Optimizing the Use of Patient Data to Improve Outcomes for Patients: Narcotics for Chronic Noncancer Pain

Jason W Busse; Gordon H Guyatt


Expert Rev Pharmacoeconomics Outcomes Res. 2009;9(2):171-179. 

In This Article

Abstract and Introduction


Randomized trials can provide important direction to clinical decision-making; however, their strength of inferences may be weakened by methodological limitations, the extent that their reported outcomes fail to address patient-important end points and by failing to report results that provide interpretable estimates of magnitude of effect. Strategies that investigators can use to address interpretability include reporting mean differences between groups in relation to the minimal important difference and reporting the proportion of patients who benefit from treatment and the associated number needed to treat. These strategies also apply to reporting pooled estimates from meta-analyses, even when studies use different instruments to measure the same construct. We illustrate these techniques using, as an example, current evidence for the use of opioids in chronic noncancer pain.


Treatment with opioids for patients presenting with chronic noncancer pain (CNCP) remains controversial and, when considering this therapy, clinicians and patients are faced with the task of understanding the magnitude of both desirable and undesirable outcomes. Applying the results of clinical trials to individual patient care requires assessment of methodological rigor, and even high-quality studies may limit their strength of inferences by reporting an effect of treatment on surrogate end points that may or may not translate into patient-important outcomes. Interpretation of study results is further challenged when outcomes are reported as continuous data. We will offer suggestions regarding how best to report results of individual studies and systematic reviews.


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