Lymph node metastasis according to primary tumor location in T1 and T2 stage non-small cell lung cancer patients.
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ABSTRACT:
SUBMITTER: Xiong J
PROVIDER: S-EPMC4846618 | biostudies-other | 2016 Apr
REPOSITORIES: biostudies-other
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Project description:Guidelines have differed in their opinion regarding the indications for endoscopic resection of gastric-neuroendocrine neoplasms (g-NENs) and duodenal-NENs (d-NENs). We examined the association between size and lymph node metastasis (LNM) to identify candidates most suitable for endoscopic resection. We identified 706 patients with T1/T2 g-NENs and 621 patients with T1/T2 d-NENs from the SEER database. The prevalence of LNM and risk factors associated with LNM were analyzed. LNM was present in 8.1% of patients with gastroduodenal neuroendocrine tumors (NETs) and 31.6% of patients with neuroendocrine carcinomas (NECs). Multivariate logistic regression indicated that tumor size >10mm, greater invasion depth, and poor differentiation were independently associated with LNM. In addition, the percentage of g-NETs invading submucosa with LNM increased with tumor size (≤10 mm,3.9%;11-20 mm,8.6%;>20 mm,16.1%). However, in contrast to the low LNM risk in patients with small g-NETs (≤10 mm), we found that LNM rate exceeded 5% even for patients with small submucosal-infiltrating d-NETs. Among patients with nodal-negative g-NETs, the cause specific survival (CSS) was similar for those who received surgical resection and endoscopic resection. Among patients with d-NETs, the CSS was better for those who received endoscopic resection. In conclusion, patients with d-NETs had a higher probability of LNM than those with g-NETs. Endoscopic resection can be utilized for curative treatment of submucosa-infiltrating g-NETs and intramucosal d-NETs when the size is 10 mm or less. These results reinforce the need to search for LNM in lesions that are larger than 10 mm.
| S-EPMC8194267 | biostudies-literature
Project description:If we can more accurately predict the likelihood of regional lymph node metastasis (LNM) for endoscopically resected T1-stage colorectal cancers (CRC), the number of unnecessary additional surgeries can be reduced. We aimed of identify miRNA markers that can predict LNM-positive tumors among T1-stage CRCs and we also developed a miRNA classifier set for facilitating the accuracy and applicability.
2015-09-30 | GSE70574 | GEO
Project description:BackgroundLymph node (LN) status is vital to evaluate the curative potential of relatively early gastric cancer (GC; T1-T2) treatment (endoscopic or surgery). Currently, there is a lack of robust and convenient methods to identify LN metastasis before therapeutic decision-making.MethodsGenome-wide expression profiles of long noncoding RNA (lncRNA) in primary T1 gastric cancer data from The Cancer Genome Atlas (TCGA) was used to identify lncRNA expression signature capable of detecting LN metastasis of GC and establish a 10-lncRNA risk-prediction model based on deep learning. The performance of the lncRNA panel in diagnosing LN metastasis was evaluated both in silico and clinical validation methods. In silico validation was conducted using TCGA and Asian Cancer Research Group (ACRG) datasets. Clinical validation was performed on T1 and T2 patients, and the panel's efficacy was compared with that of traditional tumor markers and computed tomography (CT) scans.ResultsProfiling of genome-wide RNA expression identified a panel of lncRNA to predict LN metastasis in T1 stage gastric cancer (AUC = 0.961). A 10-lncRNA risk-prediction model was then constructed, which was validated successfully in T1 and T2 datasets (TCGA, AUC = 0.852; ACRG, AUC = 0.834). Thereafter, the clinical performance of the lncRNA panel was validated in clinical cohorts (T1, AUC = 0.812; T2, AUC = 0.805; T1 + T2, AUC = 0.764). Notably, the panel demonstrated significantly better performance compared with CT and traditional tumor markers.ConclusionsThe novel 10-lncRNA could diagnose LN metastasis robustly in relatively early gastric cancer (T1-T2), with promising clinical potential.
