A somatization comorbidity phenotype impacts response to therapy in rheumatoid arthritis: post-hoc results from the certolizumab pegol phase 4 PREDICT trial

Comorbidities have been shown to substantially contribute to disease activity and treatment response in rheumatoid arthritis (RA) and should therefore be considered when devising treatment strategies for patients with RA [1‐4]. Anxiety and depression are more common in people with RA than in the general population [5], and depression, fatigue, and fibromyalgia have been associated with increased disease activity, reduced odds for reaching clinical remission in RA, and reduced treatment effects and quality of life [4‐8]. However, the impact of these comorbidities on the magnitude of response in a clinical trial setting has not been well characterized, and an efficient approach to identifying patients with these conditions within an RA trial program has not been previously well-described.

Clinical assessment tools, such as the Disease Activity Score in 28 joints (DAS28) and Clinical Disease Activity Index (CDAI), and patient-reported outcome-only tools, such as the Routine Assessment of Patient Index Data 3 (RAPID3), have proven effective for evaluating RA disease activity and predicting treatment response to guide patient management in RA [9‐11]. The presence of comorbidities may also influence treatment outcomes indirectly due to the varying definitions of the state of remission or low disease activity (LDA) across different assessment tools [12]. There is currently no universal agreement on the best measurement tool for RA disease activity, given the strengths and limitations of each [9, 12‐14].

The goal of these exploratory, post-hoc analyses was to define a “somatization comorbidity phenotype” (SCP) that could classify patients with RA participating in a clinical trial who had one or more conditions (e.g. fibromyalgia) that might have contributed to chronic pain independent of RA disease activity, or who had conditions (e.g. depression) other than RA that could have influenced pain and the patient’s self-management of their condition. The second aim was to evaluate whether this phenotype influenced treatment response as assessed by the CDAI and RAPID3 tools and more traditional measures (e.g. ACR response). The analysis was conducted in the Patient/Physician Reported Efficacy Determination in Clinical Practice (PREDICT) trial, among patients with moderate to severe RA initiating treatment with the anti-tumor necrosis factor (anti-TNF) agent, certolizumab pegol (CZP).

In this large RA population with moderate to severe, active RA, we have described a method to efficiently identify a potentially important patient phenotype in a clinical trial setting that includes depression, anxiety, and chronic pain syndromes such as fibromyalgia and neuropathic pain. Patients enrolled in the PREDICT study were assigned to this phenotype based on concomitant medications and/or medical diagnosis at baseline. In total, 43% of patients met the SCP classification at study baseline, and patients with this phenotype demonstrated a substantially lower likelihood of treatment response.

In particular, the SCP that we have defined appears to be important with respect to both predicting treatment response at week 12 (23.3% of +SCP patients achieved DAS28(ESR) LDA versus 29.0% of −SCP patients) and the likelihood of achieving an LDA state after one year of treatment with CZP (25.3% of +SCP patients versus 36.8% of −SCP patients). Furthermore, +SCP patients were 5–14% less likely to achieve ACR20, ACR50, and ACR70 throughout the duration of the 52-week study. Those with the SCP were also 9% more likely to withdraw over the course of this one-year trial. Although speculative, this higher rate of withdrawal for patients with the SCP could be due to perceived lack of benefit of CZP, lower adherence, a higher rate of some AEs, or other factors.

Overall, when using CDAI as the assessment tool, patients with the SCP appeared less likely to be classified as treatment responders by week 12. Response rates appeared to be more comparable regardless of SCP status when the RAPID3 tool was used. This may reflect the fact that CDAI and the DAS28(ESR) – the primary outcome used in the PREDICT trial – are more highly correlated with each other than the RAPID3 and the DAS28(ESR) [30‐32].

Our results may have implications for routine clinical care in deciding which tool to use for RA assessment, given that the RAPID3 reflects a more patient-centric and arguably more holistic assessment than the CDAI, and it is also likely to be easier to implement in busy practices [33]. Irrespective of the SCP phenotype, the primary results of the PREDICT trial showed some differences between the CDAI versus the RAPID3 in the proportion of people classified as responders at 12 weeks [15]. Ultimately, the choice of the preferred tool to assess RA disease activity and treatment response for patients both with and without the SCP phenotype must balance multiple considerations related to performance, feasibility, and the relative importance of physician versus patient data.

