The Clinical Utility of a Chemokine-Cytokine Multiplex Assay in Fibromyalgia Diagnosis at an Academic Medical Center

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Mohabbat, Elizabeth C. Wight, Tammi R. Johnson, Page E. McCarthy, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4145257/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction/Objective: To assess the clinical utility of the FM/a® chemokine-cytokine assay in diagnosing fibromyalgia at an academic medical center. Methods: We performed a cross-sectional study on 50 patients diagnosed with fibromyalgia at a specialty fibromyalgia clinic between January 1, 2021 through July 31, 2021. Patients completed questionnaires and provided a venous blood sample sent to EpicGenetics, to complete the FM/a® test. Demographic, symptom, and historical data was obtained from chart review. Statistical analysis was performed. Results: Of 50 patients with a clinical diagnosis of fibromyalgia, the FM/a® test was positive in 45 (90%). Performance of the FM/a® test compared to the 2016 ACR criteria yielded an odds ratio of 3.5 with sensitivity of 0.91, specificity of 0.25. Univariate regression demonstrated an area under the curve (AUC) of 0.7337, which improved to 0.89 when adjusted for age, gender, and race. When compared to the 1990 ACR criteria, a positive FM/a® test had an odds ratio of 2.33 with sensitivity 0.92 and specificity 0.17. Univariate regression analysis demonstrated an AUC of 0.571, when adjusted for age, gender and race, AUC was similar at 0.585. Conclusion: The FM/a® test performed well overall, though inferiorly compared to the 1990 and 2016 ACR diagnostic criteria. When adjusted for age, gender, and race the test performed almost equivalently to the 2016 ACR criteria. The FM/a® test may be useful in general clinical practices to differentiate patients who are more likely to have FM. Fibromyalgia Pain Diagnosis FMa Assay Figures Figure 1 Introduction Fibromyalgia (FM) is a chronic centralized pain sensitivity disorder, characterized by widespread pain, fatigue, cognitive and sleep disturbances, and numerous other symptoms [ 1 , 2 ]. The estimated prevalence of FM ranges between 2–8% of the population [ 1 , 2 ]. The average medical costs associated with FM are 2–3 times higher compared to a healthy individual [ 3 , 4 ]. The diagnosis of FM has relied on clinical history, physical examination, and the usage of standardized diagnostic criteria, such as the American College of Rheumatology (ACR) diagnostic criteria from 1990 as well as the revised 2016 ACR criteria [ 5 – 8 ]. These validated criteria take into account factors such pain distribution, tender points, Widespread Pain Index scale (WPI), and the Symptom Severity scale (SS) [ 7 ]. Of note, the WPI and SS are often added together to form the Fibromyalgia Score (FS), providing a composite score of both pain (WPI) and non-pain (SS) related symptoms in FM. In addition to the requisite clinical history, examination, and above diagnostic criteria, many healthcare professionals concomitantly obtain numerous screening tests to rule in or out other diagnostic possibilities (Table 1 ). As a consequence, several studies have demonstrated the significant time delay, effort, and cost associated with obtaining a formal diagnosis of FM [ 1 , 9 – 12 ]. The FM/a® test is a chemokine-cytokine multiplex assay that assesses the production and concentration patterns of four distinct immunological markers (IL-6, IL-8, MIP-1 alpha, and MIP-1 beta) after mitogenic stimulation of peripheral blood mononuclear cells [ 13 , 14 ]. Previous results have demonstrated a distinct biomarker pattern in FM, allowing it to distinguish FM from healthy controls as well as other studied conditions (rheumatoid arthritis and systemic lupus erythematous) [ 13 , 14 ]. The FM/a® test report contains both a score result (ranging 0-100) as well as clinical interpretation statement: score 0–49, not confirmable (-); score 50–80, confirmable (+); score 81–90, strongly confirmable (++); score 91–100, extremely confirmable (+++) [ 13 , 14 ]. We designed a cross-sectional study to assess the overall diagnostic clinical utility of the FM/a® test in our specialized clinical practice (Mayo Clinic Fibromyalgia and Chronic Fatigue Clinic). We sought to address the following aims: (1) to compare the diagnostic utility of the FM/a® test to the 1990 and 2016 ACR diagnostic criteria; (2) to assess if the FM/a® test result correlates with FM severity, as assessed via validated instruments (WPI, SS, FS, or tender point count); (3) to identify any demographic differences in the diagnostic clinical utility of the FM/a® test in our clinical practice; (4) to analyze the cost-effectiveness between the FM/a® test vs our standard clinical practice ; and (5) to assess patient interest and satisfaction with the use of the FM/a® test. Methods Study Design This investigation was designed as a cross-sectional study, consisting of a prospective observational component (health questionnaires and venous blood sample analysis) along with a retrospective chart review component (demographic and FM-applicable historical data capture). Participant Population and Selection Participants included patients who attended Mayo Clinic’s Fibromyalgia and Chronic Fatigue Clinic (Rochester, MN) from January 2021 through July 2021. The study cohort consisted of 50 patients who received (or confirmed) a formal diagnosis of FM based on clinical history, examination, and by meeting the diagnostic criteria set forth by the 1990 and/or 2016 ACR diagnostic criteria (per our clinic’s standard clinical practice). Formal inclusion criteria consisted of participants aged 18 or older, ability and willingness to complete research surveys, and willingness to undergo an additional phlebotomy session. Furthermore, based on the specific characteristics of the FM/a® chemokine-cytokine multiplex assay, patients were screened (by a study team member) to ensure that they had not utilized, within the past 60 days, any of the medications known to interact with the multiplex assay; this medication list was provided by the test manufacturer (Table 2 ). Informed consent was obtained from the participants to participate in the current study. This study was performed in accordance with the principles of the Declaration of Helsinki and ethical standards of Mayo Clinic. Mayo Clinic’s Institutional Review Board committee approved this study (protocol number 20-010430). Data Collection The retrospective components of the study were achieved via chart review, consisting of demographic and clinical information abstraction. Prospective data components consisted of completing a study interest/satisfaction survey along with the venous blood sample for the FM/a® test. The study interest/satisfaction questionnaire consisted of questions asking participants if they thought there exists a specific diagnostic blood test for FM, as well as whether they would be interested in pursuing such a test. The venous blood sample consisted of a onetime blood draw into a 5 mL, purple top tube. Samples were shipped the same day they were drawn via ambient temperature, overnight, to EpicGenetics for FM/a® testing. Additional details regarding the processing and laboratory analysis of samples have been previously described [ 13 , 14 ]. Statistical Analysis Survey results and data abstracted from the electronic medical records were electronically collected and stored using the Research Electronic Data Capture (REDCap) software hosted by the Mayo Clinic Center for Clinical and Translational Science. All information was password protected. Continuous variables were summarized as either median with interquartile range (IQR) or mean with standard deviation. Fisher’s exact test was utilized for categorical variables, the t-test was used for continuous variables with two groups, and ANOVA for continuous variables with three or more groups. Sensitivity, specificity, and odds ratios were calculated using an FM/a® score of 50 or greater as a positive result. Correlation was evaluated using Pearson’s product-moment. Univariate and multivariate logistic regression and receiver operating curves were used to evaluate the association between the FM/a score and the 1990 and 2016 ACR diagnostic criteria. Univariate and multivariate logistic regression was performed to determine the degree of correlation between the FM/a® score and FM severity as determined by the FS. Statistical significance was defined as p-value of less than 0.05 from two-sided tests. All analyses were performed using BlueSky Statistics version 10 software (BlueSky Statistics LLC, Chicago, Illinois) Results Participant Demographics In total, 50 individuals with FM