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Bade BC, Blasberg JD, Mase VJ, Kumbasar U, Li AX, Park HS, Decker RH, Madoff DC, Brandt WS, Woodard GA, Detterbeck FC. A guide for managing patients with stage I NSCLC: deciding between lobectomy, segmentectomy, wedge, SBRT and ablation-part 3: systematic review of evidence regarding surgery in compromised patients or specific tumors. J Thorac Dis 2022; 14:2387-2411. [PMID: 35813753 PMCID: PMC9264070 DOI: 10.21037/jtd-21-1825] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 05/09/2022] [Indexed: 11/06/2022]
Abstract
Background Clinical decision-making for patients with stage I lung cancer is complex. It involves multiple options [lobectomy, segmentectomy, wedge, stereotactic body radiotherapy (SBRT), thermal ablation], weighing multiple outcomes (e.g., short-, intermediate-, long-term) and multiple aspects of each (e.g., magnitude of a difference, the degree of confidence in the evidence, and the applicability to the patient and setting at hand). A structure is needed to summarize the relevant evidence for an individual patient and to identify which outcomes have the greatest impact on the decision-making. Methods A PubMed systematic review from 2000-2021 of outcomes after lobectomy, segmentectomy and wedge resection in older patients, patients with limited pulmonary reserve and favorable tumors is the focus of this paper. Evidence was abstracted from randomized trials and non-randomized comparisons (NRCs) with adjustment for confounders. The analysis involved careful assessment, including characteristics of patients, settings, residual confounding etc. to expose degrees of uncertainty and applicability to individual patients. Evidence is summarized that provides an at-a-glance overall impression as well as the ability to delve into layers of details of the patients, settings and treatments involved. Results In older patients, perioperative mortality is minimally altered by resection extent and only slightly affected by increasing age; sublobar resection may slightly decrease morbidity. Long-term outcomes are worse after lesser resection; the difference is slightly attenuated with increasing age. Reported short-term outcomes are quite acceptable in (selected) patients with severely limited pulmonary reserve, not clearly altered by resection extent but substantially improved by a minimally invasive approach. Quality-of-life (QOL) and impact on pulmonary function hasn't been well studied, but there appears to be little difference by resection extent in older or compromised patients. Patient selection is paramount but not well defined. Ground-glass and screen-detected tumors exhibit favorable long-term outcomes regardless of resection extent; however solid tumors <1 cm are not a reliably favorable group. Conclusions A systematic, comprehensive summary of evidence regarding resection extent in compromised patients and favorable tumors with attention to aspects of applicability, uncertainty and effect modifiers provides a foundation for a framework for individualized decision-making.
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Affiliation(s)
- Brett C. Bade
- Department of Pulmonary Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Justin D. Blasberg
- Department of Thoracic Surgery, Yale University School of Medicine, New Haven, CT, USA
| | - Vincent J. Mase
- Department of Thoracic Surgery, Yale University School of Medicine, New Haven, CT, USA
| | - Ulas Kumbasar
- Department of Thoracic Surgery, Hacettepe University School of Medicine, Ankara, Turkey
| | - Andrew X. Li
- Department of General Surgery, Yale University School of Medicine, New Haven, CT, USA
| | - Henry S. Park
- Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, CT, USA
| | - Roy H. Decker
- Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, CT, USA
| | - David C. Madoff
- Department of Radiology & Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Whitney S. Brandt
- Department of Cardiothoracic Surgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Gavitt A. Woodard
- Department of Thoracic Surgery, Yale University School of Medicine, New Haven, CT, USA
| | - Frank C. Detterbeck
- Department of Thoracic Surgery, Yale University School of Medicine, New Haven, CT, USA
