Establishment of Risk Prediction Model and Nomogram for Lymph Node Metastasis of Cervical Cancer: Based on SEER Database

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.

Magnetic resonance imaging-based lymph node radiomics for predicting the metastasis of evaluable lymph nodes in rectal cancer

BACKGROUND Lymph node(LN)staging in rectal cancer(RC)affects treatment decisions and patient prognosis.For radiologists,the traditional preoperative assessment of LN metastasis(LNM)using magnetic resonance imaging(MRI)poses a challenge.AIM To explore the value of a nomogram model that combines Conventional MRI and radiomics features from the LNs of RC in assessing the preoperative metastasis of evaluable LNs.METHODS In this retrospective study,270 LNs(158 nonmetastatic,112 metastatic)were randomly split into training(n=189)and validation sets(n=81).LNs were classified based on pathology-MRI matching.Conventional MRI features[size,shape,margin,T2-weighted imaging(T2WI)appearance,and CE-T1-weighted imaging(T1WI)enhancement]were evaluated.Three radiomics models used 3D features from T1WI and T2WI images.Additionally,a nomogram model combining conventional MRI and radiomics features was developed.The model used univariate analysis and multivariable logistic regression.Evaluation employed the receiver operating characteristic curve,with DeLong test for comparing diagnostic performance.Nomogram performance was assessed using calibration and decision curve analysis.RESULTS The nomogram model outperformed conventional MRI and single radiomics models in evaluating LNM.In the training set,the nomogram model achieved an area under the curve(AUC)of 0.92,which was significantly higher than the AUCs of 0.82(P<0.001)and 0.89(P<0.001)of the conventional MRI and radiomics models,respectively.In the validation set,the nomogram model achieved an AUC of 0.91,significantly surpassing 0.80(P<0.001)and 0.86(P<0.001),respectively.CONCLUSION The nomogram model showed the best performance in predicting metastasis of evaluable LNs.

Predictive value of machine learning models for lymph node metastasis in gastric cancer: A two-center study

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.

Histological Risk Factors for Lymph Node Metastasis in pT1 Colorectal Cancer:Does Submucosal Invasion Depth Really Matter?

Objective After endoscopic resection of colorectal cancer with submucosal invasion(pT1 CRC),additional surgical treatment is recommended if deep submucosal invasion(DSI)is present.This study aimed to further elucidate the risk factors for lymph node metastasis(LNM)in patients with pT1 CRC,especially the effect of DSI on LNM.Methods Patients with pT1 CRC who underwent lymph node dissection were selected.The Chi-square test and multivariate logistic regression were used to analyze the relationship between clinicopathological characteristics and LNM.The submucosal invasion depth(SID)was measured via 4 methods and analyzed with 3 cut-off values.Results Twenty-eight of the 239 patients presented with LNM(11.7%),and the independent risk factors for LNM included high histological grade(P=0.003),lymphovascular invasion(LVI)(P=0.004),intermediate to high budding(Bd 2/3)(P=0.008),and cancer gland rupture(CGR)(P=0.008).Moreover,the SID,width of submucosal invasion(WSI),and area of submucosal invasion(ASI)were not significantly different.When one,two,three or more risk factors were identified,the LNM rates were 1.1%(1/95),12.5%(7/56),and 48.8%(20/41),respectively.Conclusion Indicators such as the SID,WSI,and ASI are not risk factors for LNM and are subjective in their measurement,which renders them relatively inconvenient to apply in clinical practice.In contrast,histological grade,LVI,tumor budding and CGR are relatively straightforward to identify and have been demonstrated to be statistically significant.It would be prudent to focus on these histological factors rather than subjective measurements.

Can we triumph over locally advanced cervical cancer with colossal para-aortic lymph nodes? A case report

BACKGROUND Para-aortic lymph nodes(PALNs)are common sites for the regional spread of cervical squamous cell carcinoma(SCC).CASE SUMMARY We report the case of a 36-year-old woman who presented with cervical SCC with multiple bulky PALNs,largest measured 4.5 cm×5 cm×10 cm.The patient was treated with radical intent with definitive chemoradiation using sequential doseescalated adaptive radiotherapy,followed by maintenance chemotherapy.The patient achieved a complete response;she has been doing well since the completion of treatment with no evidence of the disease for 2 years.CONCLUSION Regardless of the size of PALN metastases of cervical carcinoma origin,it is still treatable(with radical intent)via concurrent chemoradiation.Adaptive radiotherapy allows dose escalation with minimal toxicity.

