Asalamul alaikom, welcome back to a new series on our channel about biostats we're gonna be starting
with our first video about how to evaluate a diagnostic test so it'll cover sensitivity and
specificity so with that said let's start with sensitivity if you open any textbook
you'll probably be greeted with this definition of sensitivity which is the proportion of those who
do have a disease or test positive in other words it's the probability that when the disease is
present the test is positive now this definition is good when you want to come back and review
sensitivity but it doesn't really alone explain sensitivity so we need a consistent framework
that we can always apply sensitivity to so as to not ever forget it so what is gonna be that
consistent framework let's have it in the form of a two-by-two table so we're gonna put disease
up here and test down here and whenever you know you get a question on sensitivity or specificity
always try and keep the positives where the positives are in the negatives where the negatives
are that way you don't get confused during the actual exam so disease up here test down here
positive here negative here positive here negative here some people do have the disease and look at
tested positive that's a true positive some people do not have the disease and they'll get tested
negative and that is a true negative now sometimes you can have mistakes sometimes the person does
have the disease but they look at tested negative now that's a wrong negative wrong negative false
negative sometimes people do not have the disease they'll get tested positive that's a
wrong positive wrong positive false positive so keep these terms in your head as they'll become
very relevant in the next few concepts so let's talk about the formula for sensitivity it's true
positive / true positive plus false negative so if you go back to the definition it's the
proportion of those who do have the disease who test positive recall that people who do have the
disease in other words these guys true positive and false negative and we're only interested in
these guys which are the true positives those who test positive so it's going to be true positive
these guys over everyone with the disease which are all of these guys - positive and
false negative a good mnemonic to remind you with to always apply it to sensitivity sensitivity you
hear that n and there's a reason why I wrote SN as sensitivity to always remind you that it's going
to be true positive over true positive plus false negative so just remember that false negative and
then flip the other two terms true positive true positive before we talk further about how
sensitivity can rule out disease role in disease etc etc let's quickly contrast it with specificity
which is its exact opposite so specificity its definition is the proportion of those who do
not have the disease who test negative in other words it's the probability that when the disease
is absent the test is negative so those who do not have the disease true negative and false positive
these guys and we're only interested in those who test negative so these guys so it's going to be
true negative true negative over true negative plus false positive everyone without a disease
and that's how the formula makes sense another visual mnemonic specificity here that P just
remember false positive and flip the other two terms to negative to negative so what is all this
talk about ruling in and ruling out diseases if you came across any textbook you probably had the
question in your head how does sensitivity rule out diseases if the entire formula is people with
the disease and I always use this example to hopefully explain this common misconception so
two dogs we'll name the left one max will name the right one Miley Max is a very sensitive dog Miley
is a very specific dog for the purposes of this example let's just pretend that they are a hundred
percent sensitive and specific respectively so to elaborate further on this example let's add a few
more key items so a car a cat and a criminal and just to add the last bit of detail let's suppose
that criminals can wear only two different colors for example red or blue okay so let's start with
max and how he can rule out diseases now recall that he's a sensitive dog and he's a hundred
percent sensitive so go back to your layman term for sensitive it is someone with heightened senses
someone who will not let anything go by without alerting so that's no different for max if a car
walks by he will bark the cat walks by he will bark criminal walks by wearing either color he
will bark now barking here is a positive but if he barks on the cabin car that's false positive
we don't care if a cat or a car walks by we only care for if the criminal walks by so what's the
important interpretation here max can sometimes give us false positives max can sometimes give
us true positives however max when he does not bark I am sure that there is no one outside in
other words if he gives me a negative I am sure there's no one outside I can rule out that there's
no car cats or criminal outside that's where the rules out comes from what about Miley well she's
the exact opposite Miley really hates the color red so if a criminal walks by wearing the color
red she's gonna go nuts and she's gonna start barking so what's the important interpretation
here Miley can sometimes give us false negatives a criminal wearing blue can come in and we'd never
know he's not gonna bark that's a false negative sometimes she can give us true negatives a car
is gonna walk by a cat's gonna walk by and we're never gonna know because Miley is not
gonna bark so that's a true negative however if she starts barking I am certain that there is a
criminal wearing red outside in other words I can rule in the fact that there is a criminal
outside because she's barking that's where the rules in comes from so that's how sensitivity
rules out diseases that's how specificity rules in diseases and with that last part said tune in
for our next video about biostats consider liking and subscribing and as always thanks for watching