participated in the study. All of the collected demographic and symptom/clinical factors are presented in Table 3 . Fibromyalgia Diagnostic Criteria, Severity, and Scores In accordance with the study inclusion criteria, all 50 of the participants received a clinical diagnosis of FM; 38 (76%) individuals fulfilled the 1990 ACR criteria, 46 (92%) individuals met the 2016 ACR criteria, and 37 (74%) participants met both criteria (Table 3 ). Additional information regarding symptom duration and specific validated FM diagnostic scores can be found in Table 3 . FM/a® results Blood sample results demonstrated that 45 (90%) samples were positive (confirmable), while 5 (10%) samples were negative (not confirmable). The mean FM/a® score was 78.8 (range 5.0–98.0; 1st quartile 76.5; 3rd quartile 94.0; median 88.5) (Table 4 ). FM/a® scores were independently associated with gender, age, and race. The FM/a® score was significantly associated with gender (mean FM/a® score of 81.6 +/- 22.9 in women vs 42.6 +/- 36.6 in men; p < 0.001), race (mean FM/a® score of 89.3 +/- 10.5 in non-whites vs 72.1 +/- 30.7 in whites; p < 0.01), and age (mean age of 43.9 years +/- 12.5 in those with a positive FM/a® test result vs 32.6 years +/- 7.2 in those with a negative FM/a® test result; p < 0.05). The FM/a® score directly correlated with the TP count (r = 0.314; p < 0.05) but was not correlated with the WPI (p = 0.23) or FS (p = 0.67). (Table 4 ). Additional analysis revealed no statistically significant correlations between the FM/a® score and the duration of symptoms (p = 0.32), number of medications (p = 0.95), smoking status (p = 0.296), opioid use (p = 0.74), or disability status (p = 0.31) FM/a® Performance Analysis 1. Performance Analysis Compared to the 2016 ACR Criteria We analyzed the FM/a® test performance solely against the 2016 ACR criteria. Using a cut-off of 50, sensitivity was 0.91 and specificity was 0.25. A positive FM/a® result yielded an odds ratio of 3.5. Univariate logistic regression of the FM/a® score vs the 2016 ACR criteria demonstrated an area under the curve (AUC) of 0.7337, with an optimal cutoff of 67 in our population yielding a sensitivity of 0.87 and specificity of 0.75 (Fig. 1 [1a]). When adjusted for the factors of age, gender, and race, the performance of the FM/a® test vs the 2016 ACR criteria improved notably. The adjustment increased the AUC to 0.89 when the FM/a results were treated as a binary variable, and 0.91 when treated as a continuous variable (Fig. 1 [1b]). Logistic regression analysis demonstrated no statistically significant association between the FM/a® score and FM disease severity as measured by the FS (r = 0.0017, p = 0.9537 for univariate analysis; r = 0.251, p = 0.71 for multivariate analysis). Performance Analysis Compared to the 1990 ACR Criteria We analyzed the FM/a® test performance solely against the 1990 ACR criteria. A positive FM/a® test had an odds ratio of 2.33 with a sensitivity of 0.92 and specificity of 0.17. Univariate logistic regression analysis demonstrated an AUC of 0.5711. Adjusting for age, gender and race yielded similar performance (AUC of 0.585). Performance Analysis Compared to the FS We evaluated the performance of the FS (WPI + SS) as a simplified diagnostic tool compared to the 2016 and 1990 criteria. Univariate logistic regression resulted in an AUC of 0.93 with an optimal FS score of 17 in our specific clinic/patient population (SN = 0.86; SP = 1.00) (Fig. 1 [2a]). When the FS was adjusted for age, gender, and race, the AUC increased to 0.9701 with a sensitivity of 0.89 and specificity of 1.00 at the optimal cut point (Fig. 1 [2b]). Performance of the FS was significantly diminished when applied to the 1990 ACR criteria. Univariate analysis yielded an optimal cut point of 22, resulting in a sensitivity of 0.55, specificity of 0.67, and AUC of 0.62. Adjusting for age, gender and race gave a marginal improvement (optimal sensitivity of 0.50, specificity of 0.83; AUC of 0.63). Cost-effectiveness comparison We evaluated the cost differences between the FM/a® test and our clinic’s standardized prerequisite testing approach (Table 1 ). The retail cost (assuming no insurance coverage) for the FM/a® test was $ 1080. In comparison, the combined retail cost of our prerequisite studies, which are obtained to evaluate for potential alternative diagnoses, is approximately $ 2,200; this does not include the costs associated with consultations (office visits, subspeciality referrals). Health questionnaires: interest/satisfaction results Most patients (72%) were unsure if there was a diagnostic test available for FM, while nearly all patients (92%) reported they would be interested or strongly interested in such a test. Only 3 patients (6%) reported being aware of a diagnostic test for FM. Discussion This cross-sectional study was conducted with multiple previously stated aims. Each of these aims will be discussed in-depth separately. Diagnostic Utility of the FM/a® Test In the cohort of 50 participants with FM, 45 (90%) were positive (confirmable) based on the FM/a® test, while 5 (10%) were negative (not confirmable). This result exceeded our group’s initial hypothesis (75% confirmability). On a more granular level, the performance analysis of the FM/a® test in direct comparison to the 1990/2016 ACR criteria demonstrated that the FM/a® test performed inferiorly to both the 1990 and 2016 ACR diagnostic criteria. This inferiority was more notable when not adjusting for certain demographic factors such as age, gender, and race. When adjusted for, the performance of the FM/a® test improved significantly, almost reaching equivalence to the ACR criteria in terms of diagnostic accuracy. We also noted poor predictive accuracy of the FM/a® test in a specific subtype of FM (non-pain predominant FM); these are individuals, who though meet the diagnostic criteria for FM, exhibit less of a pain phenotype (low WPI) and a more of a non-pain phenotype (high SS). The analysis also demonstrated that in our specialized FM clinic, where there is a higher prevalence of FM (as compared to a general practice), better precision of test performance is needed. We were able to improve the test performance in this respect by adjusting the positive cut-off value, based on logistic regression and Youden statistical analysis. Overall, we feel that this test could be very useful in “upstream” general clinical practices, rather than in “downstream” subspecialty practices (such as our FM clinic). In general clinical practices, where the familiarity with and time required to assess the ACR criteria (or FM in general) might be limited, clinicians could obtain the FM/a® test as an initial step, and if positive, could either proceed with the ACR diagnostic criteria or refer the patient to a more specialized clinic. The adoption of the FM/a® test in such settings would greatly help to efficiently differentiate patients, streamlining the work-up and significantly helping to lessen overall burden (time, cost, appointments) for both patients and healthcare professionals. FM/a® Test Correlation with Disease Severity The analysis did not show any correlation between FM disease severity (WPI, SS, or FS score) and the FM/a® test result. In contrast, the FM/a® score did correlate directly to FM disease severity, as determined by the 1990 ACR criteria (TP count). Specifically, patients with a higher FM/a® score experienced a greater number of TP. Though we are uncertain as to the underlying correlative mechanism, we feel that this is a very useful association, which could be readily appreciated by and empowering to suffering patients, especially when given so many unrevealing test results. Demographic Differences in the Diagnostic Clinical Utility of the FM/a® Test Several demographic factors were significantly associated with the FM/a® test results. First, the FM/a® score was significantly associated with gender; when adjusted for other factors, female gender was associated with a statistically significant higher FM/a® score. Second, the FM/a® score was significantly associated to race; non-white race was associated with a statistically significant higher FM/a® score than white race. Third, the FM/a® score was significantly associated with age; a positive test result was significantly associated with increased age, as compared to a negative test result. Of note, there were no statistically significant correlations between the FM/a® score and other key factors (duration of symptoms, number of medications, smoking status, opioid use, or disability status). Given the nature of the chemokine-cytokine multiplex assay, we hypothesize that the impact of age, gender, and race are directly related to their effects on