| S-EPMC10640531 | biostudies-literature
Project description:BackgroundThe subcategory “solid component of tumor” is a new criterion of tumor categories in the updated eighth edition of the TNM classification. Nevertheless, the predictors of lymph node metastasis among patients with clinical T1 adenocarcinoma, based on the TNM classification 8th edition, remain unclear. This study aimed to identify the preoperative predictors of lymph node metastasis in clinical T1 adenocarcinoma by comparing clinicopathological characteristics between the groups with and without lymph node metastasis.MethodsWe performed a retrospective observational single-center study at the Sendai Kousei Hospital. From January 2012 to September 2019, we included 515 patients who underwent curative lobectomy or segmentectomy and mediastinal lymph node dissection among those with clinical T1 adenocarcinoma according to the UICC-TNM staging 8th edition. They were divided into two groups: those with lymph node metastasis (positive group) and those without (negative group). The clinicopathological factors were retrospectively analyzed and compared between the groups.ResultsIn univariate analysis, carcinoembryonic antigen (>5.0 ng/mL) (P=0.0007), maximum standardized uptake (>3.5) (P<0.0001), clinical T factor (T1c) (P<0.0001), and consolidation tumor ratio (>0.85) (P<0.0001) were significant predictors of lymph node metastasis. Multivariate analysis revealed that maximum standardized uptake SUVmax (>3.5) (odds ratio =10.4, P<0.0001) was independently associated with lymph node metastasis. In univariate analysis, carcinoembryonic antigen (>5.0) (P=0.048) was the only predictor of lymph node metastasis among patients of cT1b, while no parameters were identified as significant predictors among patients of cT1c.ConclusionsSUVmax and CEA are useful preoperative predictors of lymph node metastases in patients with clinical T1 adenocarcinoma, stratified to T1b and T1c, based on the 8th TNM classification.
| S-EPMC7330315 | biostudies-literature
Project description:PURPOSE:Although some studies have reported differences in clinicopathological features between left- and right-sided advanced colorectal cancer (CRC), there are few reports regarding early-stage disease. In this study, we aimed to compare the clinicopathological features of left- and right-sided T1 CRC. METHODS:Subjects were 1142 cases with T1 CRC undergoing surgical or endoscopic resection between 2001 and 2018 at Showa University Northern Yokohama Hospital. Of these, 776 cases were left-sided (descending colon to rectum) and 366 cases were right-sided (cecum to transverse colon). We compared clinical (patients age, sex, tumor size, morphology, initial treatment) and pathological features (invasion depth, histological grade, lymphatic invasion, vascular invasion, tumor budding) including lymph node metastasis (LNM). RESULTS:Left-sided T1 CRC showed significantly higher rates of LNM (left-sided 12.0% vs. right-sided 5.4%, P <?0.05) and lymphatic invasion (left-sided 32.7% vs. right-sided 23.2%, P <?0.05). Especially, the sigmoid colon and rectum showed higher rates of LNM (12.4% and 12.1%, respectively) than other locations. Patients with left-sided T1 CRC were younger than those with right-sided T1 CRC (64.9 years ±11.5 years vs. 68.7?±?11.6 years, P <?0.05), as well as significantly lower rates of poorly differentiated carcinoma/mucinous carcinoma than right-sided T1 CRC (11.6% vs. 16.1%, P <?0.05). CONCLUSION:Left-sided T1 CRC, especially in the sigmoid colon and rectum, exhibited higher rates of LNM than right-sided T1 CRC, followed by higher rates of lymphatic invasion. These results suggest that tumor location should be considered in decisions regarding additional surgery after endoscopic resection. TRIAL REGISTRATION:This study was registered with the University Hospital Medical Network Clinical Trials Registry ( UMIN 000032733 ).
| S-EPMC7508741 | biostudies-literature
Project description:Oral cavity squamous cell carcinoma (OSCC) affects more than 30 000 individuals in the United States annually, with smoking and alcohol consumption being the main risk factors. Management of early-stage tumors usually includes surgical resection followed by postoperative radiotherapy in certain cases. The cervical lymph nodes (LNs) are the most common site for local metastasis, and elective neck dissection is usually performed if the primary tumor thickness is greater than 3.5 mm. However, postoperative histological examination often reveals that many patients with early-stage disease are negative for neck nodal metastasis, posing a pressing need for improved risk stratification to either avoid overtreatment or prevent the disease progression. To this end, we aimed to identify a primary tumor gene signature that can accurately predict cervical LN metastasis in patients with early-stage OSCC. Using gene expression profiles from 189 samples, we trained K-top scoring pairs models and identified six gene pairs that can distinguish primary tumors with nodal metastasis from those without metastasis. The signature was further validated on an independent cohort of 35 patients using real-time polymerase chain reaction (PCR) in which it achieved an area under the receiver operating characteristic (ROC) curve and accuracy of 90% and 91%, respectively. These results indicate that such signature holds promise as a quick and cost effective method for detecting patients at high risk of developing cervical LN metastasis, and may be potentially used to guide the neck treatment regimen in early-stage OSCC.
