BACKGROUND The accurate prediction of lymph node metastasis(LNM)is crucial for managing locally advanced(T3/T4)colorectal cancer(CRC).However,both traditional histopathology and standard slide-level deep learning ofte...BACKGROUND The accurate prediction of lymph node metastasis(LNM)is crucial for managing locally advanced(T3/T4)colorectal cancer(CRC).However,both traditional histopathology and standard slide-level deep learning often fail to capture the sparse and diagnostically critical features of metastatic potential.AIM To develop and validate a case-level multiple-instance learning(MIL)framework mimicking a pathologist's comprehensive review and improve T3/T4 CRC LNM prediction.METHODS The whole-slide images of 130 patients with T3/T4 CRC were retrospectively collected.A case-level MIL framework utilising the CONCH v1.5 and UNI2-h deep learning models was trained on features from all haematoxylin and eosinstained primary tumour slides for each patient.These pathological features were subsequently integrated with clinical data,and model performance was evaluated using the area under the curve(AUC).RESULTS The case-level framework demonstrated superior LNM prediction over slide-level training,with the CONCH v1.5 model achieving a mean AUC(±SD)of 0.899±0.033 vs 0.814±0.083,respectively.Integrating pathology features with clinical data further enhanced performance,yielding a top model with a mean AUC of 0.904±0.047,in sharp contrast to a clinical-only model(mean AUC 0.584±0.084).Crucially,a pathologist’s review confirmed that the model-identified high-attention regions correspond to known high-risk histopathological features.CONCLUSION A case-level MIL framework provides a superior approach for predicting LNM in advanced CRC.This method shows promise for risk stratification and therapy decisions,requiring further validation.展开更多
BACKGROUND Early screening,preoperative staging,and diagnosis of lymph node metastasis are crucial for improving the prognosis of gastric cancer(GC).AIM To evaluate the diagnostic value of combined multidetector compu...BACKGROUND Early screening,preoperative staging,and diagnosis of lymph node metastasis are crucial for improving the prognosis of gastric cancer(GC).AIM To evaluate the diagnostic value of combined multidetector computed tomography(MDCT)and gastrointestinal endoscopy for GC screening,preoperative staging,and lymph node metastasis detection,thereby providing a reference for clinical diagnosis and treatment.METHODS In this retrospective study clinical and imaging data of 134 patients with suspected GC who were admitted between January 2023 and October 2024 were initially reviewed.According to the inclusion and exclusion criteria,102 patients were finally enrolled in the analysis.All enrolled patients had undergone both MDCT and gastrointestinal endoscopy examinations prior to surgical intervention.Preoperative clinical staging and lymph node metastasis findings were compared with pathological results.RESULTS The combined use of MDCT and gastrointestinal endoscopy demonstrated a sensitivity of 98.53%,specificity of 97.06%,accuracy of 98.04%,positive predictive value of 98.53%,and negative predictive value of 97.06%for diagnosing GC.These factors were all significantly higher than those of MDCT or endoscopy alone(P<0.05).The accuracy rates of the combined approach for detecting clinical T and N stages were 97.06%and 92.65%,respectively,outperforming MDCT alone(86.76% and 79.41%)and endoscopy alone(85.29% and 70.59%)(P<0.05).Among 68 patients with confirmed GC,50(73.53%)were pathologically diagnosed with lymph node metastasis.The accuracy for detecting lymph node metastasis was 66.00%with endoscopy,76.00%with MDCT,and 92.00% with the combined approach,all with statistically significant differences(P<0.05).CONCLUSION The combined application of MDCT and gastrointestinal endoscopy enhanced diagnostic accuracy for GC,provided greater consistency in preoperative staging,and improved the detection of lymph node metastasis,thereby demonstrating significant clinical utility.展开更多
The logistics nodes and logistics enterprises are the core carriers and organiza- tional subjects of the logistics space, and their location characteristics and differentiation strategies are of key importance to opti...The logistics nodes and logistics enterprises are the core carriers and organiza- tional subjects of the logistics space, and their location characteristics and differentiation strategies are of key importance to optimizing urban logistics spatial patterns and ensuring reasonable resource allocation. Based on Tencent Online Maps Platform from December 2014, 4396 logistics points of interest （POI） were collected in Beijing, China. By the methods of industrial concentration evaluation and kernel density analysis, the spatial distribution pattern of logistics in Beijing are explored, the interaction mechanism among the type differ- ence, supply-demand side factors and location choice behavior are clarified, and the internal mechanism of spatial differentiation under the combined influence of transportation, land rent and assets are revealed. The following conclusions are drawn in the paper. （1） Logistics en- terprises and logistics nodes exhibit the characteristic of both co-agglomeration and spatial separation in location, and logistics activities display the spatial pattern of ＂marginal area of downtown area, suburbs and exurban area＂, which have a weak coupling degree with logis- tics employment space. （2） The public logistics space, namely, logistics parks and logistics centers, is produced under the guidance of the government, and the terminal logistics space consisting of logistics distribution centers serving for the specific industries and terminal users is dominated by enterprises. The Iocational differentiation between the two modes of logistics space is significant. （3） In the formation of the logistics spatial location, the government can change the traffic condition by re-planning the transport routes and freight station locations, and control the land rent and availability of different areas by increasing or decreasing the land use of logistics, to impact the enterprise behavior and form different types of logistics space and function differentiation. In comparison, logistics enterprises meet the diverse de- mands of service objects through differentiation of asset allocation to promote the specializa- tion of division and form the object differentiation of logistics space.展开更多
BACKGROUND One of the main characteristics of oral squamous cell carcinoma(OSCC)is that it metastasizes to cervical lymph nodes frequently with a high degree of local invasiveness.A primary feature of malignant tumors...BACKGROUND One of the main characteristics of oral squamous cell carcinoma(OSCC)is that it metastasizes to cervical lymph nodes frequently with a high degree of local invasiveness.A primary feature of malignant tumors is their penetration of neighboring tissues,such as lymphatic and blood arteries,due to the tumor cells'capacity to break down the extracellular matrix(ECM).Matrix metalloproteinases(MMPs)constitute a family of proteolytic enzymes that facilitate tissue remodeling and the degradation of the ECM.MMP-9 and MMP-13 belong to the group of extracellular matrix degrading enzymes and their expression has been studied in OSCC because of their specific functions.MMP-13,a collagenase family member,is thought to play an essential role in the MMP activation cascade by breaking down the fibrillar collagens,whereas MMP-9 is thought to accelerate the growth of tumors.Elevated MMP-13 expression has been associated with tumor behavior and patient prognosis in a number of malignant cases.AIM To assess the immunohistochemical expression of MMP-9 and MMP-13 in OSCC.METHODS A total of 40 cases with histologically confirmed OSCC by incisional biopsy were included in this cross-sectional retrospective study.The protocols for both MMP-9 and MMP-13 immunohistochemical staining were performed according to the manufacturer’s recommendations along with the normal gingival epithelium as a positive control.All the observations were recorded and Pearson’sχ²test with Fisher exact test was used for statistical analysis.RESULTS Our study showed no significant correlation between MMP-9 and MMP-13 staining intensity and tumor size.The majority of the patients were in advanced TNM stages(III and IV),and showed intense expression of MMP-9 and MMP-13.CONCLUSION The present study suggests that both MMP-9 and MMP-13 play an important and independent role in OSCC progression and invasiveness.Intense expression of MMP-9 and MMP-13,irrespective of histological grade of OSCC,correlates well with TNM stage.Consequently,it is evident that MMP-9 and MMP-13 are important for the invasiveness and progression of tumors.The findings may facilitate the development of new approaches for evaluating lymph node metastases and interventional therapy techniques,hence enhancing the prognosis of patients diagnosed with OSCC.展开更多
