS Clinical data from EGC patients who had undergone gastrectomy at the First Affiliated Hospital of Nanjing Medical University from January 2012 to March 2022 were reviewed.The patients were divided into three groups based on type:Pure SRCC,mixed SRCC,and non-signet ring cell carcinoma(NSRC).The risk factors were identified through statistical tests using SPSS 23.0,R,and EmpowerStats software.RESULTS A total of 1922 subjects with EGC were enrolled in this study,and included 249 SRCC patients and 1673 NSRC patients,while 278 of the patients(14.46%)presented with LNM.Multivariable analysis showed that gender,tumor size,depth of invasion,lymphovascular invasion,ulceration,and histological subtype were independent risk factors for LNM in EGC.Establishment and analysis using prediction models of EGC showed that the artificial neural network model was better than the logistic regression model in terms of sensitivity and accuracy(98.0%vs 58.1%,P=0.034;88.4%vs 86.8%,P<0.001,respectively).Among the 249 SRCC patients,LNM was more common in mixed(35.06%)rather than in pure SRCC(8.42%,P<0.001).The area under the ROC curve of the logistic regression model for LNM in SRCC was 0.760(95%CI:0.682-0.843),while the area under the operating characteristic curve of the internal validation set was 0.734(95%CI:0.643-0.826).The subgroups analysis of pure types showed that LNM was more common in patients with a tumor size>2 cm(OR=5.422,P=0.038).CONCLUSION A validated prediction model was developed to recognize the risk of LNM in EGC and early gastric SRCC,which can aid in pre-surgical decision making of the best method of treatment for patients.
基金the National Natural Science Foundation of China,No.82173253the Sichuan Province Science and Technology Support Program,No.2022YFH0003 and No.2023NSFSC1900+1 种基金the Postdoctoral Research Foundation of West China Hospital,No.2021HXBH020and the Medico-Engineering Cooperation Funds from the University of Electronic Science and Technology of China and West China Hospital of Sichuan University,No.HXDZ22005.
文摘BACKGROUND Superficial esophageal squamous cell carcinoma(ESCC)is defined as cancer infiltrating the mucosa and submucosa,regardless of regional lymph node metastasis(LNM).Endoscopic resection of superficial ESCC is suitable for lesions that have no or low risk of LNM.Patients with a high risk of LNM always need further treatment after endoscopic resection.Therefore,accurately assessing the risk of LNM is critical for additional treatment options.AIM To analyze risk factors for LNM and develop a nomogram to predict LNM risk in superficial ESCC patients.METHODS Clinical and pathological data of superficial ESCC patients undergoing esophagectomy from January 1,2009 to January 31,2016 were collected.Logistic regression analysis was used to predict LNM risk factors,and a nomogram was developed based on risk factors derived from multivariate logistic regression analysis.The receiver operating characteristic(ROC)curve was used to obtain the accuracy of the nomogram model.RESULTSA total of 4660 patients with esophageal cancer underwent esophagectomy.Of these,474 superficial ESCC patientswere enrolled in the final analysis,with 322 patients in the training set and 142 patients in the validation set.Theprevalence of LNM was 3.29%(5/152)for intramucosal cancer and increased to 26.40%(85/322)for submucosalcancer.Multivariate logistic analysis showed that tumor size,invasive depth,tumor differentiation,infiltrativegrowth pattern,tumor budding,and lymphovascular invasion were significantly correlated with LNM.Anomogram using these six variables showed good discrimination with an area under the ROC curve of 0.789(95%CI:0.737-0.841)in the training set and 0.827(95%CI:0.755-0.899)in the validation set.CONCLUSIONWe developed a useful nomogram model to predict LNM risk for superficial ESCC patients which will facilitateadditional decision-making in treating patients who undergo endoscopic resection.
