Guidelines for immunologic laboratory testing in the rheumatic diseases: Anti-Sm and anti-RNP antibody tests

Authors

  • Elizabeth Benito-Garcia,

    Corresponding author
    1. Brigham and Women's Hospital, Boston, Massachusetts
    • Division of Rheumatology, Immunology, and Allergy, Brigham & Women's Hospital, Section of Clinical Sciences, 221 Longwood Avenue, BLI 341 A-G, Boston, MA 02115===

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  • Peter H. Schur,

    1. Brigham and Women's Hospital, Boston, Massachusetts
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  • Robert Lahita,

    1. Jersey City Medical Center, Jersey City, New Jersey
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  • The American College of Rheumatology Ad Hoc Committee on Immunologic Testing Guidelines

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    • American College of Rheumatology Ad Hoc Committee on Immunologic Testing Guidelines members: Arthur F. Kavanaugh, MD (Chair): University of California at San Diego; Daniel H. Solomon, MD, MPH, Peter H. Schur, MD: Brigham and Women's Hospital, Boston, Massachusetts; John D. Reveille, MD: University of Texas Health Science Center, Houston, Texas; Yvonne R. S. Sherrer, MD: Center for Rheumatology, Immunology & Arthritis, Fort Lauderdale, Florida; Robert Lahita, MD, PhD: Jersey City Medical Center, Jersey City, New Jersey.


Introduction

This article on antibodies to Sm and RNP is part of a series on immunologic testing guidelines (1–5). The introduction to the series outlines the full methodology for obtaining data, grading the literature, combining the information from multiple sources, and for developing recommendations (1).

The Sm antigen was named after a patient, Smith, who had systemic lupus erythematosus (SLE). Antibodies to Sm were identified in 1966 by immunodiffusion (ID) to a phosphate-buffered saline extract of calf thymus (subsequently called extractable nuclear antigen [ENA]) and by hemagglutination (HA) (6). The antigen to which anti-Sm antibodies bind consists of a series of proteins: B, B', D, E, F, and G complexed with small nuclear RNAs: U1, U2, U4–6, and U5. These complexes of nuclear proteins and RNAs are called small nuclear ribonucleoprotein particles (snRNPs); they are important in the splicing of precursor messenger RNA (7), an integral step in the processing of RNA transcribed from DNA.

The anti-Sm immune reaction consists of multiple antibodies binding to multiple protein antigens (8); thus the anti-Sm antibody is better described as an antibody system.

Antibodies to the RNP antigen (originally called anti-Mo) were identified using ID in sera of patients with SLE by Mattioli and Reichlin in 1971 (9). The term RNP stems from the early observation that its antigenic activity could be destroyed by treatment with ribonuclease and trypsin (9); thus it was a ribonucleoprotein or “RNA protein” antigen (10), whereas the Sm antigen was resistant to such treatment (6). In 1971, Sharp et al (11) described a group of patients with a syndrome characterized by features of SLE, inflammatory muscle disease, and scleroderma, with an absence of renal disease and called it mixed connective tissue disease (MCTD). The sera of these patients contained antibodies to ENAs measured by passive hemagglutination. Subsequent studies showed that ENA contained both the Sm and RNP antigens (10–18) and that the patients described by Sharp et al were reacting with RNP (13). In 1979, Lerner and Steitz (8) demonstrated that both the Sm and RNP antigens were located on the U1 snRNP; therefore anti-RNP is sometimes referred to as anti–U1 RNP and anti–U1 snRNP antibodies.

The dogma regarding anti-Sm states it is found only in diseased individuals and is specific for SLE (19); furthermore, it is a criterion for the classification of SLE (18, 20, 21). The dogma regarding anti-RNP states it is found in rheumatic diseases such as SLE, Sjögren's syndrome (SS), rheumatoid arthritis (RA), polymyositis (PM), and systemic sclerosis (SSc) (22–24). High titers of anti-RNP are a requisite for the diagnosis of MCTD (13, 22, 23).

Rising titers of Sm antibody have been associated with disease flares of SLE (25–28), more active SLE (29), and less renal and more central nervous system disease in patients with SLE (18, 21, 30).

The purpose of this study was to carefully examine the literature, using established guidelines, to determine the sensitivity, specificity, and predictive values of anti-Sm and anti-RNP in the diagnosis of SLE and related diseases and their clinical associations, and to determine whether titers of these antibodies varied with any of these clinical features.

Methods

Selection and grading of the literature.

A literature review was performed for each test by Elizabeth Benito-Garcia, Peter H. Schur, and Robert Lahita. Searches were conducted using electronic databases Medline and Pubmed using the search terms “anti-RNP,” “RNP or ribonucleoprotein,” “anti-Sm or anti-Smith,” restricting the references to English-language articles. The electronic searches were supplemented by thorough hand-searching of the references found in primary articles, review articles, and rheumatology textbooks. A literature database was then assembled for each test and included articles published between January 1966 and December 2003. Review articles, editorials, individual case reports, case series with <10 patients, animal studies, and articles that did not report primary data were excluded from analysis. Articles that did not report complete data (e.g., those showing data only from “representative patients”) were also excluded (1).

To identify studies with the highest methodologic quality, articles in the literature database were critically reviewed according to criteria developed by the Evidenced-Based Medicine Working Group (31, 32): 1) Was complete data provided (e.g., were likelihood ratios [LRs] or the data to calculate LRs provided)? 2) Was there an independent blind comparison with a reference standard (e.g., were the American College of Rheumatology diagnostic criteria used; what measures of disease activity were used, etc)? 3) Did the patient sample include an appropriate spectrum of patients to whom the test would be applied in clinical practice? 4) Were the methods used to perform the test described and currently available? and 5) Did the results of the test being evaluated influence the decision to make a specific diagnosis (e.g., SLE, etc)? (1, 31).

