Coverage Policy Manual
Policy #: 2011060
Category: Laboratory
Initiated: August 2011
Last Review: April 2023
  Biomarker, Auto-antibody, and Molecular Signature Testing for Monitoring Disease Activity in Rheumatoid Arthritis

Description:
Assessment of disease activity in rheumatoid arthritis (RA) is an important component of management with a goal of treatment to maintain low disease activity or remission. There are a variety of available instruments for measuring RA disease activity. The instruments use combinations of physical exam findings, radiologic results, and serum biomarkers to construct a disease activity score. A multibiomarker disease activity (MBDA) instrument is a disease activity measure that is comprised entirely of serum biomarkers. The Vectra test is a commercially available MBDA blood test that measures 12 biomarkers to construct a disease activity score. Concentrations of these 12 biomarkers are entered into a proprietary formula which, after adjustment by age, gender, and adiposity (i.e., leptin) levels, generates a disease activity score ("adjusted MBDA score") that ranges from 1 (low disease activity) to 100 (high disease activity).
 
RA is characterized by chronic joint inflammation leading to painful symptoms, progressive joint destruction, and loss of function. The disorder is relatively common and is associated with a high burden of morbidity for affected patients.
 
Treatment of RA has undergone a shift from symptom management to a more proactive strategy of reducing disease activity and delaying disease progression (Upchurch, 2012). The goal of treatment is to reduce irreversible joint damage that occurs from ongoing joint inflammation and synovitis by keeping disease activity as low as possible. The availability of an increasing number of effective disease modifying antirheumatic drugs has made achievement of remission, or sustained low disease activity, a feasible goal in a large proportion of patients with RA. This treatment strategy has been called a “tight control” approach.
 
The concept of “tight control” in the management of RA has gained wide acceptance. Evidence from clinical trials has demonstrated that outcomes are improved with a tight control strategy, in which treatment targets are mainly based on measures of disease activity. In a systematic review published in 2010, Schoels et al identified 7 trials that evaluated the efficacy of tight control (Schoels, 2010). Four of these trials randomized patients to either a tight control using treatment targets or routine management. The treatment targets were heterogeneous, including symptom-based measures, joint scores on exam, validated treatment activity measures, lab values, or combinations of these factors. In all 4 trials, there was a significant decrease in the Disease Activity Score (DAS) or its 28 joints version (DAS28) and in the likelihood of achieving remission for patients in the tight control group.
 
According to the American College of Rheumatology (ACR) guidelines, initial treatment of patients with RA is monotherapy (usually a disease-modifying antirheumatic drug). Treatment may progress to combination therapy if disease activity remains moderate or high despite monotherapy (Fraenkel, 2021). Combination therapy may consist of additional disease-modifying antirheumatic drugs or the addition of tumor necrosis factor inhibitors or non-tumor necrosis factor biologics.
 
For a strategy of tight control to be successful, reliable and valid measurement of disease activity is necessary. Numerous measurements exist that assess various aspects of RA disease activity, including patient self-reporting of symptom severity and functional capacity, physician examination of joints for swelling and tenderness, laboratory testing of serum biomarkers, and imaging. Various assessment tools exist that range from those that rely only on single types of measurements, to composite tools that combine information from multiple measurement sources. These assessment tools vary in their psychometric properties and their feasibility of implementation and these trade-offs must be considered in their selection for use. For example, although composite tools are more comprehensive, in some cases they may be less feasible for regular use.
 
Based on a systematic review of the psychometric properties of 46 tools, an ACR working group determined that the following 11 measures of disease activity fulfilled a minimum standard for regular use in most clinical settings (England, 2019): DAS , Routine Assessment of Patient Index Data 3 (RAPID3), Routine Assessment of Patient Index Data 5 (RAPID5), Clinical Disease Activity Index (CDAI), Disease Activity Score with 28 joints (DAS28-ESR/CRP), Patient Derived DAS28, Hospital Universitario La Princesa Index (HUPI), Multibiomarker Disease Activity Score (MBDA score, Vectra DA), Rheumatoid Arthritis Disease Activity Index (RADAI),Rheumatoid Arthritis Disease Activity Index 5 (RADAI-5), and the Simplified Disease Activity Index (SDAI). Additionally, using a modified Delphi process, the ACR working group further identified the following 5 measures as “preferred” for regular use in most clinic settings: the DAS28-ESR/CRP, CDAI, DSAI, RAPID3, and Patient Activity Scale-II.
 
Vectra DA test
The Vectra Test is a commercially available multibiomarker disease activity (MBDA) test that is an approach to measuring RA disease activity that uses only serum biomarkers obtained through a laboratory blood draw. The manufacturer describes Vectra as a complement to clinical judgment (Crescendo Bioscience, 2020). Although not explicitly stated, it appears that the test may be used as an adjunct to other disease activity measures, to potentially identify patients at high-risk of progression who would, therefore, benefit from a more aggressive treatment strategy.
 
The Vectra test measures the serum concentrations of the following 12 biomarkers: interleukin-6 (IL-6), tumor necrosis factor receptor type I (TNFRI), vascular cell adhesion molecule 1 (VCAM-1), epidermal growth factor (EGF), vascular endothelial growth factor A (VEGF-A), YKL-40, matrix metalloproteinase 1 (MMP-1), matrix metalloproteinase 3 (MMP-3), C-reactive protein (CRP), serum amyloid A (SAA), leptin, and resistin. The concentrations of these 12 biomarkers are measured in serum and, combined with age, gender, and adiposity (i.e., leptin) information, are entered in a proprietary formula to generate a score on a scale of 1 to 100 that represents the level of RA disease activity (Labcorp, 2021).
 
Categories of scores were constructed to correlate with the DAS28-CRP scale (Crescendo Bioscience, 2022; Centola, 2013)
 
    • 45-100: high disease activity
    • 30-44: moderate disease activity
    • 1-29: low disease activity.
 
Prior to December 2017, the Vectra test was originally referred to as Vectra DA and the original MBDA score did not include adiposity (i.e., leptin) adjustment (Curtis, 2019). However, as the current, commercially available version of the test includes the leptin-adjusted MBDA score (now called the "adjusted MBDA score"), the focus of this policy will primarily be on the leptin-adjusted Vectra test (Labcorp, 2021).
 
In the ACR working group's systematic review reported by England et al, they also graded feasibility of the RA disease activity measurement tools (England, 2019). Any measure not commercially available or requiring advanced imaging was graded as infeasible. All other measures started with 4 points (i.e., “++++”) and were downgraded by 1-point for each of the following implementation considerations: requiring a provider joint count, requiring a laboratory test, not possible to complete during a routine clinic visit, and not possible to complete on the same day as the clinic visit. The ACR Working Group downgraded the feasibility of the Vectra DA by 3 points (i.e., score of “++++" decreased to “+"). This was due to its requirement of a laboratory test and because its result is not available on the same day as the clinic visit. Although the current, commercially available version of the Vectra test was not assessed in the 2019 ACR guideline, because it requires the same laboratory testing that is not available on the same days as the clinic visit, likely it would have a similar feasibility rating as the older version.
 
Regulatory Status
Clinical laboratories may develop and validate tests in-house and market them as a laboratory service; laboratory-developed tests must meet the general regulatory standards of the Clinical Laboratory Improvement Amendments (CLIA). The Vectra® test (Myriad, formerly Crescendo Bioscience) is available under the auspices of CLIA. Laboratories that offer laboratory-developed tests must be licensed by CLIA for high-complexity testing. To date, the U.S. Food and Drug Administration has chosen not to require any regulatory review of this test.
 
Coding
 
Effective 3/2015, CPT published a specific CPT code for Vectra DA test service:
 
81490 Autoimmune (rheumatoid arthritis), analysis of 12 biomarkers using immunoassays, utilizing serum, prognostic algorithm reported as a disease activity score. CPT 81490 should not be reported in conjunction with 86140.
 