文摘BACKGROUND For the prognosis of patients with early gastric cancer(EGC),lymph node metastasis(LNM)plays a crucial role.A thorough and precise evaluation of the patient for LNM is now required.AIM To determine the factors influencing LNM and to construct a prediction model of LNM for EGC patients.METHODS Clinical information and pathology data of 2217 EGC patients downloaded from the Surveillance,Epidemiology,and End Results database were collected and analyzed.Based on a 7:3 ratio,1550 people were categorized into training sets and 667 people were assigned to testing sets,randomly.Based on the factors influencing LNM determined by the training sets,the nomogram was drawn and verified.RESULTS Based on multivariate analysis,age at diagnosis,histology type,grade,T-stage,and size were risk factors of LNM for EGC.Besides,nomogram was drawn to predict the risk of LNM for EGC patients.Among the categorical variables,the effect of grade(well,moderate,and poor)was the most significant prognosis factor.For training sets and testing sets,respectively,area under the receiver-operating characteristic curve of nomograms were 0.751[95%confidence interval(CI):0.721-0.782]and 0.786(95%CI:0.742-0.830).In addition,the calibration curves showed that the prediction model of LNM had good consistency.CONCLUSION Age at diagnosis,histology type,grade,T-stage,and tumor size were independent variables for LNM in EGC.Based on the above risk factors,prediction model may offer some guiding implications for the choice of subsequent therapeutic approaches for EGC.
文摘BACKGROUND Colorectal cancer(CRC)is a significant global health issue,and lymph node metastasis(LNM)is a crucial prognostic factor.Accurate prediction of LNM is essential for developing individualized treatment strategies for patients with CRC.However,the prediction of LNM is challenging and depends on various factors such as tumor histology,clinicopathological features,and molecular characteristics.The most reliable method to detect LNM is the histopathological examination of surgically resected specimens;however,this method is invasive,time-consuming,and subject to sampling errors and interobserver variability.AIM To analyze influencing factors and develop and validate a risk prediction model for LNM in CRC based on a large patient queue.METHODS This study retrospectively analyzed 300 patients who underwent CRC surgery at two Peking University Shenzhen hospitals between January and December 2021.A deep learning approach was used to extract features potentially associated with LNM from primary tumor histological images while a logistic regression model was employed to predict LNM in CRC using machine-learning-derived features and clinicopathological variables as predictors.RESULTS The prediction model constructed for LNM in CRC was based on a logistic regression framework that incorporated machine learning-extracted features and clinicopathological variables.The model achieved high accuracy(0.86),sensitivity(0.81),specificity(0.87),positive predictive value(0.66),negative predictive value(0.94),area under the curve for the receiver operating characteristic(0.91),and a low Brier score(0.10).The model showed good agreement between the observed and predicted probabilities of LNM across a range of risk thresholds,indicating good calibration and clinical utility.CONCLUSION The present study successfully developed and validated a potent and effective risk-prediction model for LNM in patients with CRC.This model utilizes machine-learning-derived features extracted from primary tumor histology and clinicopathological variables,demonstrating superior performance and clinical applicability compared to existing models.The study provides new insights into the potential of deep learning to extract valuable information from tumor histology,in turn,improving the prediction of LNM in CRC and facilitate risk stratification and decision-making in clinical practice.
文摘BACKGROUND Malignant proliferating trichilemmal tumor(MPTT)is an infrequent malignant neoplasm originating from cutaneous appendages,with only a handful of documented cases.This report delineates a unique instance of MPTT situated in the neck,accompanied by lymph node metastasis.A comprehensive exposition of its clinical trajectory and imaging manifestation is presented,aiming to enhance comprehension and management of this atypical ailment.CASE SUMMARY Patient concerns:A 79-year-old male presented with a longstanding right neck mass persisting for over six decades,exhibiting recent enlargement over the past year.Diagnoses:Enhanced magnetic resonance imaging of the neck unveiled an elliptical mass on the right neck side,characterized by an ill-defined border and a heterogeneous signal pattern.The mass exhibited subdued signal intensity on T1-weighted imaging(T1WI)and a heterogeneous high signal on T2-weighted imaging(T2WI),interspersed with a lengthy T1 and T2 cystic signal motif.Close anatomical association with the submandibular gland joint was noted,and intravenous gadolinium diethylene triamine pentaacetic acid administration facilitated conspicuous enhancement.Substantial enhancement of the solid segment prompted an initial preoperative diagnosis of malignant nerve sheath tumor.However,post-surgery histopathological and immunohistochemical analysis conclusively confirmed the diagnosis as malignant hyperplastic external hair root sheath tumor.Intervention:Complete excision of the tumor was successfully executed.Outcomes:The patient experienced a favorable postoperative recovery.CONCLUSION Malignant proliferative trichilemmal tumor external hair root sheath tumor is a cystic-solid lesion,appearing as low signal on T1WI images or high signal on T2WI with enhancement of the solid component.Suspicions of malignancy are heightened when the tumor border is indistinct,tissue planes are breached,or when linear or patchy high signals are observed in the subcutaneous tissue on T1 liver acquisition with volume acceleration enhanced images along with intermediate signal on T2WI and restricted diffusion on diffusion-weighted imaging images.Strong consideration for malignancy should arise if there are signs of compromised adjacent tissue relationships or direct invasion evident on imaging.We have incorporated the above-mentioned content into the entire manuscript.
