| Coverage Policy Manual | |
| Policy #: | 2014018 |
| Category: | Laboratory |
| Initiated: | September 2014 |
| Last Review: | June 2023 |
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| Biomarker Panel Testing for Systemic Lupus Erythematosus | |
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| Description: |
Systemic lupus erythematosus (SLE) is an autoimmune connective tissue disease (CTD) that can be difficult to diagnose because patients often present with diverse, nonspecific symptoms that overlap with other CTDs; to further complicate matters, commonly used laboratory tests are not highly accurate. Moreover, similar symptoms may also present themselves in patients individuals with fibromyalgia. Currently, differential diagnosis depends on a combination of clinical signs and symptoms and individual laboratory tests. More accurate laboratory tests for SLE and other CTDs could facilitate the diagnosis of the disease. Laboratory-developed, diagnostic panel tests with proprietary algorithms and/or index scores for the diagnosis of SLE and other autoimmune CTDs are commercially available.
Systemic lupus erythematous (SLE) is one of several types of lupus, the others being cutaneous and drug-induced. About 90% of lupus patients are women between the ages of 15 and 44 years. Systemic lupus erythematous causes inflammation and can affect any part of the body, most commonly the skin, heart, joints, lungs, blood vessels, liver, kidneys, and nervous system. Although generally not fatal, SLE can increase mortality, most commonly from cardiovascular disease due to accelerated atherosclerosis. Systemic lupus erythematous can also lead to kidney failure, which may reduce survival. The survival rate in the U.S. is approximately 95% at 5 years and 78% at 20 years (Kasitanon, 2006). The morbidity associated with SLE is substantial. Symptoms such as joint and muscle pain can impact quality of life and functional status. Systemic lupus erythematous also increases patients' risk of infection, cancer, avascular necrosis (bone death), and pregnancy complications (e.g., preeclampsia, preterm birth). The course of the disease is variable, and patients generally experience flares of mild-to-severe illness and remission.
Several other connective tissue diseases (CTDs) may require a differential diagnosis from SLE (e.g., rheumatoid arthritis, thyroid disease, Sjögren syndrome, antiphospholipid syndrome, and polymyositis).
Rheumatoid arthritis is a chronic inflammatory peripheral polyarthritis. Rheumatoid arthritis can lead to deformity through stretching of tendons and ligaments and destruction of joints through erosion of cartilage and bone. Rheumatoid arthritis can also affect the skin, eyes, lungs, heart, and blood vessels.
Graves disease is an autoimmune disorder that leads to overactivity of the thyroid gland. The disease arises from thyroid-stimulating hormone receptor antibodies. It is the most common cause of hyperthyroidism. Blood tests may show raised thyroid-stimulating immunoglobulin antibodies.
Hashimoto disease, also known as chronic lymphocytic thyroiditis, is an autoimmune disorder and is the most common cause of hypothyroidism second to iodine insufficiency. It is characterized by an underactive thyroid gland and gradual thyroid failure. Diagnosis is confirmed with blood tests for thyroid-stimulating hormone (T4) and antithyroid antibodies.
Sjögren syndrome is an autoimmune disorder characterized by dryness of the eyes and mouth due to diminished lacrimal and salivary gland function. Affected individuals may also have symptoms of fatigue, myalgia, and cognitive dysfunction, which may be difficult to distinguish clinically from fibromyalgia or medication side effects. Typical antibodies include antinuclear antibody (ANA), anti-Sjögren-syndrome-related antigen, anti-Sjögren syndrome type B, or rheumatoid factor.
Antiphospholipid syndrome is a systemic autoimmune disorder characterized by venous or arterial thrombosis and/or pregnancy morbidity. Antiphospholipid antibodies are directed against phospholipid-binding proteins.
Polymyositis and dermatomyositis are inflammatory myopathies characterized by muscle weakness and inflammation. Dermatomyositis may also have skin manifestation
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 Act (CLIA). The Avise® tests (Exagen Diagnostics) are available under the auspices of CLIA. Laboratories that offer laboratory-developed tests must be licensed by the CLIA Clinical 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
There is no specific CPT code for this panel of tests.