underlying T-cell function and other immune-related mechanisms. We believe that the FM/a® test would benefit (greater predictive accuracy) from further analytic refinement to address and correct for the impact of factors, including age, gender, race, and potentially other un-analyzed factors. Cost-Effectiveness of the FM/a® Test The FM/a® test is positioned as a “rule in” study; this is contrast to the “rule out” paradigm that many clinical practices utilize, ordering numerous tests and sub-speciality consultations to exclude alternative diagnoses. The retail cost of the FM/a® test is $ 1080 with results usually available within 7 business days. In direct comparison, our specialized referral-based clinic in an academic medical center, requires several tests/studies (Table 1 ) to be performed prior to formal evaluation in our clinic. The combined retail cost of our prerequisite studies is approximately $ 2,200. The results of these studies, which are usually available with 1–2 days, are primarily used (in conjunction with the clinical history and physical examination) to exclude conditions that commonly mimic the presentation of FM. Patient Interest in the FM/a® Test The majority (72%) of patients were unaware or unsure of the availability of a potential diagnostic test for FM. However, an overwhelming 92% of participants reported that they would be interested or strongly interested in such a test. In our assessment, patients have awaited a FM-specific diagnostic study for a long time and would be very eager to obtain this for diagnostic purposes. FM/a® test and Medication Interactions During the development of the study protocol, we received a list of medications that according to EpicGenetics would significantly interfere with the multiplex assay (Table 4 ). According to the manufacturer, participants would need to have been off all the listed medications for at least 60 days. Accordingly, we incorporated this into our participant screening process and exclusion criteria. The medication/assay interactions resulted in numerous logistical challenges, and we predict will likely create issues for its widespread adoption in general clinical practices. The list of medications, which continues to evolve, is currently at more than 50 medications. Many of these medications are commonly utilized for highly prevalent conditions. We foresee that this intrinsic test limitation will be challenging for many clinical practices, as it will be difficult to consistently identify patients that have entirely abstained from these exclusionary medications. Furthermore, we would not recommend tapering/discontinuing a chronic medication regimen solely for test obtainment purposes, especially given the well performing ACR criteria. Strengths and Limitations This study was the first independently designed and performed trial looking at the clinical utility of the FM/a® test in a specialized FM practice at an academic medical center. This study was conducted using a rigorous protocol and data analysis to provide an unbiased conclusion on the utility of this assay in our practice. There are several limitations to the study. First, the sample size of our cohort was limited to 50 participants with FM. Future studies should aim for a larger sample size, evaluating performance in other chronic pain population, as well as in patients with frequent comorbid conditions, such as chronic fatigue, irritable bowel syndrome, and interstitial cystitis. Second, though the study was designed and analyzed independently from the test manufacturer, the blood samples were processed and resulted by EpicGenetics. Third, our study was performed in a referral-based speciality FM clinic, where we have extensive experience and familiarity with the ACR criteria. Future studies should assess the clinical utility of the assay in more general clinical practices. Conclusion The FM/a® test is a novel and useful tool for the diagnosis of FM. The assay correctly identified 90% of cases. Overall, it performed inferior to the 1990 and 2016 ACR diagnostic criteria in our specialized FM practice. However, once adjusted for factors such age, gender, and race, the performance of the FM/a® test improved significantly, nearing equivalence with the ACR criteria. Further analytical refinement due to the impact of these demographic factors, as well as the numerous medication-assay interactions is strongly recommended. Declarations Acknowledgements The authors would like to acknowledge the staff at Mayo Clinic’s Fibromyalgia and Chronic Fatigue Clinic for their assistance in the study and the participants for donating their time for the study. Data availability: The datasets utilized during and/or analyzed during the current study are available from the corresponding author on reasonable request. Funding: Financial and material support provided by EpicGenetics Conflicts of interest/Competing interests: The authors do not have any conflicts of interest to disclose. Data availability: The datasets utilized during and/or analyzed during the current study are available from the corresponding author on reasonable request. Code availability: Not applicable Ethical Guidelines: This study was performed in accordance with the principles of the Declaration of Helsinki and ethical standards of Mayo Clinic. Authors’ contributions: All included authors certify they contributed to the work and approve of the submitted manuscript according to the guidelines on the Role of Authors and Contributers,ICMJE. References Clauw DJ. Fibromyalgia: A clinical review. JAMA. 2014; 311 (15), 1547–1555. doi: 10.1001/jama.2014.3266 Clauw DJ, D’Arcy Y, Gebke K, Semel D, Pauer L, Jones KD. Normalizing fibromyalgia as a chronic illness. 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The American College of Rheumatology 1990 Criteria for the Classification of Fibromyalgia. Report of the Multicenter Criteria Committee. Arthritis Rheum. 1990;33(2):160–72. https://doi.org/10.1002/art.1780330203 Wolfe F, Clauw DJ, Fitzcharles MA, Goldenberg DL, Häuser W, Katz RS, Mease P, Russell AS, Russell IJ, Winfield JB. Fibromyalgia criteria and severity scales for clinical and epidemiological studies: a modification of the ACR Preliminary Diagnostic Criteria for Fibromyalgia. J Rheumatol. 2011;38(6):1113–22. https://doi.org/10.3899/jrheum.100594 Wolfe F, Clauw DJ, Fitzcharles MA, Goldenberg DL, Häuser W, Katz RL, Mease PJ, Russell AS, Russell IJ, Walitt B. 2016 Revisions to the 2010/2011 fibromyalgia diagnostic criteria. Semin Arthritis Rheum. 2016; https://doi.org/10.1016/j.semarthrit.2016.08.012 Chandran A, Schaefer C, Ryan K, Baik R, McNett M, Zlateva G. The comparative economic burden of mild, moderate, and severe fibromyalgia: results from a retrospective chart review and cross-sectional survey of working-age U.S. adults. J Manag Care Pharm. 2012;18(6):415–26. https://doi.org/10.18553/jmcp.2012.18.6.415 Berger A, Dukes E, Martin S, Edelsberg J, Oster G. Characteristics and healthcare costs of patients with fibromyalgia syndrome. Int J Clin Pract. 2007; 61(9):1498–508. https://doi.org/10.1111/j.1742-1241.2007.01480.x Wolfe F, Anderson J, Harkness D, Bennett RM, Caro XJ, Goldenberg DL, Russell IJ, Yunus MB. A prospective, longitudinal, multicenter study of service utilization and costs in fibromyalgia. Arthritis Rheum. 1997;40(9):1560–70. https://doi.org/10.1002/art.1780400904 Choy, E., Perrot, S., Leon, T. et al. A patient survey of the impact of fibromyalgia and the journey to diagnosis. BMC Health Serv Res 2010;. https://doi.org/10.1186/1472-6963-10-102 Behm FG, Gavin IM, Karpenko O, Lindgren V, Gaitonde S, Gashkoff PA, Gillis BS. Unique immunologic patterns in fibromyalgia. BMC Clin Pathol. 