Drugs A and B are 2 new experimental drugs being tested for the treatment of a novel respiratory viral infection that causes acute respiratory failure and death in children. Part of the testing process is to analyze the 2-week survival after treatment to determine the clinical efficacy of the experimental drugs. A total of 60 children recently diagnosed with the disease are randomly assigned in a 1:1:1 ratio to receive Drug A, Drug B, or placebo. The absolute risk reduction of Drug A compared to placebo was found to be 0.05, whereas the absolute risk reduction of Drug B compared to placebo was found to be 0.20. Based on these results, which of the following statements comparing the effectiveness of Drugs A and B in treating children infected with the novel virus is most appropriate?

Question

Drugs A and B are 2 new experimental drugs being tested for the treatment of a novel respiratory viral infection that causes acute respiratory failure and death in children.  Part of the testing process is to analyze the 2-week survival after treatment to determine the clinical efficacy of the experimental drugs.  A total of 60 children recently diagnosed with the disease are randomly assigned in a 1:1:1 ratio to receive Drug A, Drug B, or placebo.  The absolute risk reduction of Drug A compared to placebo was found to be 0.05, whereas the absolute risk reduction of Drug B compared to placebo was found to be 0.20.  Based on these results, which of the following statements comparing the effectiveness of Drugs A and B in treating children infected with the novel virus is most appropriate?

Quizplus · Accepted Answer

11ec160b_370e_7b74_9249_8f62d449d977_MD0001_00 The absolute risk reduction (ARR) describes the efficacy of a treatment (eg, Drug A) compared to a control group (eg, placebo); it is the difference in the risk (or rate) of a negative event (eg, death) between treatment and control groups: ARR = (Risk_control − Risk_treatment) ARR expressed as a percentage describes the number of negative events (eg, deaths) prevented in 100 patients. For example, an ARR of 0.05 indicates that 5 of 100 patients treated with a treatment (eg, Drug A) would be prevented from developing a negative event. Therefore, to prevent 1 patient from developing a negative event, it would be necessary to treat 100 / 5 = 1 / 0.05 = 20 patients. This is the number needed to treat (NNT). NNT is the number of patients who need to be treated with a treatment (eg, Drug A) to prevent 1 additional negative event (eg, death) compared to a control group (eg, placebo); NNT is the inverse of the ARR: NNT = 1 / ARR A lower NNT indicates more effective treatments because fewer patients would need to be treated to prevent 1 additional negative outcome. NNTs can be used to compare the effectiveness of different treatments within a single study or between similar studies (eg, similar patient characteristics, control groups, duration of follow-up). In this example, a single study is testing 2 treatments (ie, Drugs A and B) against placebo (ie, control group) to prevent death (ie, negative effect) in recently diagnosed children randomized to treatment groups with a similar follow-up (ie, 2-week survival): Drug A requires treating more children to prevent 1 additional death compared to Drug B (20 vs 5). A higher NNT indicates a lower effectiveness; therefore, Drug A is less effective compared to Drug B (Choices A, B, C, and E). Educational objective: The number needed to treat (NNT) is the number of patients who need to receive a treatment to prevent 1 additional negative event. NNT is the inverse of the absolute risk reduction. The lower the NNT, the more effective the treatment because fewer patients need be treated to prevent 1 additional negative event.

Drugs a and B Are 2 New Experimental Drugs Being