| S-EPMC8760163 | biostudies-literature
Project description:BackgroundThe occurrence of cervical lymph node metastasis in T1 stage papillary thyroid carcinoma (PTC) is frequently observed. Notably, lateral lymph node metastasis (LLNM) emerges as a critical risk factor adversely affecting prognostic outcomes in PTC. The primary aim of this investigation was to delineate the risk factors associated with LLNM in the initial stages of PTC.MethodsThis retrospective analysis encompassed 3,332 patients diagnosed with T1 stage PTC without evident LLNM at the time of diagnosis. These individuals underwent primary surgical intervention at West China Hospital, Sichuan University between June 2017 and February 2023. The cohort was divided into two groups: patients manifesting LLNM and those without metastasis at the time of surgery. Additionally, T1 stage PTC patients were subdivided into T1a and T1b categories. Factors influencing LLNM were scrutinized through both univariate and multivariate analyses.ResultsThe incidence of LLNM was observed in 6.2% of the cohort (206 out of 3,332 patients). Univariate analysis revealed significant correlations between LLNM and male gender (P<0.001), tumor localization in the upper lobe (P<0.001), maximal volume of the primary tumor (P<0.001), largest tumor diameter (P<0.001), multifocality (P<0.001), and bilaterality (P<0.001), with the exception of age (P=0.788) and duration of active surveillance (AS) (P=0.978). Multivariate logistic regression analysis identified male gender (P<0.001), upper lobe tumor location (P<0.001), maximal primary tumor volume (P<0.001), and multifocality (P<0.001) as independent predictors of LLNM. However, age categories (≤55, >55 years), maximum tumor diameter, bilaterality, and surveillance duration did not exhibit a significant impact. Comparative analyses between T1a and T1b subgroups showed congruent univariate results but revealed differences in multivariate outcomes. In the T1a subgroup, gender, tumor location, and multifocality (all P<0.05) were associated with elevated LLNM risk. Conversely, in the T1b subgroup, tumor location, dimensions, and multifocality (all P<0.05) were significant predictors of LLNM risk, whereas gender (P=0.097) exerted a marginal influence.ConclusionsThe investigation highlights several key risk factors for LLNM in T1 stage PTC patients, including gender, upper lobe tumor location, larger tumor size, and multifocality. Conversely, prolonged AS and younger age did not significantly elevate LLNM risk, suggesting the viability of AS as a strategic option in selected cases.
| S-EPMC11002491 | biostudies-literature
Project description:ObjectivesTo develop and validate the imbalanced data correction based PET/CT radiomics model for predicting lymph node metastasis (LNM) in clinical stage T1 lung adenocarcinoma (LUAD).MethodsA total of 183 patients (148/35 non-metastasis/LNM) with pathologically confirmed LUAD were retrospectively included. The cohorts were divided into training vs. validation cohort in a ratio of 7:3. A total of 487 radiomics features were extracted from PET and CT components separately for radiomics model construction. Four clinical features and seven PET/CT radiological features were extracted for traditional model construction. To balance the distribution of majority (non-metastasis) class and minority (LNM) class, the imbalance-adjustment strategies using ten data re-sampling methods were adopted. Three multivariate models (denoted as Traditional, Radiomics, and Combined) were constructed using multivariable logistic regression analysis, where the combined model incorporated all of the significant clinical, radiological, and radiomics features. One hundred times repeated Monte Carlo cross-validation was used to assess the application order of feature selection and imbalance-adjustment strategies in the machine learning pipeline. Prediction performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC) and Geometric mean score (G-mean).ResultsA total of 2 clinical parameters, 2 radiological features, 3 PET, and 5 CT radiomics features were significantly associated with LNM. The combined model with Edited Nearest Neighbors (ENN) re-sampling methods showed strong prediction performance than traditional model or radiomics model with the AUC of 0.94 (95%CI = 0.86-0.97) vs. 0.89 (95%CI = 0.79-0.93), 0.92 (95%CI = 0.85-0.97), and G-mean of 0.88 vs. 0.82, 0.80 in the training cohort, and the AUC of 0.75 (95%CI = 0.57-0.91) vs. 0.68 (95%CI = 0.36-0.83), 0.71 (95%CI = 0.48-0.83) and G-mean of 0.76 vs. 0.64, 0.51 in the validation cohort. The combination of performing feature selection before data re-sampling obtains a better result than the reverse combination (AUC 0.76 ± 0.06 vs. 0.70 ± 0.07, p<0.001).ConclusionsThe combined model (consisting of age, histological type, C/T ratio, MATV, and radiomics signature) integrated with ENN re-sampling methods had strong lymph node metastasis prediction performance for imbalance cohorts in clinical stage T1 LUAD. Radiomics signatures extracted from PET/CT images could provide complementary prediction information compared with traditional model.
