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Wang ZM, Ning ZL, Ma C, Liu TB, Tao B, Guo L. Low expression of lysosome-related genes KCNE1, NPC2, and SFTPD promote cancer cell proliferation and tumor associated M2 macrophage polarization in lung adenocarcinoma. Heliyon 2024; 10:e27575. [PMID: 38509982 PMCID: PMC10950582 DOI: 10.1016/j.heliyon.2024.e27575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 03/01/2024] [Accepted: 03/01/2024] [Indexed: 03/22/2024] Open
Abstract
Background Recent research has shown that lysosomes play a critical role in the onset and progression of malignancy by regulating tumor cell death through several mechanisms. Nevertheless, the involvement of lysosome-associated genes (LSAGs) in lung adenocarcinoma (LUAD) is still not well understood. Methods LSAGs were identified in malignant lung epithelial cells, as well as biologically and functionally annotated by the comprehensive integration of single-cell and bulk RNA-sequencing data. Prognostic characterization of LSAGs was established, of which the accuracy and reliability were assessed by one-way Cox and LASSO regression. Correlations between LSAG properties and immune cell infiltration, chemotherapy, and immunotherapy were analyzed by integrated omics data. Finally, we characterized the expression of three LSAGs (KCNE1, NPC2, and SFTPD) in malignant lung epithelium and assessed their impact on tumor malignancy related phenotypes. Results We identified 18 LSAGs associated with prognosis, of which 3 LSAGs were used to construct prognostic models. High-risk patients had worse survival and the model predicted it better than other clinical indicators. Based on the functional enrichment analyses, LSAGs were associated with binding and molecular activity functions, inhibition of DNA damage repair and tumor growth, IL7 signaling pathway, and glycolysis. M0 macrophages and M1 macrophages were substantially enriched in high-risk patients. Conversely, there was a considerable enrichment of resting dendritic cells and M2 macrophages in patients at low risk. We also found that risk scores predicted the outcome of immunotherapy. In vitro, we found that KCNE1, NPC2, and SFTPD were lowly expressed in malignant epithelial cells and patients with low expression of KCNE1, NPC2, and SFTPD had a higher percentage of M2 macrophage infiltration. Overexpression of KCNE1, NPC2, and SFTPD suppressed the proliferation and invasion of malignant cells, and M0 macrophages remarkably reduced M2 macrophage polarization and cellular secretion of pro-tumor cytokines. Conclusions We used three LASGs-KCNE1, NPC2, and SFTPD-to develop and validate a predictive signature for LUAD patients. Furthermore, we found that low expression of KCNE1, NPC2, and SFTPD promotes lung cancer cell proliferation and invasion and M2 macrophage polarization. Our study may provide fresh perspectives for customized immunotherapy.
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Affiliation(s)
- Zi-Ming Wang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200443, China
| | - Zhi-Lin Ning
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Chao Ma
- Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450052, Henan, China
| | - Tang-Bin Liu
- Department of Thoracic surgery, Anhui Chest Hospital, Hefei 230061, Anhui, China
| | - Bo Tao
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200443, China
| | - Liang Guo
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200443, China
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Sayan M, Celik A, Kankoc A, Akarsu I, Aslan MT, Kurtoglu A, Ahmedova G, Tastepe AI. Is tumor diameter a risk factor for occult N1 metastasis in patients with peripheral non-small cell lung cancer which is smaller than 3 cm? Updates Surg 2023; 75:2335-2342. [PMID: 37382803 DOI: 10.1007/s13304-023-01575-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 06/22/2023] [Indexed: 06/30/2023]
Abstract
The optimum treatment option is surgery for clinical early stage non-small cell lung cancer. Despite all non-invasive and invasive staging effort, occult lymph-node metastasis can be detected in pathological staging. Here, we investigated whether there was any correlation between tumor diameter and occult lymph-node metastasis in N1 stations. Data of patient with non-small cell lung cancer clinical stage 1A were reviewed retrospectively. Those with tumor diameter smaller than 3 cm and pN0-pN1 in pathological staging were included in the study. Overall survival (OS) was calculated by Kaplan-Meier and survival differences between pN0 and pN1 groups were investigated by Log-Rank methods. Cut-off value of tumor diameter for lymph-node metastasis was investigated by Receiver-Operating Characteristics test. Significance between pN0-pN1 and other categorical groups was investigated with Pearson Chi-square or Fisher's exact tests. A total of 257 patients meet to criteria included in the study. Fifty-five (21.4%) of the patients were females. The mean age was 62.7 ± 8.5 and median tumor diameter was 20 mm (Range: 2-30 mm). We detected occult lymph-node metastasis at the N1 stations (pN1) in 33 patients (12.8%) in histopathological examination of resected specimens and lymph-node dissection materials. The cut-off value of tumor diameter was calculated as 21.5 mm for occult lymph-node metastasis by Receiver-Operating Characteristics analysis (Area Under Curved: 70.1%, p = 0.004). There was a significant correlation between pN1 positivity and high tumor diameter (p = 0.02). However, we did not find a correlation between the lymph-node metastasis and age, gender, tumor histopathology, tumor localization, and visceral pleural invasion. Tumor diameter may be an indicator for occult lymph-node metastasis in patients with clinical stage-1A non-small cell lung cancer. This result should be considered in patient with mass which larger than 21.5 mm and planned stereotactic body radiotherapy instead of surgery.