The results of our study align with data from previous reports, which demonstrate that depression, anxiety, fibromyalgia, and neuropathic pain are prevalent comorbidities in patients with RA and are associated with increased disease activity, poor treatment adherence, and a reduced likelihood of achieving LDA or remission [2, 6, 7, 24, 34, 35]. Ours is among the first to quantify the impact on a large RA clinical trial patient population with active disease starting treatment with a therapeutic agent known to be effective based on the results of previous phase 3 studies. These differences extended not only to the clinical efficacy outcomes, but also to safety endpoints. The incident rate of TEAEs was higher in +SCP patients than in −SCP patients, with a notably higher rate of infectious events in the +SCP group, including SIEs. The magnitude of the difference in the rates of SIEs between +SCP and −SCP patients (3.3/100 PY) in this analysis, all of whom were receiving CZP therapy, was comparable to the difference between CZP and placebo treatment in other RA studies [36]. Depression and other patient factors have been associated with adverse events such as infections [37], cardiovascular disease [38], myocardial infarction [39], and an increased risk of mortality [40], according to past studies. This may reflect a true biologic association, as inflammatory markers such as C-reactive protein have been shown to be associated with depression [41], although these conditions may be a proxy for related factors (e.g. health-seeking behavior, perceived illness severity) that could impact the reporting of more subjective or less severe adverse events. Collectively, these findings suggest that the SCP phenotype may be a useful and easily ascertained proxy in an RA clinical trial population for factors making patients less likely to achieve a good clinical response and less likely to tolerate some RA treatments.

The limitations of these analyses included the fact that the PREDICT study only enrolled patients in the USA, and the patients with fibromyalgia symptomatic enough to be treated were excluded by protocol at the discretion of the local investigator, though no systematic identification or exclusion at the time of randomization was enforced. In addition, it is possible that patients with the SCP but who did not have a formal diagnosis and who were not taking any indicated medications, were misclassified. Assuming that the patients with the most severe manifestations of this condition were excluded from the study, and that some patients had not been diagnosed nor were using medication to manage their SCP, our results likely represent a conservative estimate of the effect that the SCP phenotype had on treatment response as measured by standard tools such as the achievement of DAS28(ESR) LDA and ACR response, suggesting that the impact of this phenotype in real-world settings may be even more profound. This exclusion might raise concerns about the generalizability of the study’s results to the typical RA patient population seen in the USA. However, even with the exclusion in place, we note that a high proportion of patients using medications indicated for depression, anxiety, neuropathic pain, and fibromyalgia were in fact enrolled in the study and had the SCP (43% of the PREDICT trial population). Moreover, in many other RA trials, study criteria commonly exclude patients with conditions deemed by the site investigator “to be symptomatic enough to interfere with the measurement of treatment response” [19, 42]. However, this exclusion criterion is highly subjective and is rarely enforced in a reproducible fashion. For this reason, RA trials can be expected to include a mix of these patients, but previously these individuals have not been easily identified without the added burden of incorporating additional, specific screening tools to classify patients as having fibromyalgia [43] or depression [44]. While these types of screening instruments could be systematically applied to an RA cohort or trial [45], the phenotype we defined has the advantage that it can be applied to data routinely captured at baseline in RA clinical trials, requiring only concomitant medications and/or diagnoses instead of a specific screening instrument, thereby minimizing participant burden for additional data collection.

These analyses have highlighted that the inclusion of large numbers of patients with the phenotype in an RA trial may appreciably affect the proportion of patients who are able to achieve an absolute disease state treatment target, such as LDA or remission. On the other hand, if new trials excluded individuals with the somatization comorbidity phenotype from a trial, this could somewhat limit the generalizability of the results and hinder comparability between trials, as the proportion of such patients in RA trials across the globe is likely to vary widely. In addition, allowing patients with the somatization comorbidity phenotype in RA studies may contribute to a ceiling effect, as patients may not demonstrate as much improvement with effective RA therapies in comparison to patients without this phenotype.

In the PREDICT clinical trial, 43% of patients met the “somatization comorbidity phenotype” classification criteria for diagnosis and/or use of medications indicated for depression, fibromyalgia, anxiety, or neuropathic pain. These patients were significantly more likely to withdraw from the trial and/or experience adverse events, and approximately 10–14% less likely to achieve a clinical response. These results suggest that depending on the outcome measure used (e.g. DAS28), enrolling large numbers of patients with this phenotype may affect the proportion able to achieve LDA or remission, making it advisable to consider whether to include, identify, or stratify these patients during the study design or study screening processes in future RA clinical trials.