基金Natural Science Foundation of Tibetan Autonomous Region,No.XZ202101ZR0015GMedical Program of Group Aid to Tibet,Natural Science Foundation of Tibetan Autonomous Region,No.XZ2021ZR-ZY27(Z).
文摘BACKGROUND Given the poor prognosis of patients with lymph node metastasis,estimating the lymph node status in patients with early esophageal cancer is crucial.Indicators that could be used to predict lymph node metastasis in early esophageal cancer have been reported in many recent studies,but no recent studies have included a review of this subject.AIM To review indicators predicting lymph node metastasis in early esophageal squamous cell carcinoma(ESCC)and early esophageal adenocarcinoma(EAC).METHODS We searched PubMed with“[early esophageal cancer(Title/Abstract)]and[lymph node(Title/Abstract)]”or“[early esophageal carcinoma(Title/Abstract)]and[lymph node(Title/Abstract)]”or“[superficial esophageal cancer(Title/Abstract)]and[lymph node(Title/Abstract)].”A total of 29 studies were eligible for analysis.RESULTS Preoperative imaging(size),serum markers(microRNA-218),postoperative pathology and immunohistochemical analysis(depth of invasion,tumor size,differentiation grade,lymphovascular invasion,neural invasion,expression of PIM-1<30%)were predictive factors for lymph node metastasis in both early ESCC and EAC.Serum markers(thymidine kinase 1≥3.38 pmol/L;cytokeratin 19 fragment antigen 21-1>3.30 ng/mL;stathmin-1)and postoperative pathology and immunohistochemical analysis(overexpression of cortactin,mixed-lineage leukaemia 2,and stanniocalcin-1)were predictive for lymph node metastasis in early ESCC.Transcription of CD69,myeloid differentiation protein 88 and toll-like receptor 4 and low expression of olfactomedin 4 were predictive of lymph node metastasis in early EAC.A total of 6 comprehensive models for early ESCC,including logistic regression model,nomogram,and artificial neural network(ANN),were reviewed.The areas under the receiver operating characteristic curve of these models reached 0.789-0.938,and the ANN performed best.As all these models relied on postoperative pathology,further models focusing on serum markers,imaging and immunohistochemical indicators are still needed.CONCLUSION Various factors were predictive of lymph node metastasis in early esophageal cancer,and present comprehensive models predicting lymph node metastasis in early ESCC mainly relied on postoperative pathology.Further studies focusing on serum markers,imaging and immunohistochemical indicators are still in need.
文摘Objective: To predict the risk factors of lymph node metastasis in cervical cancer by using large sample clinical data, and to construct and verify the nomogram for predicting lymph node metastasis. Methods: A total of 5940 patients with cervical cancer from 2004 to 2015 in the National Cancer Institute Surveillance Epidemiology and End Results database were retrospectively screened and randomly assigned to training group (n = 4172) and validation group (n = 1768). Multivariate Logistic regression analysis was used, and the optimal model was selected according to AIC or BIC and likelihood ratio test, and a nomogram was drawn. The accuracy and robustness of the prediction model were evaluated in three aspects: discrimination, calibration and clinical net benefit. Results: The prediction model based on race, tumor tissue differentiation degree, tumor histopathological type, distant metastasis of tumor, tumor diameter and other risk factors was successfully established and a nomogram was constructed. The AUCs of training group and validation group were: 0.736 and 0.714, respectively. And the p-values of the Hosmer-Lemeshow test were 0.28 and 0.11, respectively. The calibration curve was in good agreement with the ideal curve. It had high accuracy and applicability after internal verification. Conclusion: A prediction model is constructed based on the risk factors of lymph node metastasis of cervical cancer. The nomogram has a good effective prediction and can provide a theoretical basis for clinicians to assess the disease quickly before surgery.