Prior to 3/2015, there was no specific CPT code for this test and it may have been submitted using 11 units of code 83520 (Immunoassay for analyte other than infectious agent antibody or infectious agent antigen; quantitative, not otherwise specified) and 1 unit of 86140 (C-reactive protein).
 
There is no specific code for the AVISE Anti-CarP test. It may be billed with CPT 83516 or 83520.
 
83516 Immunoassay for analyte other than infectious agent antibody or infectious agent antigen; qualitative or semiquantitative, multiple step method
 
83520 Immunoassay for analyte other than infectious agent antibody or infectious agent antigen; quantitative, not otherwise specified
 
PrismRA is a molecular signature test used to predict non-response to tumor necrosis factor inhibitors (TNFI) for patients with rheumatoid arthritis (PrismRA, 2022). There is no specific code for the PrismRA test. It may be billed with 81479 or 81599.
 
81479 Unlisted molecular pathology procedure
 
81599 Unlisted multianalyte assay with algorithmic analysis

Policy/
Coverage:
Effective September 2022
 
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
 
The use of biomarker testing to monitor disease activity in individuals diagnosed with rheumatoid arthritis (e.g., Vectra™ DA test) does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness.
 
For members with contracts without primary coverage criteria, the use of biomarker testing to monitor disease activity in individuals diagnosed with rheumatoid arthritis (e.g., Vectra™ DA test) is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 
Testing for autoantibodies to carbamylated proteins for the diagnosis and prognosis of individuals with rheumatoid arthritis (e.g., AVISE Anti-CarP) does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness.
 
For members with contracts without primary coverage criteria, testing for autoantibodies to carbamylated proteins for the diagnosis and prognosis of individuals with rheumatoid arthritis (e.g., AVISE Anti-CarP) is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 
The use of molecular signature testing (e.g., PrismRA™) does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes for any situation, including but not limited to monitoring therapy, assessing treatment response, or predicting treatment response to Tumor Necrosis Factor inhibitor (TNFi) therapy in rheumatoid arthritis.
 
For members with contracts without primary coverage criteria, the use of molecular signature testing (e.g., PrismRA™) for any situation, including but not limited to monitoring therapy, assessing treatment response, or predicting treatment response to Tumor Necrosis Factor inhibitor (TNFi) therapy in rheumatoid arthritis is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 
Effective Prior to September 2022
 
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
 
The use of biomarker testing to monitor disease activity in patients diagnosed with rheumatoid arthritis (e.g., Vectra™ DA test) does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
 
For members with contracts without primary coverage criteria, the use of biomarker testing to monitor disease activity in patients diagnosed with rheumatoid arthritis (e.g., Vectra™ DA test) is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 
Testing for autoantibodies to carbamylated proteins for the diagnosis and prognosis of patients with rheumatoid arthritis (e.g., AVISE Anti-CarP) does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
 
For members with contracts without primary coverage criteria, testing for autoantibodies to carbamylated proteins for the diagnosis and prognosis of patients with rheumatoid arthritis (e.g., AVISE Anti-CarP) is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 
Effective Prior to April 2022
 
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
 
The use of biomarker testing using the Vectra™ DA test to monitor disease activity in patients diagnosed with rheumatoid arthritis does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
 
For contracts without primary coverage criteria, the use of biomarker testing using the Vectra™ DA test to monitor disease activity in patients diagnosed with rheumatoid arthritis is considered investigational.  Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 
Testing for autoantibodies to carbamylated proteins for the diagnosis and prognosis of patients with rheumatoid arthritis, including but not limited to AVISE-CarP testing, does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
 
For members with contracts without primary coverage criteria, testing for autoantibodies to carbamylated proteins for the diagnosis and prognosis of patients with rheumatoid arthritis, including but not limited to AVISE-CarP testing, is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 
Effective Prior to March 2021
 
The use of biomarker testing using the Vectra™ DA test to monitor disease activity in patients diagnosed with rheumatoid arthritis does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
 
For contracts without primary coverage criteria, the use of biomarker testing using the Vectra™ DA test to monitor disease activity in patients diagnosed with rheumatoid arthritis is considered investigational.  Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 

Rationale:
Preliminary evidence on the utility of this test has begun to appear in the form of meeting abstracts and presentations. No full-length articles in the peer-reviewed literature have yet been published.  An abstract presented at the American College of Rheumatology annual meeting in November 2010 (Curtis, 2010) reported on the accuracy of this test compared to the DAS28CRP.  The Vectra™ DA test was found to have a moderate correlation with scores on the DAS28CRP (r=0.56, 95% confidence interval [CI] 0.46-0.64, p<0.001).  The area under the curve for Vectra DA, when using a DAS28CRP upper threshold of 2.67 to define low activity, was 0.77 (95% CI 0.70-0.83, p<0.001).  In other abstracts (Fleischman, 2010) (Cavet, 2010), the Vectra score was shown to be correlated with clinical response to treatment, to predict future joint damage, and to differentiate between patients with remission and low disease activity.
 
This preliminary evidence establishes that the Vectra™ DA test has validity in measuring disease activity.  However, the clinical utility of this test depends on whether actionable, clinically meaningful, thresholds can be identified for this test. In order to determine that this test has a role in the clinical management of rheumatoid arthritis, it needs to be shown that changes in management that result from the test subsequently lead to improved health outcomes.
 
2014 Update
A literature search conducted through March 2014 did not reveal any new information that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
Multibiomarker disease activity (MBDA) tests for disease activity in rheumatoid arthritis (RA) are best evaluated in the framework of a prognostic test, as they provide prognostic information that assists in treatment decisions. Assessment of a prognostic tool typically focuses on 3 categories of evidence: 1) technical performance; 2) clinical validity (ie, statistically significant association between the test result and health outcomes); and 3) clinical utility (ie, demonstration that use of the prognostic information clinically can alter clinical management and/or improve health outcomes compared with patient management without use of the prognostic tool). In some cases, it is important to evaluate whether the test provides incremental information above the standard workup to determine whether the test has utility in clinical practice.
 
Technical Performance
Eastman et al described aspects of the technical performance of the MBDA Vectra test in 2012 (Eastman, 2012). The 12 individual biomarkers in the Vectra test were measured using multiplexed sandwiched immunoassays with biomarker-specific capture antibodies. The total MBDA score had good reproducibility over time, with a coefficient of variation of less than 2%. Crossreactivity by serum rheumatoid factor, other RA antibodies, and/or common RA therapies, was minimal.
 
Centola et al published a study on the development of the Vectra DA test in 2013 (Centola, 2013). This publication described a multistage process for development and validation of the score. In the first phase, the screening phase, proteins were identified that could be readily measured and had the potential to be associated with RA disease activity. A comprehensive total of 130 candidate biomarkers were selected. In the second phase, 4 separate patient cohorts were utilized to refine the biomarkers by their correlations with multiple measures of disease activity. In the final phase, assay optimization and training, the biomarkers with the greatest predictive ability were optimized for multiplex assay. In addition, the combined cohorts of patients were used for algorithm training using a number of statistical techniques. The final model included 12 individual biomarkers and an algorithm that generated a score between 0 and 100.
 
Clinical Validity
Curtis et al used blood samples from 3 cohorts of arthritis patients (Index for Rheumatoid Arthritis Measurement, Brigham and Women’s Hospital Rheumatoid Arthritis Sequential Study, Leiden EarlyArthritis Clinic) to validate the Vectra DA MBDA against the Disease Activity Score with 28 joints (DAS28)-CRP (C-reactive protein) and other known markers of disease activity (Curtis, 2012). There was a positive correlation of the Vectra Score with the DAS28-CRP score, with a Pearson product-moment correlation coefficient ( r) of 0.56 in seropositive RA patients and 0.43 in seronegative patients. The area under the curve (AUC) for discriminating low disease activity from moderate to high disease activity was 0.77 in seropositive patients and 0.70 in seronegative patients, using the DAS28-CRP as the criterion standard. The Vectra score was also correlated with other measures of disease activity, including the Simplified Disease Activity Index (SDAI), the Clinical Disease Activity Index (CDAI), and the Routine Assessment of Patient Index Data (RAPID3), with r values ranging from 0.47 to 0.55 for seropositive patients and 0.21 to 0.29 for seronegative patients.
 
