Recognizing Pain Phenotypes: Biopsychosocial Sources of Variability in the Transition to Chronic Postsurgical Pain

Abstract

Chronic postsurgical pain (CPSP) is a cause of new chronic pain, with a wide range of reported incidence. Previous longitudinal studies suggest that development of CPSP may depend more upon the constellation of risk factors around a patient (pre-existing pain phenotype) rather than upon the extent of surgical injury itself. The biopsychosocial model of pain outlines a broad array of factors that modulate the severity, longevity, and impact of pain. Biological variables associated with CPSP include age, sex, baseline pain sensitivity, and opioid tolerance. Psychological factors, including anxiety, depression, somatization, sleep disturbance, catastrophizing, and resilience, and social factors, like education and social support, may also importantly modulate CPSP. Prevention efforts have targeted acute pain reduction using multimodal analgesia (regional anesthesia and intraoperative analgesic adjuvant medications). However, studies that do not measure or take phenotypic risk factors into account (either using them for enrichment or statistically as effect modifiers) likely suffer from underpowering, and thus, fail to discern subgroups of patients that preventive measures may be most helpful to. Early preoperative identification of a patient’s pain phenotype allows estimation of their constellation of risk factors, and may greatly enhance successful, personalized prevention of postoperative pain. Effective preoperative employment of behavioral interventions like cognitive behavioral therapy (CBT), stress reduction, and physical and mental prehabilitation may particularly require knowledge of a patient’s pain phenotype. Preoperative assessment of patients’ pain phenotypes will not only inform high-quality personalized perioperative care clinically, but it will enable enriched testing of novel therapies in future scientific studies.

Chronic Post-Surgical Pain as a source of new chronic pain

Over 100 million U.S. adults are affected by chronic pain, exceeding the combined numbers of those affected by diabetes, cancer, and heart disease.¹ Chronic pain is associated with worse quality of life, and carries both personal and societal costs. Chronic Postsurgical Pain (CPSP) has been recognized as a type of new chronic pain.² As our population ages and life expectancy increases, so does the number of surgical procedures and number of postsurgical years lived. Reported incidence of CPSP ranges widely, depending on the definition and means used to measure it.^{4; 5} In addition to the problem of adequately controlling CPSP, a small but significant proportion of patients may also develop chronic opioid use after their surgery as they try to manage their pain,³ further emphasizing the importance of preventing CPSP. Notably, CPSP is multifactorial, influenced by a combination of biological, psychological, and social factors, and difficult to treat once established, making it particularly important to identify patients at high risk to implement timely intervention.

CPSP as a Model of the Acute to Chronic Pain Transition

The Opportunity of Perioperative Physicians

Unlike other injuries leading to chronic pain, surgery occurs within a highly structured environment, under the care of a specialized physician who pays attention to small but salient differences in a patient’s physiology, including their response to painful stimuli and analgesics. With an armamentarium of medications and techniques, anesthesiologists have the ability to modify responses to the peripheral and central nervous system before, during, and immediately after a surgical injury, thus affording them the opportunity to prevent key mechanistic events that comprise pain sensitization. While anesthesiologists are by necessity adept at addressing their patients’ pain during the intraoperative and postoperative period, gaining early knowledge of a patient’s risk of developing greater pain, specifically in the preoperative period, would allow enhanced planning for preventive intervention. Using brief, validated tools as part of the preoperative assessment may allow earlier discernment of a patient’s “pain phenotype” and inform the delivery of high-quality clinical care. More broadly, careful study of patients who transition from surgical injury to CPSP could provide an opportunity to better understand the relevant mechanisms of chronic pain development in humans.

Nervous system Plasticity: friend or foe?