基金Supported by National Basic Research Program of China(973 Program),No.2010CB529301Tianjin Health Bureau Research Foundation,No.09KC74
文摘AIM:To investigate the correlation between gastric cancer growth and signal transducer and activator of transcription-3(STAT3) expression.METHODS:We assessed the expressions of STAT3,phosphor-STAT3(pSTAT3),suppressor of cytokine signaling-1(SOCS-1),survivin and Bcl-2 in gastric cancer patients after gastrectomy by immunohistochemical method.In addition,in situ hybridization was used to further demonstrate the mRNA expression of STAT3 in gastric cancer.RESULTS:With the univariate analysis,expressions of STAT3,pSTAT3,SOCS-1,survivin and Bcl-2,the size of primary tumor and the lymph node metastasis were found to be associated with the overall survival(OS) of gastric cancer patients.However,only pSTAT3 expression and the lymph node metastasis were identified as the independent factors of OS of gastric cancer with multivariate analysis.STAT3 expression was correlated with the lymph node metastasis.There were positive correlations between expressions of STAT3,survivin,Bcl-2 and pSTAT3 in gastric cancer,whereas there was negative correlation between STAT3 expression and SOCS-1 expression in gastric cancer.CONCLUSION:STAT3 can transform into pSTAT3 to promote the survival and inhibit the apoptosis of gastric cancer cells.SOCS-1 might be the valid molecular antagonist to inhibit the STAT3 expression in gastric cancer.
文摘The aim of the present study was to examine the relationship between the protein expression of vascular endothelial growth factor(VEGF) and lymph node metastasis(LNM) in papillary thyroid cancer(PTC). VEGF-related articles that had been published until August 2016 were searched from the Pub Med, EMBASE, and MEDLINE to identify the risk factors of LNM in PTC. Rev Man 5.3 software was used for the meta-analysis. Finally, 9 articles met the inclusion criteria and were included in our meta-analysis. LNM was found to be present in 176 of 318 patients(57.8%) with high VEGF expression and in 71 of 159 patients(47.0%) with low VEGF expression. The overall OR was 2.81(95% confidence interval, 1.49–5.29). LNM occurred more frequently in patients with high VEGF expression than in those with low VEGF expression(P=0.001). Heterogeneity was markedly decreased in the subgroup analyses of LNM in terms of the patients' country of origin and the detection methods. Our meta-analysis concluded that the VEGF protein expression is associated with LNM in PTC.
基金supported by the National Natural Science Foundation of China(No.81471781,No.81502665 and No.81302314/H1622)the Fundamental Research Funds of Health and Family Planning Commission of Hubei Province(No.JS-20110118)the Fundamental Research Funds for the Central Universities of China(No.2042014kf0189)
文摘The purpose of this study was to assess the differences in clinical and sonographic features of papillary thyroid carcinoma(PTC) between cervical lymph node metastatic(CLNM) and nonmetastatic groups.Clinical data of PTC patients(414 patients with 624 malignant nodules) who underwent a preoperative ultrasonography and surgery between June 2010 and March 2015 at Renmin Hospital of Wuhan University were retrospectively analyzed.Clinical factors,preoperative ultrasound features and the final pathological findings were obtained.The differences in the sonographic features of PTC between the CLNM group and the non-CLNM group were analyzed.There were 187 CLNM and 227 non-CLNM patients.The median age at the diagnosis of this cohort was 45.4 years old(ranging from 18 to 77 years).Ultrasonographic parameters that were significantly associated with CLNM [OR=2.569(1.502,4.393),P<0.001)] were as follows:the mulifocality of the nodules,size over 2 cm,the presence of microcalcifications,the distance ratio(DR) pattern showing the contact of the nodules with the thyroid capsule,and the extracapsular spread of the nodules.No significant differences in age,gender,thyroid stimulating hormone(TSH) levels and other ultrasonography parameters were found between the CLNM and the non-CLNM groups.Therefore,our results suggest that a larger size,microcalcifications,mulifocality,and the DR pattern showing the contact of the nodules with the thyroid capsule and extracapsular spread are significantly more indicative of CLNM in PTC.
