Imagine the following situation: you read a paper in the New England Journal of Medicine and see that disease prognosis has gone up for a certain disease. Your colleague sitting next to you claims that she doesn’t believe the data and that she thinks that this perceived improvement of prognosis is actually due to better screening. Could that really be the case? Find out in this short video from our Epidemiology Essentials course.
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[00:00:00] Once a disease has been diagnosed, we as clinicians and the patients would like to know the outlook or, in other words, the prognosis. There are a couple of ways to express prognosis. In this lesson, we are going to talk about two commonly applied indicators. The five-year survival rate and the case fatality rate. Let's start with the five-year survival rate. It's commonly used in oncology to express the proportion of individuals surviving a cancer for at least five years.
[00:00:30] If 60% make it to the fifth year, the five-year survival rate is set to be 60%. Now, there are certain problems associated with the five-year survival rate. This is the natural course of a disease like cancer. the five-year period starts at diagnosis. However, the disease itself starts earlier. Biologic onset is when something goes wrong, on a cellular level, that's when the disease starts. Then there's a point at which pathological evidence could be found,
[00:01:00] if it was sought, then usually signs and symptoms develop, which get the patient to seek medical care after which the diagnosis is usually established and therapy is initiated. The five-year period used for the calculation of five-year survival starts with the diagnosis. Now, imagine a new screening test being introduced, which detects the disease at a much earlier point than before. Let's assume we have a patient whom prostate cancer
[00:01:30] is diagnosed in 2012 and in 2016, after disease duration of four years, he dies from it. So, with respect to five-year survival, he would be calculated as a death. Now, let's assume that in 2010, men were aggressively screened for prostate cancer with PSA analysis in this community. And let's say his cancer was picked up earlier by the screening initiative in 2010. Now, even without
[00:02:00] any improvements with respect to treatment, the same patient would now live for six years after diagnosis and he'd be counted as a survivor and not as a death in the same five-year survival analysis. So, the key take-home message is this, if you see an improvement of five-year survival rates, over time, such as shown here, ask yourself, does this have to do with an improvement of care or is it due to better screening? Now, let's turn to case fatality
[00:02:30] rate. As we have learned, in the previous lessons, case fatality rate is calculated as the number of people who die from a disease, divided by the number of people with the disease, times 100. Case fatality rate is generally used for acute diseases and here's why. So, this is the duration of the acute disease. If a person with the disease dies within this short time period, it's very likely due to his acute illness. Conversely, this is the duration of a chronic disease,
[00:03:00] which ends in death or cure, let's say. Case fatality rate is less useful here because the disease can go on for years and decades. Think about it. Throughout the life of a chronically ill patient, many potentially life-threatening diseases or accidents can occur. So, if someone with the disease dies, it's quite possible that the cause of death is unrelated to the disease of interest, which makes case fatality rates less useful in this setting. Coming up,
[00:03:30] more cool ways to measure disease prognosis. So, stay tuned.