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Multibiomarker Disease Activity Blood Test for Rheumatoid Arthritis

Policy Number: MP-564

Latest Review Date: June 2019

Category: Laboratory

Policy Grade: B

DESCRIPTION OF PROCEDURE OR SERVICE:

Assessment of disease activity in rheumatoid arthritis (RA) is an important component of management because a main goal of treatment is to maintain low disease activity or remission. There are a variety of available instruments for measuring RA disease activity. These use combinations of physical exam findings, radiologic results, and serum biomarkers to construct a disease activity score. A Multi-biomarker Disease Activity (MBDA) instrument is a disease activity measure that is comprised entirely of serum biomarkers. The Vectra DA test is a commercially available MBDA blood test that uses 12 biomarkers to construct a disease activity score ranging from one (low disease activity) to 100 (high disease activity).

Rheumatoid Arthritis

RA is characterized by chronic joint inflammation leading to painful symptoms, progressive joint destruction and loss of function. The disorder is relatively common and associated with a high burden of morbidity for affected patients.

Treatment

Treatment of RA has undergone a shift from symptom management to a more proactive strategy of minimizing disease activity and delaying disease progression. 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 anti-rheumatic 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, Schoels et al (2010) identified seven studies that evaluated the efficacy of tight control. Four of these trials randomized patients to tight control using treatment targets or to routine management, two studies compared different treatment targets, and one study compared results from a targeted treatment with historical controls. The treatment targets were heterogeneous, including symptom-based measures, joint scores on the exam, validated treatment activity measures, lab values, or combinations of these factors. In all four trials that randomized patients to tight control or routine management, 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 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. Combination therapy may consist of additional disease-modifying antirheumatic drugs or the addition of tumor necrosis factors or non-tumor necrosis factors biologics.

Validated Disease Activity Assessment Tools

For a strategy of tight control to be successful, a reliable and valid measurement of disease activity is necessary. There are numerous disease activity measurements that can be used in clinical care.

Through a five-stage process that included review by an expert advisory panel in RA disease activity and detailed evaluation of psychometric properties, an ACR working group determined that six measures were accurate reflections of disease activity: Clinical Disease Activity Index (CDAI), DAS28, Patient Activity Scale, Patient Activity Scale II, Routine Assessment of Patient Index Data 3, and the Simplified Disease Activity Index (SDAI).

Two systematic reviews were published the same year as the ACR’s recommendations, one by Gaujoux-Viala et al (2012) and the other by Salaffi et al (2012), which compared disease activity measures for patients with RA. Results from the systematic reviews were consistent with the ACR working group recommendations, citing the DAS28, SDAI, and CDAI as appropriate disease activity measures for RA.

Table 1 summarizes the clinical and laboratory measurements included in each of the six disease activity measures recommended by ACR. The table also includes the laboratory measures included in the Vectra DA, a multi-biomarker disease activity (MBDA) test which currently does not have a recommendation from ACR.

Table 1. Clinical and Laboratory Components of Rheumatoid Arthritis Disease Activity Measurements

Recommended by ACR

No ACR Recommendation

DAS28

CDAI and SDAI

PAS

PAS II

RAPID3

Vectra DA

No. of swollen joints out of 28a

No. of swollen joints out of 28a

Patient describes ability to do each of 20 activitiesb as “without any difficulty,” “with some difficulty,” “with much difficulty,” or “unable to do”

Patient describes ability to do each of 10 activitiesc as “without any difficulty,” “with some difficulty,” “with much difficulty,” or “unable to do”

Patient describes ability to do each of 13 activitiesd as “without any difficulty,” “with some difficulty,” “with much difficulty,” or “unable to do”

  • Interleukin-6
  • Tumor necrosis factor receptor type I
  • Vascular cell adhesion molecule 1
  • Epidermal growth factor
  • Vascular endothelial growth factor A
  • YKL-40 glycoprotein
  • MMP-1
  • MMP-3
  • C-reactive protein
  • Serum amyloid A
  • Leptin
  • Resistin

No. of tender joints out of 28a

No. of tender joints out of 28a

Patient indicates need for cane, crutches, walker, wheelchair, or devices to assist with dressing or eating

Patient rates pain on scale of 0 (no pain) to 10 (severe pain)

Patient rates pain on scale of 0 (no pain) to 10 (severe pain)

ESR (mm/h)

CRP (mg/L) (only in the SDAI, not part of CDAI calculation)

Patient indicates need for assistance in dressing, rising, eating, walking, hygiene, reaching, gripping, or chores

Patient rates how they are doing on scale of 0 (very well) to 10 (very poor)

Patient rates how they are doing on scale of 0 (very well) to 10 (very poor)

CRP (mg/L)

Patient Global Assessment (0 [very well] to 10 [very poor])

Patient indicates if special devices needed in bathroom or kitchen

Patient Global Assessment (0 [best] to 100 [worst])

Physician Global Assessment (0 [very well] to 10 [very poor])

Patient rates pain on scale of 0 (no pain) to 10 (severe pain)

Patient rates how they are doing on scale of 0 (very well) to 10 (very poor)

Adapted by Anderson et al (2012).

ACR: American College of Rheumatology; CDAI: Clinical Disease Activity Index; CRP: C-reactive protein; DAS28: Disease Activity Score 28; ESR: erythrocyte sedimentation rate; MMP: matrix metalloproteinase; PAS: Patient Activity Scale; RAPID3: Routine Assessment of Patient Index Data 3; SDAI: Simplified Disease Activity Index.

a Twenty-eight joints: shoulders, elbows, wrists, metacarpophalangeal joints, proximal interphalangeal joints, and knees.

b Dress self; shampoo hair; stand from chair; get in and out of bed; cut meat; bring cup to mouth; open milk carton; walk outdoors on flat ground; climb five steps; wash and dry body; take tub bath; get on and off toilet; reach and bring down five pound object from above head; bend and pick up clothing from floor; open car door; open new jar; turn faucets on and off; run errands; get in and out of car; do chores (e.g., vacuum or yard work).

c Stand from chair; walk outdoors on flat ground; get on and off toilet; reach and bring down five pound object from above head; open car door; do outside work such as yard work; wait in line for 15 minutes; lift heavy objects; move heavy objects; climb two or more flights of stairs.

d Dress self; get in and out of bed; bring cup to mouth; walk outdoors on flat ground; wash and dry body; bend and pick up clothing from floor; turn faucets on and off; get in and out of car; walk two miles; participate in recreational activities; sleep well; deal with feelings of anxiety or nervousness; deal with feelings of depression or sadness.

