Lymph Node Metastasis In Patients Research Articles

AIUM Practice Parameter for the Performance and Interpretation of Diagnostic Ultrasound of the Thyroid and Extracranial Head and Neck.

AIUM Practice Parameter for the Performance and Interpretation of Diagnostic Ultrasound of the Thyroid and Extracranial Head and Neck.

Application of machine learning algorithm in prediction of lymph node metastasis in patients with intermediate and high-risk prostate cancer.

This study aims to establish the best prediction model of lymph node metastasis (LNM) in patients with intermediate- and high-risk prostate cancer (PCa) through machine learning (ML), and provide the guideline of accurate clinical diagnosis and precise treatment for clinicals. A total of 24,470 patients with intermediate- and high-risk PCa were included in this study. Multivariate logistic regression model was used to screen the independent risk factors of LNM. At the same time, six algorithms, namely random forest (RF), naive Bayesian classifier (NBC), xgboost (XGB), gradient boosting machine (GBM), logistic regression (LR) and decision tree (DT) are used to establish risk prediction models. Based on the best prediction performance of ML algorithm, a prediction model is established, and the performance of the model is evaluated from three aspects: area under curve (AUC), sensitivity and specificity. In multivariate logistic regression analysis, T stage, PSA, Gleason score and bone metastasis were independent predictors of LNM in patients with intermediate- and high-risk PCa. By comprehensively comparing the prediction model performance of training set and test set, GBM model has the best prediction performance (F1 score = 0.838, AUROC = 0.804). Finally, we developed a preliminary calculator model that can quickly and accurately calculate the regional LNM in patients with intermediate- and high-risk PCa. T stage, PSA, Gleason and bone metastasis were independent risk factors for predicting LNM in patients with intermediate- and high-risk PCa. The prediction model established in this study performs well; however, the GBM model is the best one.

Diagnostic accuracy of contrast-enhanced dual-energy computed tomography for detecting metastatic lymph nodes in patients with malignant tumors: a systematic review and meta-analysis.

This meta-analysis evaluated the diagnostic accuracy of contrast-enhanced dual-energy computed tomography (DECT) for detecting metastatic lymph nodes in patients with cancer. PubMed, Embase and Cochrane Library databases were searched for literature published from database inception until September 2022. Only studies that investigated the diagnostic accuracy of DECT for metastatic lymph nodes in patients with malignant tumors and surgically removed metastatic lymph nodes for pathological confirmation were included. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies tool. The threshold effect was determined by calculating Spearman correlation coefficients and summary receiver operating characteristic (SROC) curve patterns. Deeks test was used to assess publication bias. All of the included studies were observational studies. A total of 16 articles involving 984 patients were included (2,577 lymph nodes) in this review. A total of 15 variables were included in the meta-analysis, including 6 individual parameters and 9 combined parameters. Normalized iodine concentration (NIC) in the arterial phase combined with the slope in the arterial phase showed better identification of metastatic lymph nodes. The spearman correlation coefficient was -0.371 (P=0.468), and the SROC curve did not show a "shoulder-arm" shape, suggesting that there was no threshold effect and that heterogeneity was present. The combined sensitivity was 94% [95% confidence interval (CI): 86-98%], the specificity was 74% (95% CI: 52-88%), and the area under the curve was 0.94. The Deeks test suggested no significant publication bias in the included studies (P=0.06). NIC in arterial phase combined with the slope in the arterial phase has some diagnostic value in differentiating between metastatic and benign lymph nodes, but this should be further evaluated in additional studies with rigorous design and high homogeneity.

Differential profile of protumor immunological factors between the tumor site and the tumor-free site - predictive potential of IL-8 and COX2 for colorectal cancer and metastasis.

