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N. Secen
Moderator of
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SC24 - Management of Indeterminate Pulmonary Nodules (ID 348)
- Event: WCLC 2016
- Type: Science Session
- Track: Pulmonology
- Presentations: 5
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SC24.01 - Risk Assessment in the Management of Pulmonary Nodules (ID 6700)
11:00 - 11:20 | Author(s): S. Shiono, N. Yanagawa
- Abstract
- Presentation
Abstract:
Background Solitary pulmonary nodules are seen on approximately 0.1% of all chest X-ray films.[1] High-resolution computed tomography (HRCT), which is used in lung cancer screening programs, can detect pulmonary nodules that are smaller than those detected by conventional radiography. The radiological diagnosis and treatment of these small pulmonary nodules are now the focus of lung cancer research. The timely detection of lung cancers is essential for successful treatment. The guidelines and recommendations for the management of pulmonary nodules include follow up, nonsurgical biopsy, or surgery; and are based on the size of the nodule, and ground glass opacity (GGO) ratio or size of the solid component.[2-4] Diagnosis The diagnosis of a pulmonary nodule is frequently problematic. The management of pulmonary nodules is based on their characteristics. When a pulmonary nodule is monitored by CT, the important features include not only its size but also its density. According to the guidelines of the American College of Chest Physicians, solid nodules measuring > 8 mm in diameter need further examination.[3] The Fleischner Society for Thoracic Imaging and Diagnosis uses a cutoff diameter of 5 mm for decision making for subsolid nodules.[2] It should be kept in mind that solid nodules that are suspicious for lung cancer are frequently invasive. A subsolid nodule can be classified as a pure ground glass nodule (GGN) or part-solid nodule. Subsolid nodules grow slowly and may develop a solid component. The HRCT findings of early lung adenocarcinomas were significantly correlated with the histopathologic findings of the resected specimens.[5] In the evaluation of subsolid nodules, the features indicating noninvasive lung adenocarcinoma include tumor disappearance rate, diameter of consolidation, and GGO ratio.[6] However, even HRCT cannot accurately assess the areas of solid opacities or GGO, and results might vary between investigators. In the upcoming 8[th] TNM classification, the Lung Cancer Staging Project of the International Association for the Study of Lung Cancer showed that the solid part of a nodule on HRCT represents the clinical T factor, and that measurement of the solid part is essential for lung cancer staging.[5] Positron emission tomography (PET)-CT has a clearly established role in lung cancer clinical practice. Based on the pretest probability, PET-CT should be used for patients with a solid, indeterminate nodule > 8 mm in size.[3,4] For adenocarcinomas in situ (AIS) and minimally invasive adenocarcinomas (MIA) of the lung that show solid opacities on HRCT, the preoperative PET-CT and thin-section CT findings together can provide information on the aggressiveness of the tumor. Our study group found that these modalities used together could detect aggressive lung cancers in clinical stage IA (Fig. 1).[7] However, since PET-CT can show false-negative results for slow-growing and low-grade lung malignancies, we think that HRCT is the best modality for identifying indolent lung cancers. Transthoracic biopsy, bronchoscopy, or surgery is used for obtaining specimens for histopathological diagnosis. The definitive diagnosis of small pulmonary nodules, especially GGO-dominant nodules, is challenging. The diagnostic yields of percutaneous CT-guided fine needle aspiration biopsy for GGO-dominant and solid-dominant lesions were 51.2% and 75.6%, respectively (p = 0.018).[9] The diagnostic yield of GGO-dominant lesions < 10 mm was 35.2%. Since invasive biopsy is not without risk, a histopathological diagnosis should be limited to nonsurgical candidates. For cases with high likelihood of lung cancer, a surgical biopsy followed by lung resection might be warranted. Although surgery might be performed on patients with benign nodules, it does provide the definitive diagnosis. If surgery is performed after careful preoperative assessment, the surgical mortality is very low, and the surgical risk may be acceptable. Treatment While lobectomy is the standard procedure for lung cancers, sublobar resection, meaning segmentectomy or wedge resection, might be justified for patients with noninvasive small lung cancers. However, to date, which procedure, sublobar resection or lobectomy, provides a better outcome remains unclear in these cases, since prospective randomized control trials are ongoing (JCOG0802/WJOG4607L[8] and CALGB140503). One of the concerns in sublobar resection is recurrence at the surgical margin (Fig. 2). Recurrence at the surgical margin might be accounted for by tumor cells spreading via air spaces.