Pain is a complex and serious medical condition, affecting more than 75 million Americans. Moreover, Gatchel and Gremillion have reported that the most frequently cited reason patients in the United States seek medical care is due to pain. Besides the human suffering, there are enormous economic costs as well associated with chronic pain, in terms of medical care and lost productivity. According to recent statistics from the National Academy of Sciences, the societal costs of chronic pain and related disability in the United States alone is $560 billion to $635 billion each year. Gaskin and Richard have also reported similar costs and note that these annual costs for pain were greater than the annual costs for heart disease, cancer, and diabetes. Unfortunately, many chronic pain conditions are not being successfully treated. Indeed, the important and influential Institute of Medicine (IOM) report, Relieving Pain in America , has highlighted the urgent need for the development of more cost-effective approaches to pain management because the ever-increasing costs associated with current treatment approaches cannot be sustained. Moreover, ongoing pain has been underdiagnosed and undertreated in nearly all health care settings. Therefore, there is still an urgent need for the development of treatment- and cost-effective methods for managing chronic pain, especially when it becomes intractable.
As Gatchel noted, since the early 2000s there has been an expanding role of spinal cord and peripheral nerve stimulation as a potential treatment option for intractable chronic pain. Stimulated by Melzack and Wall’s gate-control theory of pain, which proposes that the activation of low-threshold afferent nerve fibers decreases the response of dorsal horn neurons to unmyelinated nociceptors (thereby “closing the gate” to pain transmission from the spinal cord), a number of clinical applications of this theory have been developed. For example, Shealy and colleagues were the first to apply this theory when they stimulated the dorsal columns for the treatment of chronic, intractable pain. Since that time, implantable dorsal column stimulation (i.e., spinal cord stimulation [SCS]) was developed to treat a wide variety of pain syndromes. As Cameron and Elliot noted, since the time that the SCS procedure was first prompted by the gate-control theory, its potential efficacy has been linked to a number of other mechanisms, such as the activation of spinal pain inhibitory circuits, as well as regional blood flow to various regions at the cerebral level. Subsequently, several groups started to use implantable peripheral nerve stimulators. Peripheral nerve stimulation (PNS) applies an electrical current to the peripheral nerves to relieve the chronic pain symptoms. PNS techniques are used for treating pain in a nerve region that is not accessible by SCS. Nerve regions that are more easily accessed by PNS include the trigeminal nerve, occipital nerve, and subcutaneous peripheral nerves. Conditions for which PNS might be indicated include trigeminal neuropathic pain, occipital neuralgia, supraorbital neuralgia, and inguinal neuralgia. Headache disorders, including migraines and cluster headaches, might also benefit from cranial forms of PNS currently under investigation.
Thousands of stimulators were implanted in the decade following the first attempts. However, successful results with SCS and PNS have been difficult to define empirically, although some consensus in the literature has identified greater than 50% relief of index pain 12 months following implantation as a potential benchmark. Although success rates vary widely from 40% to 80%, conditions commonly treated by SCS include failed back surgery syndrome, peripheral vascular disease, neuropathic pain, multiple sclerosis (MS), and reflex sympathetic dystrophies. Moreover, the initial short-term expense of these implantable therapies has proven to be potentially offset in the long term by the benefits and resultant reduction in treatment expenses. For example, Kumar, Malik, and Demeria evaluated costs for patients who received SCS and compared them to the costs for treatment by conventional pain therapies (CPT) in a control group. Although the cost for SCS was significantly higher than for CPT in the first 2.5 years, after that time point the cost of treating patients with SCS not only became less than the cost for CPT, but it also remained less expensive during the rest of the 5-year follow-up period. Demonstrated success rates are no greater than 50%, although these initial high costs for implantable therapies make it necessary in the current evidence-based medicine environment to find means of better identifying those 50% of patients who are more likely not to benefit from the procedure.