Nomogram established using risk factors of early gastric cancer for predicting the lymph node metastasis

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.

Primary Treatment for Clinically Early Cervical Cancer with Lymph Node Metastasis:Radical Surgery or Radiation?

Objective To compare survival outcomes between primary radical surgery and primary radiation in early cervical cancer.Methods Patient information was extracted from the Surveillance,Epidemiology,and Results database.Patients diagnosed with early cervical cancer of stage T1a,T1b,and T2a(American Joint Committee on Cancer,7th edition)from 1998 to 2015 were included in this study after propensity score matching.Overall survival(OS)was analyzed using the Kaplan-Meier method.Results Among the 4964 patients included in the study,1080 patients were identified as having positive lymph nodes(N1),and 3884 patients were identified as having negative lymph nodes(N0).Patients with primary surgery had significantly longer 5-year OS than those with primary radiotherapy in both the N1 group(P<0.001)and N0 group(P<0.001).In the subgroup analysis,similar results were found in patients with positive lymph nodes of stage T1a(100.0%vs.61.1%),T1b(84.1%vs.64.3%),and T2a(74.4%vs.63.8%).In patients with T1b1 and T2a1,primary surgery resulted in longer OS than primary radiation,but not in patients with T1b2 and T2a2.In multivariate analysis,the primary treatment was identified as an independent prognostic factor in both N1 and N0 patients(HR_(N1)=2.522,95%CI=1.919–3.054,PN1<0.001;HR_(N0)=1.895,95%CI=1.689–2.126,PN0<0.001).Conclusion In early cervical cancer stage T1a,T1b1,and T2a1,primary surgery may result in longer OS than primary radiation for patients with and without lymph node metastasis.

ScRNA-seq reveals the correlation between M2 phenotype of tumorassociated macrophages and lymph node metastasis of breast cancer

The process of lymphatic metastasis was proved to be associated with podoplanin-expressing macrophages in breast cancer(BC).This study aimed to investigate the role of the M2 phenotype of tumor-associated macrophages and mine the key M2 macrophages-related genes for lymph node metastasis in BC.We downloaded the GSE158399 dataset from the Gene Expression Omnibus(GEO)database,which includes transcriptomic profiles of individual cells from primary tumors,negative lymph nodes(NLNs),and positive lymph nodes(PLNs)of breast cancer patients.The cell subsets were identified by clustering analysis after quality control of the scRNA-seq using Seurat.The activation and migration capability of M2 macrophages were evaluated with R package“GSVA”.The key M2 macrophages-related genes were screened from the differential expressed genes(DEGs)and M2 macrophages activation and migration gene sets collected from MSigDB database.Our analysis identified three main cell types in primary tumors,NLNs,and PLNs:basal cells,luminal cells,and immune cell subsets.The further cell type classification of immune cell subsets indicated M2 macrophages accumulation in NLs and PLs.The GSVA enrichment scores for activation and migration capability were increased significantly in M2 macrophages from primary tumors than NLNs and PLNs(pvalue<0.001).Seven M2 macrophages activation-related and 15 M2 macrophages migration-related genes were significantly up-regulated in primary tumors than NLNs and PLNs.The proportion and GSVA enrichment scores for activation and migration of M2 macrophages may be potential markers for lymph node metastasis in breast cancer.Our study demonstrated that twenty-two up-regulated mRNA may be possible therapeutic targets for lymph node metastasis in breast cancer.

Predicting lymph node metastasis in colorectal cancer:An analysis of influencing factors to develop a risk model

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.

Prediction of lymph node metastasis in early esophageal cancer

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.

Progress in the Study of Lymph Node Metastasis in Early-stage Cervical Cancer

Spread into regional lymph node is the major route of metastasis in cervical cancer. Although lymph node status is not involved in the International Federation of Gynecology and Obstetrics staging system of uterine cervical cancer, the presence or absence of lymph node metastasis provides important information for prognosis and treatment. In this review, we have attempted to focus on the incidence and patterns of lymph node metastasis, and the issues surrounding surgical assessment of lymph nodes. In addition, the preoperative prediction of lymph node status, as well as the intraoperative assessment by sentinel nodes will be reviewed. Finally, lymph node micrometastasis also will be discussed.