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Affiliation(s)
- Muhammet Sayan
- Department of Thoracic Surgery, Gazi University, 06560, Ankara, Turkey.
| | - Ali Celik
- Department of Thoracic Surgery, Gazi University, 06560, Ankara, Turkey
| | - Aykut Kankoc
- Department of Thoracic Surgery, Gazi University, 06560, Ankara, Turkey
| | - Irmak Akarsu
- Department of Thoracic Surgery, Gazi University, 06560, Ankara, Turkey
| | | | - Aysegul Kurtoglu
- Department of Thoracic Surgery, Gazi University, 06560, Ankara, Turkey
| | - Gunel Ahmedova
- Department of Thoracic Surgery, Gazi University, 06560, Ankara, Turkey
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Zeng C, Zhang W, Liu M, Liu J, Zheng Q, Li J, Wang Z, Sun G. Efficacy of radiomics model based on the concept of gross tumor volume and clinical target volume in predicting occult lymph node metastasis in non-small cell lung cancer. Front Oncol 2023; 13:1096364. [PMID: 37293586 PMCID: PMC10246750 DOI: 10.3389/fonc.2023.1096364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Accepted: 05/09/2023] [Indexed: 06/10/2023] Open
Abstract
Objective This study aimed to establish a predictive model for occult lymph node metastasis (LNM) in patients with clinical stage I-A non-small cell lung cancer (NSCLC) based on contrast-enhanced CT. Methods A total of 598 patients with stage I-IIA NSCLC from different hospitals were randomized into the training and validation group. The "Radiomics" tool kit of AccuContour software was employed to extract the radiomics features of GTV and CTV from chest-enhanced CT arterial phase pictures. Then, the least absolute shrinkage and selection operator (LASSO) regression analysis was applied to reduce the number of variables and develop GTV, CTV, and GTV+CTV models for predicting occult lymph node metastasis (LNM). Results Eight optimal radiomics features related to occult LNM were finally identified. The receiver operating characteristic (ROC) curves of the three models showed good predictive effects. The area under the curve (AUC) value of GTV, CTV, and GTV+CTV model in the training group was 0.845, 0.843, and 0.869, respectively. Similarly, the corresponding AUC values in the validation group were 0.821, 0.812, and 0.906. The combined GTV+CTV model exhibited a better predictive performance in the training and validation group by the Delong test (p<0.05). Moreover, the decision curve showed that the combined GTV+CTV predictive model was superior to the GTV or CTV model. Conclusion The radiomics prediction models based on GTV and CTV can predict occult LNM in patients with clinical stage I-IIA NSCLC preoperatively, and the combined GTV+CTV model is the optimal strategy for clinical application.
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Affiliation(s)
- Chao Zeng
- Hebei Key Laboratory of Medical-industrial Integration Precision Medicine, Clinical Medicine College, Affiliated Hospital, North China University of Science and Technology, Tangshan, Hebei, China
| | - Wei Zhang
- Department of Radiotherapy, Yantai Yuhuangding Hospital, The Affiliated Hospital of Qingdao University, Yantai, Shandong, China
| | - Meiyue Liu
- Hebei Key Laboratory of Medical-industrial Integration Precision Medicine, Clinical Medicine College, Affiliated Hospital, North China University of Science and Technology, Tangshan, Hebei, China
| | - Jianping Liu
- Department of Chemoradiation, Tangshan People’s Hospital, Tangshan, Hebei, China
| | - Qiangxin Zheng
- Hebei Key Laboratory of Medical-industrial Integration Precision Medicine, Clinical Medicine College, Affiliated Hospital, North China University of Science and Technology, Tangshan, Hebei, China
| | - Jianing Li
- Hebei Key Laboratory of Medical-industrial Integration Precision Medicine, Clinical Medicine College, Affiliated Hospital, North China University of Science and Technology, Tangshan, Hebei, China
| | - Zhiwu Wang
- Department of Chemoradiation, Tangshan People’s Hospital, Tangshan, Hebei, China
| | - Guogui Sun
- Hebei Key Laboratory of Medical-industrial Integration Precision Medicine, Clinical Medicine College, Affiliated Hospital, North China University of Science and Technology, Tangshan, Hebei, China
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Kawamoto N, Tsutani Y, Kamigaichi A, Ohsawa M, Mimae T, Miyata Y, Okada M. Tumour location predicts occult N1 nodal metastasis in clinical stage I non-small-cell lung cancer. EUROPEAN JOURNAL OF CARDIO-THORACIC SURGERY : OFFICIAL JOURNAL OF THE EUROPEAN ASSOCIATION FOR CARDIO-THORACIC SURGERY 2023; 63:6960926. [PMID: 36571485 DOI: 10.1093/ejcts/ezac575] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 12/06/2022] [Accepted: 12/25/2022] [Indexed: 12/27/2022]
Abstract
OBJECTIVES Pathological lymph node metastases are often observed in patients with clinical N0 lung cancer. Identifying preoperative predictors of occult hilar nodal metastasis (OHNM) is important in determining the surgical procedure in patients with clinical stage I non-small-cell lung cancer. This study aimed to determine the frequency and predictors of OHNM by tumour location in these patients. METHODS Between April 2007 and May 2019, data of patients who underwent lobectomy or segmentectomy for clinical stage I pure-solid non-small-cell lung cancer were retrospectively reviewed. The ratio of the distance from the pulmonary hilum to the proximal side of the tumour to the distance from the pulmonary hilum to the visceral pleural surface through the centre of the tumour, named 'distance ratio (DR)', was calculated. The relationship of the DR with clinicopathological findings and prognosis was discussed. RESULTS A total of 357 patients were enrolled. OHNM frequency was 14.6%. Patients were divided into 2 groups based on whether the DR was ≤0.67 (central type) or >0.67 (peripheral type). The frequency of OHNM was significantly higher in the DR ≤0.67 group (21.5% vs 7.4%; P < 0.001). Multivariable analysis revealed that DR was the only independent preoperative predictor of OHNM (odds ratio, 3.63; 95% confidence interval, 1.83-7.18; P < 0.001). CONCLUSIONS The frequency of OHNM was significantly lower in peripheral-type lung cancer; therefore, tumour location was the most important preoperative predictor of OHNM.