It should also be noted that various side effects (e.g., neural impairment and scarring) have been observed. There were reports of high complications and failure rates. In an attempt to determine both the positive and negative outcome indicators for surgical procedures, Spengler and Freeman initially performed a retrospective analysis of 30 patients who had unsuccessful outcomes from various surgical procedures for low back pain, sciatica, or both. Among their findings, the most commonly reported cause of the poor results was a poor initial candidate-selection process, despite initial indications for the surgical procedures. A more focused investigation identified instances of drug abuse, alcoholism, marital discord, and personality factors that were likely to have played a role in the patients’ postsurgical success or failure. Spengler and colleagues therefore recommended presurgical psychological evaluation in order to reduce the likelihood of unsuccessful procedures. Following closely on the heels of the report by Spengler and colleagues, Long and colleagues performed a retrospective analysis of their own patients, who received surgically implanted dorsal column stimulators between 1970 and 1973. At that time, the only method for identifying candidates for this procedure was a persisting self-report of pain after failing all other treatments. Long and colleagues found that too few patients achieved satisfactory pain relief with SCS and that approximately half of those patients originally selected for the procedure would have been rejected using updated inclusion criteria. Psychosocial factors were the most frequent reasons for failures, including substance use disorders.
Thus, it was soon recognized that not all patients were good candidates for such implantable devices. Indeed, starting with spinal surgery, clinical researchers became more involved in prescreening patients for these invasive interventions. Before discussing an example of more current attempts, a discussion of the biopsychosocial approach to assessment is warranted.
The Biopsychosocial Approach to Assessment
The biopsychosocial approach is recognized as the most comprehensive and heuristic approach to the evaluation of medical disorders. The biopsychosocial model focuses on the complex interaction among biologic, psychological, and medicolegal variables that patients encounter when coping with a persistent, distressing medical condition. This interaction may perpetuate, and even worsen, the clinical presentation. This complex interaction accounts for the likelihood that a patient’s life will be adversely affected in a variety of ways by his or her medical condition, thus requiring a comprehensive assessment and treatment approach designed to address all aspects of required care (i.e., biologic and psychosocial). This approach is in contrast to the former biomedical reductionist approach, which mistakenly assumed that most medical conditions, such as chronic pain, can be separated into distinct, independent physical and psychosocial components. Each patient experiences a medical condition uniquely. The complexity of a condition can be especially evident when it persists over time as a range of psychological, social, and economic factors emerge. These factors interact with the physical pathology to modulate a patient’s discomfort and disability associated with the condition. Therefore, any successful assessment of patients needs to comprehensively evaluate these various factors.
A review by Gatchel and coworkers highlighted how individuals significantly differ in the frequency of reporting physical symptoms, in their tendency to visit physicians when experiencing identical symptoms, and in their responses to the same treatment. Moreover, the nature of a patient’s response to treatment has little to do with his or her objective physical condition. A comprehensive assessment of a patient proceeds from a global biopsychosocial diagnosis of the disorder in question, to a more detailed evaluation for the most important interactive factors needed for the diagnosis. For example, for a patient reporting low back pain, a comprehensive physical examination would initially be conducted to assess the bio-component of the equation. This examination would consist of the assessment of range of motion, tenderness, gait, posture, sciatic stretch tests, and the neurologic components of myotomal/dermatomal deficits or reflex change. The examination is valuable when it defines objective signs that may lead to further diagnostic or treatment recommendations. It is less valuable when it is nonspecific or demonstrates pain inhibition. Waddell and colleagues were the first to describe behaviors of back pain patients on physical examination that they termed nonorganic or behavioral signs. They suggested that a patient might not have a simple, straightforward physical diagnostic problem. Thus, a comprehensive biopsychosocial assessment of each patient is needed before the development of a treatment plan. The same such comprehensive assessment is needed before prescribing use of implantable devices for chronic pain.
The Biopsychosocial Prescreening Process
Summary of Clinical Rationale and Process of Prescreening
The process of test selection for prescreening can be difficult for the clinician not experienced with this process. The instruments described herein are a comprehensive battery, based on the work of Block and colleagues. These can be used as a foundational starting point for the clinician who has been asked to screen and evaluate patient candidates for SCS or PNS (Block’s work will be reviewed at greater length in the next section of this chapter). A general survey of pain symptoms is a necessary starting point for any pretreatment evaluation in a pain program. A general intake assessment should include a survey of pain symptoms, along with other self-report items such as demographic information, date of onset and pertinent details of the pain condition, prior treatments or surgeries, employment status, education level, disability payment status, workers’ compensation or personal injury litigation involvement, health care utilization, additional contact numbers, and other comorbid chronic health problems. A brief summary of these assessment tools is provided here:
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First developed in 1976, the visual analog scale (VAS), also referred to as the pain drawing analog (PAD), is a scale designed to rate the patient’s degree of pain on a scale from 0 (no pain) to 10 (worst possible pain). It is made up of a 10-centimeter horizontal line divided at two-point intervals, and patients mark an “X” on the line to represent current levels of pain. The psychometric properties and utility with chronic pain populations of the VAS/PDA are further described in the literature.