Hirata et al studied the correlation of the Vectra DA score with other validated measures of disease activity in 125 patients from the Behandel Strategieen study. Blood samples were available from 179 visits, 91 baseline visits and 88 visits at 1-year follow-up. Validated disease activity measures were DAS28, SDAI, CDAI, and the HAQ disability index. The Vectra DA scores were significantly correlated with the DAS28 measure (Spearman correlation coefficient (p) = 0.66, p<0.001), as were the changes in scores between baseline and 1 year (Spearman correlation (p) = 0.55, p<0.001). The Vectra scores were also significantly correlated with the SDAI, CDAI, and HAQ disability index at the p<0.001 level.
 
Bakker et al examined the correlation of the MBDA score (Vectra DA score) with the DAS28 score and response to therapy, in a subset of patients from the CAMERA trial. (9) In the larger CAMERA trial, 299 patients were randomized to standard or intensive management of RA. For the Bakker substudy, 74 of 299 patients (24.7%) had blood drawn for measurement of the 20 biomarkers, including the 12 comprising the MBDA test. There were 72 samples collected at baseline and 48 samples collected at 6 months. The total test score was a number between 0 and 100, calculated through use of a proprietary algorithm.
 
The MBDA score was significantly correlated with the DAS28 score at baseline (Pearson ® = 0.72, p<0.001). When using the DAS28-CRP cutoff of 2.7 as the criterion standard, the MBDA score discriminated between remission/low disease activity and moderate/high disease activity with an AUC of 0.86,. The kappa score for agreement with the DAS28-CRP for classifying disease activity was 0.34 (95% confidence interval [CI], 0.19 to 0.49). The MBDA score decreased following therapy, from a baseline of 53 (standard deviation, SD18) to 39 (SD16) at 6 months
 
Overall, evidence for the clinical validity of the Vectra DA test consists of studies that correlate the score with other measures of disease activity, including the DAS28 score. These studies show a positive correlation that is in the moderate range, with reported r values ranging from 0.5 to 0.7. One study reported a kappa value of 0.34 for the DAS28 and Vectra DA, indicating a moderate level of agreement above chance. There is also some evidence that the Vectra DA score correlates with response to treatment. For discriminating levels of disease activity, 2 studies that used the DAS28 as the criterion standard reported an AUC in the moderate to high range, with values ranging from 07 to 0.86 for different populations.
 
Clinical Utility
To demonstrate clinical utility, there should be evidence that the MBDA score is at least as good a measure of disease activity as other available measures. This could be demonstrated directly by an randomized controlled trial (RCT) that compared a management strategy using Vectra DA score with an alternate management strategy using another measure of disease activity, and that reported clinical outcomes such as symptoms, functional status, quality of life, or disease progression on radiologic imaging. Indirect measures of clinical utility could be obtained from high-quality evidence that clinical validity of the MBDA is equivalent to other measures used in clinical care, together with guidance on the optimal use of the score in decision making, ie, evidence linking management changes to specific results on the MBDA score.
 
One RCT was identified that tested the impact of the Vectra DA score on simulated decision making by experienced rheumatologists. (10) A total of 81 rheumatologists without previous experience with the Vectra DA test were randomized to decision making with and without the Vectra DA score, using 3validated clinical vignettes representing typical clinical care in RA. A quality score for each vignette was calculated using predefined criteria. Quality scores in the group receiving the Vectra DA score improved by 3% compared with the control group (p=0.02). The largest benefits in the Vectra DA group were improvements in the quality of disease activity and treatment decisions of 12% (p<0.01), and more appropriate use of biologics and disease modifying drugs (p<0.01).
In a study using physician surveys, Li et al examined the impact of a MBDA score on treatment decisions for patients with RA. (11) This study examined the treatment decisions made by 6 health care providers, all who had shown previous interest in using the MBDA score. A total of 108 patients were enrolled who were at least 18 years-old, had a diagnosis of RA, completed a MBDA test, and had a survey completed by a physician. Surveys of treatment decisions were done before and after the results of the MBDA score was provided. After receiving the MBDA score, treatment plans were changed in 38/101 cases (38%, 95% CI, 29% to 48%). Changes in treatment decisions were a change in the type of drug in 21/38 cases, and a change in the dose or route of administration of a drug in 17/38 cases. There was no data collected on outcomes associated with the different treatment decisions.
 
Overall, there is some evidence that treatment decisions can be influenced by the Vectra DA score. This evidence comes from simulated cases and/or surveys of physician behavior. There are no RCTs that compare use of the Vectra DA score to an alternative method of measuring disease activity, and as a result there is no direct evidence that Vectra DA improves outcomes. Other disease activity measures have been associated with improvements in health outcomes in clinical trials. Thus, the evidence from RCTs on other measures, together with the correlation of Vectra DA with these measures is indirect evidence that outcomes may be improved with use of the Vectra DA test. However, there is insufficient evidence to determine whether Vectra DA is as good as other more established disease activity measures in improving outcomes.
 
Clinical Input Received through Physician Specialty Societies and Academic Medical Centers
None
 
In conclusion the Vectra DA is a biomarker-based measurement of disease activity in rheumatoid arthritis (RA) that uses results of 12 serum biomarkers to construct a score ranging from 0 to 100. It is one of numerous disease activity measures that are available for use in clinical care, and there are other disease activity scores (eg, Disease Activity Score with 28 joints, DAS28) that have been more extensively validated. Evidence of validity for the measure consists of several studies that correlate Vectra DA with other previously validated measures such as the DAS28. These studies show moderate correlations of Vectra with the DAS28. A small number of studies evaluate clinical utility by examining changes in decision making associated with use of Vectra, but these are limited by the design of using simulated cases or physician surveys and do not report any outcome data. This limited body of evidence on the Vectra DA test is not sufficient to determine whether it is as good as or better than other disease activity measures, and it is possible that it is not as accurate as the DAS28. As a result, the Vectra DA test is considered investigational for use as a measure of disease activity in the patients with RA.
 
2015 Update
A literature search conducted through February 2015 did not reveal any new information that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
Clinical Validity
Evidence on clinical validity consists primarily of studies that correlate the Vectra DA score with other disease activity measures, markers of disease progression, and/or response to therapy. These are either observational cohort studies, or post-hoc analyses of RCTs that were performed for a different purpose and in which serum samples were available to retrospectively evaluate the Vectra DA test.
 
Post-hoc analyses of completed RCTs
Two publications report on the evaluation of the Vectra DA score from the BeST trial, which was a multicenter RCT of 508 patients with early RA, randomized to 4 different treatment strategies. For both of these studies, a subset of patients who had serum samples available were included, Of the 508 patients, there were 125 patients with serum samples, 91 baseline samples, 89 from 1-year follow-up, and 55 patients who had both baseline and follow-up serum available. Comparison of patients who had samples available and those who did not revealed that the population with serum available differed from those who did not on gender (75% vs 65% female, p=0.04), the median number of tender joints (11 vs 14, p<0.001), and the median number of erosions seen on imaging (1.0 vs 2.0, p=0.005).
 