文摘The study aimed to examine the applicability of carbon nanoparticles as a tracer for lymph node mapping and the related factors of lymph node and No.8p subgroup metastasis in patients with gastric cancer.Clinical data of 50 patients with gastric cancer,who had not received treatment preoperatively and underwent gastrectomy in Department of Gastrointestinal Surgery,Wuhan Union Hospital,between October 2014 and August 2015,were retrospectively analyzed.These patients were found to have no distant metastasis preoperatively.Thirty-five out of 50 patients were subjected to lymphatic mapping technique using carbon nanoparticles as the tracer,and the rest 15 cases did not experience the lymphatic mapping and served as controls.The sensitivity,specificity,false positive rate and false negative rate were calculated according to the number of lymph nodes,and the staining and metastasis condition of lymph nodes.The diagnostic value of carbon nanoparticles on metastatic lymph nodes was evaluated.The relationship between the metastasis of lymph nodes or subgroup No.8p lymph nodes and clinicopathologic features was analyzed by χ2-test or Fisher's exact test.All patients underwent D2 surgery(lymph node dissection including all the group 1 and group 2 nodes) plus the dissection of the subgroup No.8p lymph nodes.It was found that the average number of harvested lymph nodes in lymphatic mapping technique group(45.7±14.5) was greater than that in control group(39.2±11.7),but the difference was not significantly different(P=0.138>0.05).The success rate,the accuracy,sensitivity,specificity and false negative rate was 97%,57%,28%,62% and 72% respectively.The metastasis of lymph nodes was correlated to the depth of cancer invasion(T stage)(P=0.004<0.05),and the metastasis of No.8p lymph nodes was correlated to the extent of lymph node involvement(N stage)(P=0.007<0.05).Six cases had lymph node metastasis in subgroup No.8p,and their TNM stages and clinical stages were as follows:T1N2M0 ⅡA,T3N3M0 ⅢB,T4 a N3M0 ⅢC,T4 a N3M0 ⅢC,T4 a N3M0 ⅢC,and T4 b N3M0 ⅢC.In conclusion,our study indicated that carbon nanoparticles failed to show good selectivity for metastatic lymph nodes;the result of lymphatic mapping does not achieve a satisfactory performance;the incidence of lymph node metastasis may increase,accompanying with the increase of the depth of cancer invasion;No.8p lymph node metastasis tends to occur for gastric carcinoma patients with the extent of lymph node metastasis over N2 stage.
基金supported by National Natural Science Fund(No.31842033)。
文摘Objective:The current standard D2 lymphadenectomy for gastric cancer(GC)includes dissection of lymph nodes(LNs)along the proper hepatic artery(No.12 a),however,the survival benefit remains controversial.The purpose of this study was to evaluate the pattern of No.12 a LN metastasis(LNM)in GC and explore the indications for No.12 a LN dissection.Methods:Medical records of 413 consecutive GC patients who underwent curative surgery in Zhongshan Hospital,Fudan University between January 2015 and December 2018 were enrolled and reviewed retrospectively.The correlation between No.12 a LNM and clinicopathologic characteristics of patients was analyzed.Results:The overall incidence of No.12 a LNM was 2.67%(11/413).Tumor location(P=0.012),depth of tumor infiltration(P<0.01)and N stage(P=0.018)were significant factors associated with No.12 a LNM.All the tumors with No.12 a LNM involved the lower third of the stomach and were in T3-4 stages.Patients with No.12 a LNM had extensive LNM than those without(20.91±4.25 vs.5.0±0.54,P<0.001).For advanced GC patients(stage III/IV)with tumors involving the lower third of the stomach,the incidence of No.12 a LNM increased to 10.7%(11/103).Patients with No.12 a LNM had a significantly poorer recurrence-free survival(RFS)(P=0.005)and overall survival(OS)(P=0.017).According to the result of multivariable Cox regression,No.12 a LNM was not an independent impact factor on RFS and OS.Conclusions:The overall incidence of No.12 a LNM was low but it was much higher in GC patients who had very advanced tumors involving the lower third of the stomach.No.12 a LN dissection should be considered for these patients to improve the survival outcomes.
