scholarly journals Consolidation Tumor Ratio Combined With Pathological Features Could Predict Status of Lymph Nodes of Early-Stage Lung Adenocarcinoma

2022 ◽  
Vol 11 ◽  
Author(s):  
Liang Zhao ◽  
Guangyu Bai ◽  
Ying Ji ◽  
Yue Peng ◽  
Ruochuan Zang ◽  
...  

IntroductionStage IA lung adenocarcinoma manifested as part-solid nodules (PSNs), has attracted immense attention owing to its unique characteristics and the definition of its invasiveness remains unclear. We sought to develop a nomogram for predicting the status of lymph nodes of this kind of nodules.MethodsA total of 2,504 patients between September 2018 to October 2020 with part-solid nodules in our center were reviewed. Their histopathological features were extracted from paraffin sections, whereas frozen sections were reviewed to confirm the consistency of frozen sections and paraffin sections. Univariate and multivariate logistic regression analyses and Akaike information criterion (AIC) variable selection were performed to assess the risk factors of lymph node metastasis and construct the nomogram. The nomogram was subjected to bootstrap internal validation and external validation. The concordance index (C-index) was applied to evaluate the predictive accuracy and discriminative ability.ResultsWe enrolled 215 and 161 eligible patients in the training cohort and validation cohort, respectively. The sensitivity between frozen and paraffin sections on the presence of micropapillary/solid subtype was 78.4%. Multivariable analysis demonstrated that MVI, the presence of micropapillary/solid subtype, and CTR >0.61 were independently associated with lymph node metastasis (p < 0.01). Five risk factors were integrated into the nomogram. The nomogram demonstrated good accuracy in estimating the risk of lymph node metastasis, with a C-index of 0.945 (95% CI: 0.916–0.974) in the training cohort and a C-index of 0.975 (95% CI: 0.954–0.995) in the validation cohort. The model’s calibration was excellent in both cohorts.ConclusionThe nomogram established showed excellent discrimination and calibration and could predict the status of lymph nodes for patients with ≤3 cm PSNs. Also, this prediction model has the prediction potential before the end of surgery.

2021 ◽  
Author(s):  
Xiaoxiao Wang ◽  
Cong Li ◽  
Mengjie Fang ◽  
Liwen Zhang ◽  
Lianzhen Zhong ◽  
...  

Abstract Background:This study aimed to evaluate the value of radiomic nomogram in predicting lymph node metastasis in T1-2 gastric cancer according to the No. 3 station lymph nodes.Methods:A total of 159 T1-2 gastric cancer (GC) patients who had undergone surgery with lymphadenectomy between March 2012 and November 2017 were retrospectively collected and divided into a primary cohort (n = 80) and a validation cohort (n = 79). Radiomic features were extracted from both tumor region and No. 3 station lymph nodes (LN) based on computed tomography (CT) images per patient. Then, key features were selected using minimum redundancy maximum relevance algorithm and fed into two radiomic signatures, respectively. Meanwhile, the predictive performance of clinical risk factors was studied. Finally, a nomogram was built by merging radiomic signatures and clinical risk factors and evaluated by the area under the receiver operator characteristic curve (AUC) as well as decision curve.Results: Two radiomic signatures, reflecting phenotypes of the tumor and LN respectively, were significantly associated with LN metastasis. A nomogram incorporating two radiomic signatures and CT-reported LN metastasis status showed good discrimination of LN metastasis in both the primary cohort (AUC: 0.915; 95% confidence interval [CI]: 0.832-0.998) and validation cohort (AUC: 0.908; 95%CI: 0.814-1.000). The decision curve also indicated its potential clinical usefulness.Conclusions:The nomogram received favorable predictive accuracy in predicting No.3 station LN metastasis in T1-2 GC, and could assist the choice of therapy.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaoxiao Wang ◽  
Cong Li ◽  
Mengjie Fang ◽  
Liwen Zhang ◽  
Lianzhen Zhong ◽  
...  