Purpose: Brain functional networks (BFNs) has become important approach for diagnosis of some neurological or psychological disorders. Before estimating BFN, obtaining blood oxygen level dependent (BOLD) representativ...Purpose: Brain functional networks (BFNs) has become important approach for diagnosis of some neurological or psychological disorders. Before estimating BFN, obtaining blood oxygen level dependent (BOLD) representative signals from brain regions of interest (ROIs) is important. In the past decades, the common method is generally to take a ROI as a node, averaging all the voxel time series inside it to extract a representative signal. However, one node does not represent the entire information of this ROI, and averaging method often leads to signal cancellation and information loss. Inspired by this, we propose a novel model extraction method based on an assumption that a ROI can be represented by multiple nodes. Methods: In this paper, we first extract multiple nodes (the number is user-defined) from the ROI based on two traditional methods, including principal component analysis (PCA), and K-means (Clustering according to the spatial position of voxels). Then, canonical correlation analysis (CCA) was issued to construct BFNs by maximizing the correlation between the representative signals corresponding to the nodes in any two ROIs. Finally, to further verify the effectiveness of the proposed method, the estimated BFNs are applied to identify subjects with autism spectrum disorder (ASD) and mild cognitive impairment (MCI) from health controls (HCs). Results: Experimental results on two benchmark databases demonstrate that the proposed method outperforms the baseline method in the sense of classification performance. Conclusions: We propose a novel method for obtaining nodes of ROId based on the hypothesis that a ROI can be represented by multiple nodes, that is, to extract the node signals of ROIs with K-means or PCA. Then, CCA is used to construct BFNs.展开更多
The principal breast cancer treatment approach has long been surgical removal of the primary breast lesions and regional lymph nodes,particularly the axillary lymph nodes.However,the advent of minimally invasive diagn...The principal breast cancer treatment approach has long been surgical removal of the primary breast lesions and regional lymph nodes,particularly the axillary lymph nodes.However,the advent of minimally invasive diagnostic techniques,such as sentinel lymph node biopsy(SLNB),has markedly diminished the extent of surgery required for regional lymph nodes.展开更多
Identifying key nodes in complex networks is crucial for understanding and controlling their dynamics. Traditional centrality measures often fall short in capturing the multifaceted roles of nodes within these network...Identifying key nodes in complex networks is crucial for understanding and controlling their dynamics. Traditional centrality measures often fall short in capturing the multifaceted roles of nodes within these networks. The Page Rank algorithm, widely recognized for ranking web pages, offers a more nuanced approach by considering the importance of connected nodes. However, existing methods generally overlook the geometric properties of networks, which can provide additional insights into their structure and functionality. In this paper, we propose a novel method named Curv-Page Rank(C-PR), which integrates network curvature and Page Rank to identify influential nodes in complex networks. By leveraging the geometric insights provided by curvature alongside structural properties, C-PR offers a more comprehensive measure of a node's influence. Our approach is particularly effective in networks with community structures, where it excels at pinpointing bridge nodes critical for maintaining connectivity and facilitating information flow. We validate the effectiveness of C-PR through extensive experiments. The results demonstrate that C-PR outperforms traditional centrality-based and Page Rank methods in identifying critical nodes. Our findings offer fresh insights into the structural importance of nodes across diverse network configurations, highlighting the potential of incorporating geometric properties into network analysis.展开更多
Objective:The neglect of occult lymph nodes metastasis(OLNM)is one of the pivotal causes of early non-small cell lung cancer(NSCLC)recurrence after local treatments such as stereotactic body radiotherapy(SBRT)or surge...Objective:The neglect of occult lymph nodes metastasis(OLNM)is one of the pivotal causes of early non-small cell lung cancer(NSCLC)recurrence after local treatments such as stereotactic body radiotherapy(SBRT)or surgery.This study aimed to develop and validate a computed tomography(CT)-based radiomics and deep learning(DL)fusion model for predicting non-invasive OLNM.Methods:Patients with radiologically node-negative lung adenocarcinoma from two centers were retrospectively analyzed.We developed clinical,radiomics,and radiomics-clinical models using logistic regression.A DL model was established using a three-dimensional squeeze-and-excitation residual network-34(3D SE-ResNet34)and a fusion model was created by integrating seleted clinical,radiomics features and DL features.Model performance was assessed using the area under the curve(AUC)of the receiver operating characteristic(ROC)curve,calibration curves,and decision curve analysis(DCA).Five predictive models were compared;SHapley Additive exPlanations(SHAP)and Gradient-weighted Class Activation Mapping(Grad-CAM)were employed for visualization and interpretation.Results:Overall,358 patients were included:186 in the training cohort,48 in the internal validation cohort,and 124 in the external testing cohort.The DL fusion model incorporating 3D SE-Resnet34 achieved the highest AUC of 0.947 in the training dataset,with strong performance in internal and external cohorts(AUCs of 0.903 and 0.907,respectively),outperforming single-modal DL models,clinical models,radiomics models,and radiomicsclinical combined models(DeLong test:P<0.05).DCA confirmed its clinical utility,and calibration curves demonstrated excellent agreement between predicted and observed OLNM probabilities.Features interpretation highlighted the importance of textural characteristics and the surrounding tumor regions in stratifying OLNM risk.Conclusions:The DL fusion model reliably and accurately predicts OLNM in early-stage lung adenocarcinoma,offering a non-invasive tool to refine staging and guide personalized treatment decisions.These results may aid clinicians in optimizing surgical and radiotherapy strategies.展开更多