Vectra DA Test

The manufacturer describes Vectra DA as a complement to clinical judgment. 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 DA test scores range from one to 100. Categories of scores were constructed to correlate with the DAS28-CRP scale:

  • 45-100: high disease activity
  • 30-44: moderate disease activity
  • 1-29: low disease activity

POLICY:

The use of a multi-biomarker disease activity score for rheumatoid arthritis (RA) (e.g., Vectra® DA score) is considered not medically necessary and investigational in all situations.

KEY POINTS:

This policy has been updated regularly with searches of the MEDLINE database. The most recent literature review was updated through April 23, 2019.

Evidence reviews assess whether a medical test is clinically useful. A useful test provides information to make a clinical management decision that improves the net health outcome. That is, the balance of benefits and harms is better when the test is used to manage the condition than when another test or no test is used to manage the condition.

The first step in assessing a medical test is to formulate the clinical context and purpose of the test. The test must be technically reliable, clinically valid, and clinically useful for that purpose. Evidence reviews assess the evidence on whether a test is clinically valid and clinically useful. Technical reliability is outside the scope of these reviews, and credible information on technical reliability is available from other sources.

Multi-Biomarker Disease Activity Testing In Rheumatoid Arthritis

Clinical Context and Test Purpose

The purpose of the MBDA, specifically the Vectra DA, in patients who have rheumatoid arthritis (RA) is to determine the level of disease activity (low, medium, or high) in order to inform treatment decisions.

The question addressed in this evidence review is: Does use of a MBDA (e.g., Vectra DA) test, alone or as an adjunct, to predict disease activity in patients with RA, improve health outcomes compared with use of American College of Rheumatology (ACR) - recommended measures of disease activity?

The following PICOTS were used to select literature to inform this review.

Patients

The relevant population of interest is individuals with RA who are being managed with a disease-modifying antirheumatic drug (DMARD).

Management of patients with RA has changed from treatment of symptoms to a tight control strategy. The objective of a tight control strategy is to minimize disease progression and joint damage by monitoring disease activity and treating aggressively if an increase in activity is predicted.

Interventions

Vectra DA provides a score indicating the level of disease activity, based on blood levels of the following 12 biomarkers: interleukin-6, tumor necrosis factor (TNF) receptor type I, vascular cell adhesion molecule 1, epidermal growth factor, vascular endothelial growth factor A, YKL-40 glycoprotein, matrix metalloproteinase 1, matrix metalloproteinase 3, C-reactive protein (CRP), serum amyloid A, leptin, and resistin.

Scores range from one to 100 (1-29=low disease activity; 30-44=medium disease activity; 45-100=high disease activity).

Comparators

The reference standard for disease activity is radiographic progression at a set point in time, typically three months to one year. In addition, an ACR expert panel on RA determined the following six disease activity measures were useful and feasible to implement in a clinical setting: Clinical Disease Activity Index (CDAI), Disease Activity Score with 28 joints (DAS28), Patient Activity Scale, Patient Activity Scale II, Routine Assessment of Patient Index Data 3, and Simplified Disease Activity Index.

Outcomes

The goal of treating patients with RA is to improve quality of life and to prevent progression of the disease. Progression of disease causes irreversible joint damage.

If Vectra DA correctly assesses disease activity as low, the clinician may maintain medications at the same level or consider tapering the patient’s medication.

If Vectra DA correctly assesses disease activity as moderate or high, the clinician may be more aggressive in disease management, by either increasing doses of current medications, switching medications, or adding medications to the treatment plan.

If Vectra DA incorrectly assesses disease activity as low, the clinician may maintain or decrease medication levels, which will allow progression of the disease and further joint damage.

If Vectra DA incorrectly assesses disease activity as moderate or high, the clinician may continue to manage the patient with higher levels of medication than is necessary to prevent disease progression, exposing the patient to unnecessary toxins. DMARDs may affect the liver, stomach, and intestines. Biologic agents may increase the risk of infection, lymphoma, and skin cancer.

Timing

The test may be run as often as a clinician needs disease activity information, typically every three to six months. A test immediately after diagnosis may serve as a baseline measurement.

For purposes of assessing Vectra DA against the reference standard of radiographic progression, one year is the typical time frame.

Setting

The test may be given at an outpatient rheumatology practice or an academic or community setting. Primary care may be the main source of care in some locations.

Study Selection Criteria

For the evaluation of the clinical utility of a multibiomarker disease activity test (e.g., Vectra DA), studies would need to use the test as either an adjunct or a replacement to current disease activity measures to manage treatment decisions in patients with RA. Outcomes would be quality of life and measures of disease progression.

In the absence of direct evidence for the clinical utility of Vectra DA, evidence for clinical validity is evaluated, in which we can make inferences on clinical utility. For the evaluation of clinical validity, studies would need to compare Vectra DA used as an adjunct or as a replacement to ACR-recommended disease activity measures, with radiographic progression as a reference standard. Key validity outcomes of sensitivity, specificity, as well as positive (PPV) and negative (NPV) predictive values, should be reported.

Technically Reliable

Assessment of technical reliability focuses on specific tests and operators and requires review of unpublished and often proprietary information. Review of specific tests, operators, and unpublished data are outside the scope of this evidence review, and alternative sources exist. This evidence review focuses on the clinical validity and clinical utility.

Clinically Valid

A test must detect the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse).

