Pain Catastrophising in Individuals with Fibromyalgia: A Critical Review, Part Three

PART THREE

Effective Interventions for Pain Catastrophising in Individuals with Fibromyalgia: A Critical Review of Methods and Analyses

Introduction

Affecting nearly 2-5% of the population worldwide, fibromyalgia is a chronic pain condition regarded with frustration by both patients and the academic community alike (Lami et al., 2018). Beyond the most common complaint of systemic musculoskeletal pain, the American College of Rheumatology (ACR) allows for a wide range of symptoms including fatigue and cognitive difficulties, present for a duration of 3 months or longer, confounding diagnostic precision (Paschali et al., 2021). Currently no distinct pathophysiology nor explicit biomarkers have been defined, leaving professionals unable to agree upon the most effective treatment approach (Ellingson et al., 2018). Although predominant multi-modal care plans are heavily reliant on pharmaceuticals, these treatment models exhibit poor efficacy (Alda et al., 2011). Rather than focusing solely on targeting physiological anomalies, more promising success has been produced by recent treatment efforts aimed at modifying aberrant psychological findings such as heightened pain catastrophising (Paschali et al., 2021). While research has found pain catastrophising to be both a significant risk factor for fibromyalgia and a reliable predictor of long-term prognoses, inconsistencies across methodological and analytical approaches complicate the aggregation of results from individual studies (Paschali et al., 2021). Study populations are often poorly representative samples with diagnoses validated according to various diagnostic criteria (Lazaridou et al., 2017). Moreover, compilation is complicated by statistical procedures controlling for numerous outcome measures, dropout, and affective confounders (Andrés-Rodríguez et al., 2019). The aim of this critical review will be two-fold, focusing firstly on methodology including subject selection, study design, and measures, and secondly on the analysis and reporting of studies referencing issues pertaining to multiple comparisons corrections, intention-to-treat analyses, and depression-related confounders. A comprehensive sampling of the most influential literature, studies examining both psychological and physiological correlates of fibromyalgia will be included. This review will serve to constructively critique commonly utilized methodological and analytical strategies, allowing for more informed judgements to be made regarding generalizations between studies and suggesting ideas for improvements whenever possible throughout.

Methods

Subject Sampling

Poorly upheld across fibromyalgia literature, overall power and generalizability as well as diagnostic rigor are often compromised beginning with subject selection. Presently, studies exploring cognitive abnormalities correlated with fibromyalgia as well psychotherapeutic approaches to treatment are scarce and underpowered. Partly due to financial considerations, fMRI studies examining physiological correlates of fibromyalgia contain low numbers of experimental subjects including Cook et al. (2004) (n= 9), Burgmer et al. (2011) (n= 12), and Ellingson et al. (2018) (n= 20). While some imaging studies such as those by Gracely et al. (2004) and Feliu-Soler et al. (2020) recruited higher numbers of fibromyalgia subjects with (n= 29) and (n=47) respectively, they sacrificed the inclusion of control groups, thus preventing between group comparisons. While a greater volume of literature is still needed, promisingly, larger-scale studies across multiple arms have been conducted investigating the additive treatment value of various psychotherapies including Cognitive Behavioral Therapy (CBT) by Alda et al. (2011) (N= 169), Acceptance and Commitment Therapy (ACT) by Luciano et al. (2013) (N= 156), and Mindfulness Based Stress Reduction (MBSR) by Pérez-Aranda et al. (2019) (N=225). Still, comorbid conditions such as dementia, schizophrenia, substance abuse, and acute somatic disorders generally preclude individuals from participation (Luciano et al., 2013). As sample sizes in this area of research are still quite small, particularly in physiological correlate studies, results are disadvantaged by a higher risk of coincidence rather than a thorough representation of a broad demographic (Cook et al., 2004; Burgmer et al., 2011). More research is still needed before psychological models can offer a representative statistical sample being fully comprehensive of the general population.