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Affiliation(s)
- Nobutaka Kawamoto
- Department of Surgical Oncology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan
| | - Yasuhiro Tsutani
- Department of Surgical Oncology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan
| | - Atsushi Kamigaichi
- Department of Surgical Oncology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan
| | - Manato Ohsawa
- Department of Surgical Oncology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan
| | - Takahiro Mimae
- Department of Surgical Oncology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan
| | - Yoshihiro Miyata
- Department of Surgical Oncology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan
| | - Morihito Okada
- Department of Surgical Oncology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan
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Hu D, Li S, Zhang H, Wu N, Lu X. Using Natural Language Processing and Machine Learning to Preoperatively Predict Lymph Node Metastasis for Non-Small Cell Lung Cancer With Electronic Medical Records: Development and Validation Study. JMIR Med Inform 2022; 10:e35475. [PMID: 35468085 PMCID: PMC9086872 DOI: 10.2196/35475] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 03/31/2022] [Accepted: 04/11/2022] [Indexed: 11/21/2022] Open
Abstract
Background Lymph node metastasis (LNM) is critical for treatment decision making of patients with resectable non–small cell lung cancer, but it is difficult to precisely diagnose preoperatively. Electronic medical records (EMRs) contain a large volume of valuable information about LNM, but some key information is recorded in free text, which hinders its secondary use. Objective This study aims to develop LNM prediction models based on EMRs using natural language processing (NLP) and machine learning algorithms. Methods We developed a multiturn question answering NLP model to extract features about the primary tumor and lymph nodes from computed tomography (CT) reports. We then combined these features with other structured clinical characteristics to develop LNM prediction models using machine learning algorithms. We conducted extensive experiments to explore the effectiveness of the predictive models and compared them with size criteria based on CT image findings (the maximum short axis diameter of lymph node >10 mm was regarded as a metastatic node) and clinician’s evaluation. Since the NLP model may extract features with mistakes, we also calculated the concordance correlation between the predicted probabilities of models using NLP-extracted features and gold standard features to explore the influence of NLP-driven automatic extraction. Results Experimental results show that the random forest models achieved the best performances with 0.792 area under the receiver operating characteristic curve (AUC) value and 0.456 average precision (AP) value for pN2 LNM prediction and 0.768 AUC value and 0.524 AP value for pN1&N2 LNM prediction. And all machine learning models outperformed the size criteria and clinician’s evaluation. The concordance correlation between the random forest models using NLP-extracted features and gold standard features is 0.950 and improved to 0.984 when the top 5 important NLP-extracted features were replaced with gold standard features. Conclusions The LNM models developed can achieve competitive performance using only limited EMR data such as CT reports and tumor markers in comparison with the clinician’s evaluation. The multiturn question answering NLP model can extract features effectively to support the development of LNM prediction models, which may facilitate the clinical application of predictive models.