All evidence identified used the Vectra DA test. Eleven publications using data and serum samples from eight studies met selection criteria and are included in this review. Table 2 summarizes study characteristics of the publications:

  • Six studies (eight publications) included records and archived samples from randomized controlled trials (RCTs).
  • One study (two publications) included records and samples from a cohort study.
  • One study included records and samples from a single-arm study.
  • One study (two publications) used random (weighted) samples; the remaining were convenience samples.
  • All studies were retrospective analyses. Prospective protocols precluding the inference that these were nonconcurrent prospective studies could not be identified (as described by Simon et al [2009]).
  • Reference standard for most studies was radiographic progression, generally at one year. The definition of radiographic progression varied among studies. Some studies also included moderate radiographic progression and rapid radiographic progression.
  • Eight publications used thresholds of low (<30), moderate (30–44), and high (>44). One study used a threshold of remission (≤25) or no remission (>25). Two publications analyzed Vectra as a continuous score.
  • Outcome assessment was blinded in three publications, with no report on blinding of assessors in the remaining eight publications.

Table 3 provides clinical validity results for the studies. Below are select key points from the results:

  • Samples included in the publications ranged from 52 to 524 patients.
  • Only one publication reported sensitivity and specificity data. Hambardzumyan et al (2015) reported that the sensitivity for high Vectra risk was 98%, specificity was 17%, NPV was 97%, and PPV was 21%.The low specificity and PPV do not support the use of the test to “rule in” high-risk disease.
  • Four studies reported area under the receiver operating characteristic curve (AUROC) data, and another reported positive likelihood ratios. Seven publications reported the percentage of patients progressing by Vectra class.
  • In two publications, the AUROC for the Vectra test was numerically higher than the DAS28; however, the confidence intervals overlapped. Overlapping confidence intervals indicate uncertainty whether Vectra DA provides prognostic performance superior to DAS28.
  • In three studies, Vectra scores were not associated with radiographic progression or rapid radiographic progression, and in another, Vectra correlated with radiographic progression at one time point (26 weeks), but not at baseline or one year.
  • One study reported a higher positive likelihood ratio for Vectra compared with DAS28, again with overlapping confidence intervals.
  • One study reported that significantly more patients with low Vectra scores responded to triple therapy compared with anti-TNF therapy, while significantly more patients with high Vectra scores responded to anti-TNF therapy compared with triple therapy.

Table 2. Study Characteristics of Included Studies

Study

Study Population

Design

Reference Standard (Time From Test to RP)

Threshold for Positive Index Test

Blinding of Assessors

Comment

Bakker et al (2012)

CAMERA, early RA

Retrospective; convenience

RP at 2 y

NA: Continuous scores used in analysis

NR

Patients randomized to intensive or conventional treatment

Van der Helm-van Mil et al (2013)

Leiden EAC cohort with symptoms <2 y; samples collected between 1995 and 2005

Retrospective; random (weighted sample)

Moderate RP and RRP at 1 y

Remission (≤25) vs not remission (>25)

Yes

Infrequent use of anti-TNFs in this population

Markusse et al (2014)

BeST patients with symptoms <2 y

Retrospective; convenience

RP and RRP after 1 y

NA: Continuous scores used in analysis

NR

Same samples as Hirata et al (2013)

Hambardzumyan et al (2015)

SWEFOT, DMARD-naive

Retrospective; convenience

RRP at 1 y

Low (<30), moderate (30-44), and high (>44)

NR

Patients treatment with MTX until 3 mo, nonresponders randomized to MTX plus triple therapy or MTX plus infliximab

Hambardzumyan et al (2016)

SWEFOT, DMARD-naive

Retrospective; convenience

RRP at 2 y

Low (<30), moderate (30-44), and high (>44)

NR

Overlapping samples with Hambardzumyan et al (2015); does not explain the differing n’s

Fleischmann et al (2016)

AMPLE, biologic-naive, RA ≤5 y, inadequate response to MTX

Retrospective; convenience

RP at 1 y

Low (<30), moderate (30-44), and high (>44)

Yes

Patients randomized to MTX plus abatacept or MTX plus adalimumab

Li et al (2016)

Leiden EAC cohort with symptoms <2 y; samples collected between 1995 and 2005

Retrospective; random (weighted sample)

Moderate RP and RRP at 1 y

Low (<30), moderate (30-44), and high (>44)

NR

Overlap with van der Helm et al (2013)

Hirata et al (2016)

Patients treated with TNF inhibitor for ≥1 y at a single institution

Retrospective; convenience

Clinically relevant RP; RRP at 1 y

Low (<30), moderate (30-44), and high (>44)

Yes

Overlap with Hirata et al (2015)

Bouman et al (2017)

DRESS, RCT of tapering TNF inhibitors until discontinuation or flaring vs usual care

Retrospective, convenience

RP at 18 mo

Low (<30), moderate (30-44), and high (>44)

NR

Flare defined as increase in DAS28-CRP >1.2 vs baseline or increase in DAS28-CRP >0.6 vs baseline plus current DAS28 ≥3.2

Hambardzumyan et al (2017)

SWEFOT, inadequate responders to MTX at 3 mo

Retrospective, convenience

EULAR criteria for response to treatment

Low (<30), moderate (30-44), and high (>44)

NR

May overlap with Hambardzumyan et al (2015)

Krabbe et al (2017)

Patients treated with TNF inhibitor for 1 y at a single institution

Retrospective, single arm

RP at 1 y

Remission (≤25), low (26-29), moderate (30-44), and high >44)

NR

RP defined by MRI synovitis, MRI bone marrow edema, US synovial PD score; and US GSS

Brahe et al (2018)

OPERA, treatment naïve, RA <6 mos

Retrospective, from RCTRP

RP at 1 y

Low (<30), moderate (30-44), high (>44)

Yes

Patients randomized to MTX plus placebo or MTX plus adalimumab

AMPLE: Abatacept versus Adalimumab Comparison in Biologic-Naive RA Subjects with Background Methotrexate; BeST: Behandel Strategieën; CAMERA: Computer Assisted Management in Early Rheumatoid Arthritis; CRP: C-reactive protein; DAS28: Disease Activity Score with 28 joints; DMARD: disease-modifying antirheumatic drug; DRESS: Dose REduction Strategies of Subcutaneous TNF Inhibitors trial; EAC: Early Arthritis Clinic; EULAR: European League Against Rheumatism; GSS: grey scale synovitis; MRI: magnetic resonance imaging; MTX: methotrexate; NA: not applicable; NR: not reported; PD; power Doppler; RA: rheumatoid arthritis; RCT: randomized controlled trial; RP: radiographic progression; OPERA: Optimized Treatment in early Rheumatoid Arthritis; RRP: rapid radiographic progression; SWEFOT: Swedish Farmacotherapy; TNF: tumor necrosis factor; US: ultrasound.