Fibromyalgia disproportionately affects women nearly twice as often men (Ellingson et al., 2018). However, experimental settings exacerbate this gender disparity further, performing an estimated 85-95% of clinical trials exclusively on female subjects (Paschali et al., 2021). This statistic holds true across studies of both physiological and psychological correlates of fibromyalgia, where the populations comprised entirely of females (Burgmer et al., 2011; Curtis et al., 2011; Wicksell et al., 2012; Andrés-Rodríguez et al., 2019). Even in higher-powered studies examining benefits of various psychotherapies, no single treatment arm exceeded more than 7% males (Alda et al., 2011; Luciano et al., 2013; Pérez-Aranda et al., 2019). With sample sizes of (n= 19) females and (n= 10) males, Gracely et al. (2004) purports the most gender-diverse study included in this review. Most closely mirroring rates of fibromyalgia seen in the general public, results from this study have a high degree of generalizability and are frequently alluded to throughout pain-science literature with 627 citations to date (Gracely et al., 2004).

Though the population of interest was fibromyalgia patients throughout all reviewed literature, the operational definition of who had confirmed this diagnosis as well as according to what criteria differs between studies. The majority of research stipulated that diagnoses be confirmed by a rheumatologist, the preferred diagnostician for fibromyalgia (Burgmer et al., 2011; Sanabria-Mazo et al., 2020; Feliu-Soler et al., 2020). However, patients obtaining diagnoses from family physicians were admitted in other studies (Ellingson et al., 2018; Curtis et al., 2011; Alda et al., 2011). This is problematic as over 75% of general practitioners believe they are unfit to care for fibromyalgia patients and refer patients to rheumatologists for treatment (Zeid et al., 2021). Moreover, the diagnostic criteria for fibromyalgia put forth by the ACR underwent drastic changes between 1990 and 2010, allowing for the inclusion of cognitive symptoms and non-specific somatic issues aside from widespread pain. Unsurprisingly, older studies such as Cook et al. (2004) and Gracely et al. (2004) adhere to the 1990 criteria in which fibromyalgia diagnosis was primarily based on musculoskeletal pain and presenting with tenderness over at least 11 out of 18 standardized points around the body. However, more recent studies allow for the inclusion of subjects with a broader range of symptoms based on the 2010 criteria (Lazaridou et al., 2017; Paschali et al., 2021). These irregularities complicate the ability to draw parallels between study populations along a historical continuum.

Study Design

Both cross-sectional and longitudinal models are prevalent throughout fibromyalgia literature (Paschali et al., 2021). These designs are seen in explorations of both physiological and psychological correlates (Luciano et al., 2013; Cook et al., 2004). Regarding cross-sectional studies, as pain science is still an evolving field, this design implemented by psychological correlate studies such as Andrés-Rodríguez et al. (2019) allows for the benefit of maximal data collection through multiple outcomes measures. The vast amount of information gathered serves to direct further research to clarify what remains a disease shrouded in more questions than answers. As neuroimaging technology continues to improve, a more complete understanding of the nebulous concept of pain has slowly evolved over the past few decades. A commonly cited paper, Gracely et al. (2004) conducted a fMRI study determining specific brain centre activation related to attention, anticipation, and emotion in response to pain which continues to inspire and refine current research. Cross-sectional design additionally allows for straightforward secondary analysis of data between studies, enabling authors of physiological studies to easily compare and contrast results not only based upon study design but also due to the evolution of technological advancements. Study design by Cook et al. (2004) drew upon advancements in 2 single-photon emission computed tomography (SPECT) studies such as those by Mountz et al. (1995) which reported decreased cerebral blood flow at rest to the diencephalon. Unfortunately, regardless of internal upgrades, this design is unable to provide any explanation as to direct causal relationships regarding the elusive underlying pathophysiology of fibromyalgia itself, merely correlations between data points.

Useful for examining long-term effects of psychological therapies on fibromyalgia and protracted physiological differences, longitudinal designs are beneficial for examining delayed trends. Improvements in outcome measures were present immediately after psychological treatment as well as maintained at 8-week and 6-month follow-ups respectively (Curtis et al., 2011; Lazaridou et al., 2017). In contrast, a study examining pain catastrophising and psychological inflexibility achieved significance only upon 3-month follow-up (Sanabria-Mazo et al., 2020) while Pérez-Aranda et al. (2019) reported that MBSR lost significance in comparison to a psychoeducational treatment arm after 12 months. Common complications with longitudinal designs and potentially responsible for the discrepancy in results, Curtis et al. (2011) lacked a control group while Pérez-Aranda et al. (2019) suffered from an average 34% rate of dropout across each of the three study arms. While the latter study was the longest duration longitudinal design included in this review spanning a period of 12 months, research following patients for multiple years let alone decades is unlikely due to ethical constraints, as patients must ultimately be offered the option to take place in an effective experimental condition or return to treatment as usual (TAU) in a timely manner (Luciano et al., 2014).