To study the role of host immune surveillance in the initiation and progression of colorectal cancer (CRC), a set of protumor immunological factors was determined by quantitative real-time PCR (q-PCR) between the primary tumor and the adjacent tumor-free site tissues in 63 patients with colorectal neoplasms. Results showed that expression levels of interleukin (IL)-1β, IL-6, IL-8, IL-17A, IL-23, and cyclooxygenase 2 (COX2) mRNAs, except transforming growth factor beta (TGFβ), in adenoma tissues were significantly higher than that in relative adjacent tissues. Difference of immunological factor levels between adenoma and adjacent tissues (Δ values) was in an order of ΔIL-8>ΔIL-6>ΔIL-17A>ΔIL-1β>ΔCOX2>ΔIL-23; Analysis showed that the value of ΔCOX2 correlated to the grade of dysplastic degree in patients with adenoma. Notably, levels of all these immunological factors in CRC tissues were continuously increased, the order of values of Δ immunological factors was ΔIL-8>ΔCOX2>ΔIL-6>ΔIL-1β>ΔIL-17A>ΔIL-23>ΔTGFβ. Further analysis revealed that increased value of Δ IL-1β was associated with advanced TNM stage, a higher value of Δ COX2 tended to predicate a deeper degree of tumor invasion; and higher values of Δ IL-1β, IL-6 and COX2 closely correlated to lymph node metastasis in patients with CRC. In addition, the ratio of ΔIL-8/ΔTGFβ was most obvious changed factor and associated with node metastasis in patients with CRC. Therefore, we concluded that the difference of protumor immunological factor levels between the primary tumor site and tumor-free site along the adenoma-carcinoma sequence reflects the change of protumor/antitumor force balance, which is associated with CRC initiation and invasion.

Risk factors of lymph node metastasis in patients with T1b gallbladder cancer

BACKGROUND: Whether radical surgery or simple cholecystectomy should be performed on patients with stage T1b gallbladder cancer remains controversial. To explore the effect of lymph node metastasis on the prognosis of patients with stage T1b gallbladder cancer is very crucial for guiding the treatment and follow-up of T1b gallbladder cancer patients.METHODS: A retrospective analysis of the surveillance, epidemiology and end results (SEER) database was performed. Patients with stage T1b gallbladder cancer that underwent surgery and pathologic nodal staging were identified. Logistic regression and Cox regression were performed to identify independent predictors and prognostic factors, respectively.RESULTS: Of 427 patients (age: 69.1±13.2 years, 72.1% females), 31 (7.2%) had lymph node metastasis. In multivariable analysis, higher histology grade was independent risk factor associated with the diagnosis of the patient lymph node metastasis. In the entire cohort, lymph node metastasis indicated a worse overall survival (HR [95%CI]: 3.83 (1.54-9.47), P<0.01) and disease-specific survival (HR [95%CI]: 3.46(1.54-7.82), P<0.01) in multivariable analysis. Lymph node metastasis, in multivariable analysis, showed statistical difference for worse OS (HR [95%CI]: 4.04(1.20-13.65), P=0.02) and DSS (HR [95%CI]: 3.25(1.10-9.57), P=0.03) in moderately differentiation group.CONCLUSIONS: Higher histology grade was an independent risk factor for lymph node metastasis. Lymph node metastasis was an independent prognostic factor of worse OS and DSS. Lymph node metastasis showed statistical difference for worse OS and DSS in moderately and advanced differentiation groups, a finding that could guide the choice of surgery.

Diagnostic performance of FDG PET/MRI for cervical lymph node metastasis in patients with clinically N0 head and neck cancer.

Treatment management in cases of head and neck squamous cell cancer (HNSCC) that are clinically negative for lymph node metastases (cN0) is still an important topic of discussion. There is increasing interest in sensitive imaging modalities that can detect the risk of occult metastases at levels below 20%. This study aimed to examine the efficacy of integrated positron emission tomography (PET)/magnetic resonance imaging (MRI) in determining neck nodal metastasis status in cN0 patients with HNSCC. In this retrospective study, 44 patients who underwent neck dissection with the diagnosis of HNSCC between January 2018 and August 2020 were analyzed. Clinical examinations, including ultrasonography, were performed to identify cervical metastases in HNSCC patients with preoperative cN0. A nuclear medicine specialist visually evaluated the MRI, PET, and PET/MRI results. Histopathologically, 86.4% of patients were classified as N0. According to the histopathological results, MRI showed 50% sensitivity, 89.5% specificity, 91.8% negative predictive value (NPV), 42.8% positive predictive value (PPV) and 84% accuracy, while PET showed 83.3% sensitivity, 68.4% specificity, 96.2% NPV, 29.4% PPV and 70.4% accuracy. PET/MRI was more successful in distinguishing pathological N0 and N+ patients (83.3% sensitivity, 92.1% specificity, 97.2% NPV, 62.5% PPV and 90.9% accuracy). PET/MRI is more sensitive and has a higher NPV compared to MRI alone, while its sensitivity was found to be comparable to that of PET. In addition, with its ability to detect pathological N0 patients, PET/MRI may significantly decrease the number of unnecessary neck dissections.