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A further development of the VAS/PDA is the million visual analog scale (MVAS). The MVAS consists of 15 self-report items specific to perceived pain and disability. Patients respond on a similar 10-centimeter line, representing a range of possible answers from 0 to 10, in which the total score is the sum of all responses. Various cutoff points have been described based on psychometric testing of the MVAS. Scores of 0 to 39 indicate “mildly disabling” pain, scores of 40 to 84 indicate “moderately disabling pain,” and scores of 85 and above indicate “severely disabling pain.” The MVAS is especially helpful for discrepancies, such as when self-reported pain is higher than expected based on physical findings. This is often suggestive of a potential psychosocial component in the patient’s experience of pain.
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The Oswestry Disability Questionnaire is another self-report scale designed to assess the degree of functional impairment. Consisting of 10 items regarding limitations of activities of daily living due to pain, the Oswestry has demonstrated test-retest reliability of .99 with a 24-hour interval between administrations, as well as acceptable levels validity. Each item is scored on a 0- to 5-point scale, with a potential range of scores from 0 to 50, with higher scores significant for higher levels of pain-related limitations.
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Adams and colleagues developed the Pain Medication Questionnaire to determine the risk of medication misuse among chronic pain patients. Identified behavioral correlates and attitudes suggestive of medication misuse were used to develop the 26 self-report items that make up the PMQ. Higher scores indicate a likely greater incidence of substance abuse potential, emotional distress, impaired coping skills, reduced physical functioning, as well as higher rates of unemployment.
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The Beck Depression Inventory (BDI-II) is a 21-item self-report inventory designed to assess the intensity of depressive symptomatology. Each item is scored from 0 to 3, with a potential range of scores from 0 to 63. A total score of 0 to 9 is considered normal, 10 to 15 is mild depression, 16 to 19 represents mild to moderate depression, 20 to 29 reflects moderate to severe depression, and 30+ indicates severe depression. Being able to identify symptoms of depression is important in chronic pain populations, as is being able to delineate between cognitive and somatic specific symptoms, which is an option allowed by the BDI-2. To obtain more than the subjective self-reported symptoms of depression available with the BDI-2, an experienced clinician will also want to perform a more objective assessment of depression to validate or clarify his or her findings. One such tool that is widely available, but does require some training and experience, is the Hamilton Rating Scale for Depression (HAM-D), which is administered by the clinician in a brief interview format and could potentially be incorporated into the overall clinical interview.
In addition to examining the current emotional status of the patient candidate prior to SCS or PNS implantation, long-standing personality traits are important to consider before a patient begins a life-changing process that implantable therapies entail. Although these inventories are lengthy and time consuming, they have been used extensively in chronic pain populations. Third-party payers may limit the type or extent of testing that is performed with presurgical candidates, but the two inventories reviewed here provide valuable insight into the characteristic way these patients relate to the people and situations around them. If time and the situation allow, they should be considered as part of the comprehensive prescreening evaluation. The Millon Behavioral Medicine Diagnostic (MBMD) is a 165-item, self-report inventory that examines psychosocial factors that may impact treatment outcomes with medical patients. The MBMD includes 29 clinical scales, three response pattern scales, one validity indicator, and six negative health habits indicators. It is intended for adult clinical and rehabilitation patients (ages 18 to 85) who are undergoing medical care or surgical evaluation, making this a valuable resource for the prescreening process.