There are codes that would likely be used for some of the component tests such as:
83520: Immunoassay for analyte other than infectious agent antibody or infectious agent antigen; quantitative, not otherwise specified
86038: Antinuclear antibodies (ANA);
86039: Antinuclear antibodies (ANA); titer
86146: Beta 2 Glycoprotein I antibody, each
86147: Cardiolipin (phospholipid) antibody, each Ig class
86200: Cyclic citrullinated peptide (CCP), antibody
86225: Deoxyribonucleic acid (DNA) antibody; native or double stranded
86235: Extractable nuclear antigen, antibody to, any method (eg, nRNP, SS-A, SS-B, Sm, RNP, Sc170, J01), each antibody
86376: Microsomal antibodies (eg, thyroid or thyroid-kidney), each
86800: Thyroglobulin antibody
88184: Flow cytometry, cell surface, cytoplasmic, or nuclear marker, technical component only, first marker
88185: second marker
88187: Flow cytometry, interpretation; 2 to 8 markers
Some payers such as Medicare might instruct the use of the unlisted chemistry code for the whole panel:
84999: Unlisted chemistry procedure.
Due to the reporting of an index score for the entire panel, the test would more accurately be reported with the unlisted multianalyte assay with algorithmic analysis (MAAA) CPT code – 81599.
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Policy/ Coverage: |
EFFECTIVE JUNE 2021
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
Serum biomarker panel testing with proprietary algorithms and/or index scores (e.g., AVISE SLE, AVISE CTD, AVISE SLE Prognostic) for the diagnosis of systemic lupus erythematosus does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness.
For members with contracts without primary coverage criteria, serum biomarker panel testing with proprietary algorithms and/or index scores (e.g., AVISE SLE, AVISE CTD, AVISE SLE Prognostic) for the diagnosis of systemic lupus erythematosus is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
EFFECTIVE PRIOR TO JUNE 2021
Serum biomarker panel testing with proprietary algorithms and/or index scores (e.g., AVISE SLE, AVISE CTD, AVISE SLE Prognostic) for the diagnosis of systemic lupus erythematosus 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, serum biomarker panel testing with proprietary algorithms and/or index scores for the diagnosis of systemic lupus erythematosus is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
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| Rationale: |
This policy was created in 2014 with a search of the MEDLINE database through July 2014. Assessment of a diagnostic technology typically focuses on 3 categories of evidence: 1) technical performance (test-retest reliability or interrater reliability); 2) diagnostic accuracy (sensitivity, specificity, and positive and negative predictive value) in relevant populations of patients; and 3) demonstration that the diagnostic information can be used to improve patient outcomes. In addition, subsequent use of a technology outside of the investigational setting may also be evaluated.
Technical Accuracy
Some individual biomarkers, eg, ANA and anti-dsDNA, are considered standard of care in the diagnosis of connective tissue diseases, and, presumably, the technical accuracy of these tests has been established. The technical accuracy of tests for novel biomarkers in biomarker panel tests is not known.
Diagnostic Accuracy
Serum biomarker panel tests
No studies were identified that evaluated the diagnostic accuracy of any commercially available biomarker panel for systemic lupus erythematosus (SLE).
One study, published by Kalunian et al in 2012 and supported by Exagen Diagnostics, evaluated the performance of a 7-marker biomarker panel for the diagnosis of SLE; some of these markers are included in a commercially available panel test (Kalunian, 2012). The biomarkers included the auto-antibodies antinuclear antibodies (ANA), anti-dsDNA, and anti-mutated citrullinated vimentin (anti-MCV) measured by enzyme-linked immunosorbent assay (ELISA). In addition, the authors assessed the cell-bound complement activation products, complement receptor 1 levels on erythrocytes and complement C4d levels on erythrocytes (EC4d), platelets (PC4d) and B cells (BC4d), determined by fluorescence-activated cell sorting.
The study was cross-sectional and enrolled 593 individuals at 14 sites in the U.S. The sample consisted of 210 patients with SLE (according to the American College of Rheumatology (ACR) classification criteria, updated in 1997), 178 patients with other rheumatic diseases and 205 healthy volunteers. Test results were evaluated by scientists blinded to patient diagnosis.