AB013. SOH23ABS_148. Imaging-based approach to axillary lymph node staging in breast cancer: identification of axillary lymph node metastasis in patients with breast cancer using CT

AB013. SOH23ABS_148. Imaging-based approach to axillary lymph node staging in breast cancer: identification of axillary lymph node metastasis in patients with breast cancer using CT

Stratification of rate of lymph node metastasis according to risk factors and oncologic outcomes in patients who underwent radical resection for rectal neuroendocrine tumors.

Most predictive factors for lymph node metastasis in rectal neuroendocrine tumors (NETs) have been based on local and endoscopic resection. We aimed to evaluate the risk factors for lymph node metastasis in patients who underwent radical resection for rectal NETs and stratify the risk of lymph node metastasis. Sixty-four patients who underwent radical resection for rectal NETs between January 2001 and January 2018 were included. We investigated the risk factors of lymph node metastasis using clinicopathologic data. We also performed a risk stratification for lymph node metastases using the number of previously known risk factors. For oncologic outcomes, the 5-year overall survival and recurrence-free survival were evaluated in both groups. Among the patients who underwent radical surgery, 32 (50.0%) had lymph node metastasis and 32 (50.0%) had non-lymph node metastasis. In the multivariable analysis, only the male sex was identified as a risk factor for lymph node metastasis (odds ratio, 3.695; 95% confidence interval, 1.128-12.105; P=0.031). When there were 2 or more known risk factors, the lymph node metastasis rate was significantly higher than when there were one or no risk factors (odds ratio, 3.667; 95% confidence interval, 1.023-13.143; P=0.046). There was also no statistical difference between the 2 groups in 5-year overall survival (P=0.431) and 5-year recurrence-free survival (P=0.144). We found that the rate of lymph node metastasis increased significantly when the number of known risk factors is 2 or more.

Evaluation of the incidence of splenic hilar lymph node metastasis in patients operated on for esophagogastric junction cancer

Evaluation of the incidence of splenic hilar lymph node metastasis in patients operated on for esophagogastric junction cancer

99mTc-MAA accumulation within tumor in preoperative lung perfusion SPECT/CT associated with occult lymph node metastasis in patients with clinically N0 non-small cell lung cancer

Background99mTc-MAA accumulation within the tumor representing pulmonary arterial perfusion, which is variable and may have a clinical significance. We evaluated the prognostic significance of 99mTc-MAA distribution within the tumor in non-small cell lung cancer (NSCLC) patients in terms of detecting occult nodal metastasis and lymphovascular invasion, as well as predicting the recurrence-free survival (RFS).MethodsTwo hundred thirty-nine NSCLC patients with clinical N0 status who underwent preoperative lung perfusion SPECT/CT were retrospectively evaluated and classified according to the visual grading of 99mTc-MAA accumulation in the tumor. Visual grade was compared with the quantitative parameter, standardized tumor to lung ratio (TLR). The predictive value of 99mTc-MAA accumulation with occult nodal metastasis, lymphovascular invasion, and RFS was assessed.ResultsEighty-nine (37.2%) patients showed 99mTc-MAA accumulation and 150 (62.8%) patients showed the defect on 99mTc-MAA SPECT/CT. Among the accumulation group, 45 (50.5%) were classified as grade 1, 40 (44.9%) were grade 2, and 4 (4.5%) were grade 3. TLR gradually and significantly increased from grade 0 (0.009 ± 0.005) to grade 1 (0.021 ± 0.005, P < 0.05) and to grade 2–3 (0.033 ± 0.013, P < 0.05). The following factors were significant predictors for occult nodal metastasis in univariate analysis: central location, histology different from adenocarcinoma, tumor size greater than 3 cm representing clinical T2 or higher, and the absence of 99mTc-MAA accumulation within the tumor. Defect in the lung perfusion SPECT/CT remained significant at the multivariate analysis (Odd ratio 3.25, 95%CI [1.24 to 8.48], p = 0.016). With a median follow-up of 31.5 months, the RFS was significantly shorter in the defect group (p = 0.008). Univariate analysis revealed that cell type of non-adenocarcinoma, clinical stage II-III, pathologic stage II-III, age greater than 65 years, and the 99mTc-MAA defect within tumor as significant predictors for shorter RFS. However, only the pathologic stage remained statistically significant, in multivariate analysis.ConclusionThe absence of 99mTc-MAA accumulation within the tumor in preoperative lung perfusion SPECT/CT represents an independent risk factor for occult nodal metastasis and is relevant as a poor prognostic factor in clinically N0 NSCLC patients. 99mTc-MAA tumor distribution may serve as a new imaging biomarker reflecting tumor vasculatures and perfusion which can be associated with tumor biology and prognosis.

