Evidence-Based Medicine (EBM) figures prominently in these efforts and is vigorously pursued and implemented by corporate healthcare (whose prime directive is to create profit for shareholders).
[The authors] propose a transformation in thinking about how analgesic efficacy and harm should be assessed, and suggest several practical implications of a better understanding and appreciation of therapeutic failure rates:
“No single drug will treat successfully more than a minority of patients with a painful condition.”
Successful pain relief is also likely to improve sleep, depression, fatigue, quality of life, function, and ability to work.
Experience (and some evidence) suggests that failure with one drug does not necessarily mean failure with others, even within a class.
We do not know the best order in which to use drugs, in terms of efficacy, harm, or cost.
Success or failure can be determined within 2-4 weeks, and success, when achieved, tends to be long lasting.
Because success rates are low, a wide range of drugs is needed to do the best for most patients, especially in complex chronic conditions.”
most patient responses are either very good (above 50% pain relief) or very poor (below 15%). Therefore, the frequency distribution curve is more “U-shaped”; rather than the classic bell curve
Patients who get better (responders) typically do well, experiencing improvements in fatigue, depression, and sleep interference, plus better function and quality of life.
Fixed-dose regimens may exacerbate adverse events and discontinuations, resulting in higher failure rates. An alternate approach would be to allow patient-directed drug titration to achieve adequate pain relief with tolerable adverse events;
The authors further observe that guidelines developers often restrict treatment recommendations to 1 or 2 drugs for any pain condition. The developers consider similar drugs to operate as a class, overlooking the fact that there can be important differences in pharmacokinetics or drug interactions across similar medications. Less restrictive guidance recommendations, centered on patient-practitioner interactions
Coupled with the nuances of neurobiological pain modulation, central nervous system transformations, and genetic influences, high failure rates with single pharmacologic interventions are unsurprising.
some current arguments against opioid analgesics for chronic noncancer pain seem to demand that either the therapy works well and for all patients or it is unacceptable — there is no middle-ground or acceptance of failure.
expectations need to be lowered to the level of clinical reality; eg, while long-term opioid therapy may not benefit all patients with chronic noncancer pain, it does help a certain proportion of patients and significantly so.
There is no such thing as an “average” patient, even though research trials tend to define outcomes based on average, or mean, scores on efficacy measures. In doing this, research can be misleading
The most vital question is: what works, for whom, in what circumstances?
A degree of failure should not defeat the pursuit of success when it comes to pain management.