Table 3. Clinical Validity Results for the Vectra DA Test

Study

Initial N

Final N

Excluded Samples

Prevalence of Condition

Clinical Validity: Risk Outcome, %

Other Reported Measures
(95% CI)

Low

Medium

High

Bakker et al (2012)

NR for CAMERA

120 samples (72 at BL, 48 at 6 mo), not clear if overlapping

Serum unavailable

NR

NR

NR

NR

Vectra: BL or 6 mo not associated with RP in multivariate analyses

DAS28-CRP: AUC=0.86 (p<0.001)

Van der Helm-van Mil et al (2013)

NR

163 patients (271 samples)

Not selected by sampling

Moderate RP=26%

Vectra: 7%b

DAS28: 20%b

Vectra: 30%b

DAS28: 29%b

Vectra PLR=4.7 (1.7 to 15.0)

DAS28 PLR=1.4 (0.9 to 2.4)

Markusse et al (2014)

508 in BeST

125 (91 at BL; 89 at 1 y); 84 with BL serum and 1-y radiograph

Missing or insufficient samples

RP=37%

NR

NR

NR

RP:

Vectra AUC=0.61 (0.48 to 0.73)

DAS AUC=0.37 (0.25 to 0.50)

RRP:

Vectra AUC=0.77 (0.64 to 0.90)

DAS AUC=0.52 (0.36 to 0.68)

Hambardzumyan et al (2015)

487 in SWEFOT

235 with complete BL demographic, serologic, radiographic, and clinical data

Incomplete data

RRP=18%

Vectra: 0%

DAS28: NA

Vectra: 3%

DAS28: 20%a

Vectra: 21%

DAS28: 21%a

Vectra low/mod vs high:

Sensitivity: 98%

Specificity: 17%

NPV: 97%

PPV: 21%

Hambardzumyan et al (2016)

487 in SWEFOT

220 patients with Vectra DA scores, CRP, ESR, and DAS28 at BL, 205 at 3 mo, 133 at 1 y

Incomplete data

RRP=30%

Vectra:

3 mo: 9%

1 y: 3%

DAS28:

3 mo: 24%

1 y: 6%

Vectra:

3 mo: 26%

1 y: 8%

DAS28:

3 mo: 32%

1 y: 15%

Vectra:

3 mo: 41%

1 y: 32%

DAS28:

3 mo: 35%

1 y: 38%

No measures of sensitivity, specificity, or other performance characteristics reported

Fleischmann et al (2016)

646 in AMPLE

524 with available data

Unavailable data

RP=30%

Vectraa:

ABA group: 79%

ADM group: 77%

CDAIa:

ABA group: 64%

ADM group: 65%

Vectraa:

ABA group: 67%

ADM group: 55%

CDAIa:

ABA group: 74%

ADM group: 79%

Vectraa:

ABA group: 63%

ADM group: 80%

CDAIa:

ABA group: 91%

ADM group: 90%

No association between Vectra classes and RP

Li et al (2016)

NR

163 patients (271 samples)

Not selected by weighted sampling

Mod RP=26%;

RRP=17%

Vectra mod:

RP=10%

RRP=2%

Vectra mod:

RP, 15%-19%

RRP, 7%-8%

Vectra mod:

RP, 33%- 51%

RRP, 28%-41%

Vectra:

AUROC mod RP=0.72 (0.64 to 0.78)

AUROC RRP=0.77 (0.69 to 0.83)

DAS28:

AUROC mod RP=0.59 (0.51 to 0.67)

AUROC RRP=0.66 (0.56 to 0.75)

Hirata et al (2016)

NR

83

Patients without data at 24 wk

Clinically relevant RP=12%

Vectra: 0%

DAS28: 0%

Vectra: 4%

DAS28: 18%

Vectra: 28%

DAS28: 36%

No measures of sensitivity, specificity, or other performance characteristics reported

Bouman et al (2017)

171

167 (115 randomized to dose tapering, 59 randomized to usual care)

Patients without both serum samples and 18-mo radiographs

RP=26%

RP occurred in 31% in the dose-tapering group and in 16% in the usual care group

MBDA score was not predictive of successful tapering, flare occurrence, or RP

AUROC tapering: 0.53 (0.41 to 0.66)

AUROC flare: 0.50 ( 0.41 to 0.59)

AUROC RP: 0.53 (0.43 to 0.63)

Hambardzumyan et al (2017)

157

157 (75 randomized to triple therapy, 82 randomized to anti-TNF therapy)

No exclusions

Responders to triple therapy 47% and responders to anti-TNF therapy was 54%

19 responded to triple therapy (88%) more than to anti-TNF therapy (18%; p=0.006)

50 responded equally to triple therapy (54%) and anti-TNF therapy (62%)

88 responded to anti-TNF therapy (58%) more than to triple therapy (35%; p=0.04)

DAS28 measure at 3 mo not associated with response to particular therapy

Krabbe et al (2017)

52

--Week 10, n=46

--Week 20, n=43

--Week 30, n=42

--Week 40, n=35

--Week 50, n=35

--Week 60, n=33

Patients with missing data

RP=19%

In 10 with disease progression,

0 had low Vectra score

In 10 with disease progression,

3 had mod Vectra score

In 10 with disease progression,

7 had high Vectra score

Vectra correlated poorly with MRI/US at BL and 52 wk; Vectra correlated well with MRI/US at 26 wk

Brahe et al (2018)

180

164

No explanation for exclusion

RP=23%

Vectra: 4%; RP: 0%

DAS28: 0%; RP: 0%

Vectra: 14%; RP 4%

DAS28: 34%; RP: 26%

Vectra: 82%; RP: 31%

DAS28: 66%; RP: 26%

--Subgroup analysis by anti-CCP status;

--anti-CCP negative; neither MBDA not DAS28 identified patients that would experience RP

--anti-CCP positive; MBDA at baseline identified patients at low risk of progression; no incremental benefit to adding DAS28

                     

ABA: abatacept; ADM: adalimumab; AMPLE: Abatacept versus Adalimumab Comparison in Biologic-Naive RA Subjects with Background Methotrexate; AUC: area under the curve; BeST: Behandel Strategieën; BL: baseline; CAMERA: Computer Assisted Management in Early Rheumatoid Arthritis; BL: baseline; CCP: cyclic citrullinated peptide; CRP: C-reactive protein; CDAI: Clinical Disease Activity Index; DAS28: 28-joint Disease Activity Score; ESR: erythrocyte sedimentation rate; MBDA: multibiomarker disease activity; Mod: moderate; MRI: magnetic resonance imaging; NA: not available; NPV: negative predictive value; NR: not reported; PLR: positive likelihood ratio; PPV: positive predictive value; RP: radiographic progression; RRP: rapid radiographic progression; SWEFOT: Swedish Farmacotherapy; TNF: tumor necrosis factor; US: ultrasound.

a Estimated from figure.

b “Low” risk is remission and “high”’ risk is not remission.