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Affiliation(s)
- Danqing Hu
- College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China
| | - Shaolei Li
- Department of Thoracic Surgery II, Peking University Cancer Hospital and Institute, Beijing, China
| | - Huanyao Zhang
- College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China
| | - Nan Wu
- Department of Thoracic Surgery II, Peking University Cancer Hospital and Institute, Beijing, China
| | - Xudong Lu
- College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China
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Mandatory Nodal Evaluation During Resection of Clinical T1a Non-Small-Cell Lung Cancers. Ann Thorac Surg 2021; 113:1583-1590. [PMID: 34358520 DOI: 10.1016/j.athoracsur.2021.06.078] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 05/31/2021] [Accepted: 06/28/2021] [Indexed: 11/27/2022]
Abstract
BACKGROUND Recommendations for intraoperative lymph node evaluation are uniform regardless of whether a primary tumor is clinical T1a or T2a according to TNM 8th edition for Stage I Non-Small-Cell lung cancers (NSCLC). We quantified nodal disease risk in patients with T1a disease (≤1cm). METHODS The National Cancer Database was queried for clinical T1aN0M0 primary NSCLCs ≤1cm undergoing lobectomy with mediastinal nodal evaluation from 2004-2014. Nodal disease risk was analyzed as a function of demographics and tumor characteristics. RESULTS Among 2,157 cases, 6.7% had occult nodal disease: 5.1% occult N1 and 1.6% N2. Adenocarcinoma (7.5%), large cell carcinoma (25%), and poor differentiation (11.8%) or undifferentiated/anaplastic (25.0%) had high rates of combined pN1 and N2 disease (p<0.001). In univariable analysis, odds of pathologic N1, N2, or N1/N2 nodal disease with respect to N0 was greatest for large cell carcinoma (ref. adenocarcinoma Odds Ratio (OR): 4.31, 3.62, 4.12 respectively; all p<0.05), and anaplastic grade (OR: 10.71, 13.09, 11.55). Bronchoalveolar adenocarcinomas had the lowest odds (OR 0.41, 0.11, 0.32) and squamous cell carcinoma had lower odds for N2 (OR 0.29, all p<0.05). In multivariable analysisonly bronchoalveolar adenocarcinomas had lower odds of pathologic N2 and N1/N2 disease with respect to N0. Worsening grade remained significant for pathologic N1 and N1/N2 disease (both p<0.05). CONCLUSIONS A significant rate (6.7%) of occult nodal disease is present in primary NSCLCs ≤1cm. Risk increases with certain histology and worsening grade. We recommend mandatory systematic hilar and mediastinal nodal evaluation for T1a NSCLC tumors for accurate staging and adjuvant therapy.
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Integrative nomogram of intratumoral, peritumoral, and lymph node radiomic features for prediction of lymph node metastasis in cT1N0M0 lung adenocarcinomas. Sci Rep 2021; 11:10829. [PMID: 34031529 PMCID: PMC8144194 DOI: 10.1038/s41598-021-90367-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 04/21/2021] [Indexed: 12/23/2022] Open
Abstract
Radiomics studies to predict lymph node (LN) metastasis has only focused on either primary tumor or LN alone. However, combining radiomics features from multiple sources may reflect multiple characteristic of the lesion thereby increasing the discriminative performance of the radiomic model. Therefore, the present study intends to evaluate the efficiency of integrative nomogram, created by combining clinical parameters and radiomics features extracted from gross tumor volume (GTV), peritumoral volume (PTV) and LN, for the preoperative prediction of LN metastasis in clinical cT1N0M0 adenocarcinoma. A primary cohort of 163 patients (training cohort, 113; and internal validation cohort, 50) and an external validation cohort of 53 patients with clinical stage cT1N0M0 were retrospectively included. Features were extracted from three regions of interests (ROIs): GTV; PTV (5.0 mm around the tumor) and LN on pre-operative contrast enhanced computed tomography (CT). LASSO logistic regression method was used to build radiomic signatures. Multivariable regression analysis was used to build a nomogram. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. The discriminative performance of nomogram was validated both internally and externally. The radiomic signatures using the features of GTV, PTV and LN showed a good ability in predicting LN metastasis with an area under the curve (AUC) of 0.74 (95% CI 0.60–0.88), 0.72 (95% CI 0.57–0.87) and 0.64 (95% CI 0.48–0.80) respectively in external validation cohort. The integration of different signature together further increases the discriminatory ability: GTV + PTV (GPTV): AUC 0.75 (95% CI 0.61–0.89) and GPTV + LN: AUC 0.76 (95% CI 0.61–0.91) in external validation cohort. An integrative nomogram of clinical parameters and radiomic features demonstrated further increase in discriminatory ability with AUC of 0.79 (95% CI 0.66–0.93) in external validation cohort. The nomogram showed good calibration. Decision curve analysis demonstrated that the radiomic nomogram was clinically useful. The integration of information from clinical parameters along with CT radiomics information from GTV, PTV and LN was feasible and increases the predictive performance of the nomogram in predicting LN status in cT1N0M0 adenocarcinoma patients suggesting merit of information integration from multiple sources in building prediction model.
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Sato M, Yang SM, Tian D, Jun N, Lee JM. Managing screening-detected subsolid nodules-the Asian perspective. Transl Lung Cancer Res 2021; 10:2323-2334. [PMID: 34164280 PMCID: PMC8182721 DOI: 10.21037/tlcr-20-243] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The broad application of low-dose computed tomography (CT) screening has resulted in the detection of many small pulmonary nodules. In Asia, a large number of these detected nodules with a radiological ground glass pattern are reported as lung adenocarcinomas or premalignant lesions, especially among female non-smokers. In this review article, we discuss controversial issues and conditions involving these subsolid pulmonary nodules that we often face in Asia, including a lack or insufficiency of current guidelines; the roles of preoperative biopsy and imaging; the location of lesions; appropriate selection of localization techniques; the roles of dissection and sampling of frozen sections and lymph nodes; multifocal lesions; and the roles of non-surgical treatment modalities. For these complex issues, we have tried to present up-to-date evidence and our own opinions regarding the management of subsolid nodules. It is our hope that this article helps surgeons and physicians to manage the complex issues involving ground glass nodules (GGNs) in a balanced manner in their daily practice and provokes further discussion towards better guidelines and/or algorithms.
