Understanding Predictive Value of Positive Test
The question asks for the correct statement regarding the predictive value of a positive test. This value is crucial in interpreting medical test results.
Analyzing Predictive Value Statements
Let's examine each statement:
- Statement 1: It does not tell about diagnostic power of test
This is incorrect. The predictive value of a positive test (Positive Predictive Value, PPV) is a key measure of a test's diagnostic utility or power. It quantifies how likely a positive result accurately indicates the presence of the disease. - Statement 2: The more prevalent the disease, the less accurate the test is
This is incorrect. The relationship between disease prevalence and the predictive value of a positive test is inverse to accuracy. Specifically, a higher disease prevalence generally leads to a *higher* Positive Predictive Value (PPV), assuming the test's intrinsic characteristics (sensitivity and specificity) remain constant. It does not mean the test becomes less accurate overall, but rather the probability of a positive result being true increases. - Statement 3: It tells the probability that a patient with positive test has the disease in question
This statement accurately defines the Positive Predictive Value (PPV). PPV is formally defined as the probability that an individual has the disease given that they have tested positive. Mathematically, $PPV = P(\text{Disease} | \text{Positive Test})$. - Statement 4: It tells the probability that a patient with positive test does not have the disease in question
This is incorrect. This statement describes the complement of the PPV, i.e., $P(\text{No Disease} | \text{Positive Test}) = 1 - PPV$. The predictive value of a positive test specifically addresses the likelihood of *having* the disease.
Therefore, the only true statement is the one defining the Positive Predictive Value correctly.
Important Questions from General Epidemiology
Which of the following statements are correct for incidence rate?
1. It is useful for taking action to control a disease.
2. Rising incidence rates may indicate ineffectiveness of the current control programmes.
3. Fluctuation in incidence rate may indicate a change in aetiology of disease.
Select the answer using the code given below.
Consider the following definition :
"A high level of infection beginning early in life and affecting most of the child population, leading to a state of equilibrium such that the adult population shows evidence of the disease much less commonly than the children."
Which one of the following terms best fits this definition?
- In which one of the following study designs, the unit of study involves populations rather than individuals ?
- Which one of the following best explains the relationship among Prevalence (P), Incidence (I) and Duration (D) of a disease given the assumption that the population is stable?
- Which one of the following is a famous large prospective study that helped establish risk factors for coronary heart disease?