A more widely recognized personality assessment, which has been used extensively in chronic pain research, is the Minnesota Multiphasic Personality Inventory-2 (MMPI-2). Although the MMPI-2-RF is gaining popularity in clinical settings, most research relating to pain is based on the MMPI-2, so this chapter will focus solely on that particular inventory. The MMPI-2 is a 567-item, self-report measure of personality functioning and psychiatric symptoms. It is the most commonly used personality assessment for patients with chronic pain, who often demonstrate a higher prevalence of emotional distress, specifically depressive symptoms and potential personality disorders, relative to the general population. There are 10 empirically derived clinical scales, various supplementary scales, and validity scales provided to assess the test-taking attitudes of the patient. The MMPI-2 has a great deal of utility when used as part of the prescreening process with chronic pain patients. Findings from the MMPI-2 can help in the identification of psychopathology, personality and behavioral characteristics, treatment planning, and prediction of treatment outcomes.
Current quality of life is also an important factor for patients being considered for an implantable therapy device, as this can interrupt current lifestyle during training and adjustment and can also improve quality of life for many of those receiving this option. The Medical Outcomes Survey 36-Item Short Form Health Survey (SF-36) is a 36-item questionnaire that assesses health-related quality of life, both physical and mental, from the patient’s perspective. The SF-36, and variants of this measure, is widely used for assessment and follow-up monitoring of health care treatment outcomes. The SF-36 consists of eight subscales and two standardized summary scales, the Mental Component Scale (MCS) and the Physical Component Scale (PCS). The MCS and PCS provide an overall gauge of the patient’s sense of physical and mental well-being.
The coping skills that patients already rely on are necessary for the clinician performing the prescreening to identify, as these will likely be the set of coping skills employed during the training and postimplant phase of treatment. If there is a notable lack of healthy coping skills, this is something that might be managed prior to, and following, surgery with biobehavioral therapy. The Coping Strategy Questionnaire (CSQ) is a 42-item self-report inventory that assesses how often pain patients use six cognitive coping strategies and two behavioral coping strategies. These strategies include diverting attention or distraction, reinterpreting pain sensations, ignoring pain, praying and hoping, coping self-statements, increasing behavioral activities, and catastrophizing. Additionally, the CSQ measures the subjective ability to control and decrease pain. Patients rate on a 6-point scale activities they engage in when experiencing pain, where 0 = never do that, 3 = sometimes do that, and 6 = always do that.
Although all of the aforementioned assessment tools are useful for performing a comprehensive prescreening evaluation, again it is up to the clinician to obtain the proper training to perform these assessments, along with a thorough clinical interview. These data can then be used to prepare a detailed report of the findings for both the patient and the physician performing the implantation procedure. In addition to performing these tasks, it should also be within the clinician’s repertoire to know how to ask about what treatments the patient has found helpful in the past, what prescriptions and over-the-counter medications the patient is taking, what the patient’s activities of daily living entail now and prior to the pain condition, and what the patient’s realistic expectations are for life postprocedure.
The Prescreening Process Developed by Block and Colleagues
As noted earlier, there have been attempts to prescreen patients who were being considered for surgery. Epker and Block reviewed the methods for predicting positive outcomes for spine surgery in general and highlighted the positive and negative psychosocial risk factors that appeared to impact recovery from spine surgery. They delineated specific risk factors that had been shown to predict a poor surgical outcome and suggested the evaluation and quantification of these factors before performing spine surgery in order to predict positive outcomes. Three major categories of psychosocial factors were described: (1) personality/emotional, (2) cognitive/behavioral, and (3) environmental/historical. Scale elevations on the MMPI-2 associated with pain sensitivity (scales 1 and 3), depression (scale 2), anger (scale 4), and anxiety (scale 7) were the most noteworthy factors negatively influencing outcomes. Other significant factors included maladaptive coping strategies, workers’ compensation status, litigation related to pain, and drug and alcohol abuse. Epker and Block also discussed “quasi-medical” risk factors that could predict poor results: the duration of pain and number of previous surgeries for pain are negatively correlated with positive outcomes, and smoking and obesity can also have a negative effect on recovery from surgery. Finally, they noted that the presence of nonorganic Waddell signs (see Waddell and coworkers ) can help identify candidates who will have poor outcomes.