Abstract Background This study aimed to develope and validate a radiomics nomogram by integrating the quantitative radiomics characteristics of No.3 lymph nodes (LNs) and primary tumors to better predict preoperative lymph node metastasis (LNM) in T1-2 gastric cancer (GC) patients. Methods A total of 159 T1-2 GC patients who had undergone surgery with lymphadenectomy between March 2012 and November 2017 were retrospectively collected and divided into a training cohort (n = 80) and a testing cohort (n = 79). Radiomic features were extracted from both tumor region and No. 3 station LNs based on computed tomography (CT) images per patient. Then, key features were selected using minimum redundancy maximum relevance algorithm and fed into two radiomic signatures, respectively. Meanwhile, the predictive performance of clinical risk factors was studied. Finally, a nomogram was built by merging radiomic signatures and clinical risk factors and evaluated by the area under the receiver operator characteristic curve (AUC) as well as decision curve. Results Two radiomic signatures, reflecting phenotypes of the tumor and LNs respectively, were significantly associated with LN metastasis. A nomogram incorporating two radiomic signatures and CT-reported LN metastasis status showed good discrimination of LN metastasis in both the training cohort (AUC 0.915; 95% confidence interval [CI] 0.832–0.998) and testing cohort (AUC 0.908; 95% CI 0.814–1.000). The decision curve also indicated its potential clinical usefulness. Conclusions The nomogram received favorable predictive accuracy in predicting No.3 LNM in T1-2 GC, and the nomogram showed positive role in predicting LNM in No.4 LNs. The nomogram may be used to predict LNM in T1-2 GC and could assist the choice of therapy.


2021 ◽  
Vol 11 ◽  
Author(s):  
Qi Li ◽  
Xiao-qun He ◽  
Xiao Fan ◽  
Chao-nan Zhu ◽  
Jun-wei Lv ◽  
...  

BackgroundBased on the “seed and soil” theory proposed by previous studies, we aimed to develop and validate a combined model of machine learning for predicting lymph node metastasis (LNM) in patients with peripheral lung adenocarcinoma (PLADC).MethodsRadiomics models were developed in a primary cohort of 390 patients (training cohort) with pathologically confirmed PLADC from January 2016 to August 2018. The patients were divided into the LNM (−) and LNM (+) groups. Thereafter, the patients were subdivided according to TNM stages N0, N1, N2, and N3. Radiomic features from unenhanced computed tomography (CT) were extracted. Radiomic signatures of the primary tumor (R1) and adjacent pleura (R2) were built as predictors of LNM. CT morphological features and clinical characteristics were compared between both groups. A combined model incorporating R1, R2, and CT morphological features, and clinical risk factors was developed by multivariate analysis. The combined model’s performance was assessed by receiver operating characteristic (ROC) curve. An internal validation cohort containing 166 consecutive patients from September 2018 to November 2019 was also assessed.ResultsThirty-one radiomic features of R1 and R2 were significant predictors of LNM (all P < 0.05). Sex, smoking history, tumor size, density, air bronchogram, spiculation, lobulation, necrosis, pleural effusion, and pleural involvement also differed significantly between the groups (all P < 0.05). R1, R2, tumor size, and spiculation in the combined model were independent risk factors for predicting LNM in patients with PLADC, with area under the ROC curves (AUCs) of 0.897 and 0.883 in the training and validation cohorts, respectively. The combined model identified N0, N1, N2, and N3, with AUCs ranging from 0.691–0.927 in the training cohort and 0.700–0.951 in the validation cohort, respectively, thereby indicating good performance.ConclusionCT phenotypes of the primary tumor and adjacent pleura were significantly associated with LNM. A combined model incorporating radiomic signatures, CT morphological features, and clinical risk factors can assess LNM of patients with PLADC accurately and non-invasively.