BACKGROUND The number of tumor deposits(TDs)does not play a part in the current tumor node metastasis staging.Negative lymph node(NLN)status is associated with the prognosis of colorectal cancer(CRC),but its clear rol...BACKGROUND The number of tumor deposits(TDs)does not play a part in the current tumor node metastasis staging.Negative lymph node(NLN)status is associated with the prognosis of colorectal cancer(CRC),but its clear role in N1c stage remains to be defined.AIM To evaluate the combination of TDs and NLNs as potential prognostic indicators in N1c CRC.METHODS We retrospectively identified 107 consecutive patients who had N1c CRC radically resected at China-Japan Friendship Hospital.The combination of TDs and NLNs was calculated by the formula NLNTD=NLN/(TD+1).Cutoff values of NLNs and NLNTD were determined using the R package“survminer”.Disease-free survival(DFS),overall survival(OS)and cancer-specific survival(CSS)were determined using the Kaplan-Meier method to assess the impact of NLNTD on prognosis.Results were compared using the log-rank test.RESULTS The median follow-up time was 63.17(45.33-81.37)months for DFS,with 33.64%(36/107)of patients experiencing recurrence during follow-up.Five-year DFS was 66.0%(57.3%-76.0%).There was no significant difference in prognosis between patients with>12 and≤12 NLNs(P=0.058)for DFS.Similar results were seen according to the number of TDs.The definition of NLNTD=NLN/(TD+1)with a cutoff value of 6 divided patients into two groups with different DFS(P=0.005).Five-year DFS for patients with NLNTD>6 was 73.5%(63.6%-85.0%),compared with 50.0%(35.7%-70.0%)for those with NLNTD≤6.These two groups had different prognosis without perineural invasion(P=0.012)or lymphovascular invasion(P=0.002)even neither(P=0.053).Similar results were seen for OS and CSS.CONCLUSION NLNTD could serve as important prognostic factor for outcomes in N1c CRC patients.These patients could be stratified for prognosis through NLNTD and the high-risk should be given more attention during treatment.展开更多
Gastric cancer(GC)represents a significant global health burden due to its high morbidity and mortality.Specific behaviors of GC sub-types,distinct dissem-ination patterns,and associated risk-factors remain poorly und...Gastric cancer(GC)represents a significant global health burden due to its high morbidity and mortality.Specific behaviors of GC sub-types,distinct dissem-ination patterns,and associated risk-factors remain poorly understood.This editorial highlights several key prognostic factors,including pathological staging and vascular invasion,that impact GC.It examines a recent study’s investigation of differential metastatic lymph nodes distribution and survival in upper and lower GC sub-types,focusing on histological characterization,pathophysiology,usage of neoadjuvant chemotherapy,and additional predictive determinants.We assess the statistical robustness and clinical applicability of the findings,un-derscoring the importance of treating GC as a heterogeneous disease and em-phasizing how tailored surgical approaches informed by lymph node distribution can optimize tumor detection while minimizing unnecessary interventions.The study’s large cohort,multi-center design,and strict inclusion criteria strengthen its validity in guiding surgical planning and risk-stratification.However,inte-grating genetic and molecular data is critical for refining models and broadening applicability.Additionally,recurrence-metrics and infection-related factors,such as Helicobacter pylori and Epstein-Barr virus,absent in the original study,remain vital for directing future research.By bridging metastatic patterns with pros-pective methodologies and inclusion of diverse populations,this editorial pro-vides a framework for advancing early detection and personalized GC care.展开更多
Aim: Assess the role of hybrid modality SPECT/CT versus planar scintigraphy in sentinel lymph node (SLN) identification in patients with breast cancer. Methods: Planar scintigraphy and hybrid modality SPECT/CT were pe...Aim: Assess the role of hybrid modality SPECT/CT versus planar scintigraphy in sentinel lymph node (SLN) identification in patients with breast cancer. Methods: Planar scintigraphy and hybrid modality SPECT/CT were performed in 23 women with breast cancer (mean age 59.5 years with range 25 - 82 years) with invasive breast cancer (T0, T1 and T2), without clinical evidence of axillary lymph node metastases (N0) and no remote metastases (M0), radiocolloid was injected in four subareolar sites. Planar and SPECT/CT images were separately interpreted. Results: SLNs were detected on lymphoscintigraphy in all patients (100%), taking into consideration both techniques (planar and SPECT-CT images). Planar images identified 45 SLNs in 23 women, with a mean of 1.95 per patient, whereas 56 SLNs were detected on SPECT/CT, increasing this mean to 2.43 per patient. Drainage to internal mammary lymph nodes was seen in 4 patients (17.39%). However, two foci of uptake were identified on planar image as hot SLN in two patients (8.69%);while they have been found as a false positive non-nodal site of uptake on SPECT/CT. Conclusion: SPECT/CT is more focused than planar scintigraphy in the detection of SLN in patients with breast cancer. It detects some lymph nodes not visible on planar images, excludes false positive uptake and exactly locates axillary and non-axillary SLNs.展开更多
BACKGROUND Lymph node status is a critical prognostic factor in gastric cancer(GC),but stage migration may occur in pathological lymph nodes(pN)staging.To address this,alternative staging systems such as the positive ...BACKGROUND Lymph node status is a critical prognostic factor in gastric cancer(GC),but stage migration may occur in pathological lymph nodes(pN)staging.To address this,alternative staging systems such as the positive lymph node ratio(LNR)and log odds of positive lymph nodes(LODDS)were introduced.AIM To assess the prognostic accuracy and stratification efficacy of three nodal staging systems in GC.METHODS A systematic review identified 12 studies,from which hazard ratios(HRs)for overall survival(OS)were summarized.Sensitivity analyses,subgroup analyses,publication bias assessments,and quality evaluations were conducted.To enhance comparability,data from studies with identical cutoff values for pN,LNR,and LODDS were pooled.Homogeneous stratification was then applied to generate Kaplan-Meier(KM)survival curves,assessing the stratification efficacy of three staging systems.RESULTS The HRs and 95%confidence intervals for pN,LNR,and LODDS were 2.16(1.72-2.73),2.05(1.65-2.55),and 3.15(2.15-4.37),respectively,confirming all three as independent prognostic risk factors for OS.Comparative analysis of HRs demonstrated that LODDS had superior prognostic predictive power over LNR and pN.KM curves for pN(N0,N1,N2,N3a,N3b),LNR(0.1/0.2/0.5),and LODDS(-1.5/-1.0/-0.5/0)revealed significant differences(P<0.001)among all prognostic stratifications.Mean differences and standard deviations in 60-month relative survival were 27.93%±0.29%,41.70%±0.30%,and 26.60%±0.28%for pN,LNR,and LODDS,respectively.CONCLUSION All three staging systems are independent prognostic factors for OS.LODDS demonstrated the highest specificity,making it especially useful for predicting outcomes,while pN was the most effective in homogeneous stratification,offering better patient differentiation.These findings highlight the complementary roles of LODDS and pN in enhancing prognostic accuracy and stratification.展开更多
Gastric cancer(GC)remains a leading cause of cancer mortality.While the extent of nodal involvement is a well-known prognostic factor,the specific entity of swollen lymph node metastasis(SLNM),bulky nodal tumor deposi...Gastric cancer(GC)remains a leading cause of cancer mortality.While the extent of nodal involvement is a well-known prognostic factor,the specific entity of swollen lymph node metastasis(SLNM),bulky nodal tumor deposits detectable radiologically or pathologically,has received little attention in staging.Recent data from a study by Cui et al demonstrated that SLNM is an independent predictor of very poor survival in GC.Through robust data and rigorous propensitymatched analyses,SLNM emerged not merely as an anatomical finding but as an independent predictor of poor prognosis,even among patients undergoing curative resection.As precision oncology advances,the findings by Cui et al urge a fundamental rethinking of how SLNM is incorporated into clinical decisionmaking for GC management.In this editorial,we critically examine the prognostic significance of SLNM,challenge its omission from traditional staging frameworks,and advocate for its formal integration into preoperative risk stratification and treatment planning.Recognizing SLNM at diagnosis could unlock intensified neoadjuvant therapy strategies and optimize outcomes for a historically high-risk patient subgroup.展开更多