文摘BACKGROUND Lymph node metastasis(LNM)affects the application and outcomes of endoscopic resection in T1 esophageal squamous cell carcinoma(ESCC).However,reports of the risk factors for LNM have been controversial.AIM To evaluate risk factors for LNM in T1 ESCC.METHODS We searched Embase,PubMed and Cochrane Library to select studies related to LNM in patients with T1 ESCC.Included studies were divided into LNM and non-LNM groups.We performed a meta-analysis to examine the relationship between LNM and clinicopathologic features.Odds ratio(OR),mean differences and 95%confidence interval(CI)were assessed using a fixed-effects or randomeffects model.RESULTS Seventeen studies involving a total of 3775 patients with T1 ESCC met the inclusion criteria.After excluding studies with heterogeneity based on influence analysis,tumor size(OR=1.93,95%CI=1.49-2.50,P<0.001),tumor location(OR=1.46,95%CI=1.17-1.82,P<0.001),macroscopic type(OR=3.17,95%CI=2.33-4.31,P<0.001),T1 substage(OR=6.28,95%CI=4.93-8.00,P<0.001),differentiation(OR=2.11,95%CI=1.64-2.72,P<0.001)and lymphovascular invasion(OR=5.86,95%CI=4.60-7.48,P<0.001)were found to be significantly associated with LNM.Conversely,sex,age and infiltrative growth pattern were not identified as risk factors for LNM.CONCLUSION A tumor size>2 cm,lower location,nonflat macroscopic type,T1b stage,poor differentiation and lymphovascular invasion were associated with LNM in patients with T1 ESCC.
基金supported by the National Natural Science Foundation of China for studies on early-stage GI neoplasms(Grant No.81072032 and No.81470830).
文摘Superficial esophageal squamous cell carcinoma(SESCC)is defined as carcinoma with mucosal or submucosal invasion,regardless of regional lymph node metastasis(LNM).The lymph node status is not only a key factor to determine the training strategy,but also the most important prognostic factor in esophageal cancer.In this study,we establish a clinical nomogram for predicting LNM in patients with SESCC.A predictive model was established based on the training cohort composed of 711 patients who underwent esophagectomy for SESCC from December 2009 to June 2018.A prospective cohort of 203 patients from June 2018 to January 2019 was used for validation.Favorable calibration and well-fitted decision curve analysis were conducted and good discrimination was observed(concordance index[C-index],0.860;95%confidence interval[CI],0.825-0.894)through internal validation.The external validation cohort presented good discrimination(C-index,0.916;95%CI,0.860-0.971).This model may facilitate the prediction of LNM in patients with SESCCs.
文摘BACKGROUND Primary pancreatic paragangliomas are extremely rare tumors.Limited by the diagnostic efficacy of histopathological examination,their malignant behavior is thought to be associated with local invasion or metastasis,with only four malignant cases reported in the literature to date.As pancreatic paragangliomas share similar imaging features with other types of pancreatic neuroendocrine neoplasms,they are difficult to diagnose accurately without the support of pathological evidence.As primary pancreatic paragangliomas are rare,especially those accompanied by lymph node metastasis,there is currently no consensus on treatment.Herein,we report a case of primary pancreatic paraganglioma with lymph node metastasis.CASE SUMMARY A mass located in the pancreatic body was incidentally discovered on computed tomography in a 41-year-old Tibetan man.Distal pancreatectomy was subsequently performed and a 4.1 cm×4.2 cm tumor was found embedded in the body of the pancreas during surgery.Histological examination confirmed the characteristics of paraganglioma in which the neoplastic chief cells were arranged in a classic Zellballen pattern under hematoxylin-eosin staining.Further,immunohistochemistry demonstrated that the sustentacular cells in the tumor tissue were positive for S-100 protein,and neoplastic cells and pancreatic draining lymph nodes were positive for chromogranin A and synaptophysin;thus,the presence of lymph node metastasis(two of the eight resected pancreatic draining lymph nodes)was also confirmed.A diagnosis of primary pancreatic paraganglioma with lymph node metastasis was finally established.The patient remained disease-free for 1 year after the surgery.CONCLUSION A definite diagnosis of pancreatic paraganglioma mainly depends on postoperative histopathological and immunohistochemical examinations.Surgical resection may be the first treatment of choice for patients with primary pancreatic paraganglioma that has metastasized to the lymph nodes.