In a multivariate logistic regression, SLE diagnosis was associated with a positive ANA test, a negative anti-MCV test, and elevated values of EC4d and BC4d (area under the curve [AUC]=0.92, p<0.001). The weighted sum of these 4 markers correctly categorized 106 of 148 (71.6%) of SLE patients who were anti-dsDNA negative. (The investigators evaluated the 4-marker index score among individuals who tested negative for anti-dsDNA because of the low sensitivity of this test, 29.5%, and thus high false negative rate). The specificity of the 4-marker index was 98.0% (200 of 204 healthy volunteers with test results were correctly classified). When anti-dsDNA was added to the 4-marker panel, the test had 80% sensitivity for SLE (168 of 210 SLE patients were correctly classified). Moreover, this 5-marker test had 97.6% specificity among healthy individuals (200 of 205 were correctly classified as not having SLE). Moreover, the 5-marker test had 87% specificity in patients with other rheumatic diseases; the most false positives, 9, were in patients with rheumatoid arthritis.
Limitations of the study are that it did not include the population of greatest interest to SLE diagnostic testing; that is, individuals with symptoms suggestive of SLE who have not already received a diagnosis. Instead it included individuals either known to have SLE or another rheumatic disease or known to be healthy. Moreover, test accuracy was not compared with concurrent physician diagnosis.
It is important to note that the biomarkers in the 5-marker test are part of the 10-marker Avise 2.0 SLE test marketed by Exagen. It is not clear whether the index score reported along with the Avise 2.0 panel is the same or different as the index score reported in the Kalunian et al study.
Novel panel components: CB-CAPs
As previously discussed, CB-CAPs are key components of a commercially available biomarker panel test for lupus diagnosis. CB-CAPs include complement C4d levels on erythrocytes, platelets, and B cells. Preliminary investigations of each of these biomarkers have been done by a research team at the University of Pittsburgh.
A study on lymphyocyte-bound complement activation products was published by Liu et al in 2009 (Liu, 2009). This was a cross-sectional study including 224 patients with SLE (according to ACR criteria), 179 patients with other autoimmune or inflammatory diseases and 114 healthy controls. Levels of lymphyocyte-bound complement activation products, T-cell bound C4d and C3d (TC4d and TC3d) and B-cell- bound C4d and C3d (BC4d and BC3d) were measured in all participants. The diagnostic accuracy of these markers was accessed using receiver-operating characteristic (ROC) analysis. The AUC was 0.727 for TC4d and 0.770 for BC4d. Based on these estimates, TC4d was estimated to be 56% sensitive and 80% specific for differentiating SLE from other diseases. BC4d had 56% sensitivity and 80% specificity.
In addition, the authors compared the CB-CAPs with other, conventionally used, SLE markers. The markers were evaluated as a confirmatory test in patients who tested positive for ANA. This analysis only included the SLE patients, 223 of 224 of whom (99.6%) were positive for ANA. Of the 223 ANA-positive patients, 141 (63%) patients had elevated levels of TC4d and/or BC4d. In contrast, 59 of the 209 ANA-positive patients (28%) tested positive for anti-dsDNA. Moreover, when the more commonly used CAPs, serum C3 and serum C4, were evaluated, 67 of 221 (30%) of ANA-positive patients tested positive for C3 and 82 of 221 patients (37%) tested positive for C4.
Previously, a study on platelet C4d was published by Navratil in 2006 (Navratil, 2006). The cross-sectional study included 105 patients with SLE (according to ACR criteria), 115 patients with other autoimmune or inflammatory diseases, and 100 healthy controls. Abnormal levels of platelet C4d were detected in 18% of SLE patients. False negative rate and sensitivity rates were not reported. The authors reported that the marker was 100% specific for a diagnosis of SLE compared with healthy controls and 98% specific compared with patients who had other diseases.
Thirdly, Manzi et al reported on the diagnostic accuracy of erythrocyte C4d in 2004 (Manzi, 2004). The cross-sectional study included 100 patients with SLE (according to ACR criteria), 133 patients with other autoimmune or inflammatory diseases and 84 healthy controls. Overall, erythrocyte C4d was 86% sensitive and 71% specific. Moreover, the authors reported that erythrocyte C4d was 72% sensitive and 79% specific for SLE versus other diseases, and 81% sensitive and 91% specific for SLE versus healthy controls.