Preclinical models of chronic pain have identified that tissue injury drives nervous system plasticity, present both as peripheral and central nervous system sensitization.⁶ In the short term, such plasticity is functional. The propensity for plasticity is evolutionally selected for because of its value in protecting us from further harm and encouraging us to rest and heal. But when the nervous system gets “stuck” in a sensitized state, extending into a timeframe that no longer serves a function (after the injury is healed), this plasticity can be viewed as dysfunctional or pathophysiological. Importantly, preclinical models have demonstrated several potential mediators to target (e.g., sodium channels, NMDA receptors, inflammatory mediators) in this pathophysiological transition from acute to chronic pain.^{7; 8}

A key difference between optimized preclinical animal models vs real-world patients: Variability

Despite the insights afforded by preclinical chronic pain models, many preventive trials in humans have fallen short of expectations. There are several potential reasons for this translation failure, but one key difference between the model systems and the human clinical setting is the degree of variability of subjects. Animal model systems are optimized to reduce variability so that smaller samples can be used in experimentation. Among human patients, expression of chronic pain is more variable, with many patients developing no chronic pain (Figure 1). For other patients, however, pain at the surgical site is indeed prolonged, but the degree and duration are variable across patients. Although the duration to complete surgical wound healing varies somewhat depending upon the surgical procedure, an expert consensus group recognizes that pain extending >3 months after surgery is considered CPSP.⁴ Notably, the reported incidence of CPSP ranges widely,⁵ and may appear unrealistically high in some cases, due to varying definitions of CPSP. For example, some researchers may employ dichotomizing definitions to define CPSP. This may be problematic because among the exact same set of patients, researchers can calculate a widely disparate incidence. For example, with a very inclusive dichotomizing boundary (pain score >0/10), one calculates a higher estimated incidence (e.g., 60%), whereas a more conservative dichotomizing boundary (pain score >3/10) results in a more moderate estimated incidence (e.g. 30%), and a dichotomizing boundary set to include only severe pain (pain score >6/10) results in a low incidence (5%).

Figure 1:

CPSP as a Model of the Acute to Chronic Pain Transition

Achieving sensitive signal detection: powering up and measuring pain on a continuous scale

As CPSP may not be present to any meaningful degree in a relatively large proportion of patients, this can in fact lead to the underpowering of clinical trials testing preventive therapies. Recognizing which patients are at risk ahead of time could allow strategic powering up for preventive trials, enriching them with higher risk patients and eliminating the testing of patients with little to no risk. Additionally, while dichotomizing pain as a “yes/no” variable can be important to defining an incidence of CPSP, as well as diagnosing and clinically categorizing patients, it can further contribute to decreased sensitivity of detection of preventive analgesic efficacy. With greater resolution of CPSP severity, impact, and quality, researchers can achieve greater statistical power to detect a relationship between patient-level characteristics and CPSP (Figure 1). Dichotomization of CPSP hampers the ability to investigate this variability among patients, which is a critical component to testing the efficacy of preventive interventions.

The use of postoperative daily opioid consumption as an alternative outcome to pain has become a common practice in clinical trials, because of the negative impacts that chronic opioid use can have on patients. However, with the increasing restrictions on and protocolization of opioid use in the wake of the opioid epidemic, the tight association between pain scores and opioid use may have diminished, as is seen in some recent studies.^{9; 10} Thus, keeping surgical area pain severity and impact as central outcomes in trials is recommended.

Many Modulators of Pain Contribute to Defining the Pain “Phenotype”

Each individual patient experiences pain somewhat differently, which may serve as an important source of variation observed in CPSP among patients. Some insight into the sources of this variation may be derived from the biopsychosocial model of pain. This model conceptualizes many diverse modulators in a multidimensional framework, with dynamic interactions between biological, psychological, and social factors (Figure 2).^11–13 The biopsychosocial model provides a more comprehensive list of factors that may influence the risk of developing CPSP.¹⁴

Figure 2:

Biopsychosocial Model: Modulators of Surgical Pain

Biological Factors

Several key biological factors are consistently associated with greater pain after surgical injury, in both preclinical studies and clinical cohorts.¹⁴ For example, some potential biological risk factors include variable activity and expression of aspects that modulate the nociceptive signal (neurotransmitters, enzymes, inflammatory mediators) and lead to sensitization.^{15; 16} Both peripheral and central inflammation play an important role in pain processing.⁸ Additionally, particular patient demographic characteristics, including younger age and female sex, have shown to be related to experiencing greater acute postoperative pain and higher risk of developing CPSP.¹⁷ Wide-ranging influence from physical activity, nutrition, and the gut microbiome¹⁸ may also influence inflammation and pain.^{19; 20} Definitive prediction of CPSP based on genetics is not currently possible. Pain processing involves many mediators, and thus involves many genes. Add to this that a patient’s environment and experiences also influence expression and posttranscriptional modulation of genes, and one might understand why the overall heritability of CPSP is estimated only at 38%.²¹ Differences in immune regulation,²¹ Catechol-O-methyltransferase and the μ-opioid receptor might be among the more prominent individual contributors.^{22; 23} However, genome-wide association studies on much larger cohorts are still needed. Thus, currently, the measurement of the phenotype (the end product of gene x environment interaction) remains a more practical approach for the time being.