An article satisfying all 5 criteria was considered a grade-A article; those satisfying 3 or 4 criteria were graded as B articles; those satisfying 2 criteria were graded as C articles; and those meeting 1 or none of the criteria were graded as D. To create the guidelines, only the best available literature would be considered (1); thus, for questions on which there were ≥10 grade-A articles, lesser quality articles were not used. For questions on which there were <10 grade-A articles, grade-B articles were also used (1). These methods have been employed previously (2, 4, 5).

Data abstraction.

Formal metaanalytic techniques were not used to combine the studies because of the heterogeneity noted among the various articles, including 1) different methods used to perform the same test, 2) different substrates used to perform similar methods, 3) dissimilar populations from which the patients were acquired, 4) various lengths of disease duration at the time of testing, and 5) the use of medications or other therapies that might affect the results of diagnostic testing.

The proportion of patients with and without particular diseases who had positive or negative results for a given test was abstracted from the articles, and 2 × 2 contingency tables were created (Table 1) (1). From these tables, sensitivity, specificity, and positive and negative LRs were calculated (33). Sensitivity and specificity are interdependent, so that for a given test, an increase in sensitivity is accompanied by a decrease in specificity, and vice versa. This interdependence is depicted graphically using a summary receiver operating curve (SROC), which plots sensitivity on the Y-axis (true positive rate [TPR]), and 1 – specificity (false positive rate [FPR]) on the X-axis. The area under the SROC (AUC) gives an estimate of the accuracy of a test. An ideal test would have a cutoff value that perfectly discriminated those with disease, and would have an AUC of 1.00 (33, 34). We plotted these curves with Meta-test version 0.9 software (35) to provide a visual sense of the accuracy of the test. On these plots, the upper left corner indicates perfect discrimination between patients with and without the disease (FPR = 0 and TPR = 1) and the diagonal line, where FPR equals TPR, indicates discrimination no better than chance; the closer the points lie to the upper left corner, the more accurate the test. For the calculation of the SROC curve, when the 2 × 2 table contained a 0 cell, 0.5 was added to all counts in the table to avoid having an undefined SROC (36).

Table 1. Sensitivity, specificity, and positive and negative likelihood ratio calculations
Test OutcomeDisease presentDisease absent
  1. equation image
    equation image
    equation image
    equation image
PositiveTrue positive (TP)False positive
NegativeFalse negativeTrue negative (TN)
Totaln1n0

The LR represents a measure of the odds of having a disease relative to the prior probability of the disease and is independent of the disease prevalence (1, 33).

Data were presented for each article, but to provide a useful guide to clinicians, weighted averages for sensitivity and specificity were calculated according to a random-effects model of pooling (37), which weights study rates by the inverse of their variance plus the among-study variance for that measure. For comparison, we also performed pooling using a fixed-effects model (37). Only the random-effects calculations are reported, which provide wider confidence intervals than the fixed effects.

A test was considered to be “very useful” for a given disease if the majority of positive LRs were >5 or negative LRs were <0.2. A test was considered “useful” if the majority of positive LRs were >2 and ≤5 or negative LRs were >0.2 and ≤0.5. A test was considered “not useful” if the majority of positive LRs were ≤2 or the negative LRs were >0.5 (1, 2).

Where data were available, separate consideration was given to the use of the test in diagnosis, prognosis, and longitudinal followup, in SLE as well as other conditions (1).

Methods for detection of anti-Sm and anti-RNP.

The methods for the detection of anti-Sm and anti-RNP vary in different laboratories and affect the sensitivity, specificity, and predictive values. The methods used include immunodiffusion, radioimmunoassay, counterimmunoelectrophoresis (CIE), hemagglutination, or enzyme-linked immonosorbent assay (ELISA), and Western blotting. In our review, the method was always stated in the results section, because one method may not be entirely comparable to another method (38–41); furthermore, none of these methods have been well standardized between laboratories.

Results

Anti-Sm and Anti-RNP for diagnosis.

A total of 815 articles regarding anti-Sm and anti-RNP were identified. Of these, 17 grade-A studies assessed the utility of anti-Sm antibodies in the diagnosis of SLE (n = 1,569) versus healthy control subjects (n = 978) (Table 2); 15 grade-A studies assessed the utility of anti-Sm in the diagnosis of SLE (n = 1,523) versus patients with other rheumatic diseases (n = 2,843) (Table 3). Four grade-A studies assessed the utility of anti-Sm antibodies in the diagnosis of MCTD (n = 80) versus other rheumatic diseases (n = 348); 5 assessed its utility in the diagnosis of RA (n = 353) versus other rheumatic diseases (n = 1,159); and 5 assessed its utility in the diagnosis of SSc (n = 195) versus other rheumatic diseases (n = 1,712) (Table 4).

Table 2. Grade-A articles and population statistics for anti-Sm antibodies in diagnosis: SLE versus healthy controls*
RefTechniqueSLE patients (TP/FN)Healthy controls (FP/TN)Sensitivity (95% CI)Specificity (95% CI)+LR−LR
  • *

    SLE = systemic lupus erythematosus; TP = true positive; FN = false negative; FP = false positive; TN = true negative; 95% CI = 95% confidence interval; LR = likelihood ratio; CIE = counterimmunoelectrophoresis; ELISA = enzyme-linked immunosorbent assay; HA = hemagglutination; ID = immunodiffusion; REM = random-effects model.

