New Math: Taking on Overdiagnosis Waste and Harm Flipped Classroom: Pre-work

Transcription

1 New Math: Taking on Overdiagnosis Waste and Harm Flipped Classroom: Pre-work IHI Forum, Session C24 Faculty: Dr. James Leo, Helen Macfie

2 Session Objectives Understand the difference between absolute and relative risk reduction and the numbers needed to treat or harm, as well as the relationship between NNT and value versus waste Describe the impact of publication bias on evidence-based medicine evaluations Identify clinical decision support tools to alert practitioners to overdiagnosis and overtreatment and develop a strategic focus and tools to reduce resulting harm and waste

3 Flipped Classroom Pre-Work Please review the definitions on slide 4-7, review the attached abstract/article and then answer the questions on slide 8

4 Absolute Risk Reduction Wikipedia In epidemiology, the absolute risk reduction, risk difference or absolute effect is the change in the risk of an outcome of a given treatment or activity in relation to a comparison treatment or activity. It is the inverse of the number needed to treat. In general, absolute risk reduction is the difference between one treatment comparison group's event rate (EER) and another comparison group s event rate (CER). The difference is usually calculated with respect to two treatments A and B, with A typically a drug and B a placebo. For example, A could be a 5-year treatment with a hypothetical drug, and B is treatment with placebo, i.e. no treatment. A defined endpoint has to be specified, such as a survival or a response rate. For example: the appearance of lung cancer in a 5- year period. If the probabilities p A and p B of this endpoint under treatments A and B, respectively, are known, then the absolute risk reduction is computed as (p B p A )

5 Relative Risk Reduction Wikipedia In epidemiology, the relative risk reduction is a measure calculated by dividing the absolute risk reduction by the control event rate Like many other epidemiological measures, the same equations can be used to measure a benefit or a harm (although the signs may need to be adjusted, depending upon how the data was collected)

6 Number Needed to Treat Wikipedia The number needed to treat (NNT) is an epidemiological measure used in communicating the effectiveness of a healthcare intervention, typically a treatment with medication. The NNT is the average number of patients who need to be treated to prevent one additional bad outcome (e.g. the number of patients that need to be treated for one to benefit compared with a control in a clinical trial). It is defined as the inverse of the absolute risk reduction. It was described in The ideal NNT is 1, where everyone improves with treatment and no one improves with control. The higher the NNT, the less effective is the treatment. NNT is similar to number needed to harm (NNH), where NNT usually refers to a therapeutic intervention and NNH to a detrimental effect or risk factor. NNT is an important measure in pharmacoeconomics. If a clinical endpoint is devastating enough (e.g. death, heart attack), drugs with a high number needed to treat may still be indicated in particular situations. If the endpoint is minor, health insurers may decline to reimburse drugs with a high NNT.

7 Sample Math Mortality in Control Group = 4% Mortality in Treatment Group = 1% Answer Math RRR: Relative Risk Reduction the relative reduction in adverse outcome with a given treatment RRR = 75% (4%-1%) 4% ARR: The absolute reduction in likelihood of the adverse outcome ARR = 3% (4% - 1%) NNT: How many patients you have to treat to achieve the desired outcome, or to avoid the undesired outcome/harm (NNTB, NNTH) NNT = ARR =

8 Now You Try It Understanding Study Results: Questions re: the IMPROVE-IT Trial Please review the attached abstract from the IMPROVE-IT Trial. The full study can be accessed and downloaded for free from or by Googling IMPROVE-IT Trial and clicking on the first website listed Questions to review/answer What is the Absolute Risk Reduction for the primary endpoint for patients receiving the study drug vs. control drug? ARR: For the reader perusing the Conclusion section of the abstract, do the conclusions over-generalize the results? YES/NO If so, how so? Assuming a monthly cost of the study drug (simvastatin 40 mg ezetemibe 10 mg) of $290 (current price as of November, 2016 per in Southern California) vs. $8 per month for simvastatin 40 mg, what is the cost per primary end point avoided? Cost: What is the impact of generalizing the results of this trial on the cost per avoided event?

9 Extra Credit Review the attached Editorial from JAMA: Evolving Approaches for Statins in Primary Prevention Progress, but Questions Remain. JAMA, November 15, 2016 Evolving Approaches for Statins in Primary Prevention Progress, but Questions Remain Ann Marie Navar, MD, PhD; Eric D. Peterson, MD, MPH