2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e18005-e18005
Author(s):  
Ping Jiang ◽  
Jing Cai ◽  
Xiaoqi He ◽  
Hongbo Wang ◽  
Weihong Dong ◽  
...  

e18005 Background: Evaluation the distribution of nodal metastases in the stage IB1 cervical cancer and the risk factors associated with pelvic lymph node metastasis (LNM) at each anatomic location. Methods: 728 patients with stage IB1 cervical cancer who underwent radical hysterectomies and systemic pelvic lymphadenectomies from January 2008 to December 2017 were retrospectively studied. All removed pelvic lymph nodes were pathologically examined, and the risk factors for LNM at the obturator, internal iliac, external iliac, and common iliac regions were evaluated by univariate and multivariate logistic regression analyses. Results: 20,134 lymph nodes were analysed with the average number of 27.80 (± SD 9.43) lymph nodes per patient. Nodal metastases were present in 266 (14.6%) patients. The obturator was the most common site for nodal metastasis (42.5%) followed by the internal iliac nodes (20.3%) and the external iliac nodes (19.9%), while the common iliac (9.8%) and parametrial (7.5%) nodes were the least likely to be involved. Tumor size more than 2 cm, histologically proven lymphovascular space involvement (LVSI) and parametrial invasion correlated independently significantly with the higher risk of the lymphatic metastasis. Obesity (BMI≥25) was independently significantly negatively correlated with the risk of lymphatic metastases. All the positive common iliac nodes were found in patients with tumors greater than 2 cm. The multivariate analysis showed that tumor size greater than 3 cm was associated with a 16.6-fold increase in the risk for common iliac LNM. Interestingly, tumor size was not an independent risk factor for pelvic LNM in the lower regions, i.e., the obturator, internal iliac and external iliac areas, where LVSI was the most significant predictor for LNM. In addition, parametrial invasion was related to external and internal iliac LNM; deep stromal invasion and age less than 50 years were associated with obturator LNM. Conclusions: The incidence of lymph node metastasis in patients with stage IB1 cervical cancer is low but prognostically relevant. The data offer the opportunity for tailored individual treatment in selected patients with small tumors and obesity.


2021 ◽  
Vol 11 ◽  
Author(s):  
Xingyu Liu ◽  
Xiaoyuan Liang ◽  
Lingxiang Ruan ◽  
Sheng Yan

ObjectivesThe aim of the current study was to develop and validate a nomogram based on CT radiomics features and clinical variables for predicting lymph node metastasis (LNM) in gallbladder cancer (GBC).MethodsA total of 353 GBC patients from two hospitals were enrolled in this study. A Radscore was developed using least absolute shrinkage and selection operator (LASSO) logistic model based on the radiomics features extracted from the portal venous-phase computed tomography (CT). Four prediction models were constructed based on the training cohort and were validated using internal and external validation cohorts. The most effective model was then selected to build a nomogram.ResultsThe clinical-radiomics nomogram, which comprised Radscore and three clinical variables, showed the best diagnostic efficiency in the training cohort (AUC = 0.851), internal validation cohort (AUC = 0.819), and external validation cohort (AUC = 0.824). Calibration curves showed good discrimination ability of the nomogram using the validation cohorts. Decision curve analysis (DCA) showed that the nomogram had a high clinical utility.ConclusionThe findings showed that the clinical-radiomics nomogram based on radiomics features and clinical parameters is a promising tool for preoperative prediction of LN status in patients with GBC.


2020 ◽  
Author(s):  
Hyun-Keun Kwon ◽  
Yong-Il Cheon ◽  
Sung-Chan Shin ◽  
Eui-Suk Sung ◽  
Jin-Choon Lee ◽  
...  