In the first study, Hirata and colleagues studied the correlation of the Vectra DA score with other validated measures of disease activity. Validated disease activity measures were DAS28, SDAI, CDAI, and the HAQ Disability Index (DI). The Vectra DA scores were significantly correlated with the DAS28 measure (Spearman correlation coefficient ρ=0.66, p<0.001), as where the changes in scores between baseline and 1 year (Spearman ρ=0.55, p<0.001). The Vectra scores were also significantly correlated with the SDAI, CDAI, and HAQ-DI at the p<0.001 level. The second study by Marcuse and colleagues, evaluated how well the Vectra DA score predicted the progression of radiographic joint damage, and compared the predictive ability of Vectra DA with the DAS28 score (Markusse, 2014). Radiographic progression was defined as a change of at least 5 points on the Sharp van der Heijde Score over a one year period. ROC analysis was performed, with an AUC for the Vectra DA test of 0.77 (95% CI 0.64-0.90), which was higher than the AUC for the DAS28 (0.52, 95% CI 0.39-0.66).
 
Hambardsumyan and colleagues performed a post-hoc analysis from the Swedish Farmocotherapy (SWEFOT) trial, which was a RCT that randomized 487 patients to two different treatment regimens (Hambardzumyan, 2014). There were a total of 235 patients (48% of total) who had serum samples available and complete clinical and radiographic data. The authors evaluated the Vectra DA score as a predictor of radiographic progression, defined as a change of at least 5 points on the Sharp van der Heijde Score. The Vectra DA score was a univariate predictor of radiographic progression (odds ratio 1.05 per unit increase, 95% CI 1.02 to 1.08, p<0.001), and was an independent predictor of progression in a variety of multivariate models. For patients with a low or moderate Vectra DA score (<44), radiographic progression was uncommon, occurring in 1/40 (2/5%) patients.
 
Hirata and colleagues reported in 2014 on the correlation between the Vectra DA score and response to treatment in 147 patients treated with anti-TNF medications for at least a year (Hirata, 2014). The relationship between baseline scores and response to treatment was measured for the Vectra DA test and for a number of other disease activity scores (DAS28, SDAI, CDAI). A good response, as defined by the European League Against Rheumatism clinical criteria, was achieved by 56% of patients. The mean Vectra DA score decreased from 64 to 34 over the course of the study, and 37% of patients met the threshold for low activity (Vectra Score <30). The Vectra DA score decreased more in patients with a good clinical response (-29 points) compared to those with a moderate response (-21 points, p<0.001), and decreased more in patients with a moderate response compared to non-responders (+2 points, p<0.007). There was a positive correlation of the Vectra DA score with the DAS28- CRP (r=0.46) and the DAS28-ESR (r=0.48), but not with the SDAI or the CDAI.
 
Another study compared the discriminatory ability of Vectra DA versus the DAS28 using radiographic disease progression as the reference standard, and reported that the AUC was higher for Vectra DA compared to DAS28.
 
Ongoing and Unpublished Clinical Trials
A search of ClinicalTrials.gov  March 2015 did not identify any ongoing or unpublished trials that would likely influence this policy.
 
Evidence of validity for the Vectra DA measure consists of numerous studies that correlate Vectra DA with disease progression, response to therapy, and/or other previously validated disease activity measures such as the DAS28. These studies establish that the Vectra DA score is a predictor of disease progression and that decreases in the score are correlated with disease response. They also show moderate correlations of Vectra with the DAS28 score. A smaller number of studies evaluate clinical utility by examining changes in decision making associated with use of Vectra, but these are limited by the design of using simulated cases or physician surveys and do not report any outcome data. This limited body of evidence on the Vectra DA test is not sufficient to determine whether it is as good as or better than other disease activity measures, and it is possible that it is not as accurate as the DAS28. As a result, the Vectra DA test is considered investigational for use as a measure of disease activity in the patients with RA.
 
2016 Update
A literature search conducted through March 2016 did not reveal any new information that would prompt a change in the coverage statement.  There were no new published clinical trials since the last policy update. No ongoing clinical trials were identified.
 
2017 Update
A literature search conducted through March 2017 did not reveal any new information that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
SWEFOT trial. Hambardzumyan et al performed a post hoc analysis from the Swedish Farmacotherapy (SWEFOT) trial, which was an RCT that randomized 487 patients to 2 different treatment regimens (Hambardzumyan, 2015). A total of 235 (48%) patients had serum samples available and complete clinical and radiographic data. The authors evaluated the Vectra DA score as a predictor of radiographic progression, defined as a change of at least 5 points on the Sharp van der Heijde Score. The Vectra DA score was a univariate predictor of radiographic progression (odds ratio, 1.05 per unit increase; 95% CI, 1.02 to 1.08; p<0.001), and was an independent predictor of progression in a variety of multivariate models. For patients with a low or moderate Vectra DA score (<44), radiographic progression was uncommon, occurring in 1 (2.5%) in 40 patients.
 
A second publication from the SWEFOT reported repeat scores at multiple time points (Hambardzumyan, 2016), Of 487 patients enrolled in the SWEFOT trial, 220 had baseline Vectra DA scores (45.2%), 205 had scores at 3 months (42.1%), and 133 had scores at 1 year (27.3%). Patients with low initial scores, or with a decrease in scores over time into the low range, had the lowest rate of radiographic progression at 1 year. Cross tabulation of Vectra DA results with the DAS28, ESR, and CRP values was presented, but no statistics that addressing the comparative accuracy of the different measures were reported.
 
AMPLE trial. The AMPLE trial randomized patients with active rheumatoid arthritis and an inadequate response to methotrexate to abatacept or adalimumab and followed patients for 2 years (Fleischmann, 2016). Eligibility criteria included a DAS28-CRP score of at least 3.2 and a positive test for antibodies to either CCP or RF. Vectra DA scores were analyzed form stored serum samples at baseline, 3 months, 1 year and 2 years, and correlated with other measures of disease activity (DAS28-CRP and CDAI). There were a total of 646 patients enrolled and 524 (81%) had results for Vectra DA. The concordance of disease activity states was examined between the different measures. There was not a high concordance of classification into high, moderate and low disease categories, but there were no quantitative measures of association reported. The VECTRA DA score was not a significant predictor of radiographic progression, while the CDAI score was a significant predictor.
 
RETRO trial. The RETRO trial enrolled patients treated with DMARDs in clinical remission, and randomized participants to tapering DMARD or standard maintenance care (Rech, 2015).  Eligibility criteria included a DAS28-ESR score lower than 2.6 for at least 6 months and follow-up was for 12 months. Of 101 patients enrolled in RETRO, Vectra DA data was available for 94 (93%). The Vectra DA score was higher in patients experiencing a relapse (32.0±2.3) compared with patients who did not experience a relapse (22.6±1.2, p=0.0001). On multivariate analysis, the Vectra DA score was a significant predictor of relapse (odds ratio 8.54, 95% CI 2.0-36.4), along with treatment arm (odds ratio 5.94, 95% CI 1.3-26.7) and anti-CCP status (odds ratio 24.5, 95% CI 3.1-194.0).
 
A publication from the Leiden Early Arthritis Clinic Cohort was published in 2016 (Li, 2016). This study used the Vectra DA score and other measures of disease activity to predict radiologic progression of disease at 1 year. There were 163 patients in this cohort that had complete information on Vectra DA and other disease activity measures. The proportion of patients with radiographic progression increased as Vectra DA scores increased. For patients with a score of less than 29, 2% met criteria for radiographic progression, and for patients with a score of 60 or greater, 41% met criteria for radiographic progression. Vectra DA scores and other measures of disease activity (DAS28-CRP, swollen joint count, CRP) were predictors of radiographic progression on univariate analysis. On multivariate analysis, only the Vectra DA score was a significant predictor of progression at 1 year (p=0.005).
 
Ongoing and Unpublished Clinical Trials
A search of ClinicalTrials.gov on April 13, 2017 did not identify any ongoing or unpublished trials that would likely influence this review.
 