The CB-CAPs lymphocyte-bound BC4d, platelet C4d and erythrocyte C4d are included in the panel test evaluated in the Kalunian et al study discussed earlier (Kalunian, 2012). As in the Kalunian study, all of the other studies included individuals with known diagnoses; none included patients of greatest interest for diagnostic test—those with symptoms suggestive of disease. Also similar was the lack of a concurrent reference standard in the studies.
Effect on Patient Outcomes
No studies were identified that evaluate the impact of serum biomarker panel testing for SLE on patient management decisions or patient outcomes.
Summary
Systemic lupus erythematosus (SLE) is an autoimmune connective tissue disease that can be difficult to diagnose because patients often present with diverse, nonspecific symptoms, and commonly used laboratory tests are not highly accurate. Currently, the diagnosis of SLE depends on a combination of clinical signs and symptoms and individual laboratory tests. More accurate laboratory tests for SLE could facilitate diagnosis of the disease in many patients. Recently, laboratory-developed, diagnostic panel tests with proprietary algorithms and/or index scores for the diagnosis of SLE have become commercially available.
Panel tests for SLE include markers that are standard in the work-up of SLE, but also contain novel markers, most notably cell-bound complement activation products (CB-CAPs). The accuracy of CB-CAPs in establishing a diagnosis of SLE is not known, nor is the use of these novel biomarkers recommended in clinical practice guidelines. In addition to reporting the results of the panel of tests, an index score is reported that rates how suggestive the results of the panel are of a diagnosis of SLE. Information is not available on how this index score is calculated, nor is it known how this score performs in diagnosing SLE compared with currently accepted clinical and laboratory criteria. Finally, the utility of assessing multiple biomarkers simultaneously, rather than the more commonly performed sequential testing, is unknown.
Practice Guidelines and Position Statements
In 2014, an international group including participants in the European autoimmunity standardization initiative and the International Union of Immunologic Societies published recommendations on the assessment of autoantibodies to cellular antigens (Agmon-Levin, 2014). The recommendations included the following statements relevant to the diagnosis of SLE:
2015 Update
A literature search conducted through July 2015 did not reveal any new information that would prompt a change in the coverage statement. The key identified literature is summarized below.
Putterman and colleagues published data from a large cross-sectional industry-sponsored study evaluating serum biomarkers for the diagnosis of SLE (Putterman, 2014). This study included an analysis of the 10 markers included in the Avise SLE test (plus ANA) using 2-tier testing logic similar to that used in the commercially available panel (see Background section). The study included 2 cohorts (total N=794); 593 participants were enrolled between April to August 2010 and 201 participants enrolled between June 2011 and September 2013. Together, the 2 cohorts consisted of 304 patients who fulfilled the ACR classification criteria for SLE, 161 patients diagnosed with other rheumatic diseases and 205 heathy volunteers. Results of serum testing were available for 764 of 794 (96%) participants.
The diagnostic accuracy of the cell-bound complement activation products (CB-CAP) EC4d and BC4d were compared with reduced complement (C3, C4) and anti-dsDNA. The area under the receiver operating curve (ROC) was significantly higher for EC4d (0.82) and BC4d (0.84) than for C3 (0.73) and C4 (0.72), p<0.001. The area under the ROC curve was significantly higher for BC4d than anti-dsDNA (0.79, p=0.009) but there was not a significant difference between EC4d and anti-dsDNA.
A total of 140 patients with SLE (46%), 9 patients with other diseases (3%) and 1 healthy volunteer tested positive for at least 1 of the 4 tier 1 markers. Patients testing negative for tier 1 tests underwent tier 2 testing and an index score was calculated. A total of 102 of 164 patients with SLE analyzed in tier 2 (62%) had an index score greater than 0 (ie, suggestive of SLE). Moreover, 245 of 276 patients with other rheumatic diseases had an index score less than 0, ie, not suggestive of SLE. When results of tier 1 and tier 2 testing were combined, the overall sensitivity for SLE was 80% (242/304) and the overall specificity for distinguishing SLE from other diseases was 86% (245/285). The specificity for distinguishing between SLE and health volunteers was 98% (201/205).