Assessment of programmed death-ligand 1 expression in primary tumors and paired lymph node metastases of gastric adenocarcinoma

BACKGROUND Anti-programmed death-1/programmed death-ligand 1(PD-1/PD-L1)immuno-therapy has demonstrated promising results on gastric cancer(GC).However,PD-L1 can express differently between metastatic sites and primary tumors(PT).AIM To compare PD-L1 status in PT and matched lymph node metastases(LNM)of GC patients and to determine the correlation between the PD-L1 status and clinicopathological characteristics.METHODS We retrospectively reviewed 284 GC patients who underwent D2-gastrectomy.PD-L1 was evaluated by immunohistochemistry(clone SP142)using the com-bined positive score.All PD-L1+PT staged as pN+were also tested for PD-L1 expression in their LNM.PD-L1(-)GC with pN+served as the comparison group.RESULTS Among 284 GC patients included,45 had PD-L1+PT and 24 of them had pN+.For comparison,44 PD-L1(-)cases with pN+were included(sample loss of 4 cases).Of the PD-L1+PT,54.2%(13/24 cases)were also PD-L1+in the LNM.Regarding PD-L1(-)PT,9.1%(4/44)had PD-L1+in the LNM.The agreement between PT and LNM had a kappa value of 0.483.Larger tumor size and moderate/severe peritumoral inflammatory response were associated with PD-L1 positivity in both sites.There was no statistical difference in overall survival for PT and LNM according to the PD-L1 status(P=0.166 and P=0.837,respectively).CONCLUSION Intra-patient heterogeneity in PD-L1 expression was observed between the PT and matched LNM.This disagreement in PD-L1 status may emphasize the importance of considering different tumor sites for analyses to select patients for immunotherapy.

Relationship between Expression of Vascular Endothelial Growth Factor and Cervical Lymph Node Metastasis in Papillary Thyroid Cancer: A Meta-analysis

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.

Separate lateral parametrial lymph node dissection improves detection rate of parametrial lymph node metastasis in early-stage cervical cancer: 10-year clinical evaluation in a single center in China

Objective: To investigate the clinical significance of separate lateral parametrial lymph node dissection(LPLND) in improving parametrial lymph node(PLN) and its metastasis detection rate during radical hysterectomy for early-stage cervical cancer.Methods: From July 2007 to August 2017, 2,695 patients with cervical cancer in stage IB1-IIA2 underwent radical hysterectomy were included. Of these patients, 368 underwent separate dissection of PLNs using the LPLND method, and 2,327 patients underwent conventional radical hysterectomy(CRH). We compared the surgical parameters, PLN detection rate and PLN metastasis rate between the two groups.Results: Compared with CRH group, the rate of laparoscopic surgery was higher(60.3% vs. 15.9%, P<0.001),and the blood transfusion rate was lower(19.0% vs. 29.0%, P<0.001) in the LPLND group. PLNs were detected in 356 cases(96.7%) in the LPLND group, and 270 cases(11.6%) in the CRH group(P<0.001), respectively. The number of PLNs detected in the LPLND group was higher than that in the CRH group(median 3 vs. 1, P<0.001).The PLN metastases were detected in 25 cases(6.8%) in the LPLND group, and 18 cases(0.8%) in the CRH group(P<0.001), respectively. In multivariable analysis, LPLND is an independent factor not only for PLN detection [odds ratio(OR)=228.999, 95% confidence interval(95% CI): 124.661-420.664;P<0.001], but also for PLN metastasis identification(OR=10.867, 95% CI: 5.381-21.946;P<0.001).Conclusions: LPLND is feasible and safe. The surgical method significantly improves the detection rate of PLN and avoids omission of PLN metastasis during radical hysterectomy for early-stage cervical cancer.

Nomogram based on multimodal magnetic resonance combined with B7-H3mRNA for preoperative lymph node prediction in esophagus cancer

Accurate preoperative prediction of lymph node metastasis(LNM)in esophageal cancer(EC)patients is of crucial clinical significance for treatment planning and prognosis.AIM To develop a clinical radiomics nomogram that can predict the preoperative lymph node(LN)status in EC patients.METHODS A total of 32 EC patients confirmed by clinical pathology(who underwent surgical treatment)were included.Real-time fluorescent quantitative reverse transcription-polymerase chain reaction was used to detect the expression of B7-H3 mRNA in EC tissue obtained during preoperative gastroscopy,and its correlation with LNM was analyzed.Radiomics features were extracted from multi-modal magnetic resonance imaging of EC using Pyradiomics in Python.Feature extraction,data dimensionality reduction,and feature selection were performed using XGBoost model and leave-one-out cross-validation.Multivariable logistic regression analysis was used to establish the prediction model,which included radiomics features,LN status from computed tomography(CT)reports,and B7-H3 mRNA expression,represented by a radiomics nomogram.Receiver operating characteristic area under the curve(AUC)and decision curve analysis(DCA)were used to evaluate the predictive performance and clinical application value of the model.RESULTS The relative expression of B7-H3 mRNA in EC patients with LNM was higher than in those without metastasis,and the difference was statistically significant(P<0.05).The AUC value in the receiver operating characteristic(ROC)curve was 0.718(95%CI:0.528-0.907),with a sensitivity of 0.733 and specificity of 0.706,indicating good diagnostic performance.The individualized clinical prediction nomogram included radiomics features,LN status from CT reports,and B7-H3 mRNA expression.The ROC curve demonstrated good diagnostic value,with an AUC value of 0.765(95%CI:0.598-0.931),sensitivity of 0.800,and specificity of 0.706.DCA indicated the practical value of the radiomics nomogram in clinical practice.CONCLUSION This study developed a radiomics nomogram that includes radiomics features,LN status from CT reports,and B7-H3 mRNA expression,enabling convenient preoperative individualized prediction of LNM in EC patients.