2012;17;12:25. https://doi.org/10.1186/1472-6890-12-25 . Wallace DJ, Gavin IM, Karpenko O, Barkhordar F, Gillis BS. Cytokine and chemokine profiles in fibromyalgia, rheumatoid arthritis and systemic lupus erythematosus: a potentially useful tool in differential diagnosis. Rheumatol Int. 2015;35(6):991–996. https://doi.org/10.1007/s00296-014-3172-2 . Tables Table 1: Prerequisite Studies for Consultation in the Fibromyalgia Clinic. Complete blood count with differential Electrolyte panel Calcium Creatinine with EGFR Blood urea nitrogen Glucose, fasting Thyroid function cascade Aspartate aminotransferase Alanine aminotransferase Creatinine kinase Rheumatoid factor Cyclic citrullinated peptide Antinuclear antibody AM cortisol Celiac disease serology cascade 25-Hydroxyvitamin D2 and D3 Serum protein electrophoresis Overnight oximetry Table 2. List of pharmaceuticals known to interact with the FM/a® chemokine-cytokine multiplex assay. Medications Inhalers Prednisone Methotrexate Zafirlukast (Accolate) Montelukast (Singulair) Hydrocortisone (Cortef) Fludrocortisone (Florinef) Triamcinolone (Kenalog) Methylprednisolone (Medrol) Prednisolone (Millipred) Dexamethasone (Decadron) Budesonide (Entocort) Sirolimus (Rapamune) Leflunomide (Arava) Azathioprine (Imuran) Mycophenolic acid (CellCept, Myfortic) Tofacitinib (Xeljanz) Abatacept (Orencia) Adalimumab (Humira) Etanercept (Enbrel) Golimumab (Simponi) Infliximab (Remicade) Baricitinib (Olumiant) Tocilizumab (Actemra) Upadacitinib (Rinvoq) Sarilumab (Kevzara) Cyclosporine Tacrolimus Hydrea Advair, AirDuo, ArmonAir, Arnuity, Breo, Flovent, Trelegy, Wixela (fluticasone) Alvesco (ciclesonide) Dulera (mometasone) Pulmicort, Symbicort (budesonide) QVAR (beclomethasone) Nasal Sprays Aller-Flo, Dymista, Flonase, Veramyst, Xhance (fluticasone) Beconase, QNASL (beclomethasone) Nasacort (triamcinolone) Nasonex (mometasone) Omnaris (ciclesonide) Rhinocort (budesonide) Special considerations: Steroid or cortisone injections are problematic Topical eye/ear steroids are okay Fluocinonide topical can be problematic if used long term Table 3. Participant demographics and symptom information Demographic Value (N = 50) Age 42.7 years (32.3-50.8) Female gender 43 (86%) White race 43 (86%) Smoking status Current Former Never 4 (8%) 17 (34%) 28 (56%) Disability Current Previous Never 6 (12%) 1 (2%) 43 (86%) Opioid use for chronic pain Current Former Never 2 (4%) 13 (26%) 33 (66%) Symptom duration 11.5 years (5-15) Central sensitization disorders 3 (2-4) Widespread pain index (out of 19) 12 (7-16) Symptom severity score (out of 12) 8 (7-11) Tender points (out of 18) 15 (12.25-18) Five pain regions 43 (86%) Fibromyalgia score 21.5 (17.3-25.0) Met 1990 ACR* diagnostic criteria 38 (76%) Met 2016 ACR* diagnostic criteria 46 (92%) Met 1990 and 2016 ACR* criteria 37 (74%) *ACR: American College of Rheumatology Table 4. FM/a® test results and statistical analysis of FM/a® scores compared to demographic and symptom. Test Value p-value Positive (confirmable) (N=50) 45 (90%) Negative (not confirmable) (N=50) 5 (10%) FM/a® test score 78.8 (76.5-94.0) Gender Women: mean FM/a® score 81.6 +/- 22.9 Men: mean FM/a® score 42.6 +/- 36.6 p <0.001 Race Non-white: mean FM/a® score 89.3 +/- 10.5 White: mean FM/a® score 72.1 +/- 30.7 p < 0.01 Age Positive FM/a®: 43.9 years +/- 12.5 Negative FM/a®: 32.6 years +/- 7.2 p < 0.05 Tender Point Count r = 0.314 p < 0.05 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Mohabbat","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Arya","middleName":"B.","lastName":"Mohabbat","suffix":""},{"id":300711211,"identity":"8c3a0db1-4df6-4729-9b3b-2a1c429406d3","order_by":1,"name":"Elizabeth C. Wight","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIiWNgGAWjYDACZgY2ECUDJEGMA3JwcbxaDjAw8EC0JBwwJqyFAaqFAaolsYGQFoPj7Ncef2Cw4eHjP/zswccfd9LXtp8xfMBQYQ3Ti6nlME+5wQGGNKDDjpkbzkh4lrvtTI6xAcOZdJxazA7zpEkcYDjMw8bYYCbNk3A4d9uBHDMJxrbDhLT852FjZv8m/SfhcLrZ+TdALf/waWE/BtRygIeNjcdMmiHhcILZDZAtDbi12AOdJHHGIJmHjYen3LAn7bDhthvPig0SjqUb49Ii2X/8mURFhZ2cfP/xbQ9+2ByWNzufvPHBhxprWVxagDFiAAw3FBEOA4YEnMpBgP0BYZFRMApGwSgY2QAAYhNZxkJvF20AAAAASUVORK5CYII=","orcid":"","institution":"Mayo Clinic","correspondingAuthor":true,"prefix":"","firstName":"Elizabeth","middleName":"C.","lastName":"Wight","suffix":""},{"id":300711212,"identity":"2a767ff9-c4f7-45dd-88b6-4bf638aae033","order_by":2,"name":"Tammi R. Johnson","email":"","orcid":"","institution":"Mayo Clinic, Mayo Clinic BioPharma Diagnostics","correspondingAuthor":false,"prefix":"","firstName":"Tammi","middleName":"R.","lastName":"Johnson","suffix":""},{"id":300711214,"identity":"117f830b-d7ee-452c-bd7c-74add0908e58","order_by":3,"name":"Page E. McCarthy","email":"","orcid":"","institution":"Mayo Clinic, Mayo Clinic BioPharma Diagnostics","correspondingAuthor":false,"prefix":"","firstName":"Page","middleName":"E.","lastName":"McCarthy","suffix":""},{"id":300711217,"identity":"8b033245-8378-45ee-ab38-0c499ceee63f","order_by":4,"name":"Christopher A. Aakre","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"A.","lastName":"Aakre","suffix":""},{"id":300711220,"identity":"2be8a9d7-46a1-4943-a6cc-2fc8eaa73c66","order_by":5,"name":"Shari L. Bornstein","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Shari","middleName":"L.","lastName":"Bornstein","suffix":""},{"id":300711224,"identity":"d80ac697-9ab5-4106-859c-9541a997bf11","order_by":6,"name":"Ravindra Ganesh","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Ravindra","middleName":"","lastName":"Ganesh","suffix":""},{"id":300711227,"identity":"64fa58c6-ba90-428e-b1ee-7a741d37100e","order_by":7,"name":"Bradley R. Salonen","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Bradley","middleName":"R.","lastName":"Salonen","suffix":""},{"id":300711230,"identity":"e3d01531-9297-421c-8b9d-b164ae0111d0","order_by":8,"name":"Dennis M. Bierle","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Dennis","middleName":"M.","lastName":"Bierle","suffix":""}],"badges":[],"createdAt":"2024-03-21 17:59:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4145257/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4145257/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56410170,"identity":"45bdb77c-3f07-4d6f-89e1-d004d833030f","added_by":"auto","created_at":"2024-05-13 20:16:18","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":370497,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"SpringerFMandFMAFigures.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4145257/v1/070bc5192eaf4e197ec1fbb6.jpg"},{"id":60556549,"identity":"bab55da0-04de-4e06-9bfb-b6a9832fb899","added_by":"auto","created_at":"2024-07-18 06:37:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1068617,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4145257/v1/6ac23d6d-36cb-4574-8cb4-39431e5f22d7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Clinical Utility of a Chemokine-Cytokine Multiplex Assay in Fibromyalgia Diagnosis at an Academic Medical Center","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFibromyalgia (FM) is a chronic centralized pain sensitivity disorder, characterized by widespread pain, fatigue, cognitive and sleep disturbances, and numerous other symptoms [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The estimated prevalence of FM ranges between 2\u0026ndash;8% of the population [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The average medical costs associated with FM are 2\u0026ndash;3 times higher compared to a healthy individual [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe diagnosis of FM has relied on clinical history, physical examination, and the usage of standardized diagnostic criteria, such as the American College of Rheumatology (ACR) diagnostic criteria from 1990 as well as the revised 2016 ACR criteria [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These validated criteria take into account factors such pain distribution, tender points, Widespread Pain Index scale (WPI), and the Symptom Severity scale (SS) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Of note, the WPI and SS are often added together to form the Fibromyalgia Score (FS), providing a composite score of both pain (WPI) and non-pain (SS) related symptoms in FM.\u003c/p\u003e \u003cp\u003eIn addition to the requisite clinical history, examination, and above diagnostic criteria, many healthcare professionals concomitantly obtain numerous screening tests to rule in or out other diagnostic possibilities (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). As a consequence, several studies have demonstrated the significant time delay, effort, and cost associated with obtaining a formal diagnosis of FM [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe FM/a\u0026reg; test is a chemokine-cytokine multiplex assay that assesses the production and concentration patterns of four distinct immunological markers (IL-6, IL-8, MIP-1 alpha, and MIP-1 beta) after mitogenic stimulation of peripheral blood mononuclear cells [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Previous results have demonstrated a distinct biomarker pattern in FM, allowing it to distinguish FM from healthy controls as well as other studied conditions (rheumatoid arthritis and systemic lupus erythematous) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe FM/a\u0026reg; test report contains both a score result (ranging 0-100) as well as clinical interpretation statement: score 0\u0026ndash;49, not confirmable (-); score 50\u0026ndash;80, confirmable (+); score 81\u0026ndash;90, strongly confirmable (++); score 91\u0026ndash;100, extremely confirmable (+++) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe designed a cross-sectional study to assess the overall diagnostic clinical utility of the FM/a\u0026reg; test in our specialized clinical practice (Mayo Clinic Fibromyalgia and Chronic Fatigue Clinic). We sought to address the following aims: (1) to compare the diagnostic utility of the FM/a\u0026reg; test to the 1990 and 2016 ACR diagnostic criteria; (2) to assess if the FM/a\u0026reg; test result correlates with FM severity, as assessed via validated instruments (WPI, SS, FS, or tender point count); (3) to identify any demographic differences in the diagnostic clinical utility of the FM/a\u0026reg; test in our clinical practice; (4) to analyze the cost-effectiveness between the FM/a\u0026reg; test vs our standard clinical practice ; and (5) to assess patient interest and satisfaction with the use of the FM/a\u0026reg; test.