Over the past decade, opioids have made breakthroughs in the treatment of chronic pain, but they have also been accompanied by an increase in cases of side effects, including abuse and death. To date, there is no accepted, objective method to accurately assess whether a patient’s analgesic regimen prior to opioid treatment is the best choice, i.e., less side effects and no abuse. In this article, we discuss the concept of individualized analgesic treatment with opioids as a method to achieve this aim based on certain data. We chose traditional randomized placebo-controlled trials (RCTs) and evidence-based practice therapy (PBE) methodological tools to obtain the necessary clinical data to develop an individualized analgesic prescribing guideline. We briefly outline several predictors that may be included in this guideline, including genetic factors, factors that differ in brain structure and function, factors that differ in neurotransmitter transmission pathways, and factors that differ in the patient’s negative affect, gender, and presentation type of pain sensitivity. To date, there is insufficient literature to support the development of this guideline. However, a clinically validated quantitative analgesic prescribing guideline may eventually be developed by analyzing different factor subtypes in a large number of chronic pain patients from the proposed collaborative PBE pain registry, in conjunction with a follow-up validated randomized controlled trial.
There are relatively few studies that have selected different opioid analgesic prescription treatments based on different patient characteristics, however, the large and diverse sample of pain patients in the PBE combined with subsequent randomized controlled trial studies may be able to develop a quantitative analgesic prescribing algorithm to optimize the analgesic effects of opioids and reduce the incidence of opioid-related substance abuse and death.
More than 20% of adults experience chronic pain (CP), and 100 million people in the United States alone suffer from this condition. In the past decade, the use of opioids for chronic pain has increased dramatically. With a large population of CP emerging, the problem of prescribing high doses of opioids will become increasingly acute. Not surprisingly, the incidence of opioid-related substance abuse and death has increased significantly, driven by the increased number of prescription drugs of abuse.
Although the analgesic effects of opioids are definitive, their treatment outcomes vary from person to person. Long-term application of high doses of opioids can result in ineffectiveness or decreased tolerance in one-third of CP patients. In the long run, it will be very difficult for patients with comorbid psychosocial disorders to self-select for long-term effective treatment with opioids. In addition, any use of opioids for analgesia must be weighed against the costs associated not only with increased incidence of drug abuse in opioid-sensitive patients, but also with increased side effects such as constipation, nausea, sedation, respiratory depression, and death. Recent studies have confirmed that opioid-dependent patients have a tendency to use increasing doses of medications, with a significant portion of the population increasing at very high doses, creating a potential dilemma for clinicians in the medical treatment of such patients.
To date, there is no objectively accepted optimal treatment alternative to opioids in chronic pain management programs, i.e., a dose that results in good analgesia with minimal side effects and minimal drug abuse. Therefore, the key questions in conducting research are to determine which phenotypes and genotypes of patients have favorable or unfavorable cost/benefit ratios when applying opioid therapy and how to determine how patients are more likely to fall into the confusion that no matter what dose of opioids they are currently using, they still do not think they are getting enough.
Is individualized therapy a solution?
There has been increasing interest in the concept of individualized therapy, which is the use of different drug types and doses to achieve optimal treatment outcomes based on the patient’s genotype, biological markers and other disease-related factors. However, in the field of pain management, this treatment modality is limited to theory and is difficult to practice in practice. The research needed to individualize the treatment of CP patients with opioid prescriptions is still quite scarce. This paper intends to provide an overview of the research strategy on the key issues necessary to establish the necessary database to develop and validate personalized analgesic prescribing guidelines. Some phenotypic and genotypic factors may predict the effect of opioid application in patients and are given a brief discussion here. Due to limited space, this article focuses on opioid-prescribed analgesics in the treatment of chronic, noncancerous pain.
Research strategies for developing individualized analgesic prescribing guidelines
Traditional prospective, randomized, placebo-controlled trials (RCTs) can demonstrate interval validity with the application of relatively little data. After optimization, analgesic efficacy is demonstrated at different group levels in patients with a clear diagnosis of CP. Typically, we maximize the selection of participants in trials of the same type to exclude heterogeneity and improve clinical efficiency.
Sample size is a key limiting factor for RCT protocols because only with a large sample size can subgroups of subjects be analyzed, and RCT trials are not usually designed that way. If RCTs are conducted on different combinations of individual variables, the number of subjects can rapidly increase to an unachievable number.The limitations of the actual RCT process, the homogeneity requirements of the subjects, the need for sample size, and the duration of the trial process all constrain the development of individualized analgesic drug prescribing guidelines.