2018 Update
Annual policy review completed with a literature search using the MEDLINE database through March 2018. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
The post hoc analysis by Fleischmann et al was accompanied by an editorial by Davis (Davis, 2016). Davis summarized the evidence for the validity of the MBDA test:
    • The test measures biologic pathways and therefore provides unique information that complements clinical assessments (face validity).
    • Relevant biomarker components were chosen for the test (content validity).
    • Correlation with other measures of disease is inconsistent, ranging from discordant to strong, because there is a lack of a criterion standard in measuring RA disease activity (criterion validity).
    • Sensitivity to change following different RA treatments was inconsistent with other disease activity measures (discriminant validity).
    • High MBDA scores were predictive of radiographic progression, despite clinical measures showing no disease progression (construct validity).
 
Davis concluded that the clinical value of MBDA remains unclear. He pointed out that the manufacturer does not propose that MBDA replace current tests, but rather the test should be used as a complement to clinical evaluations.
 
In 2017, Curtis et al published a response to the Fleishmann study. The authors explained that one of the reasons for discordance between MBDA and the other RA disease activity measures in the Fleischmann study was the use of incorrect cutoff points defining low, moderate, and high disease activity
(DAS28-ESR cutoff points were used to compare MBDA and DAS28-CRP measures) (Curtis, 2017). Also, Curtis et al proposed looking at the relation between radiographic outcomes and MBDA by evaluating radiographic progressors rather than nonprogressors, which is how Fleishmann conducted the  analysis. In a rebuttal, Fleischmann et al  justified their use of nonprogressors on 2 bases: (1) nonprogressors are important patient-level assessments of therapeutic response; and (2) nonprogressors were much more common in the AMPLE database (after 1-year follow-up, there were 327 nonprogressors and 40 progressors) (Fleischmann, 2017).
 
ACT-RAY Trial of Patients With Active RA
Reiss et al conducted a post hoc analysis on patients from the ACT-RAY trial in which patients who did not respond to methotrexate therapy were randomized to add-on tocilizumab therapy or placebo (Reiss, 2016). Patients were included in the analysis if they had DAS28-CRP and CDAI scores at baseline and 24-week follow-up and sufficient serum for MBDA testing at the same time points. Disease activity level (low, moderate, high) agreement between the DAS28-CRP and MBDA at baseline was 77%; however, the agreement between the 2 measures at 24 weeks of follow-up was 24%. Agreement between the MBDA and CDAI followed a similar pattern: 72% agreement at baseline and 22% agreement after 24 weeks of tocilizumab therapy. DAS28-CRP and CDAI had high levels of agreement, both at
baseline and 24 weeks (87% and 85%, respectively).
 
 
Hambardzumyan et al analyzed a subset of data from the SWEFOT trial to investigate the use of MBDA as a predictor of optimal treatment in patients with early RA who did not respond to methotrexate Therapy (Hambardzumyan, 2017). Patients (N=157) in the SWEFOT trial were randomized to 2 groups: triple therapy (methotrexate, sulfasalazine, plus hydroxychloroquine) or to double therapy methotrexate plus infliximab). MBDA categories were defined as low disease activity (<30), moderate disease activity (30-44), and high disease activity (>44). Responders after 1 year of follow-up were defined as patients with DAS28 score of 3.2 or less. The investigators compared MBDA scores at 3 months with DAS28-ESR scores at 1 year to determine whether MBDA scores at 3 months could accurately predict patient response to therapy at the 1-year follow-up. Among patients with low MBDA scores at 3 months, 88% (7/8) subsequently had a clinical response to triple therapy, and 18% (2/11) had a clinical response to methotrexate plus infliximab at the 1-year follow-up. Among patients with high MBDA scores at 3 months, 35% (15 of 43) subsequently responded to triple therapy, and 58% (26/46) responded to methotrexate plus infliximab. The 3-month low and high MBDA scores were better predictors of clinical response to therapy than clinical and inflammatory markers. The authors concluded that 3-month MBDA scores have the potential to inform decisions on which type of therapy to recommend to patients who do not respond to initial methotrexate therapy.
 
2019 Update
Annual policy review completed with a literature search using the MEDLINE database through March 2019. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
European League Against Rheumatism
The European League Against Rheumatism updated its guidelines on the management of early arthritis (Combe, 2017). The League recommended that arthritis activity be assessed at 1- to 3-month intervals to determine target treatment. “Monitoring of disease activity should include tender and swollen joint counts, patient and physician global assessments, erythrocyte sedimentation rate, and C reactive protein, usually by applying a composite measure.” Composite measures recommended include the Disease Activity Score with 28 joints, Clinical Disease Activity Index, and Simplified Disease Activity Index. One item on the research agenda recommended by the League was to evaluate new biomarkers and multibiomarkers for the prognosis and treatment in early arthritis.
 
2020 Update
A literature search was conducted through March 2020.  There was no new information identified that would prompt a change in the coverage statement.  
 
2021 Update
Annual policy review completed with a literature search using the MEDLINE database through March 2021. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
Based on a systematic review of the psychometric properties of 46 tools, an ACR working group determined that the following 11 measures of disease activity fulfilled a minimum standard for regular use in most clinical settings: Disease Activity Score (DAS), Routine Assessment of Patient Index Data 3 (RAPID3), Routine Assessment of Patient Index Data 5 (RAPID5), Clinical Disease Activity Index (CDAI), Disease Activity Score with 28 joints (DAS28-ESR/CRP), Patient Derived DAS28, Hospital Universitario La Princesa Index (HUPI), Multibiomarker Disease Activity Score (MBDA score, Vectra DA), Rheumatoid Arthritis Disease Activity Index (RADAI),Rheumatoid Arthritis Disease Activity Index 5 (RADAI-5), and the Simplified Disease Activity Index (SDAI) (England, 2019). Additionally, using a modified Delphi process, the ACR working group further identified the following 5 measures as “preferred” for regular use in most clinic settings: the DAS28-ESR/CRP, CDAI, DSAI, RAPID3, and Patient Activity Scale-II.
 
In the ACR working group's systematic review reported by England et al (2019), they also graded feasibility of the RA disease activity measurement tools (England, 2019). Any measure not commercially available or requiring advanced imaging was graded as infeasible. All other measures started with 4 points (ie, “++++”) and were downgraded by 1-point for each of the following implementation considerations: requiring a provider joint count, requiring a laboratory test, not possible to complete during a routine clinic visit, not possible to complete on the same day as the clinic visit. The ACR Working Group downgraded the feasibility of the Vectra DA by 3 points (ie, score of “++++" decreased to “+"). This was due to its requirement of a laboratory test and because its result is not available on the same day as the clinic visit. Although the current, commercially available version of the Vectra test was not assessed in the 2019 ACR guideline, because it requires the same laboratory testing that is not available on the same days as the clinic visit, likely it would have a similar feasibility rating as the older version.
 
Evidence on the evaluation of clinical validity of the current commercially available version of the Vectra test (including the “adjusted MBDA score”) in patients with RA, consists of 1 retrospective cohort study (Curtis, 2019). This study by Curtis et al evaluated the clinical validity of the Vectra test in predicting radiographic progression at 1 year using a convenience sample of combined data from 533 patients enrolled in either the Optimized Treatment in early Rheumatoid Arthritis (OPERA) randomized controlled trial or the Brigham Rheumatoid Arthritis Sequential Study (BRASS) cohort study (Brahe, 2019; Iannaccone, 2011). The clinical validity of the Vectra test was compared to that of the original Vectra DA test and other measures of DA. Among the various disease activity measures assessed, only the new Vectra test (RR 8.38; 95% CI, 1.15 to 60.8), the original Vectra DA test (RR 5.39; 95% CI, 1.3 to 22.29) and CRP (RR 4.15; 95% CI, 1.58 to 10.95) significantly differentiated between the risk of radiographic progression for the high risk groups versus the low risk groups. Based on these outcomes, the study authors concluded that the new Vectra test (“adjusted MBDA score”) may offer “improved clinical utility” over the original and not commercially available Vectra DA test. Although the overlapping confidence intervals suggest at least similar prognostic performance to other DA measures, they indicate uncertainty as to whether Vectra provides prognostic performance superior to the original Vectra DA or CRP. Additionally, the low proportions of patients with radiographic progression in the moderate to high risk patient groups (3.9% to 9.3% for the new Vectra test and 3.5% to 9.7% for the original Vectra DA test group) do not support the use of the test to “rule in” moderate- to high-risk disease. These low rates of patients with radiographic progression the moderate to high risk patient groups suggest that 9 out of 10 patients identified as moderate or high risk could receive intensification of therapy unnecessarily. Likely this is due at least in part to the fact that the overall prevalence of radiographic progression was notably low in this study cohort (6.3%). Although the results from this study by Curtis et al are initially supportive of the Vectra test’s ability to predict radiographic progression at 1 year, its numerous relevance, design and conduct limitations provide an insufficient basis to conclude the clinical validity of the Vectra test.
 