Objective Almost 15%of prostate cancer(PCa)patients were found to have lymph node metastases(LNMs),which are associated with higher risk of biochemical recurrence.Using indocyanine green(ICG)for the sentinel node biop...Objective Almost 15%of prostate cancer(PCa)patients were found to have lymph node metastases(LNMs),which are associated with higher risk of biochemical recurrence.Using indocyanine green(ICG)for the sentinel node biopsy(SNB)before surgery was proposed to detect LNMs in PCa patients.However,its diagnostic performance still remains controversial.This study aimed to investigate the diagnostic performance of ICG for the SNB in PCa.Methods This systematic review and meta-analysis has been reported in line with the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines.The protocol has been registered in the International Prospective Register of Systematic Reviews database,and the register number is CRD42023421911.Four bibliographic databases were searched,i.e.,PubMed,EMBASE,Cochrane Library,and Web of Science,to retrieve articles studying the diagnostic performance of ICG for the SNB in PCa from the inception to Sep 9,2023.We calculated the pooled sensitivity,specificity,likelihood ratios,diagnostic odds ratios and their 95%confidence intervals(CIs).Subgroup analyses and meta-regression analyses were also conducted.Results A total of 17 articles from databases are enrolled in this study.Using lymph node-based data,our results showed that the pooled sensitivity and specificity of applying ICG alone in PCa were 71%(95%CI 52%–85%)and 68%(95%CI 64%–72%),respectively.The pooled sensitivity and specificity of applying ICG-technetium-99m-nanocolloid in PCa were 49%(95%CI 39%–59%)and 69%(95%CI 67%–71%),respectively.展开更多
The article by Yuan et al accessed the clinicopathologic and prognostic significance of the patterns of lymph node(LN)metastasis in upper and lower gastric cancer(GC).In this article,we will analyze both the strengths...The article by Yuan et al accessed the clinicopathologic and prognostic significance of the patterns of lymph node(LN)metastasis in upper and lower gastric cancer(GC).In this article,we will analyze both the strengths and limitations of this paper.The study’s methodology seems appropriate and proper statistical analyses were applied to identify significant variables.The authors applied the Cox regression model to identify independent risk factors and Kaplan-Meier survival curves to assess prognosis.The researchers found notable differences in cli-nicopathologic variables between patients with upper and lower GC.Addi-tionally,they identified specific LN stations more prone to metastasis in different Siewert classifications of GC.Despite the study’s detailed analysis,it would have been beneficial to explore whether there were survival differences among upper GC patients based on the Siewert classification.Furthermore,the study should have addressed potential confounding factors that might have influenced the results.A more comprehensive analysis could have been achieved by comparing survival outcomes based on LN metastasis patterns.Overall,this article is relevant and provides valuable insights into the significance of LN metastasis patterns in upper GC patients.展开更多
Introduction The accuracy of sentinel lymph node biopsy(SLNB)after neoadjuvant therapy(NAT)has been confirmed in clinical nodal stage 1(c N1)patients,and more patients could benefit from axillary surgery de-escalation...Introduction The accuracy of sentinel lymph node biopsy(SLNB)after neoadjuvant therapy(NAT)has been confirmed in clinical nodal stage 1(c N1)patients,and more patients could benefit from axillary surgery de-escalation after NAT(1,2).展开更多
BACKGROUND The National Comprehensive Cancer Network guidelines recommend adjuvant chemotherapy(ACT)for patients with stage II colon cancer who have undergone curative surgery when fewer than 12 lymph nodes(LNs)are re...BACKGROUND The National Comprehensive Cancer Network guidelines recommend adjuvant chemotherapy(ACT)for patients with stage II colon cancer who have undergone curative surgery when fewer than 12 lymph nodes(LNs)are retrieved.This study seeks to further examine the requirement for ACT in individuals who had 12 or more LNs harvested.AIM To investigate if stage II colon cancer patients with 12 or more LNs retrieved benefit from ACT.METHODS This retrospective cohort study included individuals diagnosed with stage II colon cancer who underwent surgery between 2008 and 2017 from the Surveillance,Epidemiology,and End Results(SEER)registry and a Chinese multicenter database.All patients had at least 12 LNs retrieved.The key endpoint was overall survival(OS).Cox regression analysis was performed to assess independent OS predictors.Propensity score matching controlled for confounders,and Kaplan-Meier analysis evaluated the impact of ACT on survival.RESULTS A total of 32742 patients with stage II colon cancer from the SEER cohort and 3153 patients from the Chinese cohort were included.The average number of LNs retrieved was 20.0(15.0,26.0)in the SEER cohort and 18.0(15.0,22.0)in the Chinese cohort.No-ACT remained an independent risk factor in both cohorts(hazard ratio=1.589,95%confidence interval:1.485-1.700 and hazard ratio=1.865,95%confidence interval:1.465-2.375,respectively).In the SEER cohort,patients in the ACT group consistently demonstrated better 5-year OS rates both before and after propensity score matching(79.4%vs 66.1%and 79.4%vs 69.4%,both P<0.0001).Similarly,these findings were further validated in the Chinese cohort(91.2%vs 82.1%and 90.0%vs 82.8%,both P<0.0001).ACT improved prognosis even in T3 and grade 1/2 patients.CONCLUSION This research,based on two large population-based cohorts,demonstrates that stage II colon cancer patients with 12 or more LNs retrieved can still benefit from ACT.展开更多
Accurately identifying key nodes is essential for evaluating network robustness and controlling information propagation in complex network analysis. However, current research methods face limitations in applicability ...Accurately identifying key nodes is essential for evaluating network robustness and controlling information propagation in complex network analysis. However, current research methods face limitations in applicability and accuracy. To address these challenges, this study introduces the K-GCN model, which integrates neighborhood k-shell distribution analysis with Graph Convolutional Network(GCN) technology to enhance key node identification in complex networks. The K-GCN model first leverages neighborhood k-shell distributions to calculate entropy values for each node, effectively quantifying node importance within the network. These entropy values are then used as key features within the GCN, which subsequently formulates intelligent strategies to maximize network connectivity disruption by removing a minimal set of nodes, thereby impacting the overall network architecture. Through iterative interactions with the environment, the GCN continuously refines its strategies, achieving precise identification of key nodes in the network. Unlike traditional methods, the K-GCN model not only captures local node features but also integrates the network structure and complex interrelations between neighboring nodes, significantly improving the accuracy and efficiency of key node identification.Experimental validation in multiple real-world network scenarios demonstrates that the K-GCN model outperforms existing methods.展开更多
基金Supported by Chongqing Medical Scientific Research Project(Joint Project of Chongqing Health Commission and Science and Technology Bureau),No.2023MSXM060.