Study Limitations for Clinical Validity

The purpose of the gaps tables (see Tables 4 and 5) is to display notable gaps identified in each study. This information is synthesized as a summary of the body of evidence following each table and provides the conclusions on the sufficiency of evidence supporting the position statement.

Table 4. Relevance Limitations for Studies

Study

Populationa

Interventionb

Comparatorc

Outcomesd

Duration of FUe

Bakker et al (2012)

3. Not consistent with current use, which is as an adjunct to other disease activity measures

3. Key clinical validity outcomes not reported (sensitivity, specificity, predictive values); only AUROC reported

Van der Helm-van Mil et al (2013)

3. Not consistent with current use, which is as an adjunct to other disease activity measures

3. Key clinical validity outcomes not reported (sensitivity, specificity, predictive values); risk of remission reported

Markusse et al (2014)

3. Not consistent with current use, which is as an adjunct to other disease activity measures

3. Key clinical validity outcomes not reported (sensitivity, specificity, predictive values); only AUROC reported

Hambardzumyan et al (2015)

3. Not consistent with current use, which is as an adjunct to other disease activity measures

Hambardzumyan et al (2016)

3. Not consistent with current use, which is as an adjunct to other disease activity measures

3. Key clinical validity outcomes not reported (sensitivity, specificity, predictive values); comparisons to other biomarkers reported

Fleischmann et al (2016)

3. Not consistent with current use, which is as an adjunct to other disease activity measures

3. Key clinical validity outcomes not reported (sensitivity, specificity, predictive values); correlations with other biomarkers reported

Li et al (2016)

3. Not consistent with current use, which is as an adjunct to other disease activity measures

3. Key clinical validity outcomes not reported (sensitivity, specificity, predictive values); correlations with radiographic progression reported

Hirata et al (2016)

3. Not consistent with current use, which is as an adjunct to other disease activity measures

3. Key clinical validity outcomes not reported (sensitivity, specificity, predictive values); correlations with radiographic progression reported

Bouman et al (2017)

3. Not consistent with current use, which is as an adjunct to other disease activity measures

3. Key clinical validity outcomes not reported (sensitivity, specificity, predictive values); AUROC reported

Hambardzumyan et al (2017)

3. Not consistent with current use, which is as an adjunct to other disease activity measures

3. Key clinical validity outcomes not reported (sensitivity, specificity, predictive values); comparisons with DAS28 reported

Krabbe et al (2017)

3. Not consistent with current use, which is as an adjunct to other disease activity measures

3. Key clinical validity outcomes not reported (sensitivity, specificity, predictive values); correlations with radiographic progression reported

Brashe et al (2018)

4. Population did not include patients with low (<3.2) DAS28 scores

3. Key clinical validity outcomes not reported (sensitivity, specificity, predictive values); comparisons with radiographic progression reported

The evidence gaps stated in this table are those notable in the current review; this is not a comprehensive gaps assessment.

AUROC: area under the receiver operating curve; DAS28: Disease Activity Score with 28 joints; FU: follow-up.
a Population key: 1. Intended use population unclear; 2. Clinical context is unclear; 3. Study population is unclear; 4. Study population not representative of intended use.

b Intervention key: 1. Classification thresholds not defined; 2. Version used unclear; 3. Not intervention of interest.

c Comparator key: 1. Classification thresholds not defined; 2. Not compared to credible reference standard; 3. Not compared to other tests in use for same purpose.

d Outcomes key: 1. Study does not directly assess a key health outcome; 2. Evidence chain or decision model not explicated; 3. Key clinical validity outcomes not reported (sensitivity, specificity and predictive values); 4. Reclassification of diagnostic or risk categories not reported; 5. Adverse events of the test not described (excluding minor discomforts and inconvenience of venipuncture or noninvasive tests).

e Follow-Up key: 1. Follow-up duration not sufficient with respect to natural history of disease (true positives, true negatives, false positives, false negatives cannot be determined).

Table 5. Study Design and Conduct Limitations for the Validity Studies

Study

Selectiona

Blindingb

Delivery of Testc

Selective Reportingd

Data Completenesse

Statisticalf

Bakker et al (2012)

2. Selection not random or consecutive; convenience serum samples from an RCT

1. Blinding of assessors not reported

Van der Helm-van Mil et al (2013)

Markusse et al (2014)

2. Selection not random or consecutive; convenience serum samples from an RCT

1. Blinding of assessors not reported

Hambardzumyan et al (2015)

2. Selection not random or consecutive; convenience serum samples from an RCT

1. Blinding of assessors not reported

Hambardzumyan et al (2016)

2. Selection not random or consecutive; convenience serum samples from an RCT

1. Blinding of assessors not reported

Fleischmann et al (2016)

2. Selection not random or consecutive; convenience serum samples from an RCT

2. No statistical test reported to compare MBDA vs alternatives, only tests comparing treatment groups

Li et al (2016)

1. Blinding of assessors not reported

Hirata et al (2016)

2. Selection not random nor consecutive; convenience serum samples from an RCT

Bouman et al (2017)

2. Selection not random nor consecutive; convenience serum samples from an RCT

1. Blinding of assessors not reported

Hambardzumyan et al (2017)

2. Selection not random or consecutive; convenience serum samples from an RCT

1. Blinding of assessors not reported

Krabbe et al (2017)

2. Selection not described; single-arm study with no explanation of how patients recruited

1. Blinding of assessors not reported

4. Expertise of evaluators not described

3. High loss of follow-up: 14% at 20 wk and 30% at 50 wk

P values only reported for some comparisons

Brahe et al (2018)

2. Selection not random nor consecutive; convenience serum samples from an RCT

The evidence gaps stated in this table are those notable in the current review; this is not a comprehensive gaps assessment.

