Clinical and Biological Interpretation of Survival Curves of Cancer Patients, Exemplified With Stage IV Non-Small Cell Lung Cancers With Long Follow-up - Baak, Jan P. A.; Li, Hegen; Guo, Huiru (Frontiers in Oncology, 2022)
Worldwide, 18.1 million new invasive cancers and 9.9 million cancer deaths occurred in 2020. Lung cancer is the second-most frequent (11.4%) and with 1.8 million deaths, remains the leading cause of cancer mortality. About 1.7 million of the lung cancers are of the Non-Small Cell Lung Cancer (NSCLC) subtype and of these, 60% - 70% are in advanced stage IV at the time of diagnosis. Thus, the annual worldwide number of new NSCLC stage IV patients is about 1 million and they have a very poor prognosis. Indeed, 25%-30% die within 3 months of diagnosis. However, the survival duration of the remaining 700,000 new patients per year surviving > 3 months varies enormously. Surprisingly little research has been done, to explain these survival differences, but a recently it was found that classical patients-´, tumour- and treatment-features cannot accurately distinguish short- and very long-term survivors. What then are the causes of these bewildering survival variations amongst “the same cancers”? Clonality, proliferation differences, neovascularization, intra-tumour heterogeneity, genetic inhomogeneity and other cancer hallmarks play important roles. Considering each of these, single or combined, can greatly improve our understanding. Another technique is analysis of the survival curve of a seemingly homogeneous group of cancer patients. This can give valuable information about the existence of subgroups and their biological characteristics. Different basic survival curves are discussed and what their shapes tell about the biological properties of these invasive cancers. Application of this analysis technique to the survival curve of 690 stage IV NSCLC patients with 3.2-120.0 months survival suggests, that this seemingly homogeneously group of patients probably consists of 4-8 subgroups with very different survival. A subsequent detailed mathematical analysis shows that a model of 8 subgroups, gives a very good match with the original survival curve of the whole group. In conclusion, the survival curve of a seemingly homogeneous group of cancer patients can give valuable information about the existence of subgroups and their biological characteristics. Application of this technique to 690 NSCLC Stage IV patients, makes it probable that 8 different subgroups with very different survival rates exist in this group of cancers.