文摘BACKGROUND The accurate prediction of lymph node metastasis(LNM)is crucial for managing locally advanced(T3/T4)colorectal cancer(CRC).However,both traditional histopathology and standard slide-level deep learning often fail to capture the sparse and diagnostically critical features of metastatic potential.AIM To develop and validate a case-level multiple-instance learning(MIL)framework mimicking a pathologist's comprehensive review and improve T3/T4 CRC LNM prediction.METHODS The whole-slide images of 130 patients with T3/T4 CRC were retrospectively collected.A case-level MIL framework utilising the CONCH v1.5 and UNI2-h deep learning models was trained on features from all haematoxylin and eosinstained primary tumour slides for each patient.These pathological features were subsequently integrated with clinical data,and model performance was evaluated using the area under the curve(AUC).RESULTS The case-level framework demonstrated superior LNM prediction over slide-level training,with the CONCH v1.5 model achieving a mean AUC(±SD)of 0.899±0.033 vs 0.814±0.083,respectively.Integrating pathology features with clinical data further enhanced performance,yielding a top model with a mean AUC of 0.904±0.047,in sharp contrast to a clinical-only model(mean AUC 0.584±0.084).Crucially,a pathologist’s review confirmed that the model-identified high-attention regions correspond to known high-risk histopathological features.CONCLUSION A case-level MIL framework provides a superior approach for predicting LNM in advanced CRC.This method shows promise for risk stratification and therapy decisions,requiring further validation.
文摘BACKGROUND Early screening,preoperative staging,and diagnosis of lymph node metastasis are crucial for improving the prognosis of gastric cancer(GC).AIM To evaluate the diagnostic value of combined multidetector computed tomography(MDCT)and gastrointestinal endoscopy for GC screening,preoperative staging,and lymph node metastasis detection,thereby providing a reference for clinical diagnosis and treatment.METHODS In this retrospective study clinical and imaging data of 134 patients with suspected GC who were admitted between January 2023 and October 2024 were initially reviewed.According to the inclusion and exclusion criteria,102 patients were finally enrolled in the analysis.All enrolled patients had undergone both MDCT and gastrointestinal endoscopy examinations prior to surgical intervention.Preoperative clinical staging and lymph node metastasis findings were compared with pathological results.RESULTS The combined use of MDCT and gastrointestinal endoscopy demonstrated a sensitivity of 98.53%,specificity of 97.06%,accuracy of 98.04%,positive predictive value of 98.53%,and negative predictive value of 97.06%for diagnosing GC.These factors were all significantly higher than those of MDCT or endoscopy alone(P<0.05).The accuracy rates of the combined approach for detecting clinical T and N stages were 97.06%and 92.65%,respectively,outperforming MDCT alone(86.76% and 79.41%)and endoscopy alone(85.29% and 70.59%)(P<0.05).Among 68 patients with confirmed GC,50(73.53%)were pathologically diagnosed with lymph node metastasis.The accuracy for detecting lymph node metastasis was 66.00%with endoscopy,76.00%with MDCT,and 92.00% with the combined approach,all with statistically significant differences(P<0.05).CONCLUSION The combined application of MDCT and gastrointestinal endoscopy enhanced diagnostic accuracy for GC,provided greater consistency in preoperative staging,and improved the detection of lymph node metastasis,thereby demonstrating significant clinical utility.
基金Foundation： National Natural Science Foundation of China, No.41501123, No.71703219
文摘The logistics nodes and logistics enterprises are the core carriers and organiza- tional subjects of the logistics space, and their location characteristics and differentiation strategies are of key importance to optimizing urban logistics spatial patterns and ensuring reasonable resource allocation. Based on Tencent Online Maps Platform from December 2014, 4396 logistics points of interest （POI） were collected in Beijing, China. By the methods of industrial concentration evaluation and kernel density analysis, the spatial distribution pattern of logistics in Beijing are explored, the interaction mechanism among the type differ- ence, supply-demand side factors and location choice behavior are clarified, and the internal mechanism of spatial differentiation under the combined influence of transportation, land rent and assets are revealed. The following conclusions are drawn in the paper. （1） Logistics en- terprises and logistics nodes exhibit the characteristic of both co-agglomeration and spatial separation in location, and logistics activities display the spatial pattern of ＂marginal area of downtown area, suburbs and exurban area＂, which have a weak coupling degree with logis- tics employment space. （2） The public logistics space, namely, logistics parks and logistics centers, is produced under the guidance of the government, and the terminal logistics space consisting of logistics distribution centers serving for the specific industries and terminal users is dominated by enterprises. The Iocational differentiation between the two modes of logistics space is significant. （3） In the formation of the logistics spatial location, the government can change the traffic condition by re-planning the transport routes and freight station locations, and control the land rent and availability of different areas by increasing or decreasing the land use of logistics, to impact the enterprise behavior and form different types of logistics space and function differentiation. In comparison, logistics enterprises meet the diverse de- mands of service objects through differentiation of asset allocation to promote the specializa- tion of division and form the object differentiation of logistics space.