FU: follow-up; MBDA: multibiomarker disease activity; RCT: randomized controlled trial.
a Selection key: 1. Selection not described; 2. Selection not random or consecutive (i.e., convenience).

b Blinding key: 1. Not blinded to results of reference or other comparator tests.

c Test Delivery key: 1. Timing of delivery of index or reference test not described; 2. Timing of index and comparator tests not same; 3. Procedure for interpreting tests not described; 4. Expertise of evaluators not described.

d Selective Reporting key: 1. Not registered; 2. Evidence of selective reporting; 3. Evidence of selective publication.

e Data Completeness key: 1. Inadequate description of indeterminate and missing samples; 2. High number of samples excluded; 3. High loss to follow-up or missing data.

f Statistical key: 1. Confidence intervals and/or p values not reported; 2. Comparison to other tests not reported.

Pooled Analysis

Curtis et al (2019) conducted a pooled analysis on data from studies of MBDA and radiographic progression. To be included in the analysis, the cohort studies needed to have patient level data, more than 100 patients, and the following measures: MBDA scores (low/moderate/high: <30, 30-44, >44), DAS28-CRP (low/moderate/high: <2.67, >2.67 to 4.09, >4.09), and CRP (low/moderate/high: <10, >10 to 30, >30 mg/L). Four studies containing five cohorts (N=929 patients) were included in the analysis, several of which are described in Tables 4 and 5. Relative risks (RR) for radiographic progression at one year for each of the measures were calculated based on high versus not high (low and moderate combined) categories. Of the three measures, MBDA scores best predicted radiographic progression, with an RR of 4.6 (95% CI: 2.4 to 8.9, p<0.0001), though DAS28-CRP and CRP alone also reliably predicted radiographic progression, with RR of 1.7 (95% CI: 1.1 to 2.6, p=0.02) and 1.7 (95% CI: 1.2 to 2.4, p=0.002), respectively.

Section Summary: Clinically Valid

Evidence for the clinical validity of the MBDA test consists of analyses of archived serum samples from RCTs as well as prospective cohort studies that have correlated MBDA with other measures of disease activity and with radiographic progression. Results from studies comparing MBDA with other disease activity measures have shown a positive correlation; however, results from studies comparing MBDA with radiographic progression are inconsistent. Only 1 study reported sensitivity and specificity, with a PPV of 21%, indicating that 4 out of 5 patients identified as positive would receive intensification of therapy unnecessarily.

Currently, MBDA is used as an adjunct to other disease activity measures. No evidence was identified that evaluated the incremental benefit of MBDA when used as an adjunct to other disease activity measures.

Overall, studies lacked reporting of sensitivity, specificity, and predictive values, which are the most informative measures for ascertaining the performance of Vectra DA in selecting high-risk patients for intensification of therapy. The evidence is insufficient to conclude the clinical validity of Vectra DA compared with ACR-recommended measures of disease activity.

Clinically Useful

A test is clinically useful if the use of the results informs management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.

Direct Evidence

Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from RCTs.

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 or that the MBDA score demonstrates an incremental benefit when used as an adjunct with other disease activity measures. To demonstrate equivalence with other measures directly, an RCT comparing health outcomes of two groups, one group managed using the Vectra DA test and the other group managed by another disease activity measure is needed.

To directly demonstrate an incremental benefit when used as an adjunct, an RCT should compare health outcomes in patients receiving treatment guided by MBDA plus a disease activity measure with outcomes in patients receiving treatment guided only by the other disease activity measure. No RCTs were identified. Below is a retrospective study conducted to evaluate MBDA scores and medication use among patients with RA.

Curtis et al (2018) used Medicare data from 2011 to 2015 to study MBDA scores and biologic and Janus kinase inhibitors use among patients with RA. The database contained 60,596 patients with RA who had MBDA testing results. Among patients not currently taking biologics (n=33,728), statistically significant differences in adding or switching medications were detected based on MBDA scores: 9.0% of patients with low scores, 11.8% with moderate scores, and 19.7% with high scores. Similarly, among patients currently taking biologics, statistically significant differences in switching medications were detected among the different levels of MBDA scores: 5.2% of patients with low scores, 8.3% with moderate scores, and 13.5% with high scores.

Chain of Evidence

Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.

Because there is insufficient evidence that the MBDA score is clinically valid, direct evidence is needed to prove clinical utility. No trials were identified that provided direct evidence of clinical utility.

Section Summary: Clinically Useful

There are no RCTs comparing the use of the Vectra DA score with an alternative method of measuring disease activity. Additionally, there are no RCTs of Vectra DA as an adjunct to other disease activity measures compared with using the disease activity measures alone. Absent direct evidence for clinical utility, a chain of evidence could be constructed with indirect evidence proving clinical validity. However, there is insufficient evidence that MBDA is clinically valid.

Summary of Evidence

For individuals who have rheumatoid arthritis who receive a MBDA (e.g., Vectra DA) test as an adjunct or as a replacement of other disease activity measures, the evidence includes analyses of archived serum samples from RCTs and prospective cohort studies. Relevant outcomes are test validity, other test performance measures, symptoms, change in disease status, functional outcomes, and quality of life. Analyses comparing Vectra DA with other previously validated disease activity measures such as the DAS28 or to radiographic progression, consisted mostly of correlations, with only one study providing sensitivity, specificity, and positive and negative predictive values. The positive predictive value from this study was 21%. Other analyses of archived serum samples evaluated the use of Vectra DA to predict treatment response. Results from those analyses were inconsistent. The body of evidence on the Vectra DA test is insufficient to determine whether it is as good as or better than other disease activity measures. Additionally, there is no evidence evaluating Vectra DA as an adjunct to other disease activity measures. The evidence is insufficient to determine the effects of the technology on health outcomes.

