The IASLC Staging and Prognostic Factors Committee has collected a new database of 94,708 cases donated from 35 sources in 16 countries around the globe. This has now been analysed by our statistical partners at Cancer Research And Biostatistics and, in close collaboration with the members of the committee proposals have been developed for the T, N, and M categories of the 8th edition of the TNM Classification for lung cancer due to be published late 2016. In this publication we describe the methods used to evaluate the resultant Stage groupings and the proposals put forward for the 8th edition.

An extensive analysis has produced stage classification proposals for lung cancer with a robust degree of discriminatory consistency and general applicability. Nevertheless, external validation is encouraged to identify areas of strength and weakness; a sound validation should have discriminatory ability and be based on an independent data set of adequate size and sufficient follow-up with enough patients for each subgroup.

This large study with highly complete follow-up shows a reduced overall mortality in male cockpit and female cabin crews, an increased mortality of aircraft accidents and an increased mortality in malignant skin melanoma in cockpit crew. Further analysis after longer follow-up is recommended.

Background: Very few population based results have been presented for survival after resection for lung cancer. The purpose of this study was to present long term survival after resection and to quantify prognostic factors for survival. Methods: All lung cancer patients diagnosed in Norway in 1993-2002 were reported to the Cancer Registry of Norway (n = 19 582). A total of 3211 patients underwent surgical resection and were included for analysis. Supplementary information from hospitals (including co-morbidity data) was collected for patients diagnosed in 1993-8. Five year observed and relative survival was analysed for patients diagnosed and operated in 1993-9. Factors believed to influence survival were analysed by a Cox proportional hazard regression model. Results: Five year relative survival in the period 1993-9 was 46.4% (n = 2144): 58.4% for stage I disease (n = 1375), 28.4% for stage II (n = 532), 15.1% for IIIa (n = 133), 24.1% for IIIb (n = 63), and 21.1% for stage IV disease (n = 41). The high survival in stage IIIb and IV was due to the contribution of multiple tumours. Cox regression analysis identified male sex, higher age, procedures other than upper and middle lobectomy, histologies such as adenocarcinoma and large cell carcinoma, surgery on the right side, infiltration of resection margins, and larger tumour size as non-favourable prognostic factors. Conclusions: Survival was favourable for resected patients in a population based group including subgroups such as elderly patients, those with advanced stage, small cell lung cancer, tumours with nodal invasion, and patients with multiple tumours. These results question the validity of the current TNM system for lung cancer with regard to tumour size and categorization of multiple tumours.

Carcinoids are rare malignant tumors and are, in most cases, resectable; the TC subgroup had better prognosis than the AC in univariate analyses. The main cause of death was metastasis/locally advanced tumor at presentation or recurrent disease following resection; both situations were three times more common in patients with AC.

Background Countries with a similar expenditure on healthcare within Europe exhibit differences in lung cancer survival. Survival in lung cancer was studied in 2001e2004 in England, Norway and Sweden. Methods Nationwide cancer registries in England, Norway and Sweden were used to identify 250 828 patients with lung cancer from England, 18 386 from Norway and 24 886 from Sweden diagnosed between 1996 and 2004, after exclusion of patients registered through death certificate only or with missing, zero or negative survival times. 5-Year relative survival was calculated by application of the period approach. The excess mortality between the countries was compared using a Poisson regression model. Results In all subcategories of age, sex and follow-up period, the 5-year survival was lower in England than in Norway and Sweden. The age-standardised survival estimates were 6.5%, 9.3% and 11.3% for men and 8.4%, 13.5% and 15.9% for women in the respective countries in 2001e2004. The difference in excess risk of dying between the countries was predominantly confined to the first year of follow-up. The relative excess risk ratio during the first 3 months of follow-up comparing England with Norway 2001e2004 varied between 1.23 and 1.46, depending on sex and age, and between 1.56 and 1.91 comparing England with Sweden.

Background: There is considerable variability in reported postoperative mortality and risk factors for mortality after surgery for lung cancer. Population-based data provide unbiased estimates and may aid in treatment selection. Methods: All patients diagnosed with lung cancer in Norway from 1993 to the end of 2005 were reported to the Cancer Registry of Norway (n = 26 665). A total of 4395 patients underwent surgical resection and were included in the analysis. Data on demographics, tumour characteristics and treatment were registered. A subset of 1844 patients was scored according to the Charlson co-morbidity index. Potential factors influencing 30-day mortality were analysed by logistic regression. Results: The overall postoperative mortality rate was 4.4% within 30 days with a declining trend in the period. Male sex (OR 1.76), older age (OR 3.38 for age band 70-79 years), right-sided tumours (OR 1.73) and extensive procedures (OR 4.54 for pneumonectomy) were identified as risk factors for postoperative mortality in multivariate analysis. Postoperative mortality at high-volume hospitals (>20 procedures/year) was lower (OR 0.76, p = 0.076). Adjusted ORs for postoperative mortality at individual hospitals ranged from 0.32 to 2.28. The Charlson co-morbidity index was identified as an independent risk factor for postoperative mortality (p = 0.017). A prediction model for postoperative mortality is presented. Conclusions: Even though improvements in postoperative mortality have been observed in recent years, these findings indicate a further potential to optimise the surgical treatment of lung cancer. Hospital treatment results varied but a significant volume effect was not observed. Prognostic models may identify patients requiring intensive postoperative care.

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