50CIE16/1370/450.10 (0.06–0.17)1.00 (0.92–1.00)0.90
43CIE27/1640/390.14 (0.10–0.20)1.00 (0.91–1.00)0.86
66ELISA16/480/400.25 (0.15–0.38)1.00 (0.91–1.00)0.75
45ELISA15/370/300.29 (0.18–0.43)1.00 (0.88–1.00)0.71
67ELISA21/421/580.33 (0.22–0.46)0.98 (0.90–1.00)16.50.68
44ELISA14/262/980.35 (0.21–0.52)0.98 (0.92–1.00)17.50.66
59ELISA27/400/330.40 (0.29–0.53)1.00 (0.89–1.00)0.60
50ELISA62/910/450.41 (0.33–0.49)1.00 (0.92–1.00)0.59
68ELISA11/1005/680.10 (0.05–0.17)0.93 (0.84–0.97)1.430.97
46HA11/610/500.15 (0.08–0.26)1.00 (0.93–1.00)0.85
69HA14/360/900.28 (0.17–0.43)1.00 (0.96–1.00)0.72
70HA14/360/250.28 (0.17–0.43)1.00 (0.86–1.00)0.72
47HA38/800/1120.32 (0.24–0.41)1.00 (0.97–1.00)0.68
71ID2/280/960.07 (0.01–0.23)1.00 (0.96–1.00)0.93
67ID11/520/590.17 (0.09–0.29)1.00 (0.94–1.00)0.83
51Radioligand assays for detecting Sm-B72/1400/520.34 (0.28–0.41)1.00 (0.93–1.00)0.66
72Western blots19/610/300.24 (0.15–0.35)1.00 (0.88–1.00)0.76
 Total, range1,5699780.07–0.410.93–1.00  
 REM pooled  0.24 (0.19–0.30)0.98 (0.96–0.99)  
Table 3. Grade-A articles and population statistics for anti-Sm antibodies in diagnosis: SLE versus non-SLE disease controls*
RefTechniqueSLE, nDisease controls, nTP/FNFP/TNSensitivity (95% CI)Specificity (95% CI)+LR−LR
  • *

    SLE = systemic lupus erythematosus; TP = true positive; FN = false negative; FP = false positive; TN = true negative; 95% CI = 95% confidence interval; LR = likelihood ratio; CIE = counterimmunoelectrophoresis; RA = rheumatoid arthritis; SSc = systemic sclerosis; PM = polymyositis; DM = dermatomyositis; SS = Sjögren's syndrome; OCTD = overlap connective tissue disease; MCTD = mixed connective tissue disease; UCTD = undifferentiated connective tissue disease; CTD = connective tissue disease; BS = Behçet's syndrome; DLE = discoid lupus erythematosus; JRA = juvenile rheumatoid arthritis; SSA = seronegative spondylarthropathies; CREST = calcinosis, Raynaud's phenomenon, esophageal dysmotility, sclerodactyly, telangiectasias; ELISA = enzyme-linked immunosorbent assay; OA = osteoarthritis; FM = fibromyalgaia; HA = hemagglutination; ID = immunodiffusion; REM = random-effects model.

73CIE102827 (595 RA, 59 SSc, 38 Raynaud's, 30 PM/DM, 61 overlap, 10 SS, 34 systemic and cutaneous vasculitides)11/910/8270.11 (0.06–0.19)1.00 (1.00–1.00)0.89
43CIE191368 (44 OCTD/MCTD, 111 RA, 18 SS, 66 SSc, 50 DM/PM, 14 UCTD, 14 other CTD [BS, DLE], 35 others [JRA, SSA], 16 systemic vasculitides)27/1646/3620.14 (0.10–0.20)0.98 (0.96–0.99)70.88
74CIE3054 (24 MCTD, 17 RA, 2Scl, 6 SS, 5 CREST)16/141/540.53 (0.35–0.71)0.98 (0.89–1.00)26.50.48
42CIE8657 (3 cutaneous SLE, 12 drug-induced SLE, 17 RA, 3 JRA, 4 MCTD, 2 Raynaud's, 2 SSc, 6 misc. rheumatic disease, 8 UCTD)47/3924/330.55 (0.44–0.65)0.58 (0.44–0.71)1.310.78
68ELISA11173 (10 SS, 10 RA, 13 MCTD, 11 limited/SSc, 7 PM/DM, 22 UCTD)11/1005/680.10 (0.05–0.17)0.93 (0.84–0.97)1.430.97
45ELISA52129 (53 RA, 20 SS, 30 SSc, 7 PM, 12 polymyalgia rheumatica, 7 OA)15/370/300.29 (0.18–0.43)1.00 (0.88–1.00)0.71
67ELISA6398 (54 RA, 11 PM, 24 SSc, 9 drug-induced SLE)21/4219/790.33 (0.22–0.46)0.81 (0.71–0.88)1.740.83
23ELISA127132 (18 RA, 7 JRA, 6 MCTD, 13 Raynaud's, 5 SSc, 1 subacute cutaneous SLE, 1 DM, 1 PM, 3 SS, 3 probable CTD, 3 nonautoimmune rheumatic disease, 53 nonrheumatic disease, 2 OCTD, 1 anti-phospholipid antibody syndrome, 8 FM, 5 OA, 1 spinal stenosis, 1 rotator cuff)43/8416/1160.34 (0.26–0.43)0.88 (0.81–0.93)2.830.75
44ELISA4058 (25 RA, 19 MCTD, 14 SSc)14/268/500.35 (0.21–0.52)0.86 (0.74–0.93)2.50.76
59ELISA6774 (31 RA, 43 SS)27/407/670.40 (0.29–0.53)0.91 (0.81–0.96)4.440.66
19ELISA393638 (nonspecific arthritis, recurrent miscarriages, dilated cardiomyopathy, reactive arthritis, OCTD with Raynaud's, RA, subacute bacterial endocarditis, SSc)157/2367/6310.40 (0.35–0.45)0.99 (0.98–1.00)400.61
70HA50133 (30 RA, 28 SS, 27 SSc, 20 DM, 16 DLE, 12 MCTD)14/361/1320.28 (0.17–0.43)0.99 (0.95–1.00)280.73
47HA118148 (57 RA, 7 DLE, 35 drug-induced SLE, 8 MCTD, 9 DM/PM, 32 CREST)38/800/1480.32 (0.24–0.41)1.00 (0.98–1.00)0.68
67ID6398 (54 RA, 11 PM, 24 SSc, 9 drug-induced SLE)11/520/980.17 (0.09–0.29)1.00 (0.96–1.00)0.83
74ID3054 (17 RA, 2 SSc, 6 SS, 5 CREST)14/160/540.47 (0.29–0.65)1.00 (0.88–1.00)0.53
   Total, range1,5232,8430.10–0.550.58–1.00  
   REM pooled  0.30 (0.23–0.38)0.96 (0.92–0.98)  
Table 4. Grade-A articles and population statistics for anti-Sm antibodies in diagnosis: other rheumatic diseases vs. SLE and other disease controls*
RefTechniquePatients (n)Controls (n)TP/FNFP/TNSensitivity (95% CI)Specificity (95% CI)+LR−LR
  • *

    For acronym and abbreviation definitions, see Table 3.