Biophysical Factors

The measurement of an individual’s general pain sensitivity using standardized psychophysical testing, such as quantitative sensory testing (QST), may also give mechanistic insight to aspects of variation in nociceptive processing among patients.²⁴ Measurement of this aspect of a patient’s pain phenotype (baseline nociceptive sensitivity) in the preoperative period has shown a consistent association of greater pain sensitivity with the development of CPSP.²⁵ Measures of pain amplification, such as temporal summation of pain (TSP), are associated with more severe acute postoperative pain and greater postoperative opioid consumption,²⁶ as well as the development of CPSP.²⁷ While we put biophysical tests in the biological category, undoubtedly responses on QST are also influenced by psychological factors (and possibly social factors), which is reflected in the alternative terminology to describe such testing (“psychophysics”).

Psychological Factors

Psychological factors have been shown to have a strong modulatory impact on chronic pain, including CPSP. Several key psychological factors have been shown to significantly and independently contribute to variance in the expression of both acute and chronic pain outcomes. Some of the most prominently studied examples include negative affect, anxiety, depression, pain catastrophizing, somatization, sleep disturbance, and past trauma.^{12; 13} When these psychological factors are prospectively and systematically measured using validated instruments within longitudinal studies, they are consistently related to the development of CPSP across surgical cohorts, even when taking surgical, medical, and demographic factors into account.^28–31

While several risk factors for CPSP have been established, less research has investigated protective factors, or resilience, which may be associated with a reduced risk of CPSP. Resilience involves the ability to adapt, recover, or grow from a challenge or injury. As recovery from surgery often involves challenges, including pain and pain-related disability, resilience may be particularly salient in the propensity to not develop CPSP,³² which is, after all, what happens to most patients after surgery. Studying resilience and protective factors may provide insight into how some patients recover more easily, quickly, and completely. It is important to acknowledge that a lack of a risk factor (e.g., anxiety) does not necessarily mean the presence of a resilience factor (e.g., self-efficacy), or vice versa, as mechanisms of resilience may be active processes working in conjunction with risk factors, and thus, the relative contribution of both risk and resilience factors must be investigated.

Social Factors

There are several social factors that have also been shown to importantly modulate CPSP. Some evidence suggests that greater perceived social support may be associated with decreased risk of CPSP. ^{33; 34} Studies during the acute phase of COVID-induced social isolation suggested an important role of isolation on worsening both the severity of and interference from chronic pain, including postsurgical pain.³⁵ Additional social risk factors, including discrimination (based on race, ethnicity, sex, age, etc.) and stigma, are also associated with worse pain in several chronic pain cohorts,^{36; 37} although these factors have yet to be prospectively investigated in the context of CPSP. Several social determinants of health have been associated with greater CPSP, including lower educational attainment and socioeconomic status. Further investigations into the role that other social determinants of health, such as access to healthcare and food insecurity, may play in influencing the development of CPSP, are needed. Importantly, these factors may be related to known demographic or psychosocial risk, making attention to covariance crucial to the design of analyses in these future studies.

Does knowing the biopsychosocial pain phenotype really add anything?

Predictors that are more easily extracted from the medical record (age, sex, surgical type) have been used in many prediction models in the past, and several earlier predictive models have been derived using these simple tools.³⁸ However, other aspects of a patient’s pain phenotype, including more accurate assessment of biological, psychological, and social modulators may add accuracy to this prediction and account for additional variance observed. Psychological and social phenotypic factors have been shown to be consistent predictors of CPSP, even when accounting for demographic, clinical, and surgical factors.^{13; 39; 40} Preoperative assessments of a wider array of risk and resilience factors may have another benefit beyond more accurate prediction- it may help identify factors that are actually modifiable- which in turn brings us closer to actual prevention of CPSP. In addition, using a patient-centered data analytic approach, using high-quality assessment of a constellation of modulatory factors, may allow empiric grouping or clustering of patients that share similar characteristics and who may derive greater efficacy from similar preventive therapies. Thus, both preoperative assessment and patient-centered analytic approaches can give insight into factors that can be targeted for patients most in need of postsurgical intervention.^{17; 41; 42}

