The overarching goals of treatments for orthopedic conditions are generally to improve or restore function and alleviate pain. Results of clinical trials are generally used to determine whether a treatment is efficacious; however, a statistically significant improvement may not actually be clinically important, i.e., meaningful to the patient. To determine whether an intervention has produced clinically important benefits requires a two-step process: first, determining the magnitude of change considered clinically important for a particular measure in the relevant population and, second, applying this yardstick to a patient’s data to determine whether s/he has benefited from treatment. Several metrics have been devised to quantify clinically important differences, including the minimum clinically important difference (MCID) and clinically important difference (CID). Herein, we review the methods to generate the MCID and other metrics and their use and interpretation in clinical trials and practice. We particularly highlight the many pitfalls associated with the generation and utilization of these metrics that can impair their correct use. These pitfalls include the fact that different pain measures yield different MCIDs, that efficacy in clinical trials is impacted by various factors (population characteristics, trial design), that the MCID value is impacted by the method used to calculate it (anchor, distribution), by the type of anchor chosen and by the definition (threshold) of improvement. The MCID is also dependent on the population characteristics such as disease type and severity, sex, age, etc. For appropriate use, the MCID should be applied to changes in individual subjects, not to group changes. The MCID and CID are useful tools to define general guidelines to determine whether a treatment produces clinically meaningful effects. However, the many pitfalls associated with these metrics require a detailed understanding of the methods to calculate them and their context of use. Orthopedic surgeons that will use these metrics need to carefully understand them and be aware of their pitfalls.

The seriousness of health outcomes associated with tampering with POs warrants the development of PO formulations that prevent or deter tampering.

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PMPs can become a useful public health surveillance tool to monitor the medical and non-medical use of prescription opioids and to inform public health and safety policy.

Qutenza® is a capsaicin patch used to treat peripheral neuropathic pain, including postherpetic neuralgia (PHN) and human immunodeficiency virus-associated neuropathy (HIV-AN). The Qutenza Clinical Trials Database has been assembled to more fully characterize the effects of Qutenza. We conducted a within-subject meta-analysis of Qutenza studies to further define the medication's efficacy profile across studies. The meta-analysis combined individual patient data from randomized, controlled studies of Qutenza in peripheral neuropathic pain (1458 subjects treated with approved doses of Qutenza or control patches; 1120 with PHN and 338 with HIV-AN). These 7 studies had similar designs and were performed with the high-dose 8% capsaicin Qutenza patch and a 0.04% low-dose control patch. The difference between treatment groups for the primary efficacy end point of percentage change from baseline to weeks 2 to 12 on pain intensity score was calculated. Response was defined as a ≥ 30% decrease in mean pain intensity score during weeks 2 to 12. The overall between-group difference in percentage change from baseline in pain intensity was 8.0% (95% confidence interval 4.6, 11.5; P<.001), which statistically significantly favored Qutenza over low-dose control. Qutenza superiority was demonstrated for both PHN and HIV-AN patients for the primary end point and the end point proportion of 30% pain reduction response, and for PHN patients for the end point of proportion of 50% pain reduction response. These results confirm that Qutenza is effective for the treatment of both PHN and HIV-AN compared to low-dose control patch.