文摘BACKGROUND One of the main characteristics of oral squamous cell carcinoma(OSCC)is that it metastasizes to cervical lymph nodes frequently with a high degree of local invasiveness.A primary feature of malignant tumors is their penetration of neighboring tissues,such as lymphatic and blood arteries,due to the tumor cells'capacity to break down the extracellular matrix(ECM).Matrix metalloproteinases(MMPs)constitute a family of proteolytic enzymes that facilitate tissue remodeling and the degradation of the ECM.MMP-9 and MMP-13 belong to the group of extracellular matrix degrading enzymes and their expression has been studied in OSCC because of their specific functions.MMP-13,a collagenase family member,is thought to play an essential role in the MMP activation cascade by breaking down the fibrillar collagens,whereas MMP-9 is thought to accelerate the growth of tumors.Elevated MMP-13 expression has been associated with tumor behavior and patient prognosis in a number of malignant cases.AIM To assess the immunohistochemical expression of MMP-9 and MMP-13 in OSCC.METHODS A total of 40 cases with histologically confirmed OSCC by incisional biopsy were included in this cross-sectional retrospective study.The protocols for both MMP-9 and MMP-13 immunohistochemical staining were performed according to the manufacturer’s recommendations along with the normal gingival epithelium as a positive control.All the observations were recorded and Pearson’sχ²test with Fisher exact test was used for statistical analysis.RESULTS Our study showed no significant correlation between MMP-9 and MMP-13 staining intensity and tumor size.The majority of the patients were in advanced TNM stages(III and IV),and showed intense expression of MMP-9 and MMP-13.CONCLUSION The present study suggests that both MMP-9 and MMP-13 play an important and independent role in OSCC progression and invasiveness.Intense expression of MMP-9 and MMP-13,irrespective of histological grade of OSCC,correlates well with TNM stage.Consequently,it is evident that MMP-9 and MMP-13 are important for the invasiveness and progression of tumors.The findings may facilitate the development of new approaches for evaluating lymph node metastases and interventional therapy techniques,hence enhancing the prognosis of patients diagnosed with OSCC.
文摘Purpose: Brain functional networks (BFNs) has become important approach for diagnosis of some neurological or psychological disorders. Before estimating BFN, obtaining blood oxygen level dependent (BOLD) representative signals from brain regions of interest (ROIs) is important. In the past decades, the common method is generally to take a ROI as a node, averaging all the voxel time series inside it to extract a representative signal. However, one node does not represent the entire information of this ROI, and averaging method often leads to signal cancellation and information loss. Inspired by this, we propose a novel model extraction method based on an assumption that a ROI can be represented by multiple nodes. Methods: In this paper, we first extract multiple nodes (the number is user-defined) from the ROI based on two traditional methods, including principal component analysis (PCA), and K-means (Clustering according to the spatial position of voxels). Then, canonical correlation analysis (CCA) was issued to construct BFNs by maximizing the correlation between the representative signals corresponding to the nodes in any two ROIs. Finally, to further verify the effectiveness of the proposed method, the estimated BFNs are applied to identify subjects with autism spectrum disorder (ASD) and mild cognitive impairment (MCI) from health controls (HCs). Results: Experimental results on two benchmark databases demonstrate that the proposed method outperforms the baseline method in the sense of classification performance. Conclusions: We propose a novel method for obtaining nodes of ROId based on the hypothesis that a ROI can be represented by multiple nodes, that is, to extract the node signals of ROIs with K-means or PCA. Then, CCA is used to construct BFNs.
基金supported by grants from the National Natural Science Foundation of China(Grant Nos.81672638 and W2421095)National Natural Science Foundation of Shandong Province(Grant No.ZR2024LMB011)Collaborative Academic Innovation Project of Shandong Cancer Hospital(Grant No.GF003)。
文摘The principal breast cancer treatment approach has long been surgical removal of the primary breast lesions and regional lymph nodes,particularly the axillary lymph nodes.However,the advent of minimally invasive diagnostic techniques,such as sentinel lymph node biopsy(SLNB),has markedly diminished the extent of surgery required for regional lymph nodes.
基金Project partially supported by the National Natural Science Foundation of China (Grant Nos. 61672298 and 62373197)the Major Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province,China (Grant No. 2018SJZDI142)the Postgraduate Research & Practice Innovation Program of Jiangsu Province,China (Grant No. KYCX23 1045)。
文摘Identifying key nodes in complex networks is crucial for understanding and controlling their dynamics. Traditional centrality measures often fall short in capturing the multifaceted roles of nodes within these networks. The Page Rank algorithm, widely recognized for ranking web pages, offers a more nuanced approach by considering the importance of connected nodes. However, existing methods generally overlook the geometric properties of networks, which can provide additional insights into their structure and functionality. In this paper, we propose a novel method named Curv-Page Rank(C-PR), which integrates network curvature and Page Rank to identify influential nodes in complex networks. By leveraging the geometric insights provided by curvature alongside structural properties, C-PR offers a more comprehensive measure of a node's influence. Our approach is particularly effective in networks with community structures, where it excels at pinpointing bridge nodes critical for maintaining connectivity and facilitating information flow. We validate the effectiveness of C-PR through extensive experiments. The results demonstrate that C-PR outperforms traditional centrality-based and Page Rank methods in identifying critical nodes. Our findings offer fresh insights into the structural importance of nodes across diverse network configurations, highlighting the potential of incorporating geometric properties into network analysis.
基金supported by the National Natural Science Foundation of China(No.82272845)the Natural Science Foundation of Shandong(No.ZR2023ZD26).
文摘Objective:The neglect of occult lymph nodes metastasis(OLNM)is one of the pivotal causes of early non-small cell lung cancer(NSCLC)recurrence after local treatments such as stereotactic body radiotherapy(SBRT)or surgery.This study aimed to develop and validate a computed tomography(CT)-based radiomics and deep learning(DL)fusion model for predicting non-invasive OLNM.Methods:Patients with radiologically node-negative lung adenocarcinoma from two centers were retrospectively analyzed.We developed clinical,radiomics,and radiomics-clinical models using logistic regression.A DL model was established using a three-dimensional squeeze-and-excitation residual network-34(3D SE-ResNet34)and a fusion model was created by integrating seleted clinical,radiomics features and DL features.Model performance was assessed using the area under the curve(AUC)of the receiver operating characteristic(ROC)curve,calibration curves,and decision curve analysis(DCA).Five predictive models were compared;SHapley Additive exPlanations(SHAP)and Gradient-weighted Class Activation Mapping(Grad-CAM)were employed for visualization and interpretation.Results:Overall,358 patients were included:186 in the training cohort,48 in the internal validation cohort,and 124 in the external testing cohort.The DL fusion model incorporating 3D SE-Resnet34 achieved the highest AUC of 0.947 in the training dataset,with strong performance in internal and external cohorts(AUCs of 0.903 and 0.907,respectively),outperforming single-modal DL models,clinical models,radiomics models,and radiomicsclinical combined models(DeLong test:P<0.05).DCA confirmed its clinical utility,and calibration curves demonstrated excellent agreement between predicted and observed OLNM probabilities.Features interpretation highlighted the importance of textural characteristics and the surrounding tumor regions in stratifying OLNM risk.Conclusions:The DL fusion model reliably and accurately predicts OLNM in early-stage lung adenocarcinoma,offering a non-invasive tool to refine staging and guide personalized treatment decisions.These results may aid clinicians in optimizing surgical and radiotherapy strategies.