73CIEDM/PM (30)984 (102 SLE, 59 SSc, 38 Raynaud's, 595 RA, 61 OCTD, 10 SS, 34 vasculitides, 85 OA and spondytarthropathies)0/3011/9730.00 (0.00–0.12)0.99 (0.98–0.99)01.01
43CIEDM/PM (50)318 (44 OCTD/MCTD, 18 SS, 66 SSc, 14 UCTD, 49 other CTD [Behçet, DLE, JRA, SSA], 111 RA, 16 systemic vasculitides)0/506/3120.00 (0.00–0.07)0.98 (0.96–0.99)01.02
42CIEDrug-induced SLE (12)131 (86 SLE, 3 cutaneous SLE, 17 RA, 3 JRA, 4 MCTD, 2 Raynaud's, 2 SSc, 6 misc, rheumatic disease, 8 UCTD)5/766/650.42 (0.17–0.71)0.50 (0.41–0.58)0.841.16
47HADrug-induced SLE (35)231 (118 SLE, 7 DLE, 57 RA, 8 MCTD, 9 DM/PM, 32 SSc)0/3538/1930.00 (0.00–0.10)0.84 (0.78–0.88)01.19
68ELISAMCTD (13)149 (111 SLE, 10 SS, 10 RA, 11 SSc, 7 PM/DM)1/1210/1390.08 (0.00–0.38)0.93 (0.88–0.97)1.140.99
44ELISAMCTD (19)79 (40 SLE, 25 RA, 14 SSc)5/1417/620.26 (0.10–0.51)0.78 (0.68–0.87)1.180.95
74IDMCTD (24)60 (30 SLE, 17 RA, 2 SSc, 6 SS, 5 CREST)0/2414/460.00 (0.00–0.14)0.77 (0.64–0.86)01.30
74CIEMCTD (24)60 (30 SLE, 17 RA, 2 SSc, 6 SS, 5 CREST)0/2417/430.00 (0.00–0.14)0.72 (0.58–0.82)03.57
46HARA (169)115 (72 SLE, 2 MCTD, 7 DM/PM, 16 SSc, 9 SS, 9 UCTD)1/16812/1030.01 (0.00–0.04)0.90 (0.82–0.94)0.11.1
42CIERA (17)126 (86 SLE, 3 cutaneous SLE, 12 drug-induced SLE, 3 JRA, 4 MCTD, 2 Raynaud's, 2 SSc, 6 misc. rheumatic disease, 8 UCTD)8/963/630.47 (0.24–0.71)0.50 (0.41–0.59)0.941.06
44ELISARA (25)73 (40 SLE, 14 SSc, 19 MCTD)0/2522/510.00 (0.00–0.14)0.70 (0.58–0.80)03.30
59ELISARA (31)110 (67 SLE, 43 SS)2/2932/780.06 (0.01–0.23)0.71 (0.61–0.79)0.211.32
67ELISARA (54)107 (63 SLE, 11 PM, 24 SSc, 9 drug-induced SLE)12/4228/790.22 (0.13–0.36)0.74 (0.64–0.82)0.851.05
47HARA (57)209 (118 SLE, 7 DLE, 35 drug-induced SLE, 8 MCTD, 9 DM/PM, 32 SSc)0/5738/1710.00 (0.00–0.06)0.82 (0.76–0.87)01.22
73CIERA (595)419 (102 SLE, 59 SSc, 38 Raynaud's, 30 DM/PM, 61 OCTD, 10 SS, 34 vasculitides, 85 OA and spondyarthropathies)0/59511/4080.00 (0.00–0.01)0.97 (0.95–0.99)01.03
44ELISASSc (14)84 (40 SLE, L25 RA, 19 MCTD)3/1119/650.21 (0.06–0.51)0.77 (0.67–0.85)0.911.03
67ELISASSc (24)137 (63 SLE, 54 RA, 11PM, 9 drug-induced SLE)6/1834/1030.25 (0.11–0.47)0.75 (0.67–0.82)1.001.00
47HASSc (32)234 (118 SLE, 7 discoid SLE, 35 drug-induced SLE, 8 MCTD, 9 DM/PM, 57 RA)0/3238/1960.00 (0.00–0.11)0.84 (0.78–0.88)01.19
73CIESSc (59)955 (102 SLE, 595 RA, 38 Raynaud's, 30 DM/PM, 61 OCTD, 10 SS, 34 vasculitides, 85 OA and spondytarthropathies)0/5911/9440.00 (0.00–0.06)0.99 (0.98–0.99)01.01
43CIESSc (66)302 (44 OCTD/MCTD, 18 SS, 50 DM/PM, 14 UCTD, 49 other CTD [Behçet, DLE, JRA, SSA], 111 RA, 16 systemic vasculitides)0/666/2960.00 (0.00–0.05)0.84 (0.96–0.99)01.19
59ELISASS (43)98 (67 SLE, 31 RA)5/3829/690.12 (0.04–0.26)0.70 (0.60–0.79)0.401.14

Of the 815 articles identified, 11 grade-A studies assessed the utility of anti-RNP in the diagnosis of SLE (n = 1,030) versus healthy controls (n = 662) (Table 5) and 15 grade-A studies assessed the utility of anti-RNP in the diagnosis of SLE (n = 1198) versus other rheumatic diseases (n = 2,287) (Table 6). Five grade-A studies assessed the utility of anti-RNP antibodies in the diagnosis of MCTD (n = 91) versus other rheumatic diseases (n = 720); 5 grade-A studies assessed its utility in the diagnosis of RA (n = 807) versus other rheumatic diseases (n = 1,168); and 5 grade-A studies assessed its utility in the diagnosis of SSc (n = 364) versus other rheumatic diseases (n = 1,058) (Table 7).