Comparison of efficacy and safety between late-course and simultaneous integrated dose-increasing intensity-modulated radiation therapy for cervical cancer complicated with pelvic lymph node metastasis

Objective This study aimed to compare and analyze the clinical efficacy and safety of late-course and simultaneous integrated dose-increasing intensity-modulated radiation therapy(IMRT) for cervical cancer complicated with pelvic lymph node metastasis. Methods Sixty patients with cervical cancer complicated with pelvic lymph node metastasis who were admitted to our hospital from January 2013 to January 2015 were enrolled. The patients were randomly divided into the late-course dose-increasing IMRT group and the simultaneous integrated dose-increasing IMRT group, with 30 cases included in each group, respectively. All patients were concurrently treated with cisplatin. After treatment, the clinical outcomes of the two groups were compared. Results The remission rate of symptoms in the simultaneous integrated dose-increasing IMRT group was significantly higher than that in the late-course dose-increasing IMRT group(P < 0.05). The follow-up results showed that the overall survival time, progression-free survival time, and distant metastasis time of patients in the simultaneous integrated dose-increasing IMRT group were significantly longer than those in the late-course dose-increasing IMRT group(P < 0.05). The recurrent rate of lymph nodes in the radiation field in the simultaneous integrated dose-increasing IMRT group was significantly lower(P < 0.05) than in the late-course dose-increasing IMRT group. There was no significant difference in the incidence of cervical and vaginal recurrence and distant metastasis between the two groups(P > 0.05). The radiation doses of Dmax in the small intestine, D1 cc(the minimum dose to the 1 cc receiving the highest dose) in the bladder, and Dmax in the rectum in the simultaneous integrated dose-increasing IMRT group were significantly lower(P < 0.05) than in the late-course dose-increasing IMRT group. There was no significant difference in intestinal D2 cc(the minimum dose to the 2 cc receiving the highest dose) between the two groups(P > 0.05). The incidence of bone marrow suppression in the simultaneous integrated dose-increasing IMRT group was significantly lower(P < 0.05) than in the late-course dose-increasing IMRT group.Conclusion The application of simultaneous integrated dose-increasing IMRT in the treatment of cervical cancer patients complicated with pelvic lymph node metastasis can significantly control tumor progression, improve the long-term survival time, and postpone distant metastasis time with high safety.

Prediction of lymph node metastasis in early gastric signet-ring cell carcinoma:A real-world retrospective cohort study

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.

Advantage of log odds of positive lymph nodes in prognostic evaluation of patients with early-onset colon cancer