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Affiliation(s)
- Masaaki Sato
- Department of Thoracic Surgery, University of Tokyo Hospital, Tokyo, Japan
| | - Shun-Mao Yang
- Department of Thoracic Surgery, University of Tokyo Hospital, Tokyo, Japan.,Department of Thoracic Surgery, National Taiwan University Hospital, Hsin-Chu Branch, Hsinchu
| | - Dong Tian
- Department of Thoracic Surgery, University of Tokyo Hospital, Tokyo, Japan.,Department of Thoracic Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.,Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Nakajima Jun
- Department of Thoracic Surgery, University of Tokyo Hospital, Tokyo, Japan
| | - Jang-Ming Lee
- Department of Thoracic Surgery, National Taiwan University Hospital, Taipei
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Yamamichi T, Kakihana M, Nitta Y, Hamanaka W, Kajiwara N, Ohira T, Ikeda N. F-18 fluorodeoxyglucose uptake in lymph nodes and sonographic features on endobronchial ultrasonography predict lymph node metastasis in lung cancer patients. J Thorac Dis 2020; 12:5420-5429. [PMID: 33209375 PMCID: PMC7656352 DOI: 10.21037/jtd-20-1888] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Background Sonographic findings of lymph nodes on endobronchial ultrasonography (EBUS) images have been reported to be useful to predict lymph node metastasis (LNM) in lung cancer patients. F-18 fluorodeoxyglucose (FDG) uptake in lymph nodes was also found to be useful. In this study, we aimed to clarify whether a combination of sonographic features and maximum standardized uptake values of lymph nodes (LN-SUVmax) is useful for predicting LNM in lung cancer patients. Methods From January 2014 to December 2019, a total of 147 lymph nodes from 104 patients with lung cancer, who underwent preoperative EBUS and FDG-positron emission tomography (PET)/computed tomography (CT) followed by surgery were retrospectively assesses. The characteristics of the patients, LN-SUVmax, and sonographic findings of lymph nodes were reviewed. Predictive factors associated with LNM were identified using the logistic regression model. Results The average size of the lymph nodes was 8.55 (range, 3–22) mm and the average LN-SUVmax was 5.36 (range, 1.79–31.19). The prevalence of nodal metastasis was 26/147 (17.4%), including 22 in mediastinal lymph nodes and 4 in hilar lymph nodes. Multivariate analysis demonstrated four independent predictive factors for LNM; size, round or oval shape, absence of a central hilar structure, and LN-SUVmax. The optimal cutoff value for lymph node size and LN-SUVmax were 10 mm and 6.00, respectively. By combinating of the two modalities, we obtained the results with sensitivity of 76.9%, specificity of 95.1% and accuracy of 93.2%. Conclusions A combination of sonographic findings and LN-SUVmax showed a higher diagnostic rate of LNM than either modality alone in lung cancer patients.
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Affiliation(s)
| | | | - Yasuyuki Nitta
- Department of Surgery, Tokyo Medical University, Tokyo, Japan
| | - Wakako Hamanaka
- Department of Surgery, Tokyo Medical University, Tokyo, Japan
| | | | - Tatsuo Ohira
- Department of Surgery, Tokyo Medical University, Tokyo, Japan
| | - Norihiko Ikeda
- Department of Surgery, Tokyo Medical University, Tokyo, Japan
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Wu Y, Han C, Wang Z, Gong L, Liu J, Chong Y, Liu X, Liang N, Li S. An Externally-Validated Dynamic Nomogram Based on Clinicopathological Characteristics for Evaluating the Risk of Lymph Node Metastasis in Small-Size Non-small Cell Lung Cancer. Front Oncol 2020; 10:1322. [PMID: 32850420 PMCID: PMC7426394 DOI: 10.3389/fonc.2020.01322] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 06/25/2020] [Indexed: 12/25/2022] Open
Abstract
Background: Lymph node metastasis (LNM) status is of key importance for the decision-making on treatment and survival prediction. There is no reliable method to precisely evaluate the risk of LNM in NSCLC patients. This study aims to develop and validate a dynamic nomogram to evaluate the risk of LNM in small-size NSCLC. Methods: The NSCLC ≤ 2 cm patients who underwent initial pulmonary surgery were retrospectively reviewed and randomly divided into a training cohort and a validation cohort as a ratio of 7:3. The training cohort was used for the least absolute shrinkage and selection operator (LASSO) regression to select optimal variables. Based on variables selected, the logistic regression models were developed, and were compared by areas under the receiver operating characteristic curve (AUCs) and decision curve analysis (DCA). The optimal model was used to plot a dynamic nomogram for calculating the risk of LNM and was internally and externally well-validated by calibration curves. Results: LNM was observed in 12.0% (83/774) of the training cohort and 10.1% (33/328) of the validation cohort (P = 0.743). The optimal model was used to plot a nomogram with six variables incorporated, including tumor size, carcinoembryonic antigen, imaging density, pathological type (adenocarcinoma or non-adenocarcinoma), lymphovascular invasion, and pleural invasion. The nomogram model showed excellent discrimination (AUC = 0.895 vs. 0.931) and great calibration in both the training and validation cohorts. At the threshold probability of 0–0.8, our nomogram adds more net benefits than the treat-none and treat-all lines in the decision curve. Conclusions: This study firstly developed a cost-efficient dynamic nomogram to precisely and expediently evaluate the risk of LNM in small-size NSCLC and would be helpful for clinicians in decision-making.