Practice Guidelines and Position Statements

American College of Rheumatology

In the 2015 American College of Rheumatology guidelines on the treatment of rheumatoid arthritis, the American College of Rheumatology endorses the following measures of disease activity: Patient Activity Scale, Routine Assessment of Patient Index Data 3, Clinical Disease Activity Index, Disease Activity Score 28, and Simplified Disease Activity Index. The guidelines indicated that other measures are available to clinicians, but that including the new measures was out of scope. ACR is currently updating the guidelines for rheumatoid arthritis, with an estimated publication date of late 2019 or early 2020.

European League Against Rheumatism

The European League Against Rheumatism (2017) updated its guidelines on the management of early arthritis. The League recommended that arthritis activity be assessed at one- to three-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.

National Institute for Health and Care Excellence

The National Institute for Health and Care Excellence published guidance on the management of adult patients with rheumatoid arthritis in 2018. There is no discussion on the use of a multibiomarker disease activity blood test to monitor patients with rheumatoid arthritis.

U.S. Preventive Services Task Force Recommendations

Not Applicable.

KEY WORDS:

Vectra DA, Rheumatoid Arthritis, RA, Multi-biomarker Disease Activity (MBDA)

APPROVED BY GOVERNING BODIES:

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. The Vectra® DA test (Crescendo Bioscience) is available under the auspices of Clinical Laboratory Improvement Amendments. Laboratories that offer laboratory-developed tests must be licensed by Clinical Laboratory Improvement Amendments for high-complexity testing. To date, the U.S. Food and Drug Administration has chosen not to require any regulatory review of this test.

BENEFIT APPLICATION:

Coverage is subject to member’s specific benefits. Group specific policy will supersede this policy when applicable.

ITS: Home Policy provisions apply.

FEP: Special benefit consideration may apply. Refer to member’s benefit plan. FEP does not consider investigational if FDA approved and will be reviewed for medical necessity.

CURRENT CODING:

CPT Codes:

81490

Autoimmune (rheumatoid arthritis), analysis of 12 biomarkers using immunoassays, utilizing serum, prognostic algorithm reported as a disease activity score

83520

Immunoassay for analyte other than infectious agent antibody or infectious agent antigen; quantitative, not otherwise specified

84999

Unlisted chemistry procedure

REFERENCES:

  1. Anderson J, Caplan L, Yazdany J et al. Rheumatoid arthritis disease activity measures: American College of Rheumatology recommendations for use in clinical practice. Arthritis Care Res (Hoboken) 2012; 64(5):640-647.
  2. Bakker MF, Cavet G, Jacobs JW et al. Performance of a multi-biomarker score measuring rheumatoid arthritis disease activity in the CAMERA tight control study. Ann Rheum Dis 2012; 71(10):1692-1697.
  3. Bouman CAM, van der Maas A, van Herwaarden N, Sasso EH, van den Hoogen FHJ, den Broeder AA. 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.
  4. Brahe, CC, Johansen, JJ, Defranoux, NN, Wang, XX, Bolce, RR, Sasso, EE, Horslev-Petersen, KK, Stengaard-Pedersen, KK, Junker, PP, Ellingsen, TT, Ahlquist, PP, Lindegaard, HH, Linauskas, AA, Schlemmer, AA, Dam, MM, Hansen, II, Lottenburger, TT, Ammitzboll, CC, Jorgensen, AA, Krintel, SS, Raun, JJ, Hetland, MM. 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., 2018 Jul 10;48(1).
  5. Centola M, Cavet G, Shen Y et al. Development of a multi-biomarker disease activity test for rheumatoid arthritis. PLoS One 2013; 8(4):e60635.
  6. Combe B, Landewe R, Daien CI, et al. 2016 update of the EULAR recommendations for the management of early arthritis. Ann Rheum Dis. Jun 2017;76(6):948-959.
  7. Crescendo Bioscience. Vectra DA Patient Guide: Understanding results. n.d.; https://vectrada.com/health-care-professionals/understanding-results/?gclid=CMqLnbrTiNQCFQcaaQodcE4JRg.
  8. Curtis, JJ, Brahe, CC, Lund Hetland, MM, Hambardzumyan, KK, Saevarsdottir, SS, Wang, XX, Flake Ii, DD, Sasso, EE, Huizinga, TT. 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, 2019 Feb 20;1-11:1-11.
  9. Curtis, JJ, Xie, FF, Yang, SS, Danila, MM, Owensby, JJ, Chen, LL. Uptake and Clinical Utility of Multibiomarker Disease Activity Testing in the United States.. J. Rheumatol., 2018 Nov 18;46(3).
  10. Curtis JR, van der Helm-van Mil AH, Knevel R et al. Validation of a novel multibiomarker test to assess rheumatoid arthritis disease activity. Arthritis Care Res (Hoboken) 2012; 64(12):1794-1803.
  11. Curtis JR, Wright GC, Strand V, et al. Reanalysis of the Multi-Biomarker Disease Activity Score for Assessing Disease Activity in the Abatacept Versus Adalimumab Comparison in Biologic-Naive Rheumatoid Arthritis Subjects with Background Methotrexate Study: Comment on the Article by Fleischmann et al. Arthritis Rheumatol. Apr 2017; 69(4):863-865.
  12. Davis JM, 3rd. 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.
  13. Eastman PS, Manning WC, Qureshi F et al. Characterization of a multiplex, 12-biomarker test for rheumatoid arthritis. J Pharm Biomed Anal 2012; 70:415-424.
  14. Fleischmann R, Connolly SE, Maldonado MA, et al. Estimating disease activity using multi-biomarker disease activity scores in patients with rheumatoid arthritis treated with abatacept or adalimumab. Arthritis Rheumatol. Apr 25 2016.
  15. Fleischmann R, Connolly SE, Maldonado MA, et al. Reply. Arthritis Rheumatol. Apr 2017; 69(4):867-868.
  16. Gaujoux-Viala C, Mouterde G, Baillet A et al. 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):149-155.
  17. Hambardzumyan K, Bolce R, Saevarsdottir S, et al. 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.
  18. Hambardzumyan K, Bolce RJ, Saevarsdottir S, et al. 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.
  19. Hambardzumyan K, Saevarsdottir S, Forslind K, et al. 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.
  20. Hirata S, Dirven L, Shen Y et al. A multi-biomarker score measures rheumatoid arthritis disease activity in the BeSt study. Rheumatology 2013; 52(7): 1202-1207.
  21. Hirata S, Li W, Defranoux N, et al. 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. May 2015; 25(3):344-349.
  22. Hirata S, Li W, Kubo S, et al. 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. Mar 30 2016:1-7.
  23. Krabbe S, Bolce R, Brahe CH, et al. 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.
  24. Li W, Sasso EH, Emerling D et al. Impact of a multi-biomarker disease activity test on rheumatoid arthritis treatment decisions and therapy use. Curr Med Res Opin 2013; 29(1):85-92.
  25. Li W, Sasso EH, van der Helm-van Mil AH, et al. 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.
  26. Markusse IM, Dirven L, van den Broek M, et al. A multibiomarker disease activity score for rheumatoid arthritis predicts radiographic joint damage in the BeSt study. J Rheumatol. Nov 2014; 41(11):2114-2119.
  27. National Institute for Health and Care Excellence. Rheumatoid arthritis in adults: management [NG100]. July 2018, https://www.nice.org.uk/guidance/ng100. Accessed April 23, 2019
  28. Peabody JW, Strand V, Shimkhada R et al. Impact of rheumatoid arthritis disease activity test on clinical practice. PLoS One 2013; 8(5):e63215.
  29. Rech J, Hueber AJ, Finzel S, et al. 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.
  30. Reiss WG, Devenport JN, Low JM, et al. 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.
  31. Salaffi F, Ciapetti A, Gasparini S et al. 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):912-921.
  32. Schoels M, Knevel R, Aletaha D et al. Evidence for treating rheumatoid arthritis to target: results of a systematic literature search. Ann Rheum Dis 2010; 69(4):638-643.
  33. Simon RM, Paik S, Hayes DF. Use of archived specimens in evaluation of prognostic and predictive biomarkers. J Natl Cancer Inst. Nov 4 2009;101(21):1446-1452.
  34. Singh JA, Saag KG, Bridges SL, Jr., et al. 2015 American College of Rheumatology guideline for the treatment of rheumatoid arthritis. Arthritis Rheumatol. Jan 2016; 68(1):1-26.
  35. Upchurch KS, Kay J. Evolution of treatment for rheumatoid arthritis. Rheumatology (Oxford) 2012; 51 Suppl 6:vi28-36.
  36. van der Helm-van Mil AH, Knevel R, Cavet G, Huizinga TW, Haney DJ. An evaluation of molecular and clinical remission in rheumatoid arthritis by assessing radiographic progression. Rheumatology (Oxford). May 2013; 52(5):839-846.