A limitation of the Putterman et al and Kalunian et al studies is that study populations included patients with SLE who met ACR classification criteria, but not patients with symptoms suggestive of SLE who failed to meet ACR criteria. It is not known how the diagnostic accuracy of the panel test compares to the ACR classification criteria or to concurrent clinician diagnosis (in the Putterman et al study, the mean time since SLE diagnosis was 11 years). Furthermore, although they are included in the SLICC classification criteria, the complement factors C3 and C4 are not widely used in clinical practice to diagnose lupus and therefore the clinical significance of higher diagnostic accuracy for EC4d and BC4d is unclear.
The evidence for the diagnosis of systemic lupus erythematosus (SLE) in patients who have signs and/or symptoms of SLE, using serum biomarker panel testing, consists of several diagnostic accuracy studies. Outcomes of importance are diagnostic accuracy of the test, overall survival, symptoms and disease remission. One study evaluated a panel similar to a commercially available test; it found that the panel test had somewhat higher specificity and lower sensitivity than the most commonly currently used biomarkers. The clinical significance of this degree of difference in diagnostic accuracy is unclear. There is also uncertainly around how the use of a serum biomarker panel test for SLE would change patient management. The evidence is insufficient to determine the effects on health outcomes of the use of serum biomarker panel testing with proprietary algorithms/ and or index scores for the diagnosis of SLE.
2016 Update
A literature search conducted through August 2016 did not reveal any new information that would prompt a change in the coverage statement.
2018 Update
A literature search conducted using the MEDLINE database did not reveal any new information that would prompt a change in the coverage statement.
An industry-sponsored study analyzed serum biomarkers as well as an algorithm for diagnosing SLE (Wallace, 2016). This study analyzed markers in the Avise Lupus (plus ANA) test using a 2-tier testing logic to evaluate SLE patients who met ACR criteria (n=75) and patients with primary fibromyalgia (n=75). High expression of CB-CAP EC4d or BC4d had 43% sensitivity and 96% specificity for the diagnosis of SLE. Use of a multianalyte assay with the algorithm, including CB-CAP levels, generated indeterminate results in 12 of the 150 subjects enrolled. For the remainder of patients, use of the algorithm to diagnosis SLE was 60% sensitive and 100% specific. Study limitations included selection of patients with well-established diagnosis and long duration of disease.
The evidence remains insufficient to determine the effects of the technology on health outcomes.
2019 Update
A literature search was conducted through May 2019. There was no new information identified that would prompt a change in the coverage statement.
2020 Update
A literature search was conducted through May 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 May 2021. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
Outcomes of interest for SLE include disease activity indices, organ damage, reduction in flares, and reduction in concomitant corticosteroids (Guidance for Industry, 2010). Patient reported outcomes are also encouraged, particularly ones that measure fatigue as most experts agree that it is 1 of the most important symptoms of SLE. However, the U.S. Food and Drug Administration (FDA) has not identified an existing instrument optimal for measuring fatigue in patients with SLE. Both fatigue and pain are the most consequential and frequent symptoms in SLE and these contribute significantly to physical functioning, sleep, and the ability to complete daily tasks, among other quality of life measures (McElhone, 2007). Validated instruments for measuring quality of life in SLE are mainly used in clinical trials. Systemic lupus erythematosus-specific measures include the Lupus-quality-of-life and SLE-specific quality-of-life (SLEQOL) instruments; additionally general quality of life measures are also used to measure health-related quality of life (eg, Short Form 36 [SF-36]). Recommended health outcome measures for disease activity and organ damage per FDA guidance are summarized below (Guidance for Industry, 2010; Romero-Diaz, 2011).
Health Outcome Measures Relevant to SLE:
Organ damage assessment
Liang et al conducted a retrospective single-center study of 117 patients in a rheumatology clinic without a confirmed SLE diagnosis who had received an Avise CTD test as part of their clinical care between April 2014 and November 2016 (Liang, 2020). The study aimed to determine whether the Avise test would aid in assessing the risk of developing SLE in patients who had undifferentiated findings presenting in a real-world setting. At the clinic, patients who had inflammatory arthritis, undifferentiated CTD, or other diagnoses or features suggestive of SLE received Avise testing. In this cohort of patients without a diagnosis of SLE at baseline, the diagnosis at 2 years from baseline changed in 80% (16/20) of patients who had a positive test as opposed to only 28.9% (28/97) who had a non-positive test. Of the 20 patients who had a positive test, 13 (65%) had their diagnosis changed to SLE at 2 years. The Avise test was associated with a specificity of 93%, with a sensitivity of 57%, positive predictive value of 65% and negative predictive value of 90%. The study also observed that patients with a positive Avise test had a significant accrual of clinical features, as defined by SLICC and ACR criteria, as well as organ damage, as defined by the SLICC Damage Index, compared to those without a positive test over the 2 year period. Additionally, there were no significant differences in medication regimens received by positive versus non-positive patients at baseline or at 2 years, except for more frequent use of mycophenolate mofetil in positive patients at year 2. Limitations of the study include its retrospective design and the potential for confirmation bias as treating physicians were aware of the Avise results and were potentially less likely to diagnose SLE in a patient with a negative Avise test. The authors concluded that the Avise CTD may be useful in predicting the development of SLE.