Table 5. Grade-A articles and population statistics for anti-RNP antibodies in diagnosis: SLE versus healthy controls*
RefTechniqueSLE patients TP/FNHealthy controls FP/TNSensitivity (95% CI)Specificity (95% CI)+LR−LR
  • *

    DID = Double immunodiffusion. For other abbreviations, see Table 3.

46HA2/700/500.03 (0.00–0.11)1.00 (0.93–1.00)0.97
71ID3/270/960.10 (0.03–0.28)1.00 (0.96–1.00)0.90
47HA17/1010/1120.14 (0.09–0.22)1.00 (0.97–1.00)0.86
43CIE38/1530/390.20 (0.15–0.26)1.00 (0.91–1.00)0.80
55DID28/890/400.24 (0.17–0.33)1.00 (0.91–1.00)0.76
70HA13/370/900.26 (0.15–0.41)1.00 (0.96–1.00)0.74
69HA13/370/250.26 (0.15–0.41)1.00 (0.86–1.00)0.74
67ID19/440/590.30 (0.20–0.43)1.00 (0.94–1.00)0.70
66ELISA23/410/400.36 (0.25–0.49)1.00 (0.91–1.00)0.64
51Radioligand assay94/1181/510.44 (0.38–0.51)0.98 (0.88–1.00)220.57
67ELISA29/340/590.46 (0.34–0.59)1.00 (0.94–1.00)0.54
 Total (range)1,0306620.03–0.460.96–1.00  
 REM pooled  0.25 (0.18–0.33)0.99 (0.98–1.00)  
Table 6. Grade-A articles and population statistics for anti-RNP antibodies in diagnosis: SLE versus disease controls*
RefTechniqueSLE, nControls, nTP/FNFP/TNSensitivity (95% CI)Specificity (95% CI)+LR−LR
  • *

    SLE = systemic lupus erythematosus; TP = true positive; FN = false negative; FP = false positive; TN = true negative; 95% CI = 95% confidence interval; LR = likelihood ratio; CIE = counterimmunoelectrophoresis; RA = rheumatoid arthritis; SSc = systemic sclerosis; PM = polymyositis; DM = dermatomyositis; SS = Sjögren's syndrome; ID = immunodiffusion; MCTD = mixed connective tissue disease; HA = hemagglutination; DLE = discoid lupus erythematosus; CREST = calcinosis, Raynaud's phenomenon, esophageal dysmotility, sclerodactyly, telangiectasias; ELISA = enzyme-linked immunosorbent assay; OCTD = overlap connective tissue disease; UCTD = undifferentiated connective tissue disease; CTD = connective tissue disease; BS = Behçet's syndrome; JCA = juvenile chronic arthritis; SSA = seronegative spondylarthropathies; JRA = juvenile rheumatoid arthritis; FM = fibromyalgia; OA = osteoarthritis; REM = random-effects model.

73CIE102827 (595 RA, 59 SSc, 38 Raynaud's 30 PM/DM, 61 overlap, 10 SS, 34 systemic and cutaneous vasculitides)8/949/8180.08 (0.04–0.15)0.99 (0.98–0.99)80.93
71ID3044 (6 MCTD, 18 SSc, 20 RA)3/276/380.10 (0.03–0.28)0.86 (0.72–0.94)0.711.05
47HA118148 (57 RA, 7 DLE, 35 drug-induced SLE, 8 MCTD, 9 DM/PM, 32 CREST)17/10111/1370.14 (0.09–0.22)0.93 (0.87–0.96)20.92
68ELISA11151 (10 SS, 10 RA, 13 MCTD, 11 SSc, 7 PM/DM)19/9214/370.17 (0.11–0.26)0.73 (0.58–0.84)0.631.14
43CIE191368 (44 OCTD/MCTD, 111 RA, 18 SS, 66 SSc, 50 DM/PM, 14 UCTD, 14 other CTD [BS, DLE], 35 others [JCA, SSA], 16 systemic vasculitides)38/15320/3480.20 (0.15–0.26)0.95 (0.92–0.97)4.00.84
55ID117241 (223 SSc, 18 MCTD)28/8936/2050.24 (0.17–0.33)0.85 (0.80–0.89)1.60.89
70HA50133 (30 RA, 28 SS, 27 SSc, 20 DM, 15 DLE, 12 MCTD)13/3726/1070.26 (0.15–0.41)0.80 (0.73–0.87)1.300.93
72Western blot803023/5710/200.29 (0.19–0.40)0.67 (0.47–0.82)0.811.10
67ID6398 (54 RA, 11 PM, 24 SSc, 9 drug-induced SLE)19/442/960.30 (0.20–0.43)0.98 (0.92–1.00)150.71
74ID3054 (17 RA, 2 SSc, 6 SS, 5 CREST, 24 MCTD)11/1917/370.37 (0.21–0.56)0.69 (0.54–0.80)1.190.91
23ELISA127132 (18 RA, 7 JRA, 6 MCTD, 13 Raynaud's, 5 SSc, 1 subacute cutaneous SLE, 1 DM, 1 PM, 3 SS, 3 probable CTD, 3 nonautoimmune rheumatic disease, 53 nonrheurmatic disease, 2 overlap, 1 antiphospholipid antibody syndrome, 15 other rheumatic disease [8 FM, 5 OA, 1 spinal stenosis, 1 rotator cuff])50/7789/430.39 (0.31–0.48)0.33 (0.25–0.41)0.581.85
74CIE3054 (17 RA, 2 SSc, 6 SS, 5 CREST, 24 MCTD)12/1819/350.40 (0.23–0.59)0.65 (0.51–0.77)1.140.92
67ELISA6398 (54 RA, 11 PM, 24 SSc, 9 drug-induced SLE)29/3414/840.46 (0.34–0.59)0.86 (0.77–0.92)3.290.63
42CIE8657 (3 cutaneous SLE, 12 drug-induced SLE, 17 RA, 3 JRA, 4 MCTD, 2 Raynaud's, 2 SSc, 6 misc. rheumatic disease, 8 undifferentiated CTD)59/2743/140.69 (0.58–0.78)0.25 (0.15–0.38)0.921.24
   Total range1,19823350.08–0.690.25–0.99  
   REM pooled  0.27 (0.20–0.37)0.82 (0.58–0.91)  
Table 7. Grade-A articles and population statistic for anti-RNP antibodies in diagnosis: other rheumatic diseases versus disease controls*
RefTechniquePatients (n)Controls, nTP/FNFP/TNSensitivitySpecificity+LR−LR
  • *

    For acronym and abbreviation definitions, see Table 6.