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Affiliation(s)
- Yijun Wu
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Peking Union Medical College, Eight-year MD Program, Chinese Academy of Medical Sciences, Beijing, China
| | - Chang Han
- Peking Union Medical College, Eight-year MD Program, Chinese Academy of Medical Sciences, Beijing, China
| | - Zhile Wang
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Peking Union Medical College, Eight-year MD Program, Chinese Academy of Medical Sciences, Beijing, China
| | - Liang Gong
- Peking Union Medical College, Eight-year MD Program, Chinese Academy of Medical Sciences, Beijing, China
| | - Jianghao Liu
- Peking Union Medical College, Eight-year MD Program, Chinese Academy of Medical Sciences, Beijing, China
| | - Yuming Chong
- Peking Union Medical College, Eight-year MD Program, Chinese Academy of Medical Sciences, Beijing, China
| | - Xinyu Liu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Naixin Liang
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shanqing Li
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Wang W, Hu Z, Zhao J, Huang Y, Rao S, Yang J, Xiao S, Cao R, Ye L. Both the presence of a micropapillary component and the micropapillary predominant subtype predict poor prognosis after lung adenocarcinoma resection: a meta-analysis. J Cardiothorac Surg 2020; 15:154. [PMID: 32600473 PMCID: PMC7325156 DOI: 10.1186/s13019-020-01199-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Accepted: 06/22/2020] [Indexed: 12/16/2022] Open
Abstract
Objective It has been confirmed that the micropapillary (MP) pattern is a poor prognostic factor after resection of lung adenocarcinoma (ADC), but the proportion of the MP component as a prognostic criterion is still controversial. Hence, a meta-analysis was performed to evaluate whether the presence of an MP component has equal prognostic power as the MP predominant subtype. Methods Literature retrieval was performed in the MEDLINE, EMBASE, and Cochrane databases until December 23, 2019. Eligible studies were selected based on the inclusion and exclusion criteria. The included studies were divided into two subgroups, the MP component subgroup and the MP predominant subgroup, according to the proportion of the MP pattern to analyse the effect of this pattern on disease-free survival (DFS) and overall survival (OS). The hazard ratio (HR) and 95% confidence interval (CI) were extracted from each study. Review Manager 5.3 was used for statistical analyses. Results Finally, 10 studies, including a total of 4934 lung ADC patients, were included in this meta-analysis. Our results indicated a significantly worse pooled DFS (HR 1.62, 95% CI 1.20–2.21) and OS (HR 1.53, 95% CI 1.19–1.96) in the subgroup of MP predominant subtype patients. The pooled DFS (HR 1.80, 95% CI 1.45–2.85) and OS (HR 2.26, 95% CI 1.46–3.52) were also poor in the subgroup of patients with the presence of an MP component. Conclusions Both the presence of an MP component and the MP predominant subtype are related to poor DFS and OS after lung ADC resection and represent adverse prognostic factor for lung ADC patients. However, there are some limitations in this meta-analysis, and quantitative stratification based on the proportion of the MP component is needed to explore its effect on prognosis of lung ADC patients in the future.
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Affiliation(s)
- Wei Wang
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, No. 519 Kunzhou Road, Xishan District, Kunming City, Yunnan Province, China
| | - Zaoxiu Hu
- Department of Pathology, The Third Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Jie Zhao
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, No. 519 Kunzhou Road, Xishan District, Kunming City, Yunnan Province, China
| | - Yunchao Huang
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, No. 519 Kunzhou Road, Xishan District, Kunming City, Yunnan Province, China
| | - Sunyin Rao
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, No. 519 Kunzhou Road, Xishan District, Kunming City, Yunnan Province, China
| | - Jichen Yang
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, No. 519 Kunzhou Road, Xishan District, Kunming City, Yunnan Province, China
| | - Shouyong Xiao
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, No. 519 Kunzhou Road, Xishan District, Kunming City, Yunnan Province, China
| | - Run Cao
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, No. 519 Kunzhou Road, Xishan District, Kunming City, Yunnan Province, China
| | - Lianhua Ye
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, No. 519 Kunzhou Road, Xishan District, Kunming City, Yunnan Province, China.