Numerous studies of the validity of the original Vectra DA test (not commercially available) have been conducted based on records and archived samples from randomized controlled trials and cohorts (Bakker, 2012; Markusse, 2014; Hambardzumyan, 2015; Hambardzumyan, 2016; Fleischmann, 2016; Hirata, 2016; Bouman, 2017; Hambardzumyan, 2017; van der Helm-van Mil, 2013; Li, 2016; Krabbe, 2017; Reiss, 2016, and Roodenrijs, 2018).
 
The majority of the studies of the original Vectra DA have been previously summarized in 3 recent systematic reviews and pooled analyses (Johnson, 2019; England, 2019; and Curtis, 2019). Overall, findings from the most comprehensive and rigorous review indicated that although the original Vectra DA test has shown a positive correlation with other disease activity measures, results from studies comparing MBDA with radiographic progression are inconsistent (Johnson, 2019).
 
The most comprehensive review was conducted by Johnson et al, which reported on the results of a systematic review of 22 studies of the clinical validity of the original Vectra DA test (Johnson, 2019). Among those, 9 studies evaluated the ability of the original Vectra DA to predict radiographic progression. Studies were highly heterogenous in their radiographic progression thresholds and definitions, analytic methods, and results. For example, for the comparison of patients with a Vectra DA high-risk score versus patients with Vectra DA low-risk scores, the range of relative risks of radiographic progression was 1.04 to 14.30 and were significant in only 6 studies. Additionally, results of 8 studies that reported correlations of Vectra DA with other RA disease activity measures were included in a meta-analysis (N=3,242). The original Vectra DA test demonstrated modest correlations with the DAS28-CRP (r = 0.41; 95% CI 0.36 to 0.46) and the DAS28-ESR (r = 0.48, 95% CI 0.38 to 0.58). It demonstrated weaker correlations with the SDAI (r = 0.35, 95% CI 0.26 to 0.43), CDAI (r = 0.26, 95% CI 0.19 to 0.33), and RAPID3 (r = 0.23, 95% CI 0.19 to 0.27). Systematic review authors expressed concern that inadequate information about sample handling prevented them from ruling out the potential confounding effects of biased biomarker measurement due to variation in collection, processing, and storage of serum samples. The authors concluded that the findings need further validation in light of the high level of variability in methods and results.
 
The second most comprehensive systematic review was reported by England et al, which detailed the results of an American College of Rheumatology working group’s systematic review of the psychometric properties of 46 RA disease activity measurement tools (England, 2019). The objective of this ACR review was to determine which measures of disease activity fulfilled a minimum standard for regular use in most clinical settings. The ACR's definition of minimum standard was (1) that the tool provided a numerical value, (2) categorized to 3 disease states that separate low, moderate, and high disease activity, (3) was feasible for regular measurement in the clinic, and (4) possessed adequate psychometric properties. The ACR defined the adequacy of psychometric properties as having a level of evidence that suggested at least moderate positive results in hypothesis testing plus 1 of the following: (a) level of evidence suggesting at least moderate positive results in at least 1 of the following additional areas: internal consistency, reliability, measurement error, content validity, structural validity, or responsiveness; (b) level of evidence suggesting at least limited positive results in at least 2 of those additional areas (one of which must be responsiveness), or, (c) a defined minimum important difference/minimum clinically important difference. The ACR systematic review included 14 studies of the original version of the MBDA test, Vectra DA, that were published between 2012 and 2016. The review by England et al (2019) provided data abstraction of performance characteristic results from the individual studies, but did not draw any conclusions about specific clinical validity measures. Based on an overall qualitative assessment of the findings, including correlations and associations to other DA measures and radiographic progression, the ACR workgroup concluded that the original Vectra DA met their criteria for a moderate level of hypothesis testing, based on consistent findings in multiple studies of fair methodologic quality.
 
Additionally, findings were also mixed across 3 studies published subsequent to the above-described systematic review and pooled analyses (Bouman, 2017; Brahe, 2019; and Roodenrijs, 2018). For example, in a post hoc analysis of 3 cohort studies by Roodenrijs et al of 57 RA patients treated with rituximab 1000 mg and methylprednisolone 200 mg, among those with an original Vectra DA score of low, moderate and high MBDA scores, radiographic progression (change in SHS 5) was observed in 0 (0%), 0 (0%) and 5 (56%) patients, respectively (Roodenrijs, 2018). Additionally, change in the original Vectra DA score from baseline to 6 months was significantly associated with European League Against Rheumatism (EULAR) response (good or moderate) versus non-response at 6 months (OR 0.93; 95% CI, 0.88 to 0.98 per unit change). This association remained statistically significant even after adjustment by age, gender, smoking status, rheumatoid factor (RF) status, autoantibodies against citrullinated peptides (ACPA) status (OR 0.89; 95% CI, 0.81 to 0.98 per unit change). However, in contrast, in the Dose REduction Strategies of Subcutaneous TNF Inhibitors trial (DRESS) RCT by Bouman et al (2017), among 167 randomized, RP occurred in 31% in the dose tapering group and in 16% in the usual care group and the original Vectra DA score was not predictive of successful tapering, flare occurrence, or RP (Bouman, 2017).
 
2022 Update
Annual policy review completed with a literature search using the MEDLINE database through March 2022. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
In 2021, updated clinical validity data on the Vectra test with an adjusted MBDA score was published by Curtis and coworkers using combined data from 953 patients enrolled in the OPERA, BRASS, Leiden Early Arthritis Clinic (EAC), and SWEFOT (Swedish Farmacotherapy) cohorts (Curtis, 2021). The adjusted MBDA score was validated in the Leiden and SWEFOT cohorts and compared with conventional disease activity measures across all 4 cohorts. Among the various baseline disease activity measures, only the adjusted MBDA score (odds ratio [OR] 1.05; 95% CI, 1.03 to 1.06), seropositivity (OR 6.20; 95% CI, 2.90 to 16.1), CRP (OR 1.57; 95% CI, 1.29 to 1.91), baseline joint damage (total Shape score [TSS]) (OR 1.01; 95% CI, 1.00 to 1.01), and DAS28-CRP (OR 1.24; 95% CI, 1.05 to 1.46) were significantly predictive of radiographic progression. Risk ratios (95% CI) for change in TSS > 5 units were 2.62 (0.59 to 11.6; p =.24) and 9.37 (2.34 to 37.5; p = 2.65 x 10-6) in the moderate and high adjusted MBDA score categories compared to the low category. The risk ratio was 4.47 (2.54 to 7.87; p = 5.26 x 10-10) for the high category compared to combined low and moderate categories. Adjusted MBDA scores from the combined cohorts were cross-classified with conventional disease activity measures to evaluate discordances. The frequency of radiographic progression was low when the adjusted MBDA score was low and highest when high regardless of DAS28-CRP, CRP, swollen joint count, and CDAI score categories. These trends were not observed within conventional disease activity measures. However, while individual analysis of the 4 cohorts with cross-classification by DAS28-CRP and adjusted MBDA score were generally consistent with these trends, they should be interpreted with caution due to the limited number of progressors. Overall, the frequency of radiographic progression corresponded more consistently with the category of adjusted MBDA score than the category of DAS28-CRP, CRP, swollen joint count, or CDAI scores. Bivariable logistic regression analysis identified the adjusted MBDA score as the strongest single, independent predictor of radiographic progression. A risk curve for radiographic progression for change in TSS > 5 was generated for the adjusted MBDA score. While the risk of radiographic progression exceeded 40% at the highest adjusted MBDA score in the model, at the high-risk cutoff score (>44) the risk of radiographic progression is less than 10%. While the Leiden and SWEFOT cohorts contributed a higher proportion of patients with radiographic progression in the moderate and high-risk groups, there continues to be insufficient support for the use of the test to “rule in” moderate- to high-risk disease. Furthermore, given the high prevalence of discordant results across conventional disease activity measures, the position of the adjusted MBDA score in the clinical management pathway is unclear.
 