70HAMCTD (12)171 (50 SLE, 30 RA, 28 SS, 27 SSc, 20 DM, 16 DLE)12/027/1441.00 (0.74–1.00)0.84 (0.78–0.89)6.250
68ELISAMCTD (13)149 (111 SLE, 10 SS, 10 RA, 11 SSc, 7 PM/DM)13/020/1291.00 (0.75–1.00)0.87 (0.80–0.91)7.700
55IDMCTD (18)340 (117 SLE, 223 SSc)18/046/2941.00 (0.81–1.00)0.86 (0.82–0.90)7.140
74CIEMCTD (24)30 (17 RA, 2 SSc, 6 SS, 5 CREST)17/72/280.71 (0.49–0.86)0.93 (0.77–0.99)10.10.31
74IDMCTD (24)30 (17 RA, 2 SSc, 6 SS, 5 CREST)17/70/300.71 (0.49–0.86)1.00 (0.88–1.00)0.29
43CIERA (111)448 (191 SLE, 44 OCTD/MCTD, 50 DM/PM, 18 SS, 66 SSc, 14 UCTD, 14 other CTD [BS, DLE], 35 others [JCA, SSA], 16 systemic vasculitides)2/10956/3920.02 (0.00–0.07)0.88 (0.84–0.90)0.171.11
73CIERA (595)334 (102 SLE, 59 SSc, 38 Raynaud's 30 PM/DM, 61 overlap, 10 SS, 34 systemic and cutaneous vasculitides)0/59513/3210.00 (0.00–0.01)0.96 (0.94–0.99)0.001.04
42CIERA (17)126 (86 SLE, 3 cutaneous SLE, 12 drug-induced SLE, 3 JRA, 4 MCTD, 2 Raynaud's, 2 SSc, 6 misc. rheumatic disease, 8 undifferentiated CTD)13/489/370.76 (0.50–0.92)0.29 (0.22–0.38)1.070.83
70HARA (30)153 (50 SLE, 28 SS, 20 DM, 27 SSc, 16 DLE, 12 MCTD)3/2736/1170.10 (0.03–0.28)0.76 (0.69–0.83)0.421.18
67ELISARA (54)107 (63 SLE, 11 PM, 24 SSc, 9 drug-induced SLE)4/5039/680.07 (0.02–0.19)0.64 (0.54–0.72)0.191.45
43CIESci (66)493 (191 SLE, 44 OCTD/MCTD, 111 RA, 18 SS, 50 DM/PM, 14 UCTD, 14 other CTD [BS, DLE], 35 others [JCA, SSA], 16 systemic vasculitides)3/6355/4380.05 (0.01–0.14)0.89 (0.86–0.91)0.451.07
55IDSci (223)135 (117 SLE, 18 MCTD)18/20546/890.08 (0.05–0.13)0.66 (0.57–0.74)0.241.39
67ELISASci (24)137 (63 SLE, 54 RA, 11 PM, 9 drug-induced SLE)8/1635/1020.33 (0.17–0.55)0.74 (0.66–0.81)1.270.91
67IDSci (24)137 (63 SLE, 54 RA, 11 PM, 9 drug-induced SLE)2/229/1280.08 (0.01–0.28)0.93 (0.88–0.97)1.140.99
70HASci (27)156 (50 SLE, 30 RA, 28 SS, 20 DM, 16 DLE, 12 MCTD)6/2133/1230.22 (0.09–0.43)0.79 (0.71–0.85)1.050.99
43CIESS (18)541 (191 SLE, 44 OCTD/MCTD, 111 RA, 66 SSc, 50 DM/PM, 14 UCTD, 14 other CTD [BS, DLE], 35 others [JCA, SSA], 16 systemic vasculitides)1/1757/4840.06 (0.00–0.29)0.89 (0.86–0.92)0.551.06
68ELISASS (10)152 (111 SLE, 10 RA, 13 MCTD, 11 SSc, 7 PM/DM)1/932/1200.10 (0.01–0.46)0.79 (0.71–0.85)0.481.14
70HASS (28)155 (50 SLE, 30 RA, 20 DM, 27 SSc, 16 DLE, 12 MCTD)1/2738/1170.04 (0.00–0.20)0.75 (0.68–0.82)0.161.28
43CIEOCTD/MCTD (44)515 (191 SLE, 111 RA, 18 SS, 66 SSC, 50 DM/PM, 14 UCTD, 14 other CTD [BS, DLE], 35 others [JCA, SSA], 16 systemic vasculitides)12/3246/4690.27 (0.15–0.43)0.91 (0.88–0.93)3.000.80
73CIEOCTD (61)868 (595 RA, 102 SLE, 59 SSc, 38 Raynaud's 30 PM/DM, 10 SS, 34 systemic and cataneous vasculitides)5/569/8590.08 (0.03–0.19)0.99 (0.98–0.99)8.000.93
47HACREST (35)148 (118 SLE, 57 RA, 7 DLE, 35 drug-induced SLE, 8 MCTD, 9 DM/PM)3/3225/2090.09 (0.02–0.24)0.89 (0.84–0.93)0.821.02
43CIEDM-PM (50)509 (191 SLE, 44 OCTD/MCTD, 111 RA, 18 SS, 66 SSc, 14 UCTD, 14 other CTD [BS, DLE], 35 others [JCA, SSA], 16 systemic vasculitides)1/4957/4520.02 (0.00–0.12)0.89 (0.86–0.91)0.181.01
67ELISAPM (11)150 (63 SLE, 54 RA, 24 SSc, 9 drug-induced SLE)1/1042/1080.09 (0.01–0.43)0.72 (0.64–0.79)0.130.91

Most of the studies included in this analysis determined anti-Sm and anti-RNP antibodies directly. Of the 27 grade-A articles in the tables, 15 also performed antinuclear antibody testing and only 4 of these performed anti-Sm and anti-RNP as part of cascade testing (23, 42–44), having only determined anti-Sm and anti-RNP in patients with a positive antinuclear antibody test result.