Identification and validation of the model consisting of DDX49, EGFR, and T-stage as a possible risk factor for lymph node metastasis in patients with lung cancer.

The lymph node metastasis stage of lung cancer is an important decisive factor in the need for postoperative adjuvant treatment and the difference between stage IIIa and stage IIIB that is the necessary information to distinguish whether surgery can be performed or not. The specificity of the clinical diagnosis of lung cancer with lymph node metastasis cannot meet the requirements of preoperative evaluation of surgical indications and prediction of surgical removal range in lung cancer. This was an early experimental laboratory trial. The model identification data included the RNA sequence data of 10 patients from our clinical data and 188 patients with lung cancer from The Cancer Genome Atlas dataset. The model development and validation data consisted of RNA sequence data for 537 cases from the Gene Expression Omnibus dataset. We explore the predictive value of the model on two independent clinical data. A higher specificity of diagnostic model for patients with lung cancer with lymph node metastases consisted of DDX49, EGFR, and tumor stage (T-stage), which were the independent predictive factors. The area under the curve value, specificity, and sensitivity for predicting lymph node metastases were 0.835, 70.4%, and 78.9% at RNA expression level in the training group, and 0.681, 73.2%, and 75.7% at RNA expression level in the validation group as shown as in result part. To verify the predictive performance of the combined model for lymph node metastases, we downloaded the GSE30219 data set (n = 291) and the GSE31210 data set (n = 246) from the Gene Expression Omnibus (GEO) database as the training group and validation group, respectively. In addition, the model had a higher specificity for predicting lymph node metastases in independent tissue samples. Determination of DDX49, EGFR, and T-stage could form a novel prediction model to improve the diagnostic efficacy of lymph node metastasis in clinical application.

Intra- and Peritumoral Radiomics of Contrast-Enhanced Mammography Predicts Axillary Lymph Node Metastasis in Patients With Breast Cancer: A Multicenter Study

This multicenter study aimed to explore the feasibility of radiomics based on intra- and peritumoral regions on preoperative breast cancer contrast-enhanced mammography (CEM) to predict axillary lymph node (ALN) metastasis. A total of 809 patients with preoperative breast cancer CEM images from two centers were retrospectively recruited. Least absolute shrinkage and selection operator (LASSO) regression was used to select radiomics features extracted from CEM images in regions of the tumor and peritumoral area of five and ten mm as well as construct radiomics signature. A nomogram, including the optimal radiomics signature and clinicopathological factors, was then constructed. Nomogram performance was evaluated using AUC and compared with breast radiologists directly. In the internal testing set, AUCs of peritumoral signatures decreased when the peritumoral area increased and signaturetumor+10mm demonstrated the best performance with an AUC of 0.712. The nomogram incorporating signaturetumor+10mm, tumor diameter, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), and CEM-reported lymph node status yielded maximum AUCs of 0.753 and 0.732 in internal and external testing sets, respectively. Moreover, the nomogram outperformed radiologists and improved diagnostic performance of radiologists. The nomogram based on CEM intra- and peritumoral regions may provide a noninvasive auxiliary tool to guide treatment strategy of ALN metastasis in breast cancer.

Incidence and predictive factors of retropharyngeal lymph node metastases in patients with oropharyngeal cancer undergoing multimodality treatment planning imaging.