Measures

Relying on the use of multiple questionnaires, psychological correlate studies assessed for a wide variety of outcome measures (Lazaridou et al., 2017). Although primary outcome was most commonly functional impairment as assessed unanimously via the Revised Fibromyalgia Impact Questionnaire (FIQR), secondary outcomes as well as their mode of appraisal varied (Alda et al., 2011; Luciano et al., 2013). The most frequent secondary outcome and moreover the only questionnaire-based measure assessed on numerous physiological correlate studies, pain catastrophising was evaluated without exception by way of the Pain Catastrophizing Scale (PCS) (Campbell et al., 2012; Sanabria-Mazo et al., 2020). With similar scores reported cross-culturally, the Spanish version of the PCS exhibits meaningful internal consistency (α= 0.79) and test-retest reliability (r= 0.84) (Pérez-Aranda et al., 2019). Additionally, uniformly measured secondary outcomes include perceived stress levels as calculated by the Perceived Stress Scale (PSS-10) and mindfulness via the Five Facet Mindfulness Questionnaire (FFMQ) (Andrés-Rodríguez et al., 2018; Feliu-Soler et al., 2020). Psychological inflexibility was largely measured using the Psychological Inflexibility in Pain Scale (PIPS), with exception noted only by Sanabria-Mazo et al. (2020) instead opting for the Acceptance and Action Questionnaire (AAQ-II) to survey the same construct (Andrés-Rodríguez et al., 2018; Feliu-Soler et al., 2020). With constituent components measuring pain avoidance and fusion with pain thoughts, the PIPS exhibits good internal consistency with Cronbach’s α scores of 0.90 and 0.75 for each component, respectively (Wicksell et al., 2008). Alternatively, the AAQ-II is generally viewed as a measure of acceptance with an excellent Cronbach’s α of 0.91 (Shari et al., 2019).

In studies analysing associations between affective variables such as depression and anxiety, considerably greater heterogeneity was noted in the selected measurement. Utilized by Pérez-Aranda et al. (2019), Feliu-Soler et al. (2020), and others, the predominant determinant of depression was the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). However, Alda et al. (2011) instead employed the Hamilton Rating Scale for Depression (HAM-D) while Wicksell et al. (2012) applied the Beck Depression Inventory (BDI). Far greater than the internal consistency of the HADS-D (α= 0.82) or HAM-D (α= 0.74), the BDI asserts a Cronbach’s α of 0.89 and is particularly attuned to detecting somatic-driven distress (Bjelland et al., 2002; Todorova et al., 2012; Lee et al., 2017; Wicksell et al., 2012). Similarly, while anxiety was most commonly measured via the anxiety subscale of the HADS-A such as by Luciano et al. (2013) and Sanabria-Mazo et al. (2020), it exhibits a lower Cronbach’s α of 0.73 as compared to the State Trait Anxiety Inventory (STAI) with a score of 0.93 utilized by Wicksell et al. (2012) (Aseri et al., 2015; Gustafson et al., 2020). Alda et al. (2011) was the sole study in this review to utilize the Hamilton Anxiety Rating Scale (HARS), however this measure has been criticized for having minimally acceptable test-retest reliability (r= 0.74) (Bruss et al., 1994).

Analysis and Reporting

Overview

Although statistical procedures employed across both psychological and physiological correlate studies of fibromyalgia are quite consistent, deeper consideration of analyses casts scepticism upon obtained results. With numerous outcomes per study, multiple comparisons corrections are essentially, yet inconsistently performed (Sanabria-Mazo et al., 2020). Moreover, missing data figures are frequently projected and included within intention-to-treat analyses, which are ultimately reported as the true outcome of the study itself (Curtis et al., 2011). Lastly, depressive symptoms and antidepressants are often viewed as confounders and excluded from statistical analyses (Gracely et al., 2004). However, since 2008 the Food and Drug Administration in the United States has approved the antidepressant duloxetine as part of the recommended pharmacological treatment for fibromyalgia (Alda et al., 2011). This controversial restriction on reporting limits practicality and generalizability. This discourse will explore the benefits and limitations of such analytical choices as well as offer a dialogue of the effects they may have on data interpretation.

