The risk of developing Kaposi sarcoma after a primary malignancy: A surveillance, epidemiology and end results-based...

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...

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,...

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...

Rous Sarcoma virus or RSV was discovered by F. Peyton Rous in the year 1911 as a filterable transmissible agent that could cause tumors in chickens. He won a Nobel Prize for this discovery in 1966. His experiments clearly demonstrated that some cancers could be caused by infectious agents and led to the discovery of many more cancer-causing viruses in animals as well as humans.
RSV is a retrovirus that contains two copies of a plus-strand  RNA genome. Its genome consists of four main open...

Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.

Retroviruses are RNA viruses that have been shown to cause cancers in diverse species, including chickens, mice, cats, and monkeys. The RNA genomes of these viruses are first reverse-transcribed into single and then double-stranded DNA (dsDNA) copies. This dsDNA called proviral DNA then integrates into the host genome. Subsequently, the host cell transcribes the proviral DNA in concert with the chromosomal DNA. This leads to the production of viral RNA and proteins that assemble at the host...