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Wang T, She Y, Yang Y, Liu X, Chen S, Zhong Y, Deng J, Zhao M, Sun X, Xie D, Chen C. Radiomics for Survival Risk Stratification of Clinical and Pathologic Stage IA Pure-Solid Non-Small Cell Lung Cancer. Radiology 2021; 302:425-434. [PMID: 34726531 DOI: 10.1148/radiol.2021210109] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Background Radiomics-based biomarkers enable the prognostication of resected non-small cell lung cancer (NSCLC), but their effectiveness in clinical stage and pathologic stage IA pure-solid tumors requires further determination. Purpose To construct an efficient radiomics signature for survival risk stratification personalized for patients with clinical stage and pathologic stage IA pure-solid NSCLC. Materials and Methods In this retrospective study, six radiomics signatures were constructed for patients with stage IA pure-solid NSCLC who underwent resection between January 2011 and December 2013 at authors' institution and were tested in the radiogenomics data set. The radiomics features were extracted from the intratumoral two-dimensional region, three-dimensional volume, and peritumoral area using PyRadiomics. The discriminative abilities of the signatures were quantified using the area under the time-dependent receiver operating characteristic curve (AUC), and the optimal signature was selected for patient stratification. Results The study included 592 patients with stage IA pure-solid NSCLC (median age, 61 years; interquartile range, 55-66 years; 269 women) for radiomics analysis: 381 patients for training, 163 for internal validation, and 48 for external validation. The radiomics signature combining three-region features yielded the highest 3- and 5-year AUCs of 0.77 and 0.78, respectively, in the internal validation set and 0.76 and 0.75, respectively, in the external validation set. Multivariable analysis suggested that the radiomics signature remained an independent prognostic factor (hazard ratio, 6.2; 95% CI: 3.5, 11.0; P < .001) and improved the discriminative ability and clinical usefulness of conventional clinical predictors. Conclusion The radiomics signature with multiregional features helped stratify the survival risk of patients with clinical stage and pathologic stage IA pure-solid non-small cell lung cancer. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Hsu and Sohn in this issue.
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Affiliation(s)
- Tingting Wang
- From the Departments of Radiology (T.W., Y.Y., X.S.) and Thoracic Surgery (Y.S., X.L., Y.Z., J.D., M.Z., D.X., C.C.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, Zhengmin Rd 507, Shanghai 200443, China; and Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C.)
| | - Yunlang She
- From the Departments of Radiology (T.W., Y.Y., X.S.) and Thoracic Surgery (Y.S., X.L., Y.Z., J.D., M.Z., D.X., C.C.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, Zhengmin Rd 507, Shanghai 200443, China; and Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C.)
| | - Yang Yang
- From the Departments of Radiology (T.W., Y.Y., X.S.) and Thoracic Surgery (Y.S., X.L., Y.Z., J.D., M.Z., D.X., C.C.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, Zhengmin Rd 507, Shanghai 200443, China; and Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C.)
| | - Xinyue Liu
- From the Departments of Radiology (T.W., Y.Y., X.S.) and Thoracic Surgery (Y.S., X.L., Y.Z., J.D., M.Z., D.X., C.C.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, Zhengmin Rd 507, Shanghai 200443, China; and Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C.)
| | - Shouyu Chen
- From the Departments of Radiology (T.W., Y.Y., X.S.) and Thoracic Surgery (Y.S., X.L., Y.Z., J.D., M.Z., D.X., C.C.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, Zhengmin Rd 507, Shanghai 200443, China; and Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C.)
| | - Yifan Zhong
- From the Departments of Radiology (T.W., Y.Y., X.S.) and Thoracic Surgery (Y.S., X.L., Y.Z., J.D., M.Z., D.X., C.C.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, Zhengmin Rd 507, Shanghai 200443, China; and Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C.)
| | - Jiajun Deng
- From the Departments of Radiology (T.W., Y.Y., X.S.) and Thoracic Surgery (Y.S., X.L., Y.Z., J.D., M.Z., D.X., C.C.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, Zhengmin Rd 507, Shanghai 200443, China; and Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C.)
| | - Mengmeng Zhao
- From the Departments of Radiology (T.W., Y.Y., X.S.) and Thoracic Surgery (Y.S., X.L., Y.Z., J.D., M.Z., D.X., C.C.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, Zhengmin Rd 507, Shanghai 200443, China; and Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C.)
| | - Xiwen Sun
- From the Departments of Radiology (T.W., Y.Y., X.S.) and Thoracic Surgery (Y.S., X.L., Y.Z., J.D., M.Z., D.X., C.C.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, Zhengmin Rd 507, Shanghai 200443, China; and Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C.)
| | - Dong Xie
- From the Departments of Radiology (T.W., Y.Y., X.S.) and Thoracic Surgery (Y.S., X.L., Y.Z., J.D., M.Z., D.X., C.C.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, Zhengmin Rd 507, Shanghai 200443, China; and Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C.)
| | - Chang Chen
- From the Departments of Radiology (T.W., Y.Y., X.S.) and Thoracic Surgery (Y.S., X.L., Y.Z., J.D., M.Z., D.X., C.C.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, Zhengmin Rd 507, Shanghai 200443, China; and Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C.)