Abstract Background: Metastatic lymph nodes are occasionally found in the suprasternal lymph nodes in patients with papillary thyroid cancer (PTC), but there are few studies on these lymph nodes. Therefore, we investigated the frequency and risk factors of suprasternal lymph node metastasis in PTC patients with lateral cervical lymph node metastasis.Methods: A total of 85 patients with cN1b PTC underwent total thyroidectomy with elective lateral neck dissection including the suprasternal lymph nodes. We analyzed the correlation between suprasternal lymph node metastasis and sex, age, tumor characteristics, and cervical lymph node metastasis status.Results: Eleven patients (12.9%) had pathological suprasternal lymph node metastasis. Suprasternal lymph node metastasis was associated with tumors located in the inferior pole and level IV lymph node metastasis.Conclusion: In cN1b PTC patients, especially those with inferior pole tumors and level IV nodal metastasis, the suprasternal lymph node should be routinely dissected.


2020 ◽  
Author(s):  
Jun Du ◽  
Yangchao Shen ◽  
Wenwu Yan ◽  
Jinguo Wang

Abstract Background It remains controversial whether splenic hilum lymph nodes (SHLNs) should be excised in radical gastrectomy with D2 lymph node dissection. In this study, we evaluated the role of clinicopathological features in patients with gastric cancer in predicting splenic hilum lymph nodes metastasis.Methods We searched the Medline, Embase, PubMed and Web of Science databases from inception to May 2020 and consulted related references. 15 articles with a total of 4377 patients were included finally. The odds ratios (ORs) of each risk factor and the corresponding 95% confidence interval (CI) were determined using Revman 5.3 software. Results Meta-analysis showed that tumor size greater than 5 cm (p < 0.01), tumor localization in the greater curvature (p < 0.01), diffuse type (Lauren’s type) (p < 0.01), Borrman type 3–4 (p < 0.01), poor differentiation and undifferentiation (p < 0.01), depth of invasion T3–T4 (p < 0.01), number of lymph node metastases N2–N3 (p < 0.01), distance metastasis M1 (p < 0.01), TNM stage 3–4 (p < 0.01), vascular invasion (p = 0.01), and lymphatic invasion (p < 0.01) were risk factors of SHLNs metastasis. Moreover, No. 1-, 2-, 3-, 4sa-, 4sb-, 4d-, 6-, 7-, 9-, 11-, and 16-positive lymph node metastasis are strongly associated with splenic hilum lymph nodes metastasis.Conclusions Tumor size, tumor location, Lauren’s type, Borrman type, degree of differentiation, T stage, N stage, M stage, TNM stage, vascular invasion, lymphatic infiltration, and other positive lymph nodes metastasis were risk factors for SHLNs.


2021 ◽  
Vol 11 ◽  
Author(s):  
Qi Qi ◽  
Pan Xu ◽  
Cheng Zhang ◽  
Suping Guo ◽  
Xingzhi Huang ◽  
...  

BackgroundThis work explores the clinical significance of Delphian lymph nodes (DLN) in thyroid papillary carcinoma (PTC). At the same time, a nomogram is constructed based on clinical, pathological, and ultrasonic (US) features to evaluate the possibility of DLN metastasis (DLNM) in PTC patients. This is the first study to predict DLNM using US characteristics.MethodsA total of 485 patients, surgically diagnosed with PTC between February 2017 and June 2021, all of whom underwent thyroidectomy, were included in the study. Using the clinical, pathological, and US information of patients, the related factors of DLNM were retrospectively analyzed. The risk factors associated with DLNM were identified through univariate and multivariate analyses. According to clinical + pathology, clinical + US, and clinical + US + pathology, the predictive nomogram for DLNM was established and validated.ResultsOf the 485 patients with DLN, 98 (20.2%) exhibited DLNM. The DLNM positive group had higher positive rates of central lymph node metastasis (CLNM), lateral lymph node metastasis (LLNM), and T3b–T4b thyroid tumors than the negative rates. The number of CLNM and LLNM lymph nodes in the DLNM+ group was higher as compared to that in the DLNM- group. Multivariate analysis demonstrated that the common independent risk factors of the three prediction models were male, bilaterality, and located in the isthmus. Age ≥45 years, located in the lower pole, and nodural goiter were protective factors. In addition, the independent risk factors were classified as follows: (I) P-extrathyroidal extension (ETE) and CLNM based on clinical + pathological characteristics; (II) US-ETE and US-CLNM based on clinical + US characteristics; and (III) US-ETE and CLNM based on clinical +US + pathological features. Better diagnostic efficacy was reported with clinical + pathology + US diagnostic model than that of clinical + pathology diagnostic model (AUC 0.872 vs. 0.821, p = 0.039). However, there was no significant difference between clinical + pathology + US diagnostic model and clinical + US diagnostic model (AUC 0.872 vs. 0.821, p = 0.724).ConclusionsThis study found that DLNM may be a sign that PTC is more invasive and has extensive lymph node metastasis. By exploring the clinical, pathology, and US characteristics of PTC progression to DLNM, three prediction nomograms, established according to different combinations of features, can be used in different situations to evaluate the transfer risk of DLN.