文摘BACKGROUND Tumor deposits(TDs)are not equivalent to lymph node(LN)metastasis(LNM)but have become independent adverse prognostic factors in patients with rectal cancer(RC).Although preoperatively differentiating TDs and LNMs is helpful in designing individualized treatment strategies and achieving improved prognoses,it is a challenging task.AIM To establish a computed tomography(CT)-based radiomics model for preoperatively differentiating TDs from LNM in patients with RC.METHODS This study retrospectively enrolled 219 patients with RC[TDs+LNM-(n=89);LNM+TDs-(n=115);TDs+LNM+(n=15)]from a single center between September 2016 and September 2021.Single-positive patients(i.e.,TDs+LNM-and LNM+TDs-)were classified into the training(n=163)and validation(n=41)sets.We extracted numerous features from the enhanced CT(region 1:The main tumor;region 2:The largest peritumoral nodule).After deleting redundant features,three feature selection methods and three machine learning methods were used to select the best-performing classifier as the radiomics model(Rad-score).After validating Rad-score,its performance was further evaluated in the field of diagnosing double-positive patients(i.e.,TDs+LNM+)by outlining all peritumoral nodules with diameter(short-axis)>3 mm.RESULTS Rad-score 1(radiomics signature of the main tumor)had an area under the curve(AUC)of 0.768 on the training dataset and 0.700 on the validation dataset.Rad-score 2(radiomics signature of the largest peritumoral nodule)had a higher AUC(training set:0.940;validation set:0.918)than Radscore 1.Clinical factors,including age,gender,location of RC,tumor markers,and radiological features of the largest peritumoral nodule,were excluded by logistic regression.Thus,the combined model was comprised of Rad-scores of 1 and 2.Considering that the combined model had similar AUCs with Rad-score 2(P=0.134 in the training set and 0.594 in the validation set),Rad-score 2 was used as the final model.For the diagnosis of double-positive patients in the mixed group[TDs+LNM+(n=15);single-positive(n=15)],Rad-score 2 demonstrated moderate performance(sensitivity,73.3%;specificity,66.6%;and accuracy,70.0%).CONCLUSION Radiomics analysis based on the largest peritumoral nodule can be helpful in preoperatively differentiating between TDs and LNM.
基金Hai-Yi Feng and Yihang Yuan contributed equally to this work.We thank Prof.Gang Zheng(University of Toronto)for valuable discussion.We also thank the Core Facility of Basic Medical Sciences(SJTU-SM)for frozen section making and scanningThis work was supported by National Natural Science Foundation of China(81572998,81773274,82073379)+1 种基金Shanghai Municipal Science and Technology Commission(20ZR1451700,16520710700)Shanghai Collaborative Innovation Center for Translational Medicine(TM201731).
文摘Tumor lymph node(LN)metastasis seriously affects the treatment prognosis.Studies have shown that nanoparticles with size of sub-50 nm can directly penetrate into LN metastases after intravenous administration.Here,we speculate through introducing targeting capacity,the nanoparticle accumulation in LN metastases would be further enhanced for improved local treatment such as photothermal therapy.Trastuzumabtargeted micelles(<50 nm)were formulated using a unique surfactantstripping approach that yielded concentrated phthalocyanines with strong near-infrared absorption.Targeted micellar phthalocyanine(T-MP)was an effective photothermal transducer and ablated HT-29 cells in vitro.A HER2-expressing colorectal cancer cell line(HT-29)was used to establish an orthotopic mouse model that developed metastatic disease in mesenteric sentinel LN.T-MP accumulated more in the LN metastases compared to the micelles conjugated with control IgG.Following surgical resection of the primary tumor,minimally invasive photothermal treatment of the metastatic LN with T-MP,but not the control micelles,extended mouse survival.Our findings demonstrate for the first time that targeted small-sized nanoparticles have potential to enable superior paradigms for dealing with LN metastases.