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003e This investigation was designed as a cross-sectional study, consisting of a prospective observational component (health questionnaires and venous blood sample analysis) along with a retrospective chart review component (demographic and FM-applicable historical data capture).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eParticipant Population and Selection\u003c/h2\u003e \u003cp\u003e Participants included patients who attended Mayo Clinic\u0026rsquo;s Fibromyalgia and Chronic Fatigue Clinic (Rochester, MN) from January 2021 through July 2021. The study cohort consisted of 50 patients who received (or confirmed) a formal diagnosis of FM based on clinical history, examination, and by meeting the diagnostic criteria set forth by the 1990 and/or 2016 ACR diagnostic criteria (per our clinic\u0026rsquo;s standard clinical practice). Formal inclusion criteria consisted of participants aged 18 or older, ability and willingness to complete research surveys, and willingness to undergo an additional phlebotomy session. Furthermore, based on the specific characteristics of the FM/a\u0026reg; chemokine-cytokine multiplex assay, patients were screened (by a study team member) to ensure that they had not utilized, within the past 60 days, any of the medications known to interact with the multiplex assay; this medication list was provided by the test manufacturer (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Informed consent was obtained from the participants to participate in the current study. This study was performed in accordance with the principles of the Declaration of Helsinki and ethical standards of Mayo Clinic. Mayo Clinic\u0026rsquo;s Institutional Review Board committee approved this study (protocol number 20-010430).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData Collection\u003c/h2\u003e \u003cp\u003e The retrospective components of the study were achieved via chart review, consisting of demographic and clinical information abstraction. Prospective data components consisted of completing a study interest/satisfaction survey along with the venous blood sample for the FM/a\u0026reg; test. The study interest/satisfaction questionnaire consisted of questions asking participants if they thought there exists a specific diagnostic blood test for FM, as well as whether they would be interested in pursuing such a test. The venous blood sample consisted of a onetime blood draw into a 5 mL, purple top tube. Samples were shipped the same day they were drawn via ambient temperature, overnight, to EpicGenetics for FM/a\u0026reg; testing. Additional details regarding the processing and laboratory analysis of samples have been previously described [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eSurvey results and data abstracted from the electronic medical records were electronically collected and stored using the Research Electronic Data Capture (REDCap) software hosted by the Mayo Clinic Center for Clinical and Translational Science. All information was password protected. Continuous variables were summarized as either median with interquartile range (IQR) or mean with standard deviation. Fisher\u0026rsquo;s exact test was utilized for categorical variables, the t-test was used for continuous variables with two groups, and ANOVA for continuous variables with three or more groups. Sensitivity, specificity, and odds ratios were calculated using an FM/a\u0026reg; score of 50 or greater as a positive result. Correlation was evaluated using Pearson\u0026rsquo;s product-moment. Univariate and multivariate logistic regression and receiver operating curves were used to evaluate the association between the FM/a score and the 1990 and 2016 ACR diagnostic criteria. Univariate and multivariate logistic regression was performed to determine the degree of correlation between the FM/a\u0026reg; score and FM severity as determined by the FS. Statistical significance was defined as p-value of less than 0.05 from two-sided tests. All analyses were performed using BlueSky Statistics version 10 software (BlueSky Statistics LLC, Chicago, Illinois)\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eParticipant Demographics\u003c/h2\u003e \u003cp\u003eIn total, 50 individuals with FM participated in the study. All of the collected demographic and symptom/clinical factors are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eFibromyalgia Diagnostic Criteria, Severity, and Scores\u003c/h2\u003e \u003cp\u003eIn accordance with the study inclusion criteria, all 50 of the participants received a clinical diagnosis of FM; 38 (76%) individuals fulfilled the 1990 ACR criteria, 46 (92%) individuals met the 2016 ACR criteria, and 37 (74%) participants met both criteria (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Additional information regarding symptom duration and specific validated FM diagnostic scores can be found in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eFM/a\u0026reg; results\u003c/h2\u003e \u003cp\u003eBlood sample results demonstrated that 45 (90%) samples were positive (confirmable), while 5 (10%) samples were negative (not confirmable). The mean FM/a\u0026reg; score was 78.8 (range 5.0\u0026ndash;98.0; 1st quartile 76.5; 3rd quartile 94.0; median 88.5) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFM/a\u0026reg; scores were independently associated with gender, age, and race. The FM/a\u0026reg; score was significantly associated with gender (mean FM/a\u0026reg; score of 81.6 +/- 22.9 in women vs 42.6 +/- 36.6 in men; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), race (mean FM/a\u0026reg; score of 89.3 +/- 10.5 in non-whites vs 72.1 +/- 30.7 in whites; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and age (mean age of 43.9 years +/- 12.5 in those with a positive FM/a\u0026reg; test result vs 32.6 years +/- 7.2 in those with a negative FM/a\u0026reg; test result; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The FM/a\u0026reg; score directly correlated with the TP count (r\u0026thinsp;=\u0026thinsp;0.314; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) but was not correlated with the WPI (p\u0026thinsp;=\u0026thinsp;0.23) or FS (p\u0026thinsp;=\u0026thinsp;0.67). (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Additional analysis revealed no statistically significant correlations between the FM/a\u0026reg; score and the duration of symptoms (p\u0026thinsp;=\u0026thinsp;0.32), number of medications (p\u0026thinsp;=\u0026thinsp;0.95), smoking status (p\u0026thinsp;=\u0026thinsp;0.296), opioid use (p\u0026thinsp;=\u0026thinsp;0.74), or disability status (p\u0026thinsp;=\u0026thinsp;0.31)\u003c/p\u003e \u003cp\u003e \u003cem\u003eFM/a\u0026reg; Performance Analysis\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e1. Performance Analysis Compared to the 2016 ACR Criteria\u003c/h2\u003e \u003cp\u003eWe analyzed the FM/a\u0026reg; test performance solely against the 2016 ACR criteria. Using a cut-off of 50, sensitivity was 0.91 and specificity was 0.25. A positive FM/a\u0026reg; result yielded an odds ratio of 3.5. Univariate logistic regression of the FM/a\u0026reg; score vs the 2016 ACR criteria demonstrated an area under the curve (AUC) of 0.7337, with an optimal cutoff of 67 in our population yielding a sensitivity of 0.87 and specificity of 0.75 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e [1a]). When adjusted for the factors of age, gender, and race, the performance of the FM/a\u0026reg; test vs the 2016 ACR criteria improved notably. The adjustment increased the AUC to 0.89 when the FM/a results were treated as a binary variable, and 0.91 when treated as a continuous variable (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e [1b]). Logistic regression analysis demonstrated no statistically significant association between the FM/a\u0026reg; score and FM disease severity as measured by the FS (r\u0026thinsp;=\u0026thinsp;0.0017, p\u0026thinsp;=\u0026thinsp;0.9537 for univariate analysis; r\u0026thinsp;=\u0026thinsp;0.251, p\u0026thinsp;=\u0026thinsp;0.71 for multivariate analysis).