| S-EPMC8831550 | biostudies-literature
Project description:BackgroundLymph node metastasis is more likely in early-stage breast cancer with lower tumor-infiltrating lymphocyte (TIL) density. Therefore, we investigated the correlation between TILs and lymph node metastasis in cT1 breast cancer patients undergoing surgery and the usefulness of TILs in predicting sentinel lymph node metastasis (SLNM) in cT1N0M0 breast cancer.MethodsWe investigated 332 breast cancer patients who underwent surgery as the first-line treatment after preoperative diagnosis of cT1. A positive diagnosis of SLNM as an indication for axillary clearance was defined as macrometastasis in the sentinel lymph node (SLN) (macrometastasis: tumor diameter > 2 mm). Semi-quantitative evaluation of lymphocytes infiltrating the peritumoral stroma as TILs in primary tumor biopsy specimens prior to treatment was conducted.ResultsFor SLN biopsy (SLNB), a median of 2 (range, 1-8) SLNs were pathologically evaluated. Sixty cases (19.4%) of SLNM (macrometastasis: 46, micrometastasis: 16) were observed. Metastasis was significantly greater in breast cancers with tumor diameter > 10 mm than in those with diameter ≤ 10 mm (p = 0.016). Metastasis was significantly associated with lymphatic invasion (p < 0.001). These two clinicopathological factors correlated with SLNM even in patients diagnosed with cN0 (tumor size; p = 0.017, lymphatic invasion; p = 0.002). Multivariate analysis for SLNM predictors revealed lymphatic invasion (p = 0.008, odds ratio [OR] = 2.522) and TILs (p < 0.001, OR = 0.137) as independent factors.ConclusionsOur results suggest a correlation between lymph node metastasis and tumor immune-microenvironment in cT1 breast cancer. TIL density may be a predictor of SLNM in breast cancer without lymph node metastasis on preoperative imaging.
| S-EPMC7318528 | biostudies-literature
Project description:PurposesTo evaluate retropharyngeal lymph node metastasis on N stage of nasopharyngeal carcinoma (NPC).MethodsNPC patients were extracted from the Surveillance, Epidemiology, and End Results database between 2004 and 2016. Pathologically confirmed patients with complete data of retropharyngeal lymph node metastasis were investigated. The included patients were divided into N1a and N1b groups. Overall survival (OS) and cancer-specific survival (CSS) were assessed using the Kaplan-Meier method and propensity score matching (PSM) analyses.ResultsThis retrospective cohort study examined 759 patients: 70 who were stage N1a and 689 who were stage N1b. Before PSM, N1a group was associated with similar 5-year OS (77.7% vs. 72.4%; P = 0.15) and CSS (85.6% vs. 79.9%; P = 0.09) compared to N1b group. After PSM, a similar OS (75.0% vs. 60.7%; P = 0.12) was found between the radiotherapy and chemoradiotherapy groups. However, N1a group showed a better 5-year CSS (83.8% vs. 71.1%; P = 0.04) compared to N1b group. Stage N1b was an independent risk prognostic factor for CSS (hazard ratio = 2.54, 95% confidence interval: 1.02-6.34; P = 0.04).ConclusionsOS was not different between N1a and N1b groups. Retropharyngeal lymph node metastasis defined as stage N1 of the 8th edition American Joint Committee on Cancer staging system is reasonable.
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