Contents
What is conditional survival?
Conditional survival (CS) is defined as the probability of surviving further t years, given that a patient has already survived s years after the diagnosis of a chronic disease.
How do you calculate conditional survival probability?
The estimate for surviving through Year 1 is simply 95/100=0.95. And if one does survive through Year 1, the conditional probability of then surviving through Year 2 is 82/92=0.8913. The estimated probability of surviving through both Year 1 and Year 2 is therefore (95/100)x(82/92)=0.8467.
What is relative survival rate?
Listen to pronunciation. (REH-luh-tiv ser-VY-vul …) A way of comparing the survival of people who have a specific disease with those who don’t, over a certain period of time. This is usually five years from the date of diagnosis or the start of treatment for those with the disease.
Which is the standard definition of conditional survival?
This conditional probability, usually referred to as conditional survival ( CS; refs. 2, 3 ), is given as by using the standard definition of a conditional probability.
Which is an example of a conditional probability?
Thus, for example, denotes the conditional probability of surviving years, given that the patient is still alive at s = 2 years; with s usually being called the prediction time or, more precisely, the time at which the prediction is made.
Why is conditional survival important in cancer research?
CS provides valuable and relevant information on how prognosis develops over time. It also serves as a starting point for identifying factors related to long-term survival. Clin Cancer Res; 21 (7); 1530–6. ©2015 AACR. No potential conflicts of interest were disclosed.
What does the survival function’s ( t ) mean?
The survival function S ( t) attached to OS denotes the probability that a patient will still be alive t years after diagnosis. Thus, the survival function S ( t) provides the relevant information for the patient and the treating physician at t = 0, that is, the time of diagnosis.