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12
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Wu Y, Liu J, Han C, Liu X, Chong Y, Wang Z, Gong L, Zhang J, Gao X, Guo C, Liang N, Li S. Preoperative Prediction of Lymph Node Metastasis in Patients With Early-T-Stage Non-small Cell Lung Cancer by Machine Learning Algorithms. Front Oncol 2020; 10:743. [PMID: 32477952 PMCID: PMC7237747 DOI: 10.3389/fonc.2020.00743] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Accepted: 04/20/2020] [Indexed: 12/13/2022] Open
Abstract
Background: Lymph node metastasis (LNM) is difficult to precisely predict before surgery in patients with early-T-stage non-small cell lung cancer (NSCLC). This study aimed to develop machine learning (ML)-based predictive models for LNM. Methods: Clinical characteristics and imaging features were retrospectively collected from 1,102 NSCLC ≤ 2 cm patients. A total of 23 variables were included to develop predictive models for LNM by multiple ML algorithms. The models were evaluated by the receiver operating characteristic (ROC) curve for predictive performance and decision curve analysis (DCA) for clinical values. A feature selection approach was used to identify optimal predictive factors. Results: The areas under the ROC curve (AUCs) of the 8 models ranged from 0.784 to 0.899. Some ML-based models performed better than models using conventional statistical methods in both ROC curves and decision curves. The random forest classifier (RFC) model with 9 variables introduced was identified as the best predictive model. The feature selection indicated the top five predictors were tumor size, imaging density, carcinoembryonic antigen (CEA), maximal standardized uptake value (SUVmax), and age. Conclusions: By incorporating clinical characteristics and radiographical features, it is feasible to develop ML-based models for the preoperative prediction of LNM in early-T-stage NSCLC, and the RFC model performed best.
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Affiliation(s)
- Yijun Wu
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Peking Union Medical College, Eight-year MD Program, Chinese Academy of Medical Sciences, Beijing, China
| | - Jianghao Liu
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Peking Union Medical College, Eight-year MD Program, Chinese Academy of Medical Sciences, Beijing, China
| | - Chang Han
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Peking Union Medical College, Eight-year MD Program, Chinese Academy of Medical Sciences, Beijing, China
| | - Xinyu Liu
- Peking Union Medical College, Eight-year MD Program, Chinese Academy of Medical Sciences, Beijing, China.,Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuming Chong
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Peking Union Medical College, Eight-year MD Program, Chinese Academy of Medical Sciences, Beijing, China
| | - Zhile Wang
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Peking Union Medical College, Eight-year MD Program, Chinese Academy of Medical Sciences, Beijing, China
| | - Liang Gong
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Peking Union Medical College, Eight-year MD Program, Chinese Academy of Medical Sciences, Beijing, China
| | - Jiaqi Zhang
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xuehan Gao
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chao Guo
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Naixin Liang
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shanqing Li
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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13
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Chen Z, Xiong S, Li J, Ou L, Li C, Tao J, Jiang Z, Fan J, He J, Liang W. DNA methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model. Transl Lung Cancer Res 2020; 9:280-287. [PMID: 32420067 PMCID: PMC7225136 DOI: 10.21037/tlcr.2020.03.13] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Background Lymph node (LN) metastasis status is the most important prognostic factor and determines treatment strategy. Methylation alteration is an optimal candidate to trace the signal from early stage tumors due to its early existence, multiple loci and stability in blood. We built a diagnostic tool to screen and identify a set of plasma methylation markers in early stage occult LN metastasis. Methods High-throughput targeted methylation sequencing was performed on tissue and matched plasma samples from a cohort of 119 non-small cell lung cancer (NSCLC) patients with a primary lesion of less than 3.0 cm in diameter. The methylation profiles were compared between patients with and without occult LN metastases. We carried out a set of machine-learning analyses on our discovery cohort to evaluate the utility of cell free DNA methylation profiles in early detection of LN metastasis. Two preliminary prognostic models predictive of LN metastasis were built by random forest with differentially methylated markers shared by plasma and tissue samples and markers present either in plasma or tissue samples respectively. The performance of these models was then evaluated using receiver operating characteristic (ROC) statistics derived from ten-fold cross validation repeated ten times. Results Within this cohort, 27 cases (27/119, 22.7%) were found to have occult LN metastases found by pathological examination. Compared with those without metastases, 878 and 52 genes were differentially methylated in terms of tissue (MTA3, MIR548H4, HIST3H2A, etc.) and plasma (CIRBP, CHGB, FCHO1, etc.) respectively. 19 of these genes (ICAM1, EPH4, COCH, etc.) were overlapped. We selected 22 pairs of cases with or without occult LN metastasis by matching gender, age, smoking history and tumor histology to build and test the plasma model. The AUC of the preliminary prediction model using markers shared by plasma and tissue samples and markers present either in plasma or tissue samples is 88.6% (95% CI, 87.8–89.4%) and 74.9% (95% CI, 72.2–77.6%) respectively. Conclusions We identified a set of specific plasma methylation markers for early occult LN metastasis of NSCLC and established a preliminary non-invasive blood diagnostic tool.
