Survival after cancer diagnosis strongly depends on local tumor extent, lymph node involvement and the presence of distant metastases. However, there remains great inter-patient variability regarding treatment outcome. A combination of molecular factors, biochemical factors, histopathological features, genomic profile, environmental factors and other clinical factors are likely to influence prognosis and treatment effect, independent from tumor stage. It is however still unclear which, how, and to what extent these factors will influence tumor recurrence and mortality in both early stage (I-III) and late stage (IV) thoracic malignancies such as lung cancer. Although the results from prospective clinical trials will remain the backbone of evidence-based medicine, this concerns a highly selected patient population since the large majority (85%-95%) of patients with cancer do not participate in clinical trials for various reasons. It is unlikely that trial participation will significantly improve in the near future. This fact has the following implications: 1. It is highly desirable to validate the results from clinical trials in the general patient population. This is complicated by the fact that the documentation of patients treated in general practice (i.e. outside the scope of clinical trials) is largely insufficient to provide comparable patient cohorts in terms of prognostic characteristics and treatment parameters. 2. There is an ever increasing number of therapeutic interventions available for which its efficacy depends on known and unknown tumor-specific, clinical, demographic and other patient characteristics. Large numbers of patients are required to test the relevance of these variables. 3. As a result of rapid technical and drug developments, new minimally invasive treatment options such as stereotactic irradiation or ablation techniques or sublobar resections and new targeted and immunotherapeutic treatments have entered the clinic. These interventions have potentially less side effects compared to the conventional treatments. Still, these new interventions will have to prove their effectiveness, safety and superiority (or non-inferiority) in a real world setting. 4. Many hypotheses related to further optimization of personalized medicine can currently not be tested as they require a large prospective cohort of patients, and a less time-consuming and costly research infrastructure. A prospective observational cohort study has the potential to fill the gap between prospective randomized trials (efficacy) and patients treated in general practice (effectiveness) and it will enable accrual of clinical trials (innovation).