Multiple Comparisons Corrections

As fibromyalgia remains an area of largely exploratory research, many outcome measures are frequently used to maximize the amount of data collected. While this provides a wealth of information, it also leads to unfocused experimental paradigms and subjects data to the risk of false positives.

Table 1

Despite compelling evidence that pain catastrophising is not only a credible risk factor but also a viable treatment target, the majority of psychological correlate studies instead examine fibromyalgia impact as a primary outcome (Table 1; Paschali et al., 2021). Rather, it is typically a secondary study outcome with the exception of Sullivan et al. (1995). As questionnaires are so easily and economically administered, it is exceedingly common for studies utilizing these as measures to commonly report five or more outcomes. Not only is it impossible for study design to capitalize on multiple constructs simultaneously, but this also necessitates the use of a multiple comparisons correction. Utilized by Feliu-Soler et al. (2020), the classic Bonferroni correction applies the same adjusted p-value formula regardless of input value. Alternatively, the Benjamini-Hochberg procedure employed by Sanabria-Mazo et al. (2020) and Pérez-Aranda et al. (2019) adjusts the p-value according to numerically ranked input values. As the Bonferroni correction is more exacting, it can sometimes lead to false negatives (Benjamini, 2010). Overcoming the occasionally criticized limited sensitivity of the Benjamini-Hochberg procedure, the validity of significant findings noted in the follow-up values for Feliu-Soler et al. (2020) utilizing the Bonferroni correction is even more meaningful (Table 1; Benjamini, 2010). Despite using multiple outcome questionnaires, Andrés-Rodríguez et al. (2019) and Luciano et al. (2013) failed to utilize a multiple comparisons correction, creating uncertainty about the validity of significant findings.

Intention-to-Treat Analyses and Missing Data

Mixed-effects models are commonly utilized across fibromyalgia studies to allow for flexibility in dealing with missing data and running intention-to-treat analyses. These measures are necessitated primarily due dropout for various reasons and small sample sizes within the field (Sanabria-Mazo et al., 2020). Error rate is minimized as much as possible through the use of advanced analytical approaches to handling missing data such as via the multiple imputation method (Luciano et al., 2013). However, it remains difficult to justify medical suggestions based on extrapolated data points.

Table 1

Aside from Feliu-Soler et al. (2020), all studies in Table 1 utilized intention-to-treat analyses to calculate reported results. Within psychological treatment arms, reasons for dropout included low level of education as cited by Pérez-Aranda et al. (2019) (n=26) and poor efficacy reported by Luciano et al. (2013) (n=3). The lengthiest longitudinal study included in this review at a period of 12 months, Pérez-Aranda et al. (2013) had the highest dropout rate at follow-up of 35%. Higher than dropout from psychological and TAU study arms, recommended pharmacological treatment groups were plagued by the added issue of adverse somatic effects with most frequently reported symptoms including nausea (25%), dry mouth (23.1%), and fatigue (21.2%) (Luciano et al., 2013).

While MBSR is one of the most promising psychological therapies for fibromyalgia, conclusions reached by Andrés-Rodríguez et al. (2019) were calculated using intention-to-treat models assuming that the 100% of the experimental arm of MBSR+TAU (n= 34) attended 6 or more treatment sessions. However, in reality 38.2% (n= 13) of subjects attended 5 sessions or less (Andrés-Rodríguez et al., 2019). This is problematic as subsequent analyses showed increased effect sizes across all outcome measures as well as improvements in the ratio of IL-6/IL-10 in patients who attended 6 or more sessions, the latter of which was not seen when (n= 34) was collectively analysed (Andrés-Rodríguez et al., 2019).

