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Talking about Treatment: The Language of Populations and the Language of Individuals
In recent years, clinical decisions about treatment have been increasingly guided by the findings of randomized clinical trials. These trials use the strongest type of study design for treatment assessment. They offer the best approach to reducing bias and balancing the distribution of known or unknown patient attributes that could threaten the internal validity of the study (1). The quantitative measures of risk reduction used to report randomized clinical trials describe the collective experience of the participants in the trial. To apply the results of such trials in clinical practice, physicians must translate the concepts and measures used to describe groups of patients into a language that can inform the decisions of an individual patient. A clinical vignette illustrates the tensions inherent in this process of translation.
You are caring for a 74-year-old man whose blood pressure averages approximately 175/85 mm Hg. He has type 2 diabetes mellitus that is controlled by oral medications. On the basis of the findings of a randomized clinical trial, the Systolic Hypertension in the Elderly Program (SHEP) (2), you believe that treatment with antihypertensive medication will reduce his risk for a cardiovascular event. The patient asks you, “If I take this medication, how will it help me?” (The Table provides data from the SHEP trial to inform your answer.)
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Three problems impede an accurate response to your patient's seemingly simple question. First, reports of randomized clinical trials do not usually account for individual characteristics that modify the effect of treatment (3). Second, clinicians and patients often have difficulty interpreting quantitative data about risk and risk reduction (4, 5). Finally, the results of treatment studies can be expressed, or “framed,” in different ways; this can influence how both physicians and patients perceive the efficacy of treatment (6).
You suspect that …