We investigated the incidence and predictive factors of retropharyngeal lymph node (RPLN) metastases in patients with oropharyngeal cancer (OPC) undergoing multimodality treatment planning imaging before radiotherapy. Consecutive patients with OPC treated with curative-intent radiotherapy from 2017 to 2019 were retrospectively analyzed. Treatment planning comprised contrast-enhanced computed tomography (CT), magnetic resonance imaging (MRI), and fluorodeoxyglucose-positron emission tomography (FDG-PET) unless contraindicated. Of 300 patients, 66 (22%) had radiological evidence of RPLN involvement on planning images, compared to 17 (6%) on diagnostic CT alone. On multivariate analysis, RPLN involvement was statistically (p < 0.05) associated with tonsil, soft palate, and posterior pharyngeal wall primaries, and with disease extension to the soft palate or vallecula. Multimodality treatment planning imaging reveals a high rate of RPLN metastases from OPC compared to diagnostic CT alone. Patients with tonsil, soft palate, or posterior pharyngeal wall primaries or disease extending to the soft palate or vallecula appear at higher risk.

A novel potential inflammation-nutrition biomarker for predicting lymph node metastasis in clinically node-negative colon cancer.

The purpose of this study is to investigate the predictive significance of (platelet × albumin)/lymphocyte ratio (PALR) for lymph node metastasis (LNM) in patients with clinically node-negative colon cancer (cN0 CC). Data from 800 patients with primary CC who underwent radical surgery between March 2016 and June 2021 were reviewed. The non-linear relationship between PALR and the risk of LNM was explored using a restricted cubic spline (RCS) function while a receiver operating characteristic (ROC) curve was developed to determine the predictive value of PALR. Patients were categorized into high- and low-PALR cohorts according to the optimum cut-off values derived from Youden's index. Univariate and multivariate logistic regression analyses were used to identify the independent indicators of LNM. Sensitivity analysis was performed to repeat the main analyses with the quartile of PALR. A total of eligible 269 patients with primary cN0 CC were retrospectively selected. The value of the area under the ROC curve for PALR for predicting LNM was 0.607. RCS visualized the uptrend linear relationship between PALR and the risk of LNM (p-value for non-linearity > 0.05). PALR (odds ratio = 2.118, 95% confidence interval, 1.182-3.786, p = 0.011) was identified as an independent predictor of LNM in patients with cN0 CC. A nomogram incorporating PALR and other independent predictors was constructed with an internally validated concordance index of 0.637. The results of calibration plots and decision curve analysis supported a good performance ability and the sensitivity analysis further confirmed the robustness of our findings. PALR has promising clinical applications for predicting LNM in patients with cN0 CC.

DDIT4 Facilitates Lymph Node Metastasis via the Activation of NF-κB Pathway and Epithelial-Mesenchymal Transition.

This study was aimed to identify a novel metastasis-promoting molecule and elucidate its functional and prognostic roles in cervical cancer. DDIT4 (DNA-damage-inducible transcript 4), a hypoxia-inducible gene, was identified by analyzing multiple microarray databases. The correlation between DDIT4 expression in immunohistochemistry and clinicopathological characteristics in the public database and our cohort was evaluated by statistical analysis. Transwell® assay and wound-healing assay to determine cell migration and invasion were performed. DDIT4 was knocked down using siRNA or lentiviral vectors. The potential downstream pathways of DDIT4 were explored and verified by a gene set enrichment analysis and western blotting. The in vivo metastatic capability was determined with the use of an intraperitoneal injection mouse model. Inthe analysis ofthe public database and our cohort, DDIT4 high expression was significantly related to short overall survival and lymph node metastasis in patients with early-stage cervical cancer. The knockdown of DDIT4 attenuated the migration and invasion activity of tumor cells in vitro and reduced the expression of epithelial-mesenchymal transition (EMT)-related proteins and the NF-κB pathway in cervical cancer cells. DDIT4 also promoted tumor progression in the mouse model. Our results indicate that DDIT4 can be a prognostic indicator in cervical cancer and promote lymph node metastasis, augmenting malignancy via the EMT and NF-kB pathways.

Risk factors of lymph node metastasis in patients with T1 stage colorectal cancer-a retrospective cohort study based on the Surveillance, Epidemiology, and End Results database.