Table 2

The only physiological study to utilize an intention-to-treat analysis, Curtis et al. (2011) measured diurnal cortisol level change following an 8-week yoga program. When the sample was analysed utilizing subjects who completed the experiment (n= 19), the pre to post cortisol ratio was not significant (p= 0.08) (Table 2). However, using an intention-to-treat analysis including 3 subjects lost to dropout (N=22), a significant relationship was shown in which cortisol increased post intervention (p= 0.014) (Table 2). Concerningly, it was the latter result utilizing extrapolated data that was reported as the actual study result (Curtis et al., 2011). Large-scale research in which all data is based on patients receiving active interventions will be necessary before pivotal overhaul to standard treatment for fibromyalgia can commence.

Depression-Related Confounders

Once thought to be synonymous with pain catastrophising, depression is now known to be an entirely separate construct (Gracely et al., 2004). Despite this it remains an area of controversy and confusion as it is commonly comorbid with fibromyalgia, with wide-ranging rates from 20-80% (Curtis et al., 2011). To eliminate the possibility of affective influence, many studies controlled for this as a confounder (Tables 1 and 2).

Table 1

Psychological correlate studies primarily controlled for the use of antidepressants and number of total medications (Table 1). In studies controlling for antidepressants by Andrés-Rodríguez et al. (2019) and Sanabria-Mazo et al. (2020), MBSR and MAIR experimental arms, respectively, were adjunctive to TAU. Presently, TAU recommendations include duloxetine for fibromyalgia patients suffering from comorbid depression. The view of a condition that may afflict up to 80% of patients and a medication that is currently part of a standard treatment regimen as confounding variables is not only paradoxical but also a substantial hurdle to generalizability. Due to their potential impact on functional and affective outcome measures, future studies are well-warranted in controlling for antidepressants aside from duloxetine, however it is difficult to support excluding a component of current recommended treatment regimens from statistical analyses.

Table 2

Further controlling for additional facets of depression, physiological correlate studies largely controlled for measures of depressive symptomology (Table 2). As physiological construct studies were generally designed to explore cognitive function and activation rather than directly assessing depression as primary or secondary outcome measures, it is difficult determine the impact of controlling for symptomology on results (Table 2). The singular exception to this, Curtis et al. (2011) did in fact report on depression outcome measures via the HADS-D, finding insignificant results (Table 2). Moreover, this was also the only physiological study to control neither for any indications of affective distress nor antidepressant use (Table 2). As alterations in neural activation due to depression are vast and robust, future studies should aim to clarify variations in firing due to affective disorders versus fibromyalgia (Gracely et al., 2004). The existing literature base provides insufficient evidence to confidently establish a significant or insignificant relationship, as it may be, between physiological fibromyalgia markers and depressive symptomology.

Conclusion

Fibromyalgia is a particularly complex disorder, with dysfunctional processes suspected in both the peripheral and central nervous systems, as well as cognitive distortions such as pain catastrophising (Andrés-Rodríguez et al., 2019). It presents a significant burden at individual and societal levels alike, comprising the highest percentage of both unemployment and disability claims of all chronic pain conditions within the European Union (Luciano et al., 2014). Despite the very real suffering patients endure, this diagnosis is often received merely through of elimination of other conditions, especially as diagnostic criteria become increasingly permissive (Paschali et al., 2021). This reality combined with subpar methodological and analytical rigor across fibromyalgia literature often results in diminishing of the disorder itself and accusations of somatization (Lazaridou et al., 2017). Studies frequently suffer from small sample sizes that are disproportionately female, complicating generalization and efficacy of cross-sectional designs (Ellingson et al., 2018). Longitudinal studies offer promising data as to the reliability of psychological treatments long-term, though they are limited in duration due to ethical considerations (Curtis et al., 2011). Numerous outcome questionnaires have provided a wealth of information while research in the field remains in an exploratory phase, however it has somewhat diversified the focus of investigation and necessitated the use of multiple comparisons corrections during data analysis (Sanabria-Mazo et al., 2020). Missing data is often extrapolated and included through intention-to-treat analyses while standard comorbidities such as use of antidepressants are regularly excluded (Andrés-Rodríguez et al., 2019). While fibromyalgia research has made significant strides forward, these faults are noteworthy barriers to uninhibited cross-comparison between studies, fervently necessitating standardized large-scale research representative of affected populations. As literature continues to accumulate and correlational studies repeatedly illuminate avenues for possible causation, efforts should be transitioned to randomized experiments in attempt to ultimately determine a definitive pathogenesis.

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