2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Xiao-Yi Yin ◽  
Tao Pang ◽  
Yu Liu ◽  
Hang-Tian Cui ◽  
Tian-Hang Luo ◽  
...  

Abstract Background The status of lymph nodes in early gastric cancer is critical to make further clinical treatment decision, but the prediction of lymph node metastasis remains difficult before operation. This study aimed to develop a nomogram that contained preoperative factors to predict lymph node metastasis in early gastric cancer patients. Methods This study analyzed the clinicopathologic features of 823 early gastric cancer patients who underwent gastrectomy retrospectively, among which 596 patients were recruited in the training cohort and 227 patients in the independent validation cohort. Significant risk factors in univariate analysis were further identified to be independent variables in multivariable logistic regression analysis, which were then incorporated in and presented with a nomogram. And internal and external validation curves were plotted to evaluate the discrimination of the nomogram. Results Totally, six independent predictors, including the tumor size, macroscopic features, histology differentiation, P53, carbohydrate antigen 19-9, and computed tomography-reported lymph node status, were enrolled in the nomogram. Both the internal validation in the training cohort and the external validation in the validation cohort showed the nomogram had good discriminations, with a C-index of 0.82 (95%CI, 0.78 to 0.86) and 0.77 (95%CI, 0.60 to 0.94) respectively. Conclusions Our study developed a new nomogram which contained the most common and significant preoperative risk factors for lymph node metastasis in patients with early gastric cancer. The nomogram can identify early gastric cancer patients with the high probability of lymph node metastasis and help clinicians make more appropriate decisions in clinical practice.


2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yu Min ◽  
Xiaoyuan Wei ◽  
Hang Chen ◽  
Ke Xiang ◽  
Guobing Yin ◽  
...  

Background. Pure mucinous breast cancer (PMBC) has a better prognosis than other types of invasive breast cancer. However, regional lymph node metastasis (LNM) might reverse this outcome. We aim to determine the independent predictive factors for regional LNM and further develop a nomogram model for clinical practice. Method. Data of PMBC patients from the Surveillance, Epidemiology, and End Results (SEER) program between Jan 2010 and Dec 2015 were retrospectively reviewed. Univariate and multivariate logistic regression analyses were used to determine the risk factors for LNM in T1-2 MBC. The nomogram was constructed and further evaluated by an internal validation cohort. The receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves were performed to evaluate the accuracy of this model. Result. Five variables, including age, race, tumor size, grade, and breast subtype, were identified to be significantly associated with regional LNM in female patients with T1-2 PMBC. A nomogram was successfully established with a favorable concordance index (C-index) of 0.780, supported by an internal validation cohort with a C-index of 0.767. Conclusion. A nomogram for predicting regional LNM in female patients with T1-2 PMBC was successfully established and validated via an internal cohort. This visualized model would assist surgeons to make appropriate clinical decisions in the management of primary PMBC, especially in terms of whether axillary lymph node dissection (ALND) is warranted.


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