Using acute pain to predict CPSP

A plethora of studies have also noted the strong correlation between acute postsurgical pain and CPSP.³⁸ When acute pain is entered as a “predictor” variable in statistical models, it explains a large amount of the variability in CPSP, likely because it is simply another iteration of the same outcome (surgical pain), assayed at a different timepoint. If the goal is perfect prediction, one may need to only look at the most recent previous pain assessment, and this will likely give a reasonably accurate prognosis. However, the timing of this knowledge may come too late to truly be useful in prediction, and it certainly comes too late to employ preemptive analgesic techniques such as regional anesthesia or pharmacologic blockade of the impact of initial tissue damage. Leaving prediction aside, in terms of explanatory analysis, including acute pain in the model will often obscure the detection of associations of other (non-pain) variables with CPSP. Rather than waiting until after surgery, an alternative approach could be to assess preoperative pain, either by asking patients to rate their pain in the surgical area or other body areas (both of which have been strongly associated with subsequent CPSP) and use this value as a predictor of risk. Another approach could be to assay their general response to a standardized painful stimulus using QST.^{25; 27}

What We Do: The Impact of Surgery and Anesthetic Treatment on Prevention of CPSP

Potential targets to prevent CPSP have appropriately centered around inhibiting activation of the peripheral and central nociceptive system by surgical injury (Table 1).⁴³ Modification of the surgical approach to be less invasive and damaging is an obvious, but not always practical, solution. Surprisingly, surgical factors (greater or lesser extent) are often poor predictors of CPSP⁴³ and opioid use risk.³ Peripherally, drugs and strategies which target tissues of the nervous system itself, and processes that can sensitize the peripheral nerves, are employed as early and aggressive pain control, most prominently by regional anesthesia, but also including anti-inflammatory or other immune-modulatory medications. Other strategies aim to block central sensitization and enhance descending modulation of pain. At the cortical level, psychological-behavioral adaptation may impact how the nociceptive signal is received and processed, and to what degree it activates affective brain centers and subsequent autonomic response, or behavioral adaption. Regional anesthesia is a prominent tool in the preventive toolbox because it theoretically impacts nociceptive activation at several levels. As mentioned above, these have variable track-records of efficacy across studies.⁴⁴

Table 1:

Potential Targets and Preventive Interventions for CPSP

Targets and risk factors	Intervention
Peripheral tissues including nerves	• Modification of surgical approach
Peripheral nerve activation	• Regional anesthesia
Local inflammatory response and neurogenic inflammation	• Regional anesthesia • Anti-inflammatory (COX-2, NSAIDs, acetaminophen)
Peripheral nerve sensitization and continued ectopic firing	• Regional anesthesia • Cav α2-δ ligands (gabapentin, pregabalin)
Changes in gene expression at dorsal root ganglion	• Regional anesthesia • Corticosteroids (dexamethasone) • Anti-inflammatory (COX-2, NSAIDs)
Central sensitization	• Regional anesthesia • NMDA antagonists (ketamine, magnesium, dextromethorphan, amantadine) • Corticosteroids • α-2 adrenergic agonists (clonidine, dexmedetomidine) • Opioid receptor agonists
Descending facilitation from the brainstem	• Anti-inflammatory (COX-2, NSAIDs, acetaminophen) • Antidepressant
Limbic system and hypothalamus	• Psychological-behavioral interventions • Antidepressants • Anxiolytics
Cortical pain processing	• Assessment and pre-screening • Psychological-behavioral interventions • setting appropriate expectations
Genomic DNA leading to predisposition to chronic pain	• Assessment and pre-screening