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePerformance Analysis Compared to the 1990 ACR Criteria\u003c/h2\u003e \u003cp\u003eWe analyzed the FM/a\u0026reg; test performance solely against the 1990 ACR criteria. A positive FM/a\u0026reg; test had an odds ratio of 2.33 with a sensitivity of 0.92 and specificity of 0.17. Univariate logistic regression analysis demonstrated an AUC of 0.5711. Adjusting for age, gender and race yielded similar performance (AUC of 0.585).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePerformance Analysis Compared to the FS\u003c/h2\u003e \u003cp\u003eWe evaluated the performance of the FS (WPI\u0026thinsp;+\u0026thinsp;SS) as a simplified diagnostic tool compared to the 2016 and 1990 criteria. Univariate logistic regression resulted in an AUC of 0.93 with an optimal FS score of 17 in our specific clinic/patient population (SN\u0026thinsp;=\u0026thinsp;0.86; SP\u0026thinsp;=\u0026thinsp;1.00) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e [2a]). When the FS was adjusted for age, gender, and race, the AUC increased to 0.9701 with a sensitivity of 0.89 and specificity of 1.00 at the optimal cut point (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e [2b]). Performance of the FS was significantly diminished when applied to the 1990 ACR criteria. Univariate analysis yielded an optimal cut point of 22, resulting in a sensitivity of 0.55, specificity of 0.67, and AUC of 0.62. Adjusting for age, gender and race gave a marginal improvement (optimal sensitivity of 0.50, specificity of 0.83; AUC of 0.63).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCost-effectiveness comparison\u003c/h2\u003e \u003cp\u003eWe evaluated the cost differences between the FM/a\u0026reg; test and our clinic\u0026rsquo;s standardized prerequisite testing approach (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The retail cost (assuming no insurance coverage) for the FM/a\u0026reg; test was \u003cspan\u003e$\u003c/span\u003e1080. In comparison, the combined retail cost of our prerequisite studies, which are obtained to evaluate for potential alternative diagnoses, is approximately \u003cspan\u003e$\u003c/span\u003e2,200; this does not include the costs associated with consultations (office visits, subspeciality referrals).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eHealth questionnaires: interest/satisfaction results\u003c/h2\u003e \u003cp\u003eMost patients (72%) were unsure if there was a diagnostic test available for FM, while nearly all patients (92%) reported they would be interested or strongly interested in such a test. Only 3 patients (6%) reported being aware of a diagnostic test for FM.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cross-sectional study was conducted with multiple previously stated aims. Each of these aims will be discussed in-depth separately.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eDiagnostic Utility of the FM/a\u0026reg; Test\u003c/h2\u003e \u003cp\u003eIn the cohort of 50 participants with FM, 45 (90%) were positive (confirmable) based on the FM/a\u0026reg; test, while 5 (10%) were negative (not confirmable). This result exceeded our group\u0026rsquo;s initial hypothesis (75% confirmability). On a more granular level, the performance analysis of the FM/a\u0026reg; test in direct comparison to the 1990/2016 ACR criteria demonstrated that the FM/a\u0026reg; test performed inferiorly to both the 1990 and 2016 ACR diagnostic criteria. This inferiority was more notable when not adjusting for certain demographic factors such as age, gender, and race. When adjusted for, the performance of the FM/a\u0026reg; test improved significantly, almost reaching equivalence to the ACR criteria in terms of diagnostic accuracy. We also noted poor predictive accuracy of the FM/a\u0026reg; test in a specific subtype of FM (non-pain predominant FM); these are individuals, who though meet the diagnostic criteria for FM, exhibit less of a pain phenotype (low WPI) and a more of a non-pain phenotype (high SS). The analysis also demonstrated that in our specialized FM clinic, where there is a higher prevalence of FM (as compared to a general practice), better precision of test performance is needed. We were able to improve the test performance in this respect by adjusting the positive cut-off value, based on logistic regression and Youden statistical analysis.\u003c/p\u003e \u003cp\u003eOverall, we feel that this test could be very useful in \u0026ldquo;upstream\u0026rdquo; general clinical practices, rather than in \u0026ldquo;downstream\u0026rdquo; subspecialty practices (such as our FM clinic). In general clinical practices, where the familiarity with and time required to assess the ACR criteria (or FM in general) might be limited, clinicians could obtain the FM/a\u0026reg; test as an initial step, and if positive, could either proceed with the ACR diagnostic criteria or refer the patient to a more specialized clinic. The adoption of the FM/a\u0026reg; test in such settings would greatly help to efficiently differentiate patients, streamlining the work-up and significantly helping to lessen overall burden (time, cost, appointments) for both patients and healthcare professionals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eFM/a\u0026reg; Test Correlation with Disease Severity\u003c/h2\u003e \u003cp\u003eThe analysis did not show any correlation between FM disease severity (WPI, SS, or FS score) and the FM/a\u0026reg; test result. In contrast, the FM/a\u0026reg; score did correlate directly to FM disease severity, as determined by the 1990 ACR criteria (TP count). Specifically, patients with a higher FM/a\u0026reg; score experienced a greater number of TP. Though we are uncertain as to the underlying correlative mechanism, we feel that this is a very useful association, which could be readily appreciated by and empowering to suffering patients, especially when given so many unrevealing test results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eDemographic Differences in the Diagnostic Clinical Utility of the FM/a\u0026reg; Test\u003c/h2\u003e \u003cp\u003eSeveral demographic factors were significantly associated with the FM/a\u0026reg; test results. First, the FM/a\u0026reg; score was significantly associated with gender; when adjusted for other factors, female gender was associated with a statistically significant higher FM/a\u0026reg; score. Second, the FM/a\u0026reg; score was significantly associated to race; non-white race was associated with a statistically significant higher FM/a\u0026reg; score than white race. Third, the FM/a\u0026reg; score was significantly associated with age; a positive test result was significantly associated with increased age, as compared to a negative test result. Of note, there were no statistically significant correlations between the FM/a\u0026reg; score and other key factors (duration of symptoms, number of medications, smoking status, opioid use, or disability status).\u003c/p\u003e \u003cp\u003eGiven the nature of the chemokine-cytokine multiplex assay, we hypothesize that the impact of age, gender, and race are directly related to their effects on underlying T-cell function and other immune-related mechanisms. We believe that the FM/a\u0026reg; test would benefit (greater predictive accuracy) from further analytic refinement to address and correct for the impact of factors, including age, gender, race, and potentially other un-analyzed factors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eCost-Effectiveness of the FM/a\u0026reg; Test\u003c/h2\u003e \u003cp\u003eThe FM/a\u0026reg; test is positioned as a \u0026ldquo;rule in\u0026rdquo; study; this is contrast to the \u0026ldquo;rule out\u0026rdquo; paradigm that many clinical practices utilize, ordering numerous tests and sub-speciality consultations to exclude alternative diagnoses. The retail cost of the FM/a\u0026reg; test is \u003cspan\u003e$\u003c/span\u003e1080 with results usually available within 7 business days. In direct comparison, our specialized referral-based clinic in an academic medical center, requires several tests/studies (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) to be performed prior to formal evaluation in our clinic. The combined retail cost of our prerequisite studies is approximately \u003cspan\u003e$\u003c/span\u003e2,200. The results of these studies, which are usually available with 1\u0026ndash;2 days, are primarily used (in conjunction with the clinical history and physical examination) to exclude conditions that commonly mimic the presentation of FM.