[10] Accurate intraoperative cytology and adequate surgical margins have been reported to be important for preventing recurrence at the surgical margin. Another concern is lymph node metastasis. In a prospective radiological study for clinical stage IA lung cancer, 47 of 545 (8.6%) patients had lymph node metastasis.[6] Sublobar resection, especially wedge resection, dose not allow evaluation of lymph nodes for metastatic disease. Conclusion HRCT findings play an important role in discriminating the biological behaviors of pulmonary nodules. The definitive diagnosis by HRCT can be difficult, and the combination of HRCT and PET-CT might be beneficial. Randomized control trials should clarify the role of sublobar resection in treating patients with noninvasive lung cancer. Figure 1. Figure 1 Figure 2. Figure 2 References 1. Ost D, Fein AM, Feinsilver SH. The solitary pulmonary nodule. N Engl J Med 2003;348:2535-42. 2. Naidich D, Bankier AA, MacMahon H, Schaefer-Prokop CM, Pistolesi M, Goo JM, et al. Recommendations for the management of subsolid pulmonary nodules detected at CT: A statement from the Fleischner Society. Radiology 2013;266:304-17. 3. Gould MK, Donington J, Lunch WR, Mazzone PJ, Midthun DE, Naidich DP, et al. Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer 3[rd] ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest 2013;143:e93s-120s. 4. National Comprehensive Cancer Network. Guidelines for surveillance following therapy for non-small cell lung cancer Ver 4.2016. Available at: www.nccn.com. 5. Travis WD, Asamura H, Bankier AA, Beaseley MB, Detterbeck F, Flieder DB, et al. The IASLC Lung Cancer Staging Project: Proposals for coding T categories for subsolid nodules and assessment of tumor size in part-solid tumors in the forthcoming eighth edition of the TNM classification of lung cancer. J Thorac Oncol 2016;11:1204-23. 6. Suzuki K, Koike T, Asakawa T, Kusumot M, Asamura H, Nagai K, et al. A prospective radiological study of thin-section computed tomography to predict pathological noninvasiveness in peripheral clinical IA lung cancer (Japan Clinical Oncology Group 0201). J Thorac Oncol 2011;6:751-6. 7. Shiono S, Yanagawa N, Abiko M, Sato T. Detection of non-aggressive stage IA lung cancer using chest computed tomography and positron emission tomography/computed tomography. Interact Cardiovasc Thorac Surg. 2014;21:637-43. 8. Nakamura K, Saji H, Nakajima R, Okada M, Asamura H, Shibata T et al. A phase III randomized trial of lobectomy versus limited resection for smallsized peripheral non-small cell lung cancer (JCOG0802/WJOG4607L). Jpn J Clin Oncol 2010;40:271–4. 9. Shimizu K, Ikeda N, Tsuboi M, Hirano T, Kato H. Percutaneous CT-guided fine needle aspiration for lung cancer smaller than 2 cm and revealed by ground-glass opacity at CT. Lung Cancer 2006;51:173-9. 10. Shiono S, Yanagawa N. Spread through air spaces is a predictive factor of recurrence and a prognostic factor in stage I lung adenocarcinoma. Interact Cardiovasc Thorac Surg. 2016 Jun 26. pii: ivw211.
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SC24.02 - Radiological Techniques for the Evaluation of Pulmonary Nodules (ID 6701)
11:20 - 11:35 | Author(s): R. Munden
- Abstract
- Presentation
Abstract:
Radiologic Techniques for the Evaluation of Pulmonary Nodules The incidental detection of pulmonary nodules has increased with improved CT technology and thin section imaging techniques[1][,][2]. Adding to this increased detection of nodules is the heightened interest in the purposeful search for nodules such as in oncology patients and lung cancer screening programs. The management of CT detected nodules is a subject of much debate and dependent upon the clinical setting. For instance, in a lung cancer screening setting, there has been a large volume of investigation of solid, semi-solid and ground glass nodules that is the foundation of management recommendations such as LungRads[3]. In patients with a known malignancy, there is minimal literature on management recommendations and thus more influenced by pulmonary metastatic potential of the malignancy and clinician experience[4]. Finally incidentally detected nodule management is greatly influenced by cancer risk factors and nodule texture; for these situations, the Fleischner criteria have been the most widely used and accepted management guidelines[5]. The radiologic evaluation of nodules most often utilizes conventional imaging techniques of chest radiographs, computed tomography (CT), PET/CT. Occasionally MRI and ultrasound may be employed. Most recent changes involve risk stratification, computer software applications to enhance nodule analysis such as nodule enhancement patterns, volumetric computations, and texture analysis[6-8]. Future directions include incorporation of genomics into imaging as well as radiomic analysis and machine learning[9][,][10]. This presentation will review the highlights of the radiologic methods for evaluating pulmonary nodules with a focus on current guidelines and future directions. Reference: 1. Frank L, Quint LE. Chest CT incidentalomas: thyroid lesions, enlarged mediastinal lymph nodes, and lung nodules. Cancer imaging : the official publication of the International Cancer Imaging Society 2012;12:41-8. 