September 2022 Update
No RCTS were identified for molecular signature testing. However, the results of 2 prospective observational studies are described below.
 
An observational study of 391 targeted therapy-naïve and 113 TNFi-exposed patient samples was conducted to determine the ability of molecular signature response classifiers (MSRC) to identify patients who will inadequately respond to TNFi therapy (Cohen, 2021). A molecular signature of non-response was detected in 45% of targeted therapy-naïve patients. The MSRC had an area under the curve (AUC) of 0.64 and patients were unlikely to adequately respond to TNFi therapy according to ACR50 at 6 months with an odds ratio of 4.1 (95% confidence interval 2.0–8.3, p value 0.0001). Odds ratios (3.4–8.8) were significant (p value < 0.01) for additional endpoints at 3 and 6 months, with AUC values up to 0.74. Among TNFi-exposed patients, the MSRC had an AUC of up to 0.83 and was associated with significant odds ratios of 3.3–26.6 by ACR, DAS28-CRP, and CDAI metrics.
 
Mellors et al reported data from two patient cohorts (n=58 and n=143) whose purpose was to identify a drug response biomarker panel that predicts nonresponse to anti-TNF therapies in RA patients, before the start of treatment. In a validation cohort (n=175), the drug response biomarker panel identified nonresponders with a positive predictive value of 89.7 and specificity of 86.8.
 
2023 Update
Annual policy review completed with a literature search using the MEDLINE database through March 2023. No new literature was identified that would prompt a change in the coverage statement.

CPT/HCPCS:
81479Unlisted molecular pathology procedure
81490Autoimmune (rheumatoid arthritis), analysis of 12 biomarkers using immunoassays, utilizing serum, prognostic algorithm reported as a disease activity score
81599Unlisted multianalyte assay with algorithmic analysis
83516Immunoassay for analyte other than infectious agent antibody or infectious agent antigen; qualitative or semiquantitative, multiple step method
83520Immunoassay for analyte other than infectious agent antibody or infectious agent antigen; quantitative, not otherwise specified
84999Unlisted chemistry procedure

References: “Studies show Crescendo Biosciences Vectra™ DA can track early response to rheumatoid arthritis therapy and predict joint damage at the molecular level - Data presented at EULAR Annual European Congress of Rheumatology.” Company press release available online at http://www.crescendobio.com/crescendo/clinical/pdf/05-24-11-Crescendo-Bioscience-EULAR-PR.pdf

Anderson J, Caplan L, Yazdany J et al.(2012) Rheumatoid arthritis disease activity measures: American College of Rheumatology recommendations for use in clinical practice. Arthritis Care Res (Hoboken) 2012; 64(5):640-7.

Bakker MF, Cavet G, Jacobs JW, et al.(2012) Performance of a multi-biomarker score measuring rheumatoid arthritis disease activity in the CAMERA tight control study. Ann Rheum Dis. Oct 2012; 71(10): 1692-7. PMID 22596166

Bouman CAM, van der Maas A, van Herwaarden N, Sasso EH, et al.(2017) A multi-biomarker score measuring disease activity in rheumatoid arthritis patients tapering adalimumab or etanercept: predictive value for clinical and radiographic outcomes. Rheumatology (Oxford). Jun 1 2017;56(6):973-980. PMID 28339738

Brahe CH, Ostergaard M, Johansen JS, et al.(2019) Predictive value of a multi-biomarker disease activity score for clinical remission and radiographic progression in patients with early rheumatoid arthritis: a post-hoc study of the OPERA trial. Scand J Rheumatol. Jan 2019; 48(1): 9-16. PMID 29985080

Cavet G, Centola M, Shen Y et al.(2010) Development of a multi-biomarker test for rheumatoid arthritis (RA). Ann Rheum Dis 2010; 69(suppl 3):148.

Centola M, Cavet G, Shen Y, et al.(2013) Development of a multi-biomarker disease activity test for rheumatoid arthritis. PLoS One. 2013; 8(4): e60635. PMID 23585841

Cohen S, Wells AF, Curtis JR, et al.(2021) A molecular signature response classifier to predict inadequate response to tumor necrosis factor-a inhibitors: the NETWORK-004 prospective observational study. Rheumatol Ther. 2021 Jun 19; [Epub ahead of print]. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8214458/. Accessed on July 20, 2021.

Combe B, Landewe R, Daien CI, et al.(2017) 2016 update of the EULAR recommendations for the management of early arthritis. Ann Rheum Dis. Jun 2017;76(6):948-959. PMID 27979873

Crescendo Bioscience.(2020) Vectra DA Patient Guide: Understanding results. n.d.; https://vectrascore.com/know-your-results/. Accessed May 18, 2020.

Crescendo Bioscience.(2022) Vectra DA Patient Guide: Understanding results. n.d.; https://vectrascore.com/know-your-results/. Accessed May 9, 2022.

Curtis JR, Brahe CH, Ostergaard M, et al.(2019) Predicting risk for radiographic damage in rheumatoid arthritis: comparative analysis of the multi-biomarker disease activity score and conventional measures of disease activity in multiple studies. Curr Med Res Opin. Sep 2019; 35(9): 1483-1493. PMID 30777458

Curtis JR, Flake DD, Weinblatt ME, et al.(2019) Adjustment of the multi-biomarker disease activity score to account for age, sex and adiposity in patients with rheumatoid arthritis. Rheumatology (Oxford). May 01 2019; 58(5): 874-883. PMID 30590790

Curtis JR, Haney D, van der Helm AH et al.(2010) Validation of a multi-biomarker test for rheumatoid arthritis (RA) disease activity (Vectra™ DA) in a multi-cohort study. Arthritis Rheum 2010; 62(Suppl 10):1782.

Curtis JR, van der Helm-van Mil AH, Knevel R et al.(2012) Validation of a novel multibiomarker test to assess rheumatoid arthritis disease activity. . Arthritis Care Res (Hoboken) 2012; 64(12):1794-803

Curtis JR, Weinblatt ME, Shadick NA, et al.(2021) Validation of the adjusted multi-biomarker disease activity score as a prognostic test for radiographic progression in rheumatoid arthritis: a combined analysis of multiple studies. Arthritis Res Ther. Jan 04 2021; 23(1): 1. PMID 33397438

Davis JM, 3rd.(2016) Editorial: The Multi-Biomarker Disease Activity Test for rheumatoid arthritis: is it a valid measure of disease activity? Arthritis Rheumatol. Sep 2016;68(9):2061-2066. PMID 27111349

England BR, Tiong BK, Bergman MJ, et al.(2019) 2019 Update of the American College of Rheumatology Recommended Rheumatoid Arthritis Disease Activity Measures. Arthritis Care Res (Hoboken). Dec 2019; 71(12): 1540-1555. PMID 31709779

Exagen, Inc(2020) AVISE Testing Exclusively from Exagen Inc. Retrieved from https://avisetest.com/provider/

Fleischmann R, Connolly SE, Maldonado MA, et al.(2016) Estimating disease activity using multi-biomarker disease activity scores in patients with rheumatoid arthritis treated with abatacept or adalimumab. Arthritis Rheumatol. Apr 25 2016. PMID 27111089

Fleischmann R, Connolly SE, Maldonado MA, et al.(2017) Reply. Arthritis Rheumatol. Apr 2017;69(4):867-868. PMID 27992708

Fleischmann R, Curtis J, Hamburger M et al.(2010) RA population characteristics in INFORM, a longitudinal observational study. Ann Rheum Dis 2010; 69(Suppl3):657.