Psychological Interventions

Psychological interventions that target known psychological risk factors, while also enhancing resilience factors, may be particularly beneficial for reducing the risk of developing CPSP, although current evidence is limited. Several psychological interventions, such as cognitive behavioral therapy (CBT) and acceptance and commitment therapy (ACT), have been shown to effectively reduce pain, pain-related disability, depression, anxiety, and pain catastrophizing, as well as increase self-efficacy and psychological resilience, in patients with chronic pain. While these interventions are increasingly being integrated into the perioperative period as possible preventive measures, with some studies indicating that preoperative psychological interventions can improve pain-related postoperative outcomes,^45–47 the effects of these interventions on the prevention of CPSP is still largely unknown.⁴⁸

Practical Implications: Using the Measurement of Patient Phenotype for Precision/Personalized Perioperative CPSP Prevention

For some time, the idea of precision medicine has been a goal of treatment in chronic pain.⁴⁹ Targeting the most relevant, specific pathophysiologic mechanisms in each individual patient could optimize treatment outcomes (Figure 3),⁵⁰ providing the right treatment to the right patient, at the right dose, at the right time, potentially at a lower cost. But it requires reasonable quality knowledge about a patient’s pain phenotype. Preoperative phenotypic assessment using brief validated assessment tools can provide that knowledge.

Figure 3:

Framework of Pain Phenotyping in the Transition to CPSP

Research Implications: Using the Measurement of Patient Phenotype for Measurement of Differential Efficacy

Personalized medicine needs an evidence base. More research about the differential effect of traditional or non-traditional preventive interventions for CPSP, among patients who possess different risk and resilience factors, is needed to tailor treatments and prehabilitation regimens according to individual risk for developing CPSP (Figure 4). Even our current tried and tested prevention strategies (e.g., regional anesthesia, analgesic adjuncts) need more sensitive and strategic testing using this lens. In addition to assessing for the main average effect of a given preventive therapy across a large group of heterogenous individuals undergoing a given surgery, we need to also conduct moderation analyses to identify which individuals derive the greatest benefit from these interventions. It is possible that some strategies are, in fact, only useful for a minority of patients, but among that smaller patient group, these therapies can have a large preventive effect. To discard such therapies is akin to “throwing out the baby with the bathwater”. Thus, future randomized controlled trials (RCTs) of preventive therapies for CPSP should include some basic assessment of the pain-relevant phenotypic features of their patients, which will allow moderation analyses to be conducted to reveal this type of differential efficacy. Alternatively, enriching studies with patients with a prominent phenotypic variable (e.g., anxiety or catastrophizing) in order to test an intervention targeted at that variable (e.g., CBT), could give insight into the actual degree of importance of these factors in the plasticity underlying CPSP development. In particular, when testing novel behaviorally based preventive strategies, measurement of psychosocial aspects of a patient’s pain phenotype will be crucial for conducting moderation analyses in a larger trial, or enriching for these patients in a smaller trial. An understanding of the phenotypic features of a responder to any given treatment may facilitate a rational application of these precious resources. Prehabilitation programs to ready patients for surgery, which are becoming more common, might be customized to include elements that address each patient’s particular set of phenotypic risk factors.

Figure 4:

Phenotype-Based Testing of Preventive Analgesic Strategies

Key Message:

What is already known on this topic:

Chronic postsurgical pain (CPSP) is variable in expression, but it can significantly impact a patient’s quality of life.

What this study adds:

Considerations regarding the measurement of pain and the variable degree of CPSP that occurs may importantly inform accurate future estimation of CPSP, and testing of strategies to prevent it. Insights from the biopsychosocial model of pain modulation may enhance our understanding of relevant patient-level phenotypic factors that confer greater risk of CPSP and allow more accurate prediction. Biological phenotypic variables include preexisting pain, general pain sensitivity, opioid tolerance, age and female sex. Other phenotypic factors of interest include anxiety, depression, somatization, sleep disturbance, catastrophizing, but also resilience and social support.

How this study might affect research, practice or policy:

Identifying an individual patient’s pain phenotype is an important part of planning specific targeted perioperative preemptive interventions and increasing the chance of sensitively testing preventive therapies for CPSP.

Abbreviations:

ACT

acceptance and commitment therapy

CBT

cognitive behavioral therapy

COX-2

cyclooxygenase-2

CPSP

chronic postsurgical pain

NMDA

N-methyl-D-aspartate

NSAID

non-steroidal anti-inflammatory drug

QST

quantitative sensory testing

RCT

randomized controlled trial

TSP

temporal summation of pain