2. Jacobs PC, Mali WP, Grobbee DE, van der Graaf Y. Prevalence of incidental findings in computed tomographic screening of the chest: a systematic review. Journal of computer assisted tomography 2008;32:214-21. 3. Lung CT Screening Reporting and Data Systen (Lung-RADS). 2014. (Accessed March 27, 2015, at www.acr.org/Quality-Safety/Resources/LungRADS ) 4. Munden RF, Erasmus JJ, Wahba H, Fineberg NS. Follow-up of small (4 mm or less) incidentally detected nodules by computed tomography in oncology patients: a retrospective review. J Thorac Oncol 2010;5:1958-62. 5. McMahon PM, Meza R, Plevritis SK, et al. Comparing benefits from many possible computed tomography lung cancer screening programs: extrapolating from the National Lung Screening Trial using comparative modeling. PloS one 2014;9:e99978. 6. McWilliams A, Tammemagi MC, Mayo JR, et al. Probability of cancer in pulmonary nodules detected on first screening CT. N Engl J Med 2013;369:910-9. 7. Revel MP, Merlin A, Peyrard S, et al. Software volumetric evaluation of doubling times for differentiating benign versus malignant pulmonary nodules. AJR Am J Roentgenol 2006;187:135-42. 8. Talwar A, Gleeson FV, Rahman NM, Pickup L, Gooding M, Kadir T. A Review Of The Use Of Computer Aided Texture Analysis For Pulmonary Nodules Classification. American journal of respiratory and critical care medicine 2015;191. 9. El-Zein RA, Lopez MS, D'Amelio AM, Jr., et al. The cytokinesis-blocked micronucleus assay as a strong predictor of lung cancer: extension of a lung cancer risk prediction model. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 2014;23:2462-70. 10. Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology 2016;278:563-77.
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SC24.03 - The Role of the Pulmonologist in the Management of Pulmonary Nodules (ID 6702)
11:35 - 11:50 | Author(s): P. Lambin
- Abstract
- Presentation
Abstract not provided
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SC24.04 - The Role of the Pathologist in the Management of Indeterminate Pulmonary Nodules (ID 6703)
11:50 - 12:10 | Author(s): K. Kerr
- Abstract
- Presentation
Abstract not provided
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SC24.05 - Indication and Techniques of Surgery (ID 6704)
12:10 - 12:30 | Author(s): U. Pastorino
- Abstract
- Presentation
Abstract not provided
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Author of
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P2.03a - Poster Session with Presenters Present (ID 464)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Advanced NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 12/06/2016, 14:30 - 15:45, Hall B (Poster Area)
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P2.03a-042 - Comorbidity as a Prognostic Factor in Elderly Non-Small Cell Lung Cancer Patients Treated with Platinum-Based Chemotherapy (ID 5851)
14:30 - 14:30 | Author(s): N. Secen
- Abstract
Background:
The number of elderly lung cancer patients rises due to prolonged life expectancy, therefore the larger is proportion of patients with more comorbid conditions. The aim of this study is to evaluate influence of comorbidity on 2-year survival of elderly patients with advanced stage of non-small cell lung cancer treated with platinum-based chemotherapy.
Methods:
In our study we observed 152 elderly patients with patohistologicaly confirmed non-small cell lung cancer in advanced stage (IIIB, IV), treated with platinum-based chemotherapy, retrospectively. We evaluate the prognostic value of pretreatment comorbidity status on the 2-year survival.
Results:
Our analysis showed that the number of comorbid conditions (0-without, 1, 2, 3 comorbid conditions) didn’t statistically influence 2-year survival (p=0,894), but patients with more comorbid diseases have shorter 2-year survival (12.5% / 10.5% / 8.5% / 6.3% respectivelly). There were no statistically significant differences in 2-year survival according the value of Charlson index of comorbidity (p=0.312). There were no statistically differences in 2-year survival relative to the presence or absence of comorbid condition of particular systemic organs: respiratory (p=0.692), cardiovascular (p=0.382), gastronitestinal (p=0.657), diabetes (p=0.676), previous malignancy (p=0.586). Patients without respiratory comorbidity had better 2-year survival, but not significantly (Mantell/Cox p=0.0782).
Conclusion:
CONSLUSION: In strictly, by criteria selected, fit, elderly lung cancer patient comorbidity doesn’t significantly influence survival. Comorbidity should be a stimulus for treatment design rather than an exclusion criteria for oncologic treatment.