These shortcomings can be remedied by a systematic evidence-based treatment protocol (PBE), a prospective observational cohort study that identifies the effects of specific interventions and evaluates patient outcomes based on relevant individual variables of patient differences. Applying the PBE study method, we can obtain more clinical data information from a larger sample size and a larger number of subjects, including the genetic variability of patients, the degree of disease, clinical manifestations (symptoms, signs, brain imaging), and use the existing electronic database to collect and organize them in a uniform classification, and select different testing systems to validate them and obtain the test results we need. Thus, RCT and PBE can play complementary roles in the study of this paper. A systematic large-scale PBE study may help to accumulate the necessary data to generate hypotheses to support the development and subsequent validation of individualized analgesic prescribing guidelines through a traditional randomized placebo-controlled trial based on the evidence. A few possible predictors of feedback significance for opioid analgesics during individualized treatment are briefly described below.
Genetic variability
A large amount of experimental data obtained through the use of classical and molecular genetic methods, as well as evidence gathered from human and animal studies using genetic research methods, suggest that different genetic factors have significant variability in pain perception, sensitivity to opioid analgesics, evolution of tolerance, and dependence on opioids. However, there is still a relative lack of articles on this aspect. In future work, in addition to considering the effects of genetic variability, it is important to include the effects of gene transcription, mRNA editing, and protein translation in patients applying opioid analgesic therapy. Some of the data suggest that opioid analgesic efficacy and drug abuse are likely to be influenced by polygenic inheritance.
Chronic pain mechanisms
Patients with chronic pain whose signs and symptoms are phenotypically expressed are often the result of the interaction of multiple mechanisms, both peripheral and central, and these may influence opioid analgesic action. In neuropathic pain cases, the mechanisms may include impaired sensation, peripheral sensitization, central sensitization, ectopic activation, and local immune activation. Statistical data can distinguish different somatosensory information characteristics of patients with neuropathic pain, reflecting different combinations of the above mechanisms. The available findings suggest that the pathogenesis of chronic pain is precisely in line with the results reflected by clinical features and experimental results and may be useful for the development of individualized analgesic prescription guidelines.
Biological markers of brain and neurotransmitter function
Available data suggest that the development of individualized analgesic prescription guidelines requires documentation of brain and neurotransmitter changes in patients with CP. Recent studies have shown that different fiber connections in the brain can shift the nature of pain between acute and chronic in patients with pain, suggesting that the progression of chronic pain may be closely related to changes in functional areas of the brain. Chronic pain types may be associated with different connectivity patterns in the brain, thus affecting the responsiveness of relevant areas in the brain to opioids, and changes in opioid receptors may play a key role in this process.
The data suggest that dopaminergic neurotransmitters play a role in the processing of pain signals in the central nervous system, modulating the coordination within the neurotransmitter pathway and thus controlling the degree of opioid analgesia. Identifying changes in brain and neurotransmitter system function in different individuals plays a key role in the development of individualized analgesic treatment protocols with opioids.
General patient characteristics
The literature suggests that males can lead to increased opioid side effects, increased sensitivity to experimental acute painful stimuli and pain accumulation in the inferior temporal region, increased levels of endogenous opioids, etc., resulting in decreased responsiveness to opioids.
Feasibility of synergistic treatment
Data suggest that because of the synergistic effects of opioids, the development of individualized analgesic prescribing guidelines requires the integration of other therapeutic information. Several non-pharmacologic pain management modalities, including acupuncture, relaxation training, and aerobic exercise, may activate opioid transmission pathways and theoretically alter responsiveness to opioid analgesia, all of which may have some impact on patient dosing, side effects, patient tolerance, and abuse of opioids.
Outcome evaluation and development of individualized analgesic guidelines
A key issue in the development of individualized analgesic prescribing guidelines is how to define good analgesic outcomes. Analgesic effectiveness for the most common primary pain relies heavily on subjective evaluations by CP patients, and although this makes sense psychologically, patients’ understanding and perception of good treatment outcomes is often far from, or even out of touch with, what clinicians perceive to be successful. In recent studies, the application of brain imaging techniques to improve patients’ objectivity about the effectiveness of pain treatment has yielded significant results.
Opioid analgesics are increasingly used in chronic pain management, and their cost/benefit profile must be carefully weighed due to their side effects and substance abuse issues. While there is an urgent need for an individualized opioid analgesic prescribing guideline to guide treatment, there is insufficient theoretical basis to support the development of a quantitative approach to achieve this goal, especially given the difficulty of taking into account different individual phenotypic and genotypic factors. Despite this, the available studies have identified some possible predictors of analgesia that warrant further evaluation. Randomized controlled trials remain the gold standard for demonstrating analgesic efficacy. However, in the coming years, further development of individualized dosage methods for opioid analgesia prescribing will still require non-randomized PBE trial methods that can analyze patients’ phenotypic and genotypic factors, as they can follow a large number of different types of sample data over time to better reflect the clinical outcome of pain treatment. By combining the two, it is likely that a truly cost-effective and convenient individualized opioid analgesic prescribing guideline with evidence-based medicine will be developed to improve the actual clinical efficacy of pain and maximize the cost/benefit ratio of opioid analgesic treatment.