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Cackowski MM, Gryszko GM, Zbytniewski M, Dziedzic DA, Orłowski TM. Alternative methods of lymph node staging in lung cancer: a narrative review. J Thorac Dis 2020; 12:6042-6053. [PMID: 33209438 PMCID: PMC7656442 DOI: 10.21037/jtd-20-1997] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The nodal status indicator in non-small cell lung cancer is one of the most crucial prognostic factors available. However, there are still many arguments among scientists regarding whether the currently used nodal status descriptor should be changed in the forthcoming editions of the Tumor Node Metastasis classification or whether it is precise enough and should be maintained as is. We reviewed studies concerning nodal factor classifications to evaluate their accuracy in non-small cell lung cancer patients and to address the previously mentioned challenge. We reviewed the PubMed database regarding the following classifications: ongoing 8th edition of the Tumor Node Metastasis classification, number of positive lymph nodes, number of negative lymph nodes, number of dissected lymph nodes, lymph node ratio, nodal chains, log odds of positive lymph nodes, zone-based classification and one that is based on the number of lymph node stations involved. Moreover, we analysed data regarding various combinations of these classifications. Our analysis showed that the present nodal staging may not accurately categorize every lung cancer patient. The number of positive lymph nodes and lymph node ratio or the log odds of positive lymph nodes (as the mathematical modification of lymph node ratio) are more legitimate, as they possess very robust data and should be considered initially as additional factors that can be incorporated in ongoing nodal staging systems. Forthcoming non-small cell lung cancer staging systems could benefit from the addition of quantitative-based parameters. Additionally, the minimal extent of lymphadenectomy should be established as staging benefits from it. International, prospective validation studies need to be performed to optimize the cut-off values and prognostic groups and to confirm the superiority of the newly suggested descriptors in non-small cell lung cancer nodal staging.
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Affiliation(s)
- Marcin M Cackowski
- Department of Thoracic Surgery, National Research Institute of Chest Diseases, Warsaw, Poland
| | - Grzegorz M Gryszko
- Department of Thoracic Surgery, National Research Institute of Chest Diseases, Warsaw, Poland
| | - Marcin Zbytniewski
- Department of Thoracic Surgery, National Research Institute of Chest Diseases, Warsaw, Poland
| | - Dariusz A Dziedzic
- Department of Thoracic Surgery, National Research Institute of Chest Diseases, Warsaw, Poland
| | - Tadeusz M Orłowski
- Department of Thoracic Surgery, National Research Institute of Chest Diseases, Warsaw, Poland
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Qian J, Qian Y, Wang J, Gu B, Pei D, He S, Zhu F, Røe OD, Xu J, Liu L, Gu Y, Guo R, Yin Y, Shu Y, Chen X. A clinical prognostic scoring system for resectable gastric cancer to predict survival and benefit from paclitaxel- or oxaliplatin-based adjuvant chemotherapy. DRUG DESIGN DEVELOPMENT AND THERAPY 2016; 10:241-58. [PMID: 26966350 PMCID: PMC4771399 DOI: 10.2147/dddt.s88743] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Background Gastrectomy with D2 lymphadenectomy is a standard procedure of curative resection for gastric cancer (GC). The aim of this study was to develop a simple and reliable prognostic scoring system for GC treated with D2 gastrectomy combined with adjuvant chemotherapy. Methods A prognostic scoring system was established based on clinical and laboratory data from 579 patients with localized GC without distant metastasis treated with D2 gastrectomy and adjuvant chemotherapy. Results From the multivariate model for overall survival (OS), five factors were selected for the scoring system: ≥50% metastatic lymph node rate, positive lymphovascular invasion, pathologic TNM Stage II or III, ≥5 ng/mL preoperative carcinoembryonic antigen level, and <110 g/L preoperative hemoglobin. Two models were derived using different methods. Model A identified low- and high-risk patients for OS (P<0.001), while Model B differentiated low-, intermediate-, and high-risk patients for OS (P<0.001). Stage III patients in the low-risk group had higher survival probabilities than Stage II patients. Both Model A (area under the curve [AUC]: 0.74, 95% confidence interval [CI]: 0.69–0.78) and Model B (AUC: 0.79, 95% CI: 0.72–0.83) were better predictors compared with the pathologic TNM classification (AUC: 0.62, 95% CI: 0.59–0.71, P<0.001). Adjuvant paclitaxel- or oxaliplatin-based or triple chemotherapy showed significantly better outcomes in patients classified as high risk, but not in those with low and intermediate risk. Conclusion A clinical three-tier prognostic risk scoring system was established to predict OS of GC treated with D2 gastrectomy and adjuvant chemotherapy. The potential advantage of this scoring system is that it can identify high-risk patients in Stage II or III who may benefit from paclitaxel- or oxaliplatin-based regimens. Prospective studies are needed to confirm these results before they are applied clinically.
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Affiliation(s)
- Jing Qian
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Xuzhou, People's Republic of China
| | - Yingying Qian
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Xuzhou, People's Republic of China
| | - Jian Wang
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Xuzhou, People's Republic of China
| | - Bing Gu
- Department of Laboratory Medicine, The Affiliated Hospital of Xuzhou Medical College, Xuzhou, People's Republic of China; Medical Technology Institute, Xuzhou Medical College, Xuzhou, People's Republic of China
| | - Dong Pei
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Xuzhou, People's Republic of China
| | - Shaohua He
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Xuzhou, People's Republic of China
| | - Fang Zhu
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Xuzhou, People's Republic of China
| | - Oluf Dimitri Røe
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Department of Oncology, Clinical Cancer Research Center, Aalborg, Denmark; Department of Clinical Medicine, Aalborg University Hospital, Aalborg, Denmark; Department of Surgery, Cancer Clinic, Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Jin Xu
- Department of Molecular Cell Biology and Toxicology, Jiangsu Key Lab of Cancer Biomarkers, Prevention & Treatment, Cancer Center, Nanjing Medical University, Nanjing, People's Republic of China
| | - Lianke Liu
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Xuzhou, People's Republic of China
| | - Yanhong Gu
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Xuzhou, People's Republic of China
| | - Renhua Guo
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Xuzhou, People's Republic of China
| | - Yongmei Yin
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Xuzhou, People's Republic of China
| | - Yongqian Shu
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Xuzhou, People's Republic of China
| | - Xiaofeng Chen
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Xuzhou, People's Republic of China
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