Anti-Sm for diagnosis of SLE.

Testing for anti-Sm antibody may be useful for the diagnosis of SLE. When SLE patients were compared with healthy controls (Table 2), the sensitivity ranged from 7% to 41% and the specificity ranged from 93% to 100%; the weighted mean for sensitivity was 24% and for specificity was 98%. When SLE was compared with other rheumatic diseases (Table 3), the sensitivity ranged from 10% to 55% and the specificity ranged from 58% to 100%, with a weighted mean for sensitivity of 30% and for specificity of 96%.

The SROC for Table 3 (Figure 1) demonstrates heterogeneity in sensitivity and specificity. We sought causes for this observation and for the outlier whose sensitivity was 55% and specificity was 58%. One explanation for the heterogeneity relates to the technique used to determine the anti-Sm antibodies. The dogma is that gel-based methods (ID and CIE) for determining anti-Sm are more specific than ELISA. The SROC curve (Figure 1) shows ELISAs as white ellipses and gel-based methods as grey ellipses and suggests higher specificities for the gel-based methods. The paucity of studies, however, makes it difficult to determine valid statistical differences. Although a definite cause for the heterogeneity in Table 4 and Figure 1 was not determined, possible explanations include random chance, manufacturer and laboratory procedures used to detect anti-Sm, or population differences used in the different studies, such as the different diseases used for the control groups. The median positive LR for anti-Sm antibodies in the diagnosis of SLE versus healthy controls was infinity, and versus other rheumatic disease controls it was 26.5. The elevated specificities (close to 100%) and very high positive LR (Table 2), occur because lupus patients were compared with healthy controls. In the clinical setting, the clinician will rarely compare SLE patients with healthy subjects; therefore, only the results obtained from the studies that compared SLE patients with other disease controls were used for the guidelines.

Figure 1.

Summary receiver operating curve for anti-Sm antibodies in diagnosis: systemic lupus erythematosus (SLE) versus non-SLE disease control subjects. Each study is represented by an ellipse (numbers correspond to references). The area of the ellipse shows the relative size of each study. Ellipses are elongated in proportion to the relative contribution within each study of subjects with SLE (vertical elongation) versus disease controls (horizontal elongation). The ellipses in white depict enzyme-linked immunosorbent assays and those in black depict gel-based methods (immunodiffusion and counterimmunoelectrophoresis) for determining anti-Sm antibodies.

Anti-Sm had a low sensitivity but a very high specificity for diagnosing SLE, missing many patients who have SLE (many false negative results) but rarely identifying patients as having SLE when they do not (i.e., few false positive results) (Table 3). A positive test result will likely have a large impact on the pretest probability; substantially increasing the posttest probability of the diagnosis of SLE; thus, in the setting of some clinical suspicion of SLE, a positive anti-Sm strongly supports the diagnosis, but a negative result cannot exclude it. These results were valid for comparisons between SLE and no disease and for comparisons between SLE and other diseases.

Anti-Sm for diagnosis of other rheumatic diseases.

Patients often present to the rheumatologist with rheumatic complaints, and a differential diagnosis must often be made between different rheumatic diseases; therefore, we present data only in which rheumatic diseases were compared with other disease controls (Table 4). There were not enough grade-A studies to emanate guidelines. The 2 dermatomyositis/polymyositis (DM/PM), the 2 drug-induced SLE, the 4 MCTD, the 7 RA, the 5 SSc, and the 1 SS grade-A studies, however, showed a weighted mean sensitivity and median positive LR of 0 for each disease; thus, anti-Sm was not useful in the diagnosis of other rheumatic diseases, namely DM/PM, drug-induced SLE, MCTD, RA, SSc, and SS.

Anti-RNP for diagnosis of SLE.

Anti-RNP antibody testing is thought to help confirm the diagnosis of SLE. When SLE patients were compared with healthy controls (Table 5), the sensitivity of anti-RNP for the diagnosis of SLE ranged from 3% to 46% and the specificity ranged from 98% to 100%, with a weighted mean of 25% for sensitivity and 99% for specificity. When SLE was compared with other disease controls (Table 6 and Figure 2), the anti-RNP sensitivity for the diagnosis of SLE ranged from 8% to 69% with a weighted average of 27% and the specificity ranged from 25% to 99% with a weighted average of 82%. The median positive LR for anti-RNP antibodies in the diagnosis of SLE was infinity when healthy controls were used, but 1.2 when other rheumatic disease controls were used. The positive LR of 1.2 indicates that a positive test result will have a low clinical effect on the pretest probability; consequently, a positive test result will not have a significant effect on the posttest probability of diagnosing SLE, when compared with disease controls.

Figure 2.

Summary receiver operating curve for the utility of anti-RNP antibodies in diagnosis of systemic lupus erythematosus (SLE) versus disease controls. Each study is represented by an ellipse (numbers correspond to references). The area of the ellipse shows the relative size of each study. Ellipses are elongated in proportion to the relative contribution within each study of subjects with SLE (vertical elongation) versus disease controls (horizontal elongation).

Anti-RNP had a very low sensitivity and a moderate specificity for diagnosing SLE, missing many patients with SLE (many false negative results) and sometimes identifying patients as having SLE when they do not (i.e., some false positive results). The corresponding SROC (Figure 2) shows that besides the heterogeneity among the studies, for the same reasons referred to for the anti-Sm antibodies, many points tend to scatter along the diagonal line; thus, in the setting of some clinical suspicion of SLE, a positive anti-RNP is useless in supporting the diagnosis of SLE.

