Reply to the Letter to the Editor by Hendriks et al.
Authors: Wilfried Ernst Erich Eberhardt, Alan Mitchell, Ramon Rami-Porta
Journal: Journal of Thoracic Oncology (2016)

As the number of patients in the International Association for the Study of Lung Cancer (IASLC) database with stage M1a and M1b disease according to the seventh edition of the Union for International Cancer Control/IASLC staging system is restricted and the number of available parameters to investigate is confined to those that were implemented in the prospective data collection,1Rami-Porta R. Bolejack V. Giroux D.J. et al.The IASLC lung cancer staging project: the new database to inform the eighth edition of the TNM Classification Of Lung Cancer.J Thorac Oncol. 2014; 9: 1618-1624Abstract Full Text Full Text PDF PubMed Scopus (236) Google Scholar we would like to answer the questions brought forward by Hendriks et al. in their letter to the editor as follows: The following three points were raised by Hendriks et al., and consequently, the possibility of performing three further statistical analyses from the existing database were evaluated:1.Examine the proposed M categories by the patient data from the Bronchogenic Carcinoma Cooperative Group of the Spanish Society of Pulmonology and Thoracic Surgery.2.Examine the proposed M categories, accounting for race and histology.3.Comment on the use of positron emission tomography/magnetic resonance imaging (PET/MRI) in the current data set. The analyses in “Results” are based on the same population used for the M descriptor manuscript.2Eberhardt W.E. Mitchell A. Crowley J. et al.The IASLC Lung Cancer Staging Project: proposals for the revision of the M descriptors in the forthcoming eighth edition of the TNM Classification Of Lung Cancer.J Thorac Oncol. 2015; 10: 1515-1522Abstract Full Text Full Text PDF PubMed Scopus (291) Google Scholar The same methods described in the paper were used in these analyses, with the addition of a stratified regression analysis to include information on country, race, and histologic diagnosis. For both groups of data, M1a and M1b tend to be more similar and appear to have survival rates distinctly different from those for M1c. There is very little follow-up for subjects beyond 18 months, and care should be taken to not overinterpret the tails of the curves in the figure containing cases from China, the United States, and other countries (Fig. 1). The regression model stratified by histologic diagnosis and country provided hazard ratios nearly identical to those provided by the models presented in the article (Table 1). On the basis of this stratified model, we still see that single metastasis in a single organ is more like M1a in terms of overall survival. Similarly, cases with multiple lesions in a single organ are more similar to cases with metastases in multiple organs.Table 1Stratified Multivariate Regression Model, Overall SurvivalData from Eberhardt et al.2Eberhardt W.E. Mitchell A. Crowley J. et al.The IASLC Lung Cancer Staging Project: proposals for the revision of the M descriptors in the forthcoming eighth edition of the TNM Classification Of Lung Cancer.J Thorac Oncol. 2015; 10: 1515-1522Abstract Full Text Full Text PDF PubMed Scopus (291) Google ScholarVariablen/N (%)HR (95% CI)p Valueap Value from chi-square test score in Cox regression.M1a324/1025 (32)Reference GroupM1b, single organ/lesion225/1025 (22)1.195 (0.97–1.47)0.0943M1b, single organ/multiple lesions229/025 (22%)1.646 (1.345–2.013)<0.0001M1b, multiple organs247/1025 (24)1.997 (1.641–2.430)<0.0001Model stratified by histologic diagnosis (squamous cell carcinoma, adenocarcinoma, non–small cell cancer not otherwise specified, and other) and country/data.HR, hazard ratio, 95% CI, 95% confidence interval.a p Value from chi-square test score in Cox regression. Open table in a new tab Model stratified by histologic diagnosis (squamous cell carcinoma, adenocarcinoma, non–small cell cancer not otherwise specified, and other) and country/data. HR, hazard ratio, 95% CI, 95% confidence interval. Information on the use of imaging methods such as PET and MRI to detect distant metastatic disease was not collected in the latest version of the IASLC database. The collection and use of this information would need to be discussed for the next iteration of the IASLC database. On the basis of the best available information in the current data set for developing the proposals for the M descriptors for the eighth edition of the tumor, node, and metastasis staging classification and the requested additional analyses, our conclusions for the statement of the proposals remain basicly unchanged. We have to keep in mind that none of the previously implemented proposals in the sixth and seventh editions of the staging system were ever meant to be perfect or a final answer to the existing problems. This will also hold true for the proposals for the M descriptors of the eighth edition of the tumor, node, and metastasis staging classification for lung cancer. It is the duty of us all to prospectively collect more relevant information and data in our individual centers and submit them for the next IASLC database initiative, which will (like the ones before it) be open to participation by interested investigators in all countries worldwide. It is hoped that this enormous amount of work will then bring us a little closer to the optimal worldwide staging system toward which we are probably all aiming.