Subsequently, the most comprehensive screening approach for spine surgery was presented by Block and colleagues. They developed a “scorecard” to clarify the spine surgery candidate’s biopsychosocial risk factors, using an array of factors. The scorecard lists and quantifies each of psychosocial risk factors, along with additional medical risk factors. Based on the extant research demonstrating predictive ability, each risk factor is assigned an a priori weight of high risk (2) or medium risk (1), and the risk factors in each group (medical and psychosocial risks) are then totaled to arrive at a surgical prognosis. They based this approach on a study conducted by Block and colleagues. In that study, 204 patients were referred for psychosocial screening and were evaluated no more than 1 month prior to surgery. A semistructured interview and two psychosocial questionnaires, the MMPI-2 and the Coping Strategy Questionnaire (CSQ), were used to evaluate the psychosocial and medical risk factors. Based on the results of screening, patients were placed into one of three predictive categories (“good,” “fair,” or “poor”). Analyses of results showed the screening achieved an 82% accuracy rate, with 82.3% of patients in the “good” group experiencing a good outcome and 83.0% of patients in the “poor” prognostic group resulting in poor outcome. Logistic regression analyses were also conducted to determine which variables were the most significant predictors of outcome. These analyses yielded psychosocial test data as the most significant cluster of variables to correctly classify patients, with a correct classification rate of 78.4%. The addition of psychosocial interview data brought the model up to an 83.3% correct classification rate. Finally, the addition of the medical risk factors contributed slightly, bringing the total model to 84.3% correctly classified. This study was the first empirical investigation to show that a large number of psychosocial and medical risk factors can be identified, quantified, and used to accurately predict surgical outcomes.
The original screening scorecard, developed by Block and associates, was subsequently replaced with a new prognostic algorithm by the same group. This algorithm added several new features that enhanced its predictive utility. The changes involved the following:
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The algorithm placed psychosocial risk factors above all others because they have proven to have the most predictive power.
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A category termed adverse clinical features was also included to account for factors such as inconsistency, compliance issues, and medication seeking (which were often found in the patients’ medical charts and observed during the clinical interview).
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A set of general treatment recommendations was added. The psychologists’ recommendations fell into five categories: (1) proceed with surgery; (2) surgery, but with postoperative psychosocial treatment sessions; (3) preoperative treatment psychosocial sessions prior to surgery; (4) only noninvasive therapy recommended; or (5) no treatment of any kind is recommended.
Review of Clinical Studies
In the past, only a few studies have systematically evaluated the predictive value of biopsychosocial risk factors and treatment outcomes for implantable devices. Moreover, they have varied in their methodologies. Our clinical research group therefore decided to use a more structured, standard approach. Using the presurgical screening algorithm developed by Block and colleagues, we were the first to evaluate its validity and application in categorizing patients’ potential suitability as candidates for a subset of implantable modalities (specifically, spinal cord stimulators and intrathecal opioid pump systems). The rationale for using an algorithm developed for spinal surgery for patients being considered for potential implantable devices was noted as follows:
Of course, one might argue that, because neuromodulation is quite different from spine surgical intervention, this algorithm would not be applicable to the former. However, for any type of presurgical screening that involves stress and uncertainty, such as the current one, the global psychological resilience of the patient (including the psychological strengths and weaknesses in dealing/coping with stress) is the key entity that is evaluated. That is to say, the global capacity of the patient to respond adaptively, whatever the specific challenges of any particular surgery, is the key ingredient. With this in mind, it was expected that Block’s algorithm would be clinically applicable to neuromodulation procedures. We attempted to delineate differences found among prognostic groups with regard to psychosocial, functional and medical risk factors. (p. 238 )
The algorithm used in the investigation by Schocket and colleagues included both psychosocial and medical risk factors, as delineated in Box 68.1 . On the basis of this algorithm, patients were classified into one of five groups: Green (proceed with surgery); Yellow I (proceed with surgery, but administer postoperative psychosocial intervention); Yellow II (administer preoperative psychosocial intervention before surgery); Red I (only noninvasive intervention is recommended); and Red II (no treatment of any kind is recommended). Although this investigation did not provide the opportunity for long-term follow-up of all patients, data were collected from patients who were able to complete a 6-month follow-up evaluation. The results of this evaluation revealed a trend among the groups in terms of additional medications being taken. As expected, the Green group showed 40% of patients to be taking no new medications at the 6-month follow-up. This percentage decreased as prognosis worsened (Yellow I, 27.3%; Yellow II, 25%; and Red I and II, 0%). Although these were only statistical trends, due to limited power because of a relatively small sample size, the results do suggest a clinically significant change. Obviously, additional clinical research of this type is needed.