BACKGROUND Colon cancer(CC)is one of the most common cancers of the digestive tract,the third most common cancer worldwide,and the second most common cause of cancer-related deaths.Previous studies have demonstrated a higher risk of lymph node metastasis(LNM)in young patients with CC.It might be reasonable to treat patients with early-onset locally advanced CC with extended lymph node dissection.However,few studies have focused on early-onset CC(ECC)patients with LNM.At present,the methods of predicting and evaluating the prognosis of ECC patients with LNM are controversial.From the data of patients with CC obtained from the Surveillance,Epidemiology,and End Results(SEER)database,data of young patients with ECC(≤50 years old)was screened.Patients with unknown data were excluded from the study,while the remaining patients were included.The patients were randomly divided into a training group(train)and a testing group(test)in the ratio of 7:3,while building the model.The model was constructed by the training group and verified by the testing group.Using multiple Cox regression models to compare the prediction efficiency of LNM indicators,nomograms were built based on the best model selected for overall survival(OS)and cause-specific survival(CSS).In the two groups,the performance of the nomogram was evaluated by constructing a calibration plot,time-dependent area under the curve(AUC),and decision curve analysis.Finally,the patients were grouped based on the risk score predicted by the prognosis model,and the survival curve was constructed after comparing the survival status of the high and low-risk groups.RESULTS Records of 26922 ECC patients were screened from the SEER database.N classification,positive lymph nodes(PLN),lymph node ratio(LNR)and log odds of PLN(LODDS)were considered to be independent predictors of OS and CSS.In addition,independent risk factors for OS included gender,race,marital status,primary site,histology,grade,T,and M classification,while the independent prognostic factors for CSS included race,marital status,primary site,grade,T,and M classification.The prediction model including LODDS is composed of minimal Akaike information criterion,maximal concordance indexes,and AUCs.Factors including gender,race,marital status,primary site,histology,grade,T,M classification,and LODDS were integrated into the OS nomogram,while race,marital status,primary site,grade,T,M classification,and LODDS were included into the CSS nomogram.The nomogram representing both cohorts had been successfully verified in terms of prediction accuracy and clinical practicability.CONCLUSION LODDS is superior to N-stage,PLN,and LNR of ECC.The nomogram containing LODDS might be helpful in tumor evaluation and clinical decision-making,since it provides an appropriate prediction of ECC.

Evaluation of the Risk Factors for Pelvic Lymph Node Metastasis in Early Stage Cervical Cancer

Objective: This study evaluated the risk factors for pelvic lymph node metastasis in patients with early stage cervical cancer. Material and Methods: A cross sectional study was carried out in the Division of Gynaecologic Oncology at Bangabandhu Sheikh Mujib Medical University (BSMMU) between July 2014 and July 2015 to evaluate demographic factors and histopathological findings of women with cervical cancer stage IB-IIA who underwent primary radical hysterectomy and bilateral pelvic lymph node dissection. Results: Fifty women aged 30 years or above were included in the study. Lymph node metastases were identified in 20% of patients. By univariate analysis, preoperative anemia, a history of smoking, tumor size greater than 4 cm and lack of cervical inflammatory reaction by histopathology were significant variables associated with lymph node metastasis. Multivariate analysis showed that the lack of inflammatory reaction in the uterine cervix was the most important predictor for pelvic lymph node metastasis when adjusting for other variables. Moderate to severe inflammatory reaction in the uterine cervix was 18 times less likely to have pelvic lymph node metastasis than those who had mild inflammation. Conclusion: An association was found between the presence of pelvic lymph node metastasis in cervical cancer and certain variables: the lack of contraceptive use, smoking, preoperative anemia, bulky tumors, invasion of deep two-third of the uterine cervix, mild inflammatory reaction in the cervix, and keratinizing carcinoma. After adjusting for other factors, presence or absence of inflammatory reaction in the cervix was found to be the most important predictor for pelvic lymph node metastasis.

Diagnostic value of18F-FDG PET/CT in cervical lymph node metastasis of oral cancer: Meta-analysis

Objective:To evaluate the value of18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in the diagnosis of cervical lymph node metastasis of oral carcinoma.Methods:China national knowledge infrastructure, Wanfang, Chinese sci-tech journal database, PubMed, EMbase, the Cochrane Library and Web of Science were searched for18F-FDG PET/CT in cervical lymph node metastasis oral cancer. Literature screening, data extraction and literature quality evaluation were carried out independently by two researchers according to the unified classification criteria. Stata13.0 software and Meta-Disc1.4 software were used for meta-analysis.Results: A total of 14 studies with 849 cases of patients with cervical metastasis of oral cancer were included, among which 9 studies were conducted on patients, with a total of 299 patients, and 5 studies were conducted on lymph nodes, with 1965 patients with cervical lymph node proved pathologically. The results of meta analysis showed that18F-FDG PET/CT had good sensitivity and specificity in the diagnosis of cervical lymph node metastasis of oral cancer. The results showed that sensitivity = 0.81 (95% CI: 0.73-0.87), specificity = 0. 90 (95% CI: 0.83-0.94), combined likelihood ratio = 7. 9 (95% CI: 4.9-12.7), negative likelihood ratio = 0. 21 (95% CI: 0.15-0.30), diagnostic odds ratio=37 (95% CI: 20-67), and receiver operating characteristic curve =0.91 (95% CI: 0.89-0.94). Conclusions:18F-FDG PET/CT has high sensitivity and specificity in the diagnosis of cervical lymph node metastasis, and can be used as an important preoperative evaluation method for oral cancer.