基金Supported by the National High Level Hospital Clinical Research Funding,No.2023-NHLHCRF-BQ-32 and No.2023-NHLHCRFYYPPLC-ZR-13National Key Research and Development Program of China,No.2024YFE0198300Beijing Municipal Natural Science Foundation,No.7222316.
文摘BACKGROUND The number of tumor deposits(TDs)does not play a part in the current tumor node metastasis staging.Negative lymph node(NLN)status is associated with the prognosis of colorectal cancer(CRC),but its clear role in N1c stage remains to be defined.AIM To evaluate the combination of TDs and NLNs as potential prognostic indicators in N1c CRC.METHODS We retrospectively identified 107 consecutive patients who had N1c CRC radically resected at China-Japan Friendship Hospital.The combination of TDs and NLNs was calculated by the formula NLNTD=NLN/(TD+1).Cutoff values of NLNs and NLNTD were determined using the R package“survminer”.Disease-free survival(DFS),overall survival(OS)and cancer-specific survival(CSS)were determined using the Kaplan-Meier method to assess the impact of NLNTD on prognosis.Results were compared using the log-rank test.RESULTS The median follow-up time was 63.17(45.33-81.37)months for DFS,with 33.64%(36/107)of patients experiencing recurrence during follow-up.Five-year DFS was 66.0%(57.3%-76.0%).There was no significant difference in prognosis between patients with>12 and≤12 NLNs(P=0.058)for DFS.Similar results were seen according to the number of TDs.The definition of NLNTD=NLN/(TD+1)with a cutoff value of 6 divided patients into two groups with different DFS(P=0.005).Five-year DFS for patients with NLNTD>6 was 73.5%(63.6%-85.0%),compared with 50.0%(35.7%-70.0%)for those with NLNTD≤6.These two groups had different prognosis without perineural invasion(P=0.012)or lymphovascular invasion(P=0.002)even neither(P=0.053).Similar results were seen for OS and CSS.CONCLUSION NLNTD could serve as important prognostic factor for outcomes in N1c CRC patients.These patients could be stratified for prognosis through NLNTD and the high-risk should be given more attention during treatment.
文摘Gastric cancer(GC)represents a significant global health burden due to its high morbidity and mortality.Specific behaviors of GC sub-types,distinct dissem-ination patterns,and associated risk-factors remain poorly understood.This editorial highlights several key prognostic factors,including pathological staging and vascular invasion,that impact GC.It examines a recent study’s investigation of differential metastatic lymph nodes distribution and survival in upper and lower GC sub-types,focusing on histological characterization,pathophysiology,usage of neoadjuvant chemotherapy,and additional predictive determinants.We assess the statistical robustness and clinical applicability of the findings,un-derscoring the importance of treating GC as a heterogeneous disease and em-phasizing how tailored surgical approaches informed by lymph node distribution can optimize tumor detection while minimizing unnecessary interventions.The study’s large cohort,multi-center design,and strict inclusion criteria strengthen its validity in guiding surgical planning and risk-stratification.However,inte-grating genetic and molecular data is critical for refining models and broadening applicability.Additionally,recurrence-metrics and infection-related factors,such as Helicobacter pylori and Epstein-Barr virus,absent in the original study,remain vital for directing future research.By bridging metastatic patterns with pros-pective methodologies and inclusion of diverse populations,this editorial pro-vides a framework for advancing early detection and personalized GC care.
文摘Aim: Assess the role of hybrid modality SPECT/CT versus planar scintigraphy in sentinel lymph node (SLN) identification in patients with breast cancer. Methods: Planar scintigraphy and hybrid modality SPECT/CT were performed in 23 women with breast cancer (mean age 59.5 years with range 25 - 82 years) with invasive breast cancer (T0, T1 and T2), without clinical evidence of axillary lymph node metastases (N0) and no remote metastases (M0), radiocolloid was injected in four subareolar sites. Planar and SPECT/CT images were separately interpreted. Results: SLNs were detected on lymphoscintigraphy in all patients (100%), taking into consideration both techniques (planar and SPECT-CT images). Planar images identified 45 SLNs in 23 women, with a mean of 1.95 per patient, whereas 56 SLNs were detected on SPECT/CT, increasing this mean to 2.43 per patient. Drainage to internal mammary lymph nodes was seen in 4 patients (17.39%). However, two foci of uptake were identified on planar image as hot SLN in two patients (8.69%);while they have been found as a false positive non-nodal site of uptake on SPECT/CT. Conclusion: SPECT/CT is more focused than planar scintigraphy in the detection of SLN in patients with breast cancer. It detects some lymph nodes not visible on planar images, excludes false positive uptake and exactly locates axillary and non-axillary SLNs.
基金the Clinical Medical Team Introduction Program of Suzhou,No.SZYJTD201804.
文摘BACKGROUND Lymph node status is a critical prognostic factor in gastric cancer(GC),but stage migration may occur in pathological lymph nodes(pN)staging.To address this,alternative staging systems such as the positive lymph node ratio(LNR)and log odds of positive lymph nodes(LODDS)were introduced.AIM To assess the prognostic accuracy and stratification efficacy of three nodal staging systems in GC.METHODS A systematic review identified 12 studies,from which hazard ratios(HRs)for overall survival(OS)were summarized.Sensitivity analyses,subgroup analyses,publication bias assessments,and quality evaluations were conducted.To enhance comparability,data from studies with identical cutoff values for pN,LNR,and LODDS were pooled.Homogeneous stratification was then applied to generate Kaplan-Meier(KM)survival curves,assessing the stratification efficacy of three staging systems.RESULTS The HRs and 95%confidence intervals for pN,LNR,and LODDS were 2.16(1.72-2.73),2.05(1.65-2.55),and 3.15(2.15-4.37),respectively,confirming all three as independent prognostic risk factors for OS.Comparative analysis of HRs demonstrated that LODDS had superior prognostic predictive power over LNR and pN.KM curves for pN(N0,N1,N2,N3a,N3b),LNR(0.1/0.2/0.5),and LODDS(-1.5/-1.0/-0.5/0)revealed significant differences(P<0.001)among all prognostic stratifications.Mean differences and standard deviations in 60-month relative survival were 27.93%±0.29%,41.70%±0.30%,and 26.60%±0.28%for pN,LNR,and LODDS,respectively.CONCLUSION All three staging systems are independent prognostic factors for OS.LODDS demonstrated the highest specificity,making it especially useful for predicting outcomes,while pN was the most effective in homogeneous stratification,offering better patient differentiation.These findings highlight the complementary roles of LODDS and pN in enhancing prognostic accuracy and stratification.
