Intrapulmonary metastasis of non–small cell lung cancer: A prognostic assessment

AbstractObjective: According to the revised TNM classification in 1997, intrapulmonary metastasis within the same lobe of the primary tumor is designated as T4 and intrapulmonary metastasis in a different lobe is M1. However, their prognostic implications remain unclear. To assess their prognoses, we retrospectively analyzed the postoperative survival of patients with and without intrapulmonary metastasis. Methods: From January 1982 to December 1996, 2340 patients with non–small cell lung cancer underwent surgical resection. The survival of patients having complete resection (n = 1534) was analyzed according to their intrapulmonary metastasis status: patients without intrapulmonary metastasis (n = 1393), those with metastasis in the same lobe (n = 105), and those with metastasis in a different lobe (n = 18). For comparison, patients with T4 disease without intrapulmonary metastasis in the same lobe (n = 54) and those with M1 disease without metastasis in a different lobe (distant M1, n = 18) were also analyzed. Results: The overall 5-year survivals were as follows: no intrapulmonary metastasis, 60%; stage T4 disease with no intrapulmonary metastasis, 34%; pulmonary metastasis in the same lobe, 34%; pulmonary metastasis in a different lobe, 11%; and distant M1, 6%. The differences in survival between patients with no pulmonary metastasis and those with metastasis in the same lobe (P <.001, log-rank test) and between patients with metastasis in the same lobe and those with distant M1 (P <.001) were significant. In contrast, there was no significant difference between patients with metastasis in the same lobe and those with T4 disease and no intrapulmonary metastasis or between patients with metastasis to a different lobe and those with distant M1. Conclusions: Prognostically, intrapulmonary metastasis within the same lobe of the primary tumor was comparable with T4 and that in a different lobe was comparable with M1. In terms of postoperative prognosis, the revised TNM classification for intrapulmonary metastasis seems to be appropriate.J Thorac Cardiovasc Surg 2001;122:24-

T2 tumors larger than five centimeters in diameter can be upgraded to T3 in non–small cell lung cancer

AbstractObjective: Among the TNM criteria, tumor size is a well-assessed factor in the prognosis of small tumors. A 3-cm cutoff point separates T1 from T2 tumors, whereas a size larger than 3 cm is not ascribed any prognostic value. Instead, N2 is considered to be the worst prognostic factor for intrathoracic extended disease. Method: The prognosis of 545 patients with non–small cell lung cancer larger than 3 cm in diameter (T2, T3, and T4) was studied. These tumors were completely resected by pneumonectomy (n = 126) or lobectomy (n = 411) or were partially resected (n = 8). Survivals were compared according to the following factors: tumor size (3.1-5 cm, 5.1-7 cm, >7 cm), nodal status, age, sex, histologic type, degree of pleural involvement, operative procedure, stage, and T factor. For the multivariate analysis, the Cox proportional hazard model was used with the same variables. Results: The univariate analysis showed that age, sex, degree of pleural involvement, operative procedure, tumor size, nodal status, and stage were all significant prognostic factors. Further comparison of survival between different tumor sizes (≤5 cm vs >5 cm) in the same nodal category demonstrated a significantly poor prognosis for larger tumors in N0 (P =.00374) and N2+N3 (P =.0157), but not in N1 (P =.3452). T2 tumors (n = 349) were divided, according to size, into T2a (n = 238) and T2b (n = 111), and survival was compared with those in T3 and T4. The 5-year survivals were 51.3%, 35.1%, 47.8%, and 25.3%, respectively. The difference between T2a and T2b was statistically significant (log-rank P =.0170, Breslow P =.0055). Conclusions: A tumor size of more than 5 cm in diameter was indicative of a poor prognosis in non–small cell lung cancer, because patients with T2b tumors had a significantly different survival from that of patients with T2a tumors, and the survival curve was located between those for patients with T3 and T4 tumors. Consequently, T2b might be upgraded to at least T3.J Thorac Cardiovasc Surg 2001;122:907-1

Global consultation on cancer staging: promoting consistent understanding and use

Disease burden is the most important determinant of survival in patients with cancer. This domain, reflected by the cancer stage and codified using the tumour-node-metastasis (TNM) classification, is a fundamental determinant of prognosis. Accurate and consistent tumour classification is required for the development and use of treatment guidelines and to enable clinical research (including clinical trials), cancer surveillance and control. Furthermore, knowledge of the extent and stage of disease is frequently important in the context of translational studies. Attempts to include additional prognostic factors in staging classifications, in order to facilitate a more accurate determination of prognosis, are often made with a lack of knowledge and understanding and are one of the main causes of the inconsistent use of terms and definitions. This effect has resulted in uncertainty and confusion, thus limiting the utility of the TNM classification. In this Position paper, we provide a consensus on the optimal use and terminology for cancer staging that emerged from a consultation process involving representatives of several major international organizations involved in cancer classification. The consultation involved several steps: a focused literature review; a stakeholder survey; and a consultation meeting. This aim of this Position paper is to provide a consensus that should guide the use of staging terminology and secure the classification of anatomical disease extent as a distinct aspect of cancer classification

Global consultation on cancer staging: promoting consistent understanding and use

