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#1




The probability of Positive Test!
Medical clinic wants to assess population for CHF. measurement of BNP to be able to detect CHF with sensitivity 90% and specificity 90%. 1 in 10 in the population have CHF. Which is the approximate probability that the next patient who walks into the clinic has CHF with abnormal BNP value
A 0.09 B 0.10 C 0.50 D 0.81 E 0.90 Found this questiona bit confusing will try getting the answer. mean while any guesses and explanations!! 
#2




CHF with an abnormal BNP value implies true positive ? ? Think the answer is 0.9 ???

#3




i'm thinking E. 0.90.......i'm not sure though(i'm bad at stats)
CHF prevalence1 in 10 0.1 likelihood ratio is used to assess whether the disease condition exist in a patient(remember doing a question from uworld).. positive likelihood ratio= sensitivity/1specificity = 0.90/10.90 ==> 9 so with the prevalence of 0.1 in population for CHF, the probability he is diseased would be9 * 0.1===>0.9 thanks 
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alice (10162012) 
#4




this question is super tricky found it on kaplan q bank simulated test. keep posting in your answers , i will post the right answer in sometime.
@venky2600 & @alice  i too got the same answer 
#5




B. 0.10 ??????

#6




Quote:
ohh so i may be thinking it as A) 0.09 coz with such gr8 sensitivity and specificity test(with 9 likelihood ratiomeans the result is likely accurate) should show results very accurately as population has 1 in 10 (0.1)so, the probability of disease with this accurate test must be less than 0.1so thinking of 0.09(just thinking logically) thanks 
#7




c)
by the way i m confused by languge of question they are asking PPV?
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#8




Phew!! .. Biostats .. : waiting for the answer ...

#9




I would choose C), because the question asks what is the PPV (probability that a person with a positive test result  abnormal BNP  actually has the disease CHF)
So, if you make a 2/2 table you will get TP=9, FP=9, FN=1, TN=81, because the prevalence of the disease is 10 % (meaning that 10 people out of 100 really have the disease). So the PPV=TP/TP+FP >9/18 = 0.5 
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nishaa (10162012) 
#10




my answer :)
A 0.09

#11




Quote:
So it would be E. 0.90 Sent from my iPad using Tapatalk HD
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#12




C
Answer is C 0.50
This is the explanation I got: · Set up 2x2 table using a total of 100. Next put down as 10 people who have the disease, 90 who do not have the disease ( prevalence is 1 in 10 which is 10 in 100: prevalence of CHF = 10%) · Multiply the sensitivity of 0.90 by 10 diseased persons to get TRUE POSITIVE. TP= 9 · Remaining 1 person is FALSE NEGATIVE. FN= 1 · Multiply specificity 0.90 by 90 non diseased persons to get TRUE NEGATIVE TN=0.81 · Remaining 9 persons are FALSE POSITIVE FP= 9 disease present no disease test positive 9(TP) 9(FP) test negative 1(FN) 81(TN) PPV using above table = TP/TP+FP= 9/18 =0.50 I found this exact explanation on kaplan test.. Hope this new (wierd) concept helps ya' all @Teona congrats you nailed it!!! Last edited by nishaa; 10162012 at 09:43 PM. 
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venky2600 (10172012) 
#13




Ya this Kaplan explanation is really hard to digest. That also with GERD of other informations. Hehhee
I thought this question with other view. Need other people suggestions As question say 1 in 10 already affected. That means 10 out of 100 is already affected. So, we have diseased 10 and non disease 90. Now if we construct 2x2 table Diseased. Non diseased Test +. 9 9 Test  1. 81 Total. 10. 100 So PPV= TP/TP+FP = 9/9+9= 1/2= 0.5 Sent from my iPad using Tapatalk HD
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#14




Quote:
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#15




C is answer 9/18
PPV= 9/ 9 + 9 i.e. 50%
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#16




Answer is C:0.5
1 u make 2x2 table and assume the total as a big number minimum to be 1000. 2 You use to prevalence value giving to you to distribute it into the column of diseased people with TP= 90 FN=10 to match the 90 % sensitivity this will form total diseased as 100 which confirm the prevalence as = 100/1000 = 0.1 3 Now 2 cells left to fill by specificity data which = 90% so FP= 90 , TN=810 4 Now you have complete 2x2 table and all what's left to calculate the posttest probability (PPV)= TP/ ( TP+ FP ) PPV = 90 / ( 90 + 90 ) = 0.5
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#17




Quote:
yep you are right the explanation too means the same its just too long and bit complicated. idea is to figure out the prevalence which is 10 in 100. then compute true positive from sensitivity (90% of 10) then figure out true negative from specificity (90% of 90). rest is simple to compute ppv by making a table. i spent 2 hrs reading kaplan explanation finally got it !! 
#18




This question seems so hard for some reason!! I cant get my head around it?! And im done with the biostats part from uworld!
Do you think we'll get these sorta questions on the real exam? Cuz i better learn it well then... Thanks for the question nishaa 
#19




Quote:
as according to kaplan PPV : is the probabilty of a disease in a person WHO RECEIVES A POSITIVE TEST RESULT please can some one throw more light on how question was precisely asking PPV???? 
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Relid (10172012) 
#20




Quote:
When i first read the question i automatically recalled the multiplication rule. In this example, prevalence x TP result (maybe TP+FP???, because the test may falsely show abnormal BNP, but it's still abnormal BNP value!!!)... Exactly just what the q asks for, and not PPV. Can someone explain? Really appreciate it! 
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offpiste (10172012) 
#21




My Guess
Quote:
I see other people's posting of the correct answer from the source but the interpretation of this question does not make sense to me. I did it this way: 1 the odds that a pt has CHF = 1/10 2 odds the pt will have a true positive= 9/10 1/10 x 9/10 = 9/100 =.09 A Then I scrolled down and saw it is C, I understand how to get C but how does "Which is the approximate probability that the next patient who walks into the clinic has CHF with abnormal BNP value" mean they want you to get PPV based on the question. I think Kaplan worded this wrong or I am reading it wrong. If someone can shed some light on how that's what they were asking; do not want to be stuck on the exam answering the wrong question just because I read it wrong!! Thank you for any feedback! 
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BiostatisticsEpidemiology, Step1Questions 
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