Empirical is typically defined1 as “originating in or based on observation or experience” (e.g., empirical data), “relying on experience or observation alone often without due regard for system and theory” (e.g., an empirical basis for a theory), or “capable of being verified or disproved by observation or experiment” (e.g., empirical laws). It is quite common for this term to be used in the context of medical decision-making, especially regarding decisions about prescribing medication-based therapies. In fact, in many circumstances appropriateness of medication and dosing regimens are often reproducibly determined based on an experiential or empirical basis of a number of variables including:
1. Prior experience with the particular medication with other patients
2. Anecdotal prescribing recommendations by other healthcare providers and colleagues
3. Patient-level demographics including:
- Allergy/side effect profile history
- Presence of co-existing medical conditions
4. Physiologic status including:
- Hepatic function
- Renal function
- Cardiac function
- Volume of distribution
5. Other patient-level considerations including:
- Metabolic “competition” with other medications (e.g., drug-drug interactions)
- Serum protein levels
- State of nutrition
- Alcohol/substance abuse history
Opioid analgesics are often used in the treatment of post-surgical, cancer-related and in certain patients with non-cancer-related pain as well. While it is certainly reasonable for clinicians to make empiric decisions about specific opioid medication selection and dosing regimens, it is also important to recognize that there may also be many situations where patient responses might be different from those expected; including diminished response, exaggerated response, or no response at all to what appears to be similar medications within the drug class.
The Role of Metabolism
Efficacy and tolerability of specific opioids can vary substantially, and trials of several opioids may be necessary before finding the maximal balance of efficacy and tolerability2. A good place to start to explain variability in opioid response is metabolic variation, which can occur for a number of reasons. Opioid metabolism may vary based on specific patient demographics, such as age, gender, and ethnicity2. It is also important to remember that in the context of metabolism of opioids and most other pharmacologic agents that both pharmacokinetic and pharmacodynamics differences may often be responsible for these deviations from expected therapeutic responses.
Pharmacokinetics refers to how a body alters the medication3. — Can contribute to the variability in how a patient responds to an to opioid by affecting the bioavailability, production of active or inactive metabolites, and ultimately elimination from the body
Pharmacodynamics refers to how the medication affects the body3. — Can contribute to variability in how a patient responds to an opioid and include patient-level differences in specific opioid receptors and differences in binding to receptor subtypes2
Variability in the way opioids are metabolized can result in decreased therapeutic effect in certain situations, such as excretion from the body more rapidly than expected, inability to reach the target receptors, etc., or increased therapeutic effect resulting from prolonged exposure to increased blood levels.
Additionally, different opioid medications may vary with respect to how they are metabolized. Most opioids experience the “first-pass effect” of hepatic metabolism, which reduces the bioavailability of the opioid before it ever enters the bloodstream. Hepatic metabolism often involves the cytochrome P450 (CYP450) enzymes CYP3A4 (also found in the walls of the small intestine) and CYP2D6. This is a complex and interactive enzyme system, and there is potential with most opioids and other medications metabolized through these same enzyme systems for substantial interaction that can affect how opioid is metabolized. Some medications may act as enzyme inducers, facilitating opioid metabolism (resulting in increased metabolism and reduced blood levels) and some may act as enzyme inhibitors, hindering opioid metabolism (resulting in decreased metabolism and increased blood levels). Common inhibitors include simvastatin, some of the mycin class of antibiotics, anti-retroviral agents, and certain common foods (most notably grapefruit juice). Common inducers include statins (including simvastatin, which may also be an inhibitor in some people as well), pentobarbital, certain anticonvulsants, and even caffeine. Of note is that there are certain opioid analgesics that have relatively little or minimal amount of their metabolism through the CYP450 system; these include oxymorphone, hydromorphone, and tapentadol.
The Role of Genetics
Genetics may also play a role in the patient-level variability of metabolic responsiveness to opioids, with more than 20 possible variations in the CYP2D6 enzyme alone4. These particular poly-morphisms vary within the major ethnic groups, occurring in up to 10% of White, 2% of African-American, and 1% of Asian people5.
Different forms of clinical expression of this genetic variation include patients who may be:
“Normal” metabolizers — Will metabolize the opioid as expected responding appropriately to empiric dosing
“Poor” metabolizers — Either metabolize the opioid less effectively or possibly not at all, and may be predisposed to higher serum blood levels, prolonged half-lives, and more susceptible to toxicity
“Rapid or ultra” metabolizers — Metabolize the opioid more rapidly than empirically expected, yielding either little or no therapeutic response
Another possible genetic explanation for unexpected patient responses to opioids is the presence of receptor-level polymorphisms or multiple µ opioid receptor subtypes6. These variations are thought to have a significant clinical role in variable opioid responsiveness and support the idea that opioid therapy should be individualized on a case by case basis. As one of the leaders in opioid receptor subtypes (GW Pasternak) says “variable responses among patients for individual drugs and for multiple drugs within a single patient preclude “rules” in opioid use.”6
From a clinical standpoint, all of this complex information should be distilled down to the idea that unexpected responses to empirically prescribed opioid regimens including lack of or poor analgesic efficacy, higher than expected doses needed, or exaggerated adverse effect profile (including cognitive changes, respiratory depression, etc.) should prompt at least consideration of the possibility of a metabolic-related, or receptor-related genetic polymorphism in the differential to help determine best course to proceed.
Some valuable clinical practice points include:
1. Safe and appropriate prescribing may likely require individualization of the opioid dose and should be anticipated.
2. Individualization of the opioid selected, or even a trial of a number of different opioids (opioid rotation) may be required in order to appropriately balance safety and therapeutic efficacy7.
It may actually be more likely than not that when it comes to the use of opioid analgesics in the management of patients with pain of any type, especially considering the common co-morbid complexity of pain patients, along with the possibility of genetic variations, the frequent concomitant use of other medications as part of the pain management plan, and genetically determined metabolic and receptor-level distinctiveness that “one size” does not likely fit all.
1. Merriam-Webster Dictionary. Merriam-webster.com . Accessed 9/23/15.
2. Smith HS. Mayo Clinic Proceedings. 2009 July; 84(7):613-24.
3. Mercadante S, Bruera E. Opioid switching: a systematic and critical review. Cancer Treat Review. 2006 Jun; 32(4):304-315.
4. Watkins P. The clinical significance of CYP-3A4 enzymes. Pharmacogenetics. 1994. 4: 171-184.
5. Horsman Y. Major cytochrome P450 families: implications in health and disease. Acta Gastro-Enterelogica Balgica. 1997. 60: 1-10.
6. Pasternak GW. Molecular Insights Into µ Opioid Pharmacology: From the Clinic to the Bench. Clinical Journal of Pain. 2010 January; 26(Supplement 10): S3–S9.
7. Fine PG, Portenoy RK. Establishing “best practices” for opioid rotation: Conclusions of an expert panel. Journal of Pain and Symptom Management. 2009; 38:418–25.