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003ePatient Interest in the FM/a\u0026reg; Test\u003c/h2\u003e \u003cp\u003eThe majority (72%) of patients were unaware or unsure of the availability of a potential diagnostic test for FM. However, an overwhelming 92% of participants reported that they would be interested or strongly interested in such a test. In our assessment, patients have awaited a FM-specific diagnostic study for a long time and would be very eager to obtain this for diagnostic purposes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eFM/a\u0026reg; test and Medication Interactions\u003c/h2\u003e \u003cp\u003eDuring the development of the study protocol, we received a list of medications that according to EpicGenetics would significantly interfere with the multiplex assay (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). According to the manufacturer, participants would need to have been off all the listed medications for at least 60 days. Accordingly, we incorporated this into our participant screening process and exclusion criteria.\u003c/p\u003e \u003cp\u003eThe medication/assay interactions resulted in numerous logistical challenges, and we predict will likely create issues for its widespread adoption in general clinical practices. The list of medications, which continues to evolve, is currently at more than 50 medications. Many of these medications are commonly utilized for highly prevalent conditions. We foresee that this intrinsic test limitation will be challenging for many clinical practices, as it will be difficult to consistently identify patients that have entirely abstained from these exclusionary medications. Furthermore, we would not recommend tapering/discontinuing a chronic medication regimen solely for test obtainment purposes, especially given the well performing ACR criteria.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThis study was the first independently designed and performed trial looking at the clinical utility of the FM/a\u0026reg; test in a specialized FM practice at an academic medical center. This study was conducted using a rigorous protocol and data analysis to provide an unbiased conclusion on the utility of this assay in our practice.\u003c/p\u003e \u003cp\u003eThere are several limitations to the study. First, the sample size of our cohort was limited to 50 participants with FM. Future studies should aim for a larger sample size, evaluating performance in other chronic pain population, as well as in patients with frequent comorbid conditions, such as chronic fatigue, irritable bowel syndrome, and interstitial cystitis. Second, though the study was designed and analyzed independently from the test manufacturer, the blood samples were processed and resulted by EpicGenetics. Third, our study was performed in a referral-based speciality FM clinic, where we have extensive experience and familiarity with the ACR criteria. Future studies should assess the clinical utility of the assay in more general clinical practices.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe FM/a\u0026reg; test is a novel and useful tool for the diagnosis of FM. The assay correctly identified 90% of cases. Overall, it performed inferior to the 1990 and 2016 ACR diagnostic criteria in our specialized FM practice. However, once adjusted for factors such age, gender, and race, the performance of the FM/a\u0026reg; test improved significantly, nearing equivalence with the ACR criteria. Further analytical refinement due to the impact of these demographic factors, as well as the numerous medication-assay interactions is strongly recommended.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge the staff at Mayo Clinic\u0026rsquo;s Fibromyalgia and Chronic Fatigue Clinic for their assistance in the study and the participants for donating their time for the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003eThe datasets utilized during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eFinancial and material support provided by EpicGenetics\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest/Competing interests:\u0026nbsp;\u003c/strong\u003eThe authors do not have any conflicts of interest to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003eThe datasets utilized during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability:\u0026nbsp;\u003c/strong\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Guidelines:\u003c/strong\u003e This study was performed in accordance with the principles of the Declaration of Helsinki and ethical standards of Mayo Clinic.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u0026nbsp;\u003c/strong\u003eAll included authors certify they contributed to the work and approve of the submitted manuscript according to the guidelines on the Role of Authors and Contributers,ICMJE.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eClauw DJ. 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Rheumatol Int. 2015;35(6):991\u0026ndash;996. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00296-014-3172-2\u003c/span\u003e\u003cspan address=\"10.1007/s00296-014-3172-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1: \u0026nbsp;Prerequisite Studies for Consultation in the Fibromyalgia Clinic.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\"\u003e\n \u003cp\u003eComplete blood count with differential\u003c/p\u003e\n \u003cp\u003eElectrolyte panel\u003c/p\u003e\n \u003cp\u003eCalcium\u003c/p\u003e\n \u003cp\u003eCreatinine with EGFR\u003c/p\u003e\n \u003cp\u003eBlood urea nitrogen\u003c/p\u003e\n \u003cp\u003eGlucose, fasting\u003c/p\u003e\n \u003cp\u003eThyroid function cascade\u003c/p\u003e\n \u003cp\u003eAspartate aminotransferase\u003c/p\u003e\n \u003cp\u003eAlanine aminotransferase\u003c/p\u003e\n \u003cp\u003eCreatinine kinase\u003c/p\u003e\n \u003cp\u003eRheumatoid factor\u003c/p\u003e\n \u003cp\u003eCyclic citrullinated peptide\u003c/p\u003e\n \u003cp\u003eAntinuclear antibody\u003c/p\u003e\n \u003cp\u003eAM cortisol\u003c/p\u003e\n \u003cp\u003eCeliac disease serology cascade\u003c/p\u003e\n \u003cp\u003e25-Hydroxyvitamin D2 and D3\u003c/p\u003e\n \u003cp\u003eSerum protein electrophoresis\u003c/p\u003e\n \u003cp\u003eOvernight oximetry\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. List of pharmaceuticals known to interact with the FM/a\u0026reg; chemokine-cytokine multiplex assay.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInhalers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003ePrednisone\u003c/p\u003e\n \u003cp\u003eMethotrexate\u003c/p\u003e\n \u003cp\u003eZafirlukast (Accolate)\u003c/p\u003e\n \u003cp\u003eMontelukast (Singulair)\u003c/p\u003e\n \u003cp\u003eHydrocortisone (Cortef)\u003c/p\u003e\n \u003cp\u003eFludrocortisone (Florinef)\u003cbr\u003e\u0026nbsp;Triamcinolone (Kenalog)\u003c/p\u003e\n \u003cp\u003eMethylprednisolone (Medrol)\u003c/p\u003e\n \u003cp\u003ePrednisolone (Millipred)\u003c/p\u003e\n \u003cp\u003eDexamethasone (Decadron)\u003c/p\u003e\n \u003cp\u003eBudesonide (Entocort)\u003c/p\u003e\n \u003cp\u003eSirolimus (Rapamune)\u003c/p\u003e\n \u003cp\u003eLeflunomide (Arava)\u003c/p\u003e\n \u003cp\u003eAzathioprine (Imuran)\u003c/p\u003e\n \u003cp\u003eMycophenolic acid (CellCept, Myfortic)\u003c/p\u003e\n \u003cp\u003eTofacitinib (Xeljanz)\u003c/p\u003e\n \u003cp\u003eAbatacept (Orencia)\u003c/p\u003e\n \u003cp\u003eAdalimumab (Humira)\u003c/p\u003e\n \u003cp\u003eEtanercept (Enbrel)\u003c/p\u003e\n \u003cp\u003eGolimumab (Simponi)\u003c/p\u003e\n \u003cp\u003eInfliximab (Remicade)\u003c/p\u003e\n \u003cp\u003eBaricitinib (Olumiant)\u003c/p\u003e\n \u003cp\u003eTocilizumab (Actemra)\u003c/p\u003e\n \u003cp\u003eUpadacitinib (Rinvoq)\u003c/p\u003e\n \u003cp\u003eSarilumab (Kevzara)\u003c/p\u003e\n \u003cp\u003eCyclosporine\u003c/p\u003e\n \u003cp\u003eTacrolimus\u003c/p\u003e\n \u003cp\u003eHydrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAdvair, AirDuo, ArmonAir, Arnuity, Breo, Flovent, Trelegy, Wixela (fluticasone)\u003c/p\u003e\n \u003cp\u003eAlvesco (ciclesonide)\u003c/p\u003e\n \u003cp\u003eDulera (mometasone)\u003c/p\u003e\n \u003cp\u003ePulmicort, Symbicort (budesonide)\u003c/p\u003e\n \u003cp\u003eQVAR (beclomethasone)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNasal Sprays\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\"\u003e\n \u003cp\u003eAller-Flo, Dymista, Flonase, Veramyst, Xhance (fluticasone)\u003c/p\u003e\n \u003cp\u003eBeconase, QNASL (beclomethasone)\u003c/p\u003e\n \u003cp\u003eNasacort (triamcinolone)\u003c/p\u003e\n \u003cp\u003eNasonex (mometasone)\u003c/p\u003e\n \u003cp\u003eOmnaris (ciclesonide)\u003c/p\u003e\n \u003cp\u003eRhinocort (budesonide)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSpecial considerations:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003eSteroid or cortisone injections are problematic\u003c/li\u003e\n \u003cli\u003eTopical eye/ear steroids are okay\u003c/li\u003e\n \u003cli\u003eFluocinonide topical can be problematic if used long term\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 3. Participant demographics and symptom information\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eValue\u0026nbsp;\u003c/strong\u003e(N = 50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42.7 years (32.3-50.