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Affiliation(s)
- Zisheng Chen
- Department of Respiratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan 511518, China.,Department of Thoracic Surgery and Oncology, First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou 510120, China
| | - Shan Xiong
- Department of Thoracic Surgery and Oncology, First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou 510120, China
| | - Jianfu Li
- Department of Thoracic Surgery and Oncology, First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou 510120, China
| | - Limin Ou
- Department of Thoracic Surgery and Oncology, First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou 510120, China
| | - Caichen Li
- Department of Thoracic Surgery and Oncology, First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou 510120, China
| | - Jinsheng Tao
- AnchorDx Medical Co. Ltd., Guangzhou 510300, China
| | - Zeyu Jiang
- AnchorDx Medical Co. Ltd., Guangzhou 510300, China
| | - Jianbing Fan
- AnchorDx Medical Co. Ltd., Guangzhou 510300, China
| | - Jianxing He
- Department of Thoracic Surgery and Oncology, First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou 510120, China
| | - Wenhua Liang
- Department of Thoracic Surgery and Oncology, First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou 510120, China
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14
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Zhang Y, Xie H, Zhang Z, Zhang P, Chen P, Wang X. The Characteristics and Nomogram for Primary Lung Papillary Adenocarcinoma. Open Med (Wars) 2020; 15:92-102. [PMID: 32195357 PMCID: PMC7070103 DOI: 10.1515/med-2020-0014] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Accepted: 12/09/2019] [Indexed: 01/15/2023] Open
Abstract
Background Primary pulmonary papillary adenocarcinoma (PA) is a specific and rare subtype of invasive pulmonary adenocarcinoma (ADC). The knowledge concerning the clinicopathologic features and prognosis of patients with primary pulmonary PA has not been clarified because of its rarity. Methods The clinical data of a total of 3391 patients with primary pulmonary PA were retrospectively analyzed to confirm their clinical characteristics and factors influencing prognosis and were in comparison with 3236 patients with non- PA pulmonary adenocarcinoma. All patients were histologically diagnosed between 1988 and 2015 in The Surveillance Epidemiology and End Results (SEER) database. A nomogram with satisfactory predictive performance was established to visually predict long-term survival of these patients. Results and conclusion Collectively, primary pulmonary PA is a rare pathological cancer and its prognosis is analogous to that of non-PA pulmonary adenocarcinoma. Older age, larger lesions, distant metastases, lymph node invasion, and poor pathological differentiation are correlative with unacceptable prognosis. Surgical intervention is conducive to reaping favorable prognosis. Unfortunately, radiotherapy or chemotherapy results of no significant effects on patient survival. In our study, a nomogram with prognostic function is formulated to confer individual prediction of overall survival (OS).
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Affiliation(s)
- Yuqian Zhang
- Department of Thoracic Surgery, The Second Xiangya Hospital, Central South University, 410078, Changsha, China
| | - Hui Xie
- Department of Thoracic Surgery, The Second Xiangya Hospital, Central South University, 410078, Changsha, China
| | - Ziying Zhang
- Department of Oncology, The Third Xiangya Hospital, Central South University, No.138.Tongzipo Road, 410013, Changsha, Hunan, China
| | - Pengfei Zhang
- Department of Thoracic Surgery, The Second Xiangya Hospital, Central South University, 410078, Changsha, China
| | - Peng Chen
- Department of Urology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xiang Wang
- Department of Thoracic Surgery, The Second Xiangya Hospital, Central South University, 410078, Changsha, China
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15
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Dezube AR, Jaklitsch MT. Minimizing residual occult nodal metastasis in NSCLC: recent advances, current status and controversies. Expert Rev Anticancer Ther 2020; 20:117-130. [PMID: 32003589 DOI: 10.1080/14737140.2020.1723418] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Introduction: Nodal involvement in lung cancer is a significant determinant of prognosis and treatment management. New evidence exists regarding the management of occult lymph node metastasis and residual disease in the fields of imaging, mediastinal staging, and operative management.Areas covered: This review summarizes the latest body of knowledge on the identification and management of occult lymph node metastasis in NSCLC. We focus on tumor-specific characteristics; imaging modalities; invasive mediastinal staging; and operative management including, technique, degree of resection, and lymph node examination.Expert opinion: Newly identified risk-factors associated with nodal metastasis including tumor histology, location, radiologic features, and metabolic activity are not included in professional societal guidelines due to the heterogeneity of their reporting and uncertainty on how to adopt them into practice. Imaging as a sole diagnostic method is limited. We recommend confirmation with invasive mediastinal staging. EBUS-FNA is the best initial method, but adoption has not been uniform. The diagnostic algorithm is less certain for re-staging of mediastinal nodes after neoadjuvant therapy. Mediastinal node sampling during lobectomy remains the gold-standard, but evidence supports the use of minimally invasive techniques. More study is warranted regarding sublobar resection. No consensus exists regarding lymph node examination, but new evidence supports reexamination of current quality metrics.
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Affiliation(s)
- Aaron R Dezube
- Division of Thoracic Surgery, Brigham and Women's Hospital, Boston, MA, USA
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