基金Supported by the General Project-Social Development Field of Shaanxi Province Science and Technology Department,No. 2021SF-313Innovation Capability Support Plan of Shaanxi Science and Technology Department-Science and Technology Innovation Team,No. 2020TD-048
文摘BACKGROUND The most important consideration in determining treatment strategies for undifferentiated early gastric cancer(UEGC)is the risk of lymph node metastasis(LNM).Therefore,identifying a potential biomarker that predicts LNM is quite useful in determining treatment.AIM To develop a machine learning(ML)-based integral procedure to construct the LNM gray-level co-occurrence matrix(GLCM)prediction model.METHODS We retrospectively selected 526 cases of UEGC confirmed through pathological examination after radical gastrectomy without endoscopic treatment in four tertiary hospitals between January 2015 to December 2021.We extracted GLCM-based features from grayscale images and applied ML to the classification of candidate predictive variables.The robustness and clinical utility of each model were evaluated based on the following factors:Receiver operating characteristic curve(ROC),decision curve analysis,and clinical impact curve.RESULTS GLCM-based feature extraction significantly correlated with LNM.The top 7 GLCM-based factors included inertia value 0°(IV_0),inertia value 45°(IV_45),inverse gap 0°(IG_0),inverse gap 45°(IG_45),inverse gap full angle(IG_all),Haralick 30°(Haralick_30),Haralick full angle(Haralick_all),and Entropy.The areas under the ROC curve(AUCs)of the random forest classifier(RFC)model,support vector machine,eXtreme gradient boosting,artificial neural network,and decision tree ranged from 0.805[95%confidence interval(CI):0.258-1.352]to 0.925(95%CI:0.378-1.472)in the training set and from 0.794(95%CI:0.237-1.351)to 0.912(95%CI:0.355-1.469)in the testing set,respectively.The RFC(training set:AUC:0.925,95%CI:0.378-1.472;testing set:AUC:0.912,95%CI:0.355-1.469)model that incorporates Entropy,Haralick_all,Haralick_30,IG_all,IG_45,IG_0,and IV_45 had the highest predictive accuracy.CONCLUSION The evaluation results indicate that the method of selecting radiological and textural features becomes more effective in the LNM discrimination against UEGC patients.Additionally,the MLbased prediction model developed using the RFC can be used to derive treatment options and identify LNM,which can hence improve clinical outcomes.
文摘BACKGROUND Although PNENs generally have a better prognosis than pancreatic cancers,some PNENs display malignant behavior including lymph node(LN)metastasis.Complete tumor resection can be the only potentially curative treatment for patients with resectable PNENs.However,the indications for LN dissection are still controversial.Over the last decade,minimally invasive surgery such as laparoscopic pancreatic surgery(LPS)has been increasingly performed for pancreatic tumors including PNENs.AIM To investigate the risk factors for LN metastasis in PNENs and to select appropriate patients for limited surgery by LPS.METHODS From April 2001 to December 2019,92 patients underwent pancreatic resection for PNENs at Kumamoto University Hospital.Finally,82 patients were enrolled in this study.Using perioperative factors,we examined the predictive factors for LN metastasis in PNENs.RESULTS Among the 82 patients,the percentage of LN metastasis according to the pathological findings was 12%(10/82 cases).The median tumor size was 12 mm(range:5-90 mm).The median tumor size in the LN-positive group(37 mm)was significantly larger than that in the LN-negative group(12 mm)(P=0.0001).Multivariate analyses revealed that larger tumor size(≥20 mm)was an independent risk factor for LN metastasis(odds ratio 16.8,P=0.0062).In patients with small tumors(≤10 mm),LN metastasis was not found.CONCLUSION Larger tumor size(≥20 mm)is an independent risk factor for LN metastasis in PNENs.In smaller PNENs(≤10 mm),we may be able to choose limited surgery without LN dissection.