Ramsey-Goldman et al evaluated the usefulness of CB-CAPs and a multianalyte assay in patients with suspected SLE to predict progression to SLE as classified by ACR criteria in an industry-sponsored prospective observational study at 7 academic institutions (Ramsey-Goldman, 2020). Patients with probable SLE as suspected by lupus experts who also met 3 ACR criteria (n=92) were enrolled along with patients with established SLE based on ACR and SLICC criteria (n=53). A control group of patients with primary Sjogren's syndrome and other rheumatic diseases (n=101) were also included. The multianalyte panel with algorithm evaluated was the Avise Lupus test. The sensitivity of CB-CAPs and MAP at enrollment was higher compared to anti-dsDNA levels or low complement levels. The MAP was more sensitive and specific than CB-CAPs in patients with probable SLE (40% vs 28% and 96% vs 86%, respectively). The ability of positive CB-CAPs and MAPs to predict fulfillment of the ACR criteria at 9 to 18 months after enrollment was also analyzed. In the subgroup of 20 patients with probable SLE who fulfilled ACR criteria within 18 months, 8 (40%) had a MAP score >0.8 at enrollment. Kaplan-Meier estimates found that a MAP score >0.8 was predictive of progression to classifiable SLE (hazard ratio 3.11, 95% confidence interval 1.26 to 7.69). A limitation of the study was the relatively small population of patients with probable SLE. Ramsey-Goldman et al (2021) continued to follow patients with probable SLE from their original report to better determine whether more patients transitioned to classifiable SLE and whether the MAP score retained its ability to predict this transition (Ramsey-Goldman, 2021). Of the 92 patients with probable SLE, 74 had 1 or 2 follow-up visits 9 to 35 months after enrollment (total follow-up visits: 128). Twenty-eight patients with probable SLE (30.4%) were found to transition to ACR-classifiable SLE. This included 16 individuals in the first year and 12 afterwards. A MAP score >0.8 at enrollment continued to predict a transition to classifiable SLE during follow-up (hazard ratio 2.72; p=.012); individual biomarkers or fulfillment of SLICC criteria did not.
Serum biomarker panel tests should be compared with usual clinical diagnosis assessments. Clinical diagnosis for SLE is not standardized, but generally consists of assessments of individual biomarkers in patients with signs and symptoms suspicious of SLE. One randomized controlled trial (RCT) is available directly comparing serum biomarker panel tests to standard diagnosis laboratory testing (Wallace, 2019). The CARE for Lupus Trial was conducted in the United States at 32 sites from July 2017-December 2018. Participants include 145 patients who were referred to a rheumatologist with a clinical suspicion for SLE, including a history of ANA positivity. 72 had the Avise Lupus test and 73 had standard diagnosis laboratory testing.
Wallace et al reported quality of life measures with the 5-level EuroQOL-5 Dimension index, however, outcomes were not reported by treatment group (Wallace, 2019).
Wallace et al evaluated the clinical utility of the Avise Lupus test for the diagnosis of lupus as compared to standard diagnosis laboratory testing (Wallace, 2019). The primary endpoint of the trial was the change in the physicians' estimate of likelihood of SLE before and after testing (12 weeks after enrollment). Physicians estimated the likelihood on a 5-point Likert scale ranging from 0 (very low) to 4 (very high). At baseline, pretest likelihood was similar between the standard diagnosis laboratory testing group and the Avise Lupus test group and the likelihood of SLE decreased in both groups after testing, but the magnitude of the decrease was greater in the Avise Lupus test group. The change in likelihood of SLE from randomization to post-test was -0.44 ± 0.10 in the Avise Lupus test group versus -0.19 ± 0.07 in the standard diagnosis laboratory testing group (p=.027). The corresponding changes from baseline to end of study at week 12 was -0.31 ± 0.10 versus -0.61 ± 0.10 (p=.025), for each group respectively.