Patients with T1 stage early colorectal cancer (CRC) can be treated with radical surgery or endoscopic surgery. Endoscopic surgery has a number of advantages, including minimal trauma and a rapid recovery. However, it cannot remove regional lymph nodes to assess whether there is lymph node metastasis. Thus, the analysis of the risk factors of lymph node metastasis in patients with T1 stage CRC is of great significance in the selection of appropriate treatment methods. Although previous studies have explored the risk factors for lymph node metastasis in T1 stage CRC patients, the number of cases were relatively insufficient, and further exploration is necessary. A total of 2,085 patients who had been pathologically diagnosed with CRC from 2015 to 2017 from the Surveillance, Epidemiology, and End Results (SEER) database. Among the patients, 324 had lymph node metastasis. A multivariate logistic regression analysis was conducted to analyze the risk factors of lymph node metastasis in patients with T1 stage CRC. Next, we established a prediction model to predict lymph node metastasis in patients with T1 stage CRC. The results of the multivariate logistic regression analysis showed that age at diagnosis, rectosigmoid cancer, poorly differentiated or undifferentiated tumor cells, and distant metastasis were independent factors of lymph node metastasis in patients with T1 stage CRC (P<0.05). This study used the R4.0.3 statistical software for the statistical analysis. The data set was randomly divided into a training set and verification set. The training set comprised 1,460 patients, and the verification set comprised 625 patients. The area under the receiver operating characteristic curve (AUC) of the training set was 0.675 [95% confidence interval (CI): 0.635-0.714], and the AUC of the verification set was 0.682 (95% CI: 0.617-0.747). In the validation set, the model was tested by the Hosmer-Lemeshow Goodness-of-Fit Test (χ2=4.018, P=0.855), and the results showed that the model was reliable at predicting lymph node metastasis in patients with T1 stage CRC. For CRC patients with high risk factors of lymph node metastasis, endoscopic physicians should carefully evaluate the advantages and disadvantages of the endoscopic surgery before deciding whether to perform this surgery.

Fibrinogen-to-Lymphocyte Ratio Was an Independent Predictor of Lymph Node Metastasis in Patients with Clinically Node-Negative Advanced-Stage Gastric Cancer.

Various hematological indicators have been reported to predict lymph node metastasis (LNM) in gastric cancer (GC) patients, but the relationship between FLR and LNM has not been studied. Therefore, the aim of this study was to evaluate the role of preoperative fibrinogen-to-lymphocyte ratio (FLR) in predicting LNM in patients with clinically node-negative (cN0) advanced gastric cancer (AGC). We retrospectively reviewed 571 eligible patients with primary AGC adenocarcinoma who underwent radical gastrectomy (discoverycohort). Patients were divided into high and low FLR groups according to the optimal cutoff value determined by Youden index. FLR is an independent predictor of LNM determined by logistic regression and validated in the validation cohort of 207 patients. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive value of FLR for LNM. The nonlinear relationship between FLR and LNM risk was assessed using restricted cubic spline. Sensitivity analyses were performed according to FLR quartiles to further assess the robustness of the results. The nomogram was built based on FLR and clinicopathological characteristics, and was evaluated by calibration curves, ROC curve analysis and decision curve analysis. In the discoverycohort, the area under the curve (AUC) value for FLR to predict LNM was 0.592. There is a linear relationship between the FLR value and the risk of LNM, and the risk of LNM increased with FLR value. High FLR level is an independent risk factor for LNM, and the results of sensitivity analysis robust this finding. The nomogram for individual risk assessment performed well. Furthermore, we verified the FLR was an independent predictor of LNM in the validation cohort. FLR was an independent predictor of LNM in patients with cN0 AGC.

Predictors of nodal metastases in early stage HER2+ breast cancer: Deciding on treatment approach with neoadjuvant chemotherapy vs. upfront surgery