Fraenkel L, Bathon JM, England BR, et al.(2021) 2021 American College of Rheumatology Guideline for the Treatment of Rheumatoid Arthritis. Arthritis Care Res (Hoboken). Jul 2021; 73(7): 924-939. PMID 34101387

Gaujoux-Viala C, Mouterde G, Baillet A et al.(2012) Evaluating disease activity in rheumatoid arthritis: which composite index is best? A systematic literature analysis of studies comparing the psychometric properties of the DAS, DAS28, SDAI and CDAI. Joint Bone Spine 2012; 79(2):149-55.

Hambardzumyan K, Bolce R, Saevarsdottir S, et al.(2014) Pretreatment multi-biomarker disease activity score and radiographic progression in early RA: results from the SWEFOT trial. Ann Rheum Dis. May 8 2014. PMID 24812287

Hambardzumyan K, Bolce R, Saevarsdottir S, et al.(2015) Pretreatment multi-biomarker disease activity score and radiographic progression in early RA: results from the SWEFOT trial. Ann Rheum Dis. Jun 2015;74(6):1102-1109. PMID 24812287

Hambardzumyan K, Bolce RJ, Saevarsdottir S, et al.(2016) Association of a multibiomarker disease activity score at multiple time-points with radiographic progression in rheumatoid arthritis: results from the SWEFOT trial. RMD Open. 2016;2(1):e000197. PMID 26958364

Hambardzumyan K, Saevarsdottir S, Forslind K, et al.(2017) A Multi-Biomarker Disease Activity Score and the choice of second-line therapy in early rheumatoid arthritis after methotrexate failure. Arthritis Rheumatol. May 2017;69(5):953-963. PMID 27992691

Hambardzumyan K, Saevarsdottir S, Forslind K, et al.(2017) A Multi-Biomarker Disease Activity Score and the choice of second-line therapy in early rheumatoid arthritis after methotrexate failure. Arthritis Rheumatol. May 2017;69(5):953-963. PMID 27992691

Hirata S, Li W, Defranoux N, et al.(2014) A multi-biomarker disease activity score tracks clinical response consistently in patients with rheumatoid arthritis treated with different anti-tumor necrosis factor therapies: A retrospective observational study Mod Rheumatol. Oct 8 2014:1-6. PMID 25295918

Hirata S, Li W, Kubo S, et al.(2016) Association of the multi-biomarker disease activity score with joint destruction in patients with rheumatoid arthritis receiving tumor necrosis factor-alpha inhibitor treatment in clinical practice. Mod Rheumatol. Nov 2016; 26(6): 850-856. PMID 26873570

Iannaccone CK, Lee YC, Cui J, et al.(2011) Using genetic and clinical data to understand response to disease-modifying anti-rheumatic drug therapy: data from the Brigham and Women's Hospital Rheumatoid Arthritis Sequential Study. Rheumatology (Oxford). Jan 2011; 50(1): 40-6. PMID 20847201

Johnson TM, Register KA, Schmidt CM, et al.(2019) Correlation of the Multi-Biomarker Disease Activity Score With Rheumatoid Arthritis Disease Activity Measures: A Systematic Review and Meta-Analysis. Arthritis Care Res (Hoboken). Nov 2019; 71(11): 1459-1472. PMID 30320973

Krabbe S, Bolce R, Brahe CH, et al.(2017) Investigation of a multi-biomarker disease activity score in rheumatoid arthritis by comparison with magnetic resonance imaging, computed tomography, ultrasonography, and radiography parameters of inflammation and damage. Scand J Rheumatol. Sep 2017;46(5):353-358. PMID 27682742

Labcorp.(2021) Vectra. 2021. https://www.labcorp.com/tests/504965/vectra. Accessed May 9, 2022.

Li L, Deng C, Chen S, et al.(2016) Meta-Analysis: Diagnostic Accuracy of Anti-Carbamylated Protein Antibody for Rheumatoid Arthritis. PloS one. 2016;11(7):e0159000.

Li W, Sasso EH, van der Helm-van Mil AH, et al.(2016) Relationship of multi-biomarker disease activity score and other risk factors with radiographic progression in an observational study of patients with rheumatoid arthritis. Rheumatology (Oxford). Feb 2016;55(2):357-366. PMID 26385370

Markusse IM, Dirven L, van den Broek M, et al.(2014) A multibiomarker disease activity score for rheumatoid arthritis predicts radiographic joint damage in the BeSt study. J Rheumatol. Nov 2014;41(11):2114-2119. PMID 25128518

Mellors T, Withers JB, Ameli A, et al.(2020) Clinical validation of a blood-based predictive test for stratification of response to tumor necrosis factor inhibitor therapies in rheumatoid arthritis patients. Network and Systems Medicine. 2020; 3(1):1-14.

Palmetto GBA.(2018) Vectra DA Coding and Billing Guidelines (M00031, V10). https://www.palmettogba.com/palmetto/MolDX.nsf/DocsCat/MolDx%20Website~MolDx~Browse%20By%20Topic~Covered%20Tests~97KMQ68675?open&navmenu=%7C%7C. Accessed May 24, 2018.

PrismRA(2022) (Scipher Precision Medicine) https://www.prismra.com/

Rech J, Hueber AJ, Finzel S, et al.(2015) Prediction of disease relapses by multibiomarker disease activity and autoantibody status in patients with rheumatoid arthritis on tapering DMARD treatment. Ann Rheum Dis. Oct 19 2015. PMID 26483255

Regueiro C, Nuño L, Ortiz AM, et al.(2017) Value of Measuring Anti-Carbamylated Protein Antibodies for Classification on Early Arthritis Patients. Scientific Reports. 2017;7(1):12023.

Reiss WG, Devenport JN, Low JM, et al.(2016) Interpreting the multi-biomarker disease activity score in the context of tocilizumab treatment for patients with rheumatoid arthritis. Rheumatol Int. Feb 2016;36(2):295-300. PMID 26026604

Roodenrijs NMT, de Hair MJH, Wheater G, et al.(2018) The multi-biomarker disease activity score tracks response to rituximab treatment in rheumatoid arthritis patients: a post hoc analysis of three cohort studies. Arthritis Res Ther. Nov 20 2018; 20(1): 256. PMID 30458871

Salaffi F, Ciapetti A, Gasparini S et al.(2012) The comparative responsiveness of the patient self-report questionnaires and composite disease indices for assessing rheumatoid arthritis activity in routine care. Clin Exp Rheumatol 2012; 30(6):912-21.

Schoels M, Knevel R, Aletaha D et al.(2010) Evidence for treating rheumatoid arthritis to target: results of a systematic literature search. Ann Rheum Dis 2010; 69(4):638-43.

Upchurch KS, Kay J.(2012) Evolution of treatment for rheumatoid arthritis. Rheumatology (Oxford) 2012; 51 Suppl 6:vi28-36.

van der Helm-van Mil AH, Knevel R, Cavet G, et al.(2013) An evaluation of molecular and clinical remission in rheumatoid arthritis by assessing radiographic progression. Rheumatology (Oxford). May 2013; 52(5): 839-46. PMID 23287359

Verheul MK, Böhringer S, van Delft MAM, et al.(2018) Triple Positivity for Anti–Citrullinated Protein Autoantibodies, Rheumatoid Factor, and Anti–Carbamylated Protein Antibodies Conferring High Specificity for Rheumatoid Arthritis. Arthritis & Rheumatology. 2018;70(11):1721-1731.


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