There were some study relevance limitations in the comparator (in the standard diagnosis laboratory group, physicians were not directed to order any specific laboratory test – not standard or optimal), the outcomes (formal diagnosis, or fulfillment of classification of SLE not included – key health outcomes not addressed), and follow-up (short follow-up did not allow for confirmation of SLE diagnosis or impact on longer term health outcomes – not sufficient duration for benefit) (Wallace, 2019). Also, there were some study design and conduct limitations: Blinding (no blinding was used in the study [not blinded to treatment assignment] and post-test likelihood of SLE assessed by the treating physician [outcome assessed by treating physician]); Selective Reporting (Between group differences in quality of life measures were not reported [evidence of selective reporting]); Power (Power calculations were not performed [power calculations not reported]); and Statistical (Median differences and 95% confidence intervals between treatment groups for outcomes were not reported [comparative treatment effects not calculated]) (Wallace, 2019).
2022 Update
Annual policy review completed with a literature search using the MEDLINE database through May 2022. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
Ramsey-Goldman et al continued to follow patients with probable SLE from their original report to better determine whether more patients transitioned to classifiable SLE and whether the MAP score retained its ability to predict this transition (Ramsey-Goldman, 2021). Of the 92 patients with probable SLE, 74 had 1 or 2 follow-up visits 9 to 35 months after enrollment (total follow-up visits: 128). Twenty-eight patients with probable SLE (30.4%) were found to transition to ACR-classifiable SLE. This included 16 individuals in the first year and 12 afterwards. A MAP score >0.8 at enrollment continued to predict a transition to classifiable SLE during follow-up (hazard ratio 2.72; p=.012); individual biomarkers or fulfillment of SLICC criteria did not.
2023 Update
Annual policy review completed with a literature search using the MEDLINE database through May 2023. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
O'Malley et al reported results of the CAPSTONE retrospective study (N=44,605) of electronic health record data from 2016 to 2020 from 300 US rheumatologists (O’Malley, 2022). The study compared the likelihood of SLE diagnosis and SLE treatment initiation between AVISE testing and an ANA testing strategy. The testing results from the AVISE test were obtained directly from the laboratory vendor. The test results for the ANA tests were obtained from the electronic health record by searching for all variants of ANA and related test names. The study participants had a mean age in the early- to mid-50s, were mostly female (>80%), and mostly White (>55%). AVISE positive patients were more likely to initiate SLE medications compared with ANA positive patients (adjusted odds ratio [OR], 2.1; 95% confidence interval [CI], 1.9 to 2.4). AVISE positive patients were more likely to be diagnosed with SLE, as compared with the ANA patients (31% vs 8%; adjusted OR, 4.8; 95% CI, 4.0 to 5.7). The study is limited by its retrospective, non-paired design. The ANA comparator is only a subset of the standard diagnostic information used in practice.
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| References: |
American College of Rheumatology (ACR).(1997) 1997 Update of the 1982 American College of Rheumatology Revised Criteria for Classification of Systemic Lupus Erythematosus. n.d.; https://www.rheumatology.org/Portals/0/Files/1997%20Update%20of%201982%20Revised.pdf. Accessed April 27, 2021. Aringer M, Costenbader K, Daikh D, et al.(2019) 2019 European League Against Rheumatism/American College of Rheumatology Classification Criteria for Systemic Lupus Erythematosus. Arthritis Rheumatol. Sep 2019; 71(9): 1400-1412. PMID 31385462 Bae SC, Koh HK, Chang DK, et al.(2001) Reliability and validity of systemic lupus activity measure-revised (SLAM-R) for measuring clinical disease activity in systemic lupus erythematosus. Lupus. 2001; 10(6): 405-9. PMID 11434575 Gladman D, Ginzler E, Goldsmith C, et al.(1996) The development and initial validation of the Systemic Lupus International Collaborating Clinics/American College of Rheumatology damage index for systemic lupus erythematosus. 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