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale gender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43 (86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWhite race\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43 (86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSmoking status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Current\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Former\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Never\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4 (8%)\u003c/p\u003e\n \u003cp\u003e17 (34%)\u003c/p\u003e\n \u003cp\u003e28 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDisability\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Current\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Previous\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Never\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6 (12%)\u003c/p\u003e\n \u003cp\u003e1 (2%)\u003c/p\u003e\n \u003cp\u003e43 (86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOpioid use for chronic pain\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Current\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Former\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Never\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2 (4%)\u003c/p\u003e\n \u003cp\u003e13 (26%)\u003c/p\u003e\n \u003cp\u003e33 (66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSymptom duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.5 years (5-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCentral sensitization disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (2-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWidespread pain index (out of 19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12 (7-16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSymptom severity score (out of 12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 (7-11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTender points (out of 18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15 (12.25-18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFive pain regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43 (86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFibromyalgia score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21.5 (17.3-25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMet 1990 ACR* diagnostic criteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38 (76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMet 2016 ACR* diagnostic criteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46 (92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMet 1990 and 2016 ACR* criteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37 (74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*ACR: American College of Rheumatology\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. FM/a\u0026reg; test results and statistical analysis of FM/a\u0026reg; scores compared to demographic and symptom.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.3177570093458%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.66355140186916%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eValue\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\" valign=\"top\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.3177570093458%\" valign=\"top\"\u003e\n \u003cp\u003ePositive (confirmable) (N=50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.66355140186916%\" valign=\"top\"\u003e\n \u003cp\u003e45 (90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.3177570093458%\" valign=\"top\"\u003e\n \u003cp\u003eNegative (not confirmable) (N=50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.66355140186916%\" valign=\"top\"\u003e\n \u003cp\u003e5 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.3177570093458%\" valign=\"top\"\u003e\n \u003cp\u003eFM/a\u0026reg;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003etest score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.66355140186916%\" valign=\"top\"\u003e\n \u003cp\u003e78.8 (76.5-94.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.3177570093458%\" valign=\"top\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.66355140186916%\" valign=\"top\"\u003e\n \u003cp\u003eWomen: mean FM/a\u0026reg; score 81.6 +/- 22.9\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMen: mean FM/a\u0026reg; score 42.6 +/- 36.6\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.3177570093458%\" valign=\"top\"\u003e\n \u003cp\u003eRace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.66355140186916%\" valign=\"top\"\u003e\n \u003cp\u003eNon-white: mean FM/a\u0026reg; score 89.3 +/- 10.5\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eWhite: mean FM/a\u0026reg; score 72.1 +/- 30.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; 0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.3177570093458%\" valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.66355140186916%\" valign=\"top\"\u003e\n \u003cp\u003ePositive FM/a\u0026reg;: 43.9 years +/- 12.5\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNegative FM/a\u0026reg;: 32.6 years +/- 7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; 0.05\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.3177570093458%\" valign=\"top\"\u003e\n \u003cp\u003eTender Point Count\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.66355140186916%\" valign=\"top\"\u003e\n \u003cp\u003er = 0.314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; 0.05\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Fibromyalgia, Pain, Diagnosis, FMa, Assay","lastPublishedDoi":"10.21203/rs.3.rs-4145257/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4145257/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction/Objective: \u003c/strong\u003eTo assess the clinical utility of the FM/a® chemokine-cytokine assay in diagnosing fibromyalgia at an academic medical center.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe performed a cross-sectional study on 50 patients diagnosed with fibromyalgia at a specialty fibromyalgia clinic between January 1, 2021 through July 31, 2021. Patients completed questionnaires and provided a venous blood sample sent to EpicGenetics, to complete the FM/a® test. Demographic, symptom, and historical data was obtained from chart review. Statistical analysis was performed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOf 50 patients with a clinical diagnosis of fibromyalgia, the FM/a® test was positive in 45 (90%). Performance of the FM/a® test compared to the 2016 ACR criteria yielded an odds ratio of 3.5 with sensitivity of 0.91, specificity of 0.25. Univariate regression demonstrated an area under the curve (AUC) of 0.7337, which improved to 0.89 when adjusted for age, gender, and race. When compared to the 1990 ACR criteria, a positive FM/a® test had an odds ratio of 2.33 with sensitivity 0.92 and specificity 0.17. Univariate regression analysis demonstrated an AUC of 0.571, when adjusted for age, gender and race, AUC was similar at 0.585.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The FM/a® test performed well overall, though inferiorly compared to the 1990 and 2016 ACR diagnostic criteria. When adjusted for age, gender, and race the test performed almost equivalently to the 2016 ACR criteria. The FM/a® test may be useful in general clinical practices to differentiate patients who are more likely to have FM.\u003c/p\u003e","manuscriptTitle":"The Clinical Utility of a Chemokine-Cytokine Multiplex Assay in Fibromyalgia Diagnosis at an Academic Medical Center","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-13 20:16:12","doi":"10.21203/rs.3.rs-4145257/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"93b54024-9f32-41b2-83a4-075fe029f517","owner":[],"postedDate":"May 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-18T06:29:44+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-13 20:16:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4145257","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4145257","identity":"rs-4145257","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}