Impacto de las malignidades previas en la supervivencia de los pacientes con carcinoma de células de Merkel

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...

Mitogens and their receptors play a crucial role in controlling the progression of the cell cycle. However, the loss of mitogenic control over cell division leads to tumor formation. Therefore, mitogens and mitogen receptors play an important role in cancer research. For instance, the epidermal growth factor (EGF) - a type of mitogen and its transmembrane receptor (EGFR), decides the fate of the cell's proliferation. When EGF binds to EGFR, a member of the ErbB family of tyrosine kinase...

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...