文摘Gastric cancer(GC)remains a leading cause of cancer mortality.While the extent of nodal involvement is a well-known prognostic factor,the specific entity of swollen lymph node metastasis(SLNM),bulky nodal tumor deposits detectable radiologically or pathologically,has received little attention in staging.Recent data from a study by Cui et al demonstrated that SLNM is an independent predictor of very poor survival in GC.Through robust data and rigorous propensitymatched analyses,SLNM emerged not merely as an anatomical finding but as an independent predictor of poor prognosis,even among patients undergoing curative resection.As precision oncology advances,the findings by Cui et al urge a fundamental rethinking of how SLNM is incorporated into clinical decisionmaking for GC management.In this editorial,we critically examine the prognostic significance of SLNM,challenge its omission from traditional staging frameworks,and advocate for its formal integration into preoperative risk stratification and treatment planning.Recognizing SLNM at diagnosis could unlock intensified neoadjuvant therapy strategies and optimize outcomes for a historically high-risk patient subgroup.
文摘Objective Almost 15%of prostate cancer(PCa)patients were found to have lymph node metastases(LNMs),which are associated with higher risk of biochemical recurrence.Using indocyanine green(ICG)for the sentinel node biopsy(SNB)before surgery was proposed to detect LNMs in PCa patients.However,its diagnostic performance still remains controversial.This study aimed to investigate the diagnostic performance of ICG for the SNB in PCa.Methods This systematic review and meta-analysis has been reported in line with the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines.The protocol has been registered in the International Prospective Register of Systematic Reviews database,and the register number is CRD42023421911.Four bibliographic databases were searched,i.e.,PubMed,EMBASE,Cochrane Library,and Web of Science,to retrieve articles studying the diagnostic performance of ICG for the SNB in PCa from the inception to Sep 9,2023.We calculated the pooled sensitivity,specificity,likelihood ratios,diagnostic odds ratios and their 95%confidence intervals(CIs).Subgroup analyses and meta-regression analyses were also conducted.Results A total of 17 articles from databases are enrolled in this study.Using lymph node-based data,our results showed that the pooled sensitivity and specificity of applying ICG alone in PCa were 71%(95%CI 52%–85%)and 68%(95%CI 64%–72%),respectively.The pooled sensitivity and specificity of applying ICG-technetium-99m-nanocolloid in PCa were 49%(95%CI 39%–59%)and 69%(95%CI 67%–71%),respectively.
文摘The article by Yuan et al accessed the clinicopathologic and prognostic significance of the patterns of lymph node(LN)metastasis in upper and lower gastric cancer(GC).In this article,we will analyze both the strengths and limitations of this paper.The study’s methodology seems appropriate and proper statistical analyses were applied to identify significant variables.The authors applied the Cox regression model to identify independent risk factors and Kaplan-Meier survival curves to assess prognosis.The researchers found notable differences in cli-nicopathologic variables between patients with upper and lower GC.Addi-tionally,they identified specific LN stations more prone to metastasis in different Siewert classifications of GC.Despite the study’s detailed analysis,it would have been beneficial to explore whether there were survival differences among upper GC patients based on the Siewert classification.Furthermore,the study should have addressed potential confounding factors that might have influenced the results.A more comprehensive analysis could have been achieved by comparing survival outcomes based on LN metastasis patterns.Overall,this article is relevant and provides valuable insights into the significance of LN metastasis patterns in upper GC patients.
文摘Introduction The accuracy of sentinel lymph node biopsy(SLNB)after neoadjuvant therapy(NAT)has been confirmed in clinical nodal stage 1(c N1)patients,and more patients could benefit from axillary surgery de-escalation after NAT(1,2).
基金Supported by Shanxi Special Projects of the Central Government Guiding Local Science and Technology Development of China,No.YDZJSX2021B016Shanxi Cancer Hospital Doctoral Master’s Guide and Companion Flying Fund,No.SD2023010.
文摘BACKGROUND The National Comprehensive Cancer Network guidelines recommend adjuvant chemotherapy(ACT)for patients with stage II colon cancer who have undergone curative surgery when fewer than 12 lymph nodes(LNs)are retrieved.This study seeks to further examine the requirement for ACT in individuals who had 12 or more LNs harvested.AIM To investigate if stage II colon cancer patients with 12 or more LNs retrieved benefit from ACT.METHODS This retrospective cohort study included individuals diagnosed with stage II colon cancer who underwent surgery between 2008 and 2017 from the Surveillance,Epidemiology,and End Results(SEER)registry and a Chinese multicenter database.All patients had at least 12 LNs retrieved.The key endpoint was overall survival(OS).Cox regression analysis was performed to assess independent OS predictors.Propensity score matching controlled for confounders,and Kaplan-Meier analysis evaluated the impact of ACT on survival.RESULTS A total of 32742 patients with stage II colon cancer from the SEER cohort and 3153 patients from the Chinese cohort were included.The average number of LNs retrieved was 20.0(15.0,26.0)in the SEER cohort and 18.0(15.0,22.0)in the Chinese cohort.No-ACT remained an independent risk factor in both cohorts(hazard ratio=1.589,95%confidence interval:1.485-1.700 and hazard ratio=1.865,95%confidence interval:1.465-2.375,respectively).In the SEER cohort,patients in the ACT group consistently demonstrated better 5-year OS rates both before and after propensity score matching(79.4%vs 66.1%and 79.4%vs 69.4%,both P<0.0001).Similarly,these findings were further validated in the Chinese cohort(91.2%vs 82.1%and 90.0%vs 82.8%,both P<0.0001).ACT improved prognosis even in T3 and grade 1/2 patients.CONCLUSION This research,based on two large population-based cohorts,demonstrates that stage II colon cancer patients with 12 or more LNs retrieved can still benefit from ACT.
基金Supported by the National Natural Science Foundation of China(Grant No.12031002)。
文摘Accurately identifying key nodes is essential for evaluating network robustness and controlling information propagation in complex network analysis. However, current research methods face limitations in applicability and accuracy. To address these challenges, this study introduces the K-GCN model, which integrates neighborhood k-shell distribution analysis with Graph Convolutional Network(GCN) technology to enhance key node identification in complex networks. The K-GCN model first leverages neighborhood k-shell distributions to calculate entropy values for each node, effectively quantifying node importance within the network. These entropy values are then used as key features within the GCN, which subsequently formulates intelligent strategies to maximize network connectivity disruption by removing a minimal set of nodes, thereby impacting the overall network architecture. Through iterative interactions with the environment, the GCN continuously refines its strategies, achieving precise identification of key nodes in the network. Unlike traditional methods, the K-GCN model not only captures local node features but also integrates the network structure and complex interrelations between neighboring nodes, significantly improving the accuracy and efficiency of key node identification.Experimental validation in multiple real-world network scenarios demonstrates that the K-GCN model outperforms existing methods.