Disease burden is the most important determinant of survival in patients with cancer. This domain, reflected by the cancer stage and codified using the tumour-node-metastasis (TNM) classification, is a fundamental determinant of prognosis. Accurate and consistent tumour classification is required for the development and use of treatment guidelines and to enable clinical research (including clinical trials), cancer surveillance and control. Furthermore, knowledge of the extent and stage of disease is frequently important in the context of translational studies. Attempts to include additional prognostic factors in staging classifications, in order to facilitate a more accurate determination of prognosis, are often made with a lack of knowledge and understanding and are one of the main causes of the inconsistent use of terms and definitions. This effect has resulted in uncertainty and confusion, thus limiting the utility of the TNM classification. In this Position paper, we provide a consensus on the optimal use and terminology for cancer staging that emerged from a consultation process involving representatives of several major international organizations involved in cancer classification. The consultation involved several steps: a focused literature review; a stakeholder survey; and a consultation meeting. This aim of this Position paper is to provide a consensus that should guide the use of staging terminology and secure the classification of anatomical disease extent as a distinct aspect of cancer classification

Supplementary Prognostic Variables for Pleural Mesothelioma A Report from the IASLC Staging Committee

Introduction: The staging system for malignant pleural mesothelioma is controversial. To revise this system, the International Association for the Study of Lung Cancer Staging Committee developed an international database. This report analyzes prognostic variables in a surgical population, which are supplementary to previously published CORE variables (stage, histology, sex, age, and type of procedure). Methods: Supplementary prognostic variables were studied in three scenarios: (1) all data available, that is, patient pathologically staged and other CORE variables available (2) only clinical staging available along with CORE variables, and (3) only age, sex, histology, and laboratory parameters are known. Survival was analyzed by Kaplan– Meier, prognostic factors by log rank and stepwise Cox regression modeling after elimination of nonsignificant variables. p value less than 0.05 was significant. Results: A total of 2141 patients with best tumor, node, metastasis (TNM) stages (pathologic with/without clinical staging) had nonmissing age, sex, histology, and type of surgical procedure. Three prognostic models were defined. Scenario A (all parameters): best pathologic stage, histology, sex, age, type of surgery, adjuvant treatment, white blood cell count (WBC) (≥15.5 or not), and platelets (≥400 k or not) (n = 550). Scenario B (no surgical staging): clinical stage, histology, sex, age, type of surgery, adjuvant treatment, WBC, hemoglobin (<14.6 or not), and platelets (n = 627). Scenario C (limited data): histology, sex, age, WBC, hemoglobin, and platelets (n = 906). Conclusion: Refinement of these models could define not only the appropriate patient preoperatively for best outcomes after cytoreductive surgery but also stratify surgically treated patients after clinical and pathologic staging who do or do not receive adjuvant therapy

The IASLC Lung Cancer Staging Project: A Renewed Call to Participation

Over the past two decades, the International Association for the Study of Lung Cancer (IASLC) Staging Project has been a steady source of evidence-based recommendations for the TNM classification for lung cancer published by the Union for International Cancer Control and the American Joint Committee on Cancer. The Staging and Prognostic Factors Committee of the IASLC is now issuing a call for participation in the next phase of the project, which is designed to inform the ninth edition of the TNM classification for lung cancer. Following the case recruitment model for the eighth edition database, volunteer site participants are asked to submit data on patients whose lung cancer was diagnosed between January 1, 2011, and December 31, 2019, to the project by means of a secure, electronic data capture system provided by Cancer Research And Biostatistics in Seattle, Washington. Alternatively, participants may transfer existing data sets. The continued success of the IASLC Staging Project in achieving its objectives will depend on the extent of international participation, the degree to which cases are entered directly into the electronic data capture system, and how closely externally submitted cases conform to the data elements for the project

Ultra-High-Resolution Computed Tomography of the Lung: Image Quality of a Prototype Scanner

Purpose: The image noise and image quality of a prototype ultra-high-resolution computed tomography (U-HRCT) scanner was evaluated and compared with those of conventional high-resolution CT (C-HRCT) scanners. Materials and Methods: This study was approved by the institutional review board. A U-HRCT scanner prototype with 0.25 mm × 4 rows and operating at 120 mAs was used. The C-HRCT images were obtained using a 0.5 mm × 16 or 0.5 mm × 64 detector-row CT scanner operating at 150 mAs. Images from both scanners were reconstructed at 0.1-mm intervals; the slice thickness was 0.25 mm for the U-HRCT scanner and 0.5 mm for the C-HRCT scanners. For both scanners, the display field of view was 80 mm. The image noise of each scanner was evaluated using a phantom. U-HRCT and C-HRCT images of 53 images selected from 37 lung nodules were then observed and graded using a 5-point score by 10 board-certified thoracic radiologists. The images were presented to the observers randomly and in a blinded manner. Results: The image noise for U-HRCT (100.87 ± 0.51 Hounsfield units [HU]) was greater than that for C-HRCT (40.41 ± 0.52 HU; P <.0001). The image quality of U-HRCT was graded as superior to that of C-HRCT (P <.0001) for all of the following parameters that were examined: margins of subsolid and solid nodules, edges of solid components and pulmonary ves sels in subsolid nodules, air bronchograms, pleural indentations, margins of pulmonary vessels, edges of bronchi, and interlobar fissures. Conclusion: Despite a larger image noise, the prototype U-HRCT scanner had a significantly better image quality than the C-HRCT scanners