The number of days that a series of five patients had to wait before starting CBT at a psychotherapy unit is as follows: 12, 12, 14, 16, and 21.
The mean waiting time to get CBT is:
A. The arithmetic mean is calculated from the sum of all individual observations divided by the number of observations. Here the number of observations = 5. The sum of individual observations = 12 + 12 + 14 + 16 + 21 = 75. The average = 75/5 = 15.
Reference:
The most clinically useful measure that helps to inform the likelihood of having a disease in a patient with positive results from a diagnostic test is:
B. The probability that a test will provide a correct diagnosis is not given by the sensitivity or specificity of the test. Sensitivity and specificity are properties of the test instrument – they are not functions of the target population/clinical sample. On the other hand, positive and negative predictive values are functions of the population studied; they provide much more clinically useful information. Predictive values observed in one study do not apply universally. Positive predictive value increases with increasing prevalence of the disease; negative predictive value decreases with increasing prevalence. Sensitivity and specificity, being properties of the instrument used, do not vary with prevalence.
Zarkin et al., 2008 reported the cost-effectiveness comparison of naltrexone and placebo in alcohol abstinence. The mean effectiveness measured as percentage days of abstinence was nearly 80% for naltrexone group while it was 73% for the placebo group. The mean cost incurred for the placebo group was $400 per patient. The naltrexone group incurred a cost of 680 per patient.
How much additional cost needs to be spent per patient for each percentage point increase in total days of abstinence when using naltrexone compared with placebo?
A. The incremental cost-effectiveness ratio (ICERAB) can be defined as the difference in cost (C) of interventions A and B divided by the difference in mean effectiveness(E), (CA – CB )/ (EA – EB ), where intervention B is usually the placebo or standard intervention that is compared with intervention A. In this example, the difference in costs = $680 – 400 = $280. The difference in effectiveness as measured by percentage days of abstinence is 80 – 73% = 7%.
Hence ICER = 280/7 = $40 per patient per percentage point of days of abstinence.
Two continuous variables A and B are found to be correlated in a nonlinear fashion.
All of the following can be considered as suitable statistical techniques for examining this relationship except:
C. When the relationship between two continuous variables is plotted in a graph, the resulting distribution may be a straight line or a curve. If the relationship between the independent (X) variable and dependent (Y) variable appear to follow a straight line, then linear regression can be constructed to predict the dependent variable from the independent variable. Otherwise, one can resort to one of the following methods:
A drug representative presents data on a new trial. The data show that drug A prevents annual hospitalization in 20% more dementia patients than placebo. You are very impressed but your consultant wants to know how many patients you need to treat to prevent one hospitalization.
The correct answer is:
B. The answer to this question can be found by calculating the number needed to treat (NNT). The absolute increase in benefit (ABI) is given by the difference in outcome between two groups. This is 20% as quoted by the drug representative. Hence NNT = 100/20 = 5. You need to treat five patients with the new drug to prevent one annual hospitalization. How small must the NNT be to be clinically impressive? This depends on the availability of other interventions and their NNTs, incremental cost of the proposed intervention, and tolerability of the intervention. The last one can be partly deciphered by calculating the number needed to harm for a notable side-effect of the intervention.
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