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Kawaguchi Y, Nakao M, Omura K, Iwamoto N, Ozawa H, Kondo Y, Ichinose J, Matsuura Y, Okumura S, Mun M. The utility of three-dimensional computed tomography for prediction of tumor invasiveness in clinical stage IA lung adenocarcinoma. J Thorac Dis 2021; 12:7218-7226. [PMID: 33447410 PMCID: PMC7797862 DOI: 10.21037/jtd-20-2131] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Background It is critical to have an accurate measurement of solid tumor size in order to predict the invasiveness of small lung adenocarcinomas. Some lesions cannot be measured accurately via High-resolution computed tomography (HRCT) due to their irregular shape and unclear borders. For this reason, we evaluated the relative efficacy of three-dimensional (3D) CT for predicting invasive adenocarcinoma. Methods We evaluated 195 patients with clinical stage IA adenocarcinomas, including 109 with lesions documented as invasive that were surgically resected at our institute during 2017. All lesions were categorized as either (I) lesions that were difficult to evaluate (i.e., hazy lesions; HL) or (II) more typical lesions (TL). The relationships between solid tumor size as determined by HRCT, solid tumor volume as determined by 3D CT and pathologic diagnosis were evaluated. Results Fifty-seven patients (29%) were diagnosed with HL. We set the cut-off value for the solid volume at 225 mm3 as predictive for invasive adenocarcinoma. When evaluating all 195 patients as a group, the accuracy, sensitivity, and specificity based on the solid tumor volume were similar to those based on the solid tumor size. When we limit our analysis to the HL group, the specificity based on solid tumor volume (65.5%) was higher than that based on solid tumor size (44.8%) with a difference that approached statistical significance (P=0.070). Conclusions 3D CT was equivalent to HRCT for predicting invasive adenocarcinoma and may be particularly useful for diagnosing lesions that are difficult to evaluate on HRCT.
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Affiliation(s)
- Yohei Kawaguchi
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital, The Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Masayuki Nakao
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital, The Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Kenshiro Omura
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital, The Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Naoya Iwamoto
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital, The Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Hiroki Ozawa
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital, The Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Yasuto Kondo
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital, The Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Junji Ichinose
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital, The Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Yosuke Matsuura
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital, The Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Sakae Okumura
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital, The Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Mingyon Mun
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital, The Japanese Foundation for Cancer Research, Tokyo, Japan
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Hattori A, Takamochi K, Oh S, Suzuki K. New revisions and current issues in the eighth edition of the TNM classification for non-small cell lung cancer. Jpn J Clin Oncol 2019; 49:3-11. [PMID: 30277521 DOI: 10.1093/jjco/hyy142] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2018] [Accepted: 09/24/2018] [Indexed: 12/25/2022] Open
Abstract
In the eighth edition of the TNM classification of lung cancer, the prognostic impact of tumor size is emphasized as a descriptor of all T categories. Especially in lung cancer where tumor size is 5 cm or less, the 1-cm cutoff point significantly differentiated the survival outcome. In addition, the new staging categories were assigned, namely, Tis (adenocarcinoma in situ) and T1mi (minimally invasive adenocarcinoma). Furthermore, the measurement of a radiological solid component size excluding the ground glass opacity component or pathological invasive size without a lepidic component was proposed for deciding the cT/pT categories for lung adenocarcinoma. The N descriptors were kept the same as in the eventh edition on the whole, however, quantification of nodal disease had a prognostic impact based on the number of nodal stations involved in the eighth edition, i.e. N1a as a single N1 station, N1b as a multiple N1 station, N2a1 as a single N2 station without N1 (skip metastasis), N2a2 as a single N2 station with N1 disease, and N2b as a multiple N2 station. In the M descriptors, subclassification was performed based on the location or numbers of distantly metastatic lesions, i.e. M1a as any intrathoracic metastases, M1b as a single distant metastatic lesion in one organ, and M1c as multiple distant metastases in either a single organ or multiple organs. Survival analysis of the eighth edition of the TNM classification clearly separated the distinct groups, however, unsolved issues still remain that should be discussed and further revised for the forthcoming TNM staging system.
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Affiliation(s)
- Aritoshi Hattori
- Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan
| | - Kazuya Takamochi
- Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan
| | - Shiaki Oh
- Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan
| | - Kenji Suzuki
- Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan
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