BackgroundThe purpose of this study is to evaluate preoperative predictors of nodal metastases in patients with early-stage, HER2-positive (HER2+) breast cancer. MethodsThe SEER Database was queried to identify women with a first diagnosis of stage I-II (T1-T2) HER2-positive breast cancer treated with upfront surgery in 2018. Multivariable logistic regression was used to identify clinical characteristics independently associated with nodal involvement. ResultsOverall, 3333 women with stage I-II HER2+ breast cancer met inclusion criteria and were included in the study. The median age at diagnosis was 59 years (IQR, 51–69 years). Most patients underwent breast-conserving surgery (60.9%), with a median of 3 (IQR 2–4) axillary lymph nodes removed. On final pathology, 762 (22.9%) of T1-T2 HER2+ patients were node positive; 2.7% pN0[i+], 3.7% pN1mi, 15.1% pN1, and 1.4% pN2. Women less than 40 years and those between 40 and 49 years showed the highest proportion of axillary lymph node metastasis, in 33.7% and 30.7% respectively, and declining with age (p < 0.001). Patients with triple-positive breast cancer had the highest rates of nodal involvement (24.8%), compared to 20.7% ER+/PR-/HER2+ and 19.6% of HER2-enriched patients (p = 0.006). On adjusted analysis, age, biologic subtype, tumour size, and type of surgery remained independent predictors of nodal involvement. On subgroup analysis, women under age 50 with T1c HER2-enriched or triple-positive breast cancer had a 33% and 35% incidence of nodal involvement, which declined with age. ConclusionsThe likelihood of pathologic nodal involvement in early-stage HER2+ breast cancer is contingent on age, ER/PR status, and tumour size.

Clinical value of 18F-FDG PET/CT to predict MYCN gene, chromosome 1p36 and 11q status in pediatric neuroblastoma and ganglioneuroblastoma.

To explore the value of 18F-2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET)/computed tomography(CT) in MYCN gene and chromosome 1p36 and 11 statuses in newly diagnosed pediatric NB(neuroblastoma) and GNB(ganglioneuroblastoma). We retrospectively analyzed newly diagnosed patients with 48 NB and 12 with GNB in our hospital. The data obtained from the clinical medical records included age, sex, pathologic type, and laboratory parameters such as lactate dehydrogenase (LDH), neuron-specific enolase (NSE) and the status of MYCN gene and chromosome 1p36 and 11q. The bone conditions were also obtained in the examination of bone marrow biopsy. Primary tumors were manually segmented to measure the maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), tumor volume(MTV) and total lesion glycolysis(TLG) and the maximal length of the lesion in the axial image(LEGmax). The differences in bone marrow involvement and lymph node metastases in patients with chromosome 11q deletions were statistically significant (all p < 0.05). Chromosome 11q deletion was an independent factor affecting bone marrow involvement (OR=17.796, p=0.011). The levels of NSE, LDH, LEGmax and SUVmax, SUVmean, MTV, TLG all predicted MYCN gene amplification (all p < 0.05). The levels of LDH, LEGmax and MTV, TLG all predicted deletions in chromosomes 1p36 (all p < 0.05), while NSE, SUVmax and SUVmean did not (all p > 005). The LDH levels, LEGmax, MTV and TLG can effectively predict the status of the MYCN oncogene and chromosome 1p36 in pediatric neuroblastoma and ganglioneuroblastoma. Those patients with chromosome 11q deletions are more likely to develop bone marrow involvement and lymph node metastases, showing a worse progression-free survival.

Using machine learning to predict lymph node metastasis in patients with renal cell carcinoma: A population-based study.

Lymph node (LN) metastasis is strongly associated with distant metastasis of renal cell carcinoma (RCC) and indicates an adverse prognosis. Accurate LN-status prediction is essential for individualized treatment of patients with RCC and to help physicians make appropriate surgical decisions. Thus, a prediction model to assess the hazard index of LN metastasis in patients with RCC is needed. Partial data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Data of 492 individuals with RCC, collected from the Southwest Hospital in Chongqing, China, were used for external validation. Eight indicators of risk of LN metastasis were screened out. Six machine learning (ML) classifiers were established and tuned, focused on predicting LN metastasis in patients with RCC. The models were integrated with big data analytics and ML algorithms. Based on the optimal model, we developed an online risk calculator and plotted overall survival using Kaplan-Meier analysis. The extreme gradient-boosting (XGB) model was superior to the other models in both internal and external trials. The area under the curve, accuracy, sensitivity, and specificity were 0.930, 0.857, 0.856, and 0.873, respectively, in the internal test and 0.958, 0.935, 0.769, and 0.944, respectively, in the external test. These parameters show that XGB has an excellent ability for clinical application. The survival analysis showed that patients with predicted N1 tumors had significantly shorter survival (p < 0.0001). Our study shows that integrating ML algorithms and clinical data can effectively predict LN metastasis in patients with confirmed RCC. Subsequently, a freely available online calculator (https://xinglinyi.shinyapps.io/20221004-app/) was built, based on the XGB model.