POLICY HISTORY:

Medical Policy Panel, April 2014

Medical Policy Group, September 2014 (1): New policy, previously only listed on the Investigational Listing; remains investigational

Medical Policy Administration Committee, October 2014

Available for comment September 23 through November 6, 2014

Medical Policy Panel, April 2015

Medical Policy Group, May 2015 (3): Updates to Description, Key Points, Current Coding – added CPT code 81490 that will be effective 01/01/16, - and References; no change to policy statement.

Medical Policy Group, November 2015: 2016 Annual Coding Update. Verified new code 81490 included on policy.

Medical Policy Panel, June 2016

Medical Policy Group, June 2016 (3): 2016 Updates to Description, Key Points, & References; no change to Policy statement.

Medical Policy Panel, June 2017

Medical Policy Group, July 2017 (3): 2017 Updates to Description, Key Points and References. No change to policy statement.

Medical Policy Panel, June 2018

Medical Policy Group, July 2018 (3): 2018 Updates to Title, Description, Key Points and References. Added Key Words- multi-biomarker disease activity (MBDA). No change to policy statement.

Medical Policy Panel, June 2019

Medical Policy Group, June 2019 (9): 2019 Updates to Description, Key Points, References. No change to policy statement.


This medical policy is not an authorization, certification, explanation of benefits, or a contract. Eligibility and benefits are determined on a case-by-case basis according to the terms of the member’s plan in effect as of the date services are rendered. All medical policies are based on (i) research of current medical literature and (ii) review of common medical practices in the treatment and diagnosis of disease as of the date hereof. Physicians and other providers are solely responsible for all aspects of medical care and treatment, including the type, quality, and levels of care and treatment.

This policy is intended to be used for adjudication of claims (including pre-admission certification, pre-determinations, and pre-procedure review) in Blue Cross and Blue Shield’s administration of plan contracts.

The plan does not approve or deny procedures, services, testing, or equipment for our members. Our decisions concern coverage only. The decision of whether or not to have a certain test, treatment or procedure is one made between the physician and his/her patient. The plan administers benefits based on the member’s contract and corporate medical policies. Physicians should always exercise their best medical judgment in providing the care they feel is most appropriate for their patients. Needed care should not be delayed or refused because of a coverage determination.

As a general rule, benefits are payable under health plans only in cases of medical necessity and only if services or supplies are not investigational, provided the customer group contracts have such coverage.

The following Association Technology Evaluation Criteria must be met for a service/supply to be considered for coverage:

1. The technology must have final approval from the appropriate government regulatory bodies;

2. The scientific evidence must permit conclusions concerning the effect of the technology on health outcomes;

3. The technology must improve the net health outcome;

4. The technology must be as beneficial as any established alternatives;

5. The improvement must be attainable outside the investigational setting.

Medical Necessity means that health care services (e.g., procedures, treatments, supplies, devices, equipment, facilities or drugs) that a physician, exercising prudent clinical judgment, would provide to a patient for the purpose of preventing, evaluating, diagnosing or treating an illness, injury or disease or its symptoms, and that are:

1. In accordance with generally accepted standards of medical practice; and

2. Clinically appropriate in terms of type, frequency, extent, site and duration and considered effective for the patient’s illness, injury or disease; and

3. Not primarily for the convenience of the patient, physician or other health care provider; and

4. Not more costly than an alternative service or sequence of services at least as likely to produce equivalent therapeutic or diagnostic results as to the diagnosis or treatment of that patient’s illness, injury or disease.