Anti-RNP for diagnosis of MCTD.

Only 5 grade-A studies assessed the utility for anti-RNP antibodies in the diagnosis of MCTD (Table 7). In these studies, the sensitivity ranged from 71% to 100% and the specificity ranged from 84% to 100%. The median positive LR was 7.14 when disease controls were used. Although not shown in the table, the median positive LR was 100 when healthy controls were used, indicating that a negative anti-RNP antibody test result will not miss many patients who have MCTD (few false negative results) and will infrequently identify patients as having MCTD when they do not (i.e., few false positive results). Furthermore, a positive test result will likely have a large impact on the pretest probability, substantially increasing the posttest probability of the diagnosis of MCTD; thus, in the setting of some clinical suspicion of MCTD, a positive anti-RNP result strongly supports the diagnosis of MCTD, and a negative result will usually exclude it when the differential diagnosis must be made between MCTD and other diseases. High-quality studies are warranted to confirm these findings. An anti-RNP antibody test should be ordered to help make the diagnosis of MCTD.

Anti-RNP for diagnosis of RA, and SSc, other rheumatic diseases.

Only 5 studies were graded A for assessment of population statistics among patients with RA and SSc (Table 7). The weighted mean for sensitivity was 6% (range 0–76%) in RA and 13% (range 5–33%) in SSc; the weighted mean for specificity was 77% (range 29–96%) in RA and 82% (range 66–93%) in SSc. The median positive LR for RA was 1.1 and for SSc was 0.99. Therefore, it appears that anti-RNP antibody testing is of no utility in the diagnosis of RA and SSc; however, guidelines for the utility of anti-RNP in these diseases were not developed because of sparse data. Only 3 grade-A articles were available to evaluate the utility of anti-RNP antibodies in the diagnosis of SS; 1 for CREST (calcinosis, Raynaud's phenomenon, esophageal dysmotility, sclerodactyly, telangiectasias) syndrome, and 2 for polymyositis; therefore, we did not attempt to pool the data.

Recommendations for the use of Anti-Sm and anti-RNP antibodies in the diagnosis of rheumatic diseases.

Anti-Sm antibodies are very useful for confirming the diagnosis of SLE: A positive test result strongly supports the diagnosis, although a negative test result cannot exclude it. Therefore, it is highly recommended that anti-Sm antibody test be ordered to aid in the diagnosis of SLE, whether the differential diagnosis is to be made versus normal or other rheumatic diseases. Anti-Sm is not useful in the diagnosis of other rheumatic diseases, namely DM/PM, drug-induced SLE, MCTD, RA, SSc, and SS. Anti-RNP antibodies may be very useful for the diagnosis of MCTD and should be ordered to aid in the diagnosis of MCTD. From the reviewed literature, it appears that there is no benefit in ordering this test to help diagnose other rheumatic diseases, including SLE.

Anti-Sm and Anti-RNP for prognosis determination.

From the literature search, 8 grade-A studies assessed anti-Sm and 7 grade-A studies assessed anti-RNP in patients with lupus nephritis versus patients with SLE and no nephritis (Tables 8 and 9).

Table 8. Grade-A articles and population statistics for anti-Sm antibodies in prognosis: lupus nephritis versus no lupus nephritis*
RefTechniqueCases (lupus nephritis)Controls (no lupus nephritis)TP/FNFP/TNSensitivity (95% CI)Specificity (95% CI)+LR−LR
  • *

    For acronym and abbreviation definitions, see Table 6.

  • Lupus nephritis was defined by 1) a renal biopsy sample demonstrating World Health Organization class II–V histopathology; and/or 2) proteinuria ≥ 0.5 gm/24 hours or 3+ proteinuria attributable to SLE; and/or 3) 1 of the following features also attributable to SLE and present on 2 or more visits, which were performed at least 6 months apart; proteinuria ≥ 2+, serum creatinine ≥ 1.4 mg/dl, creatinine clearance ≤ 79 ml/minute, red blood cells or white blood cells ≥ 10 per high-power field, granular or cellular casts ≥ 3 per high-power field.

75CIE12720632/9519/1870.25 (0.18–0.34)0.91 (0.86–0.94)2.780.82
48CIE35422/334/380.06 (0.01–0.20)0.90 (0.77–0.97)0.601.04
76CIE663426/405/290.39 (0.28–0.52)0.85 (0.68–0.94)2.60.72
76CIE and HA663326/405/280.39 (0.28–0.52)0.85 (0.67–0.94)2.60.72
47HA505021/2916/340.42 (0.29–0.57)0.68 (0.53–0.80)1.310.85
58         
48IB354211/2411/310.31 (0.17–0.49)0.74 (0.58–0.86)1.190.93
77ID881610/7813/1480.11 (0.06–0.20)0.92 (0.86–0.95)1.380.97
29ID and ELISA60349/514/300.15 (0.08–0.27)0.88 (0.72–0.96)1.250.97
 Total, range  5276020.06–0.420.68–0.92  
 REM pooled    0.25 (0.17–0.36)0.85 (0.78–0.91)  
Table 9. Grade-A articles and population statistics for anti-RNP antibodies in prognosis: lupus nephritis versus no lupus nephritis*
RefTechniqueCases (lupus nephritis)Controls (no lupus nephritis)TP/FNFP/TNSensitivity (95% CI)Specificity (95% CI)+LR−LR
  • *

    TP = true positive; FN = false negative; FP = false positive; TN = true negative; 95% CI = 95% confidence interval; LR = likelihood ratio; CIE = counterimmunoelectrophoresis; HA = hemagglutination; IB = immunoblotting; ID = immunodiffusion; ELISA = enzyme-linked immunosorbent assay; REM = random-effects model.

76CIE663433/3316/180.50 (0.38–0.62)0.53 (0.35–0.70)1.060.94
48CIE35422/339/330.06 (0.01–0.20)0.79 (0.63–0.89)0.291.19
75CIE12720643/8442/1670.34 (0.26–0.43)0.80 (0.74–0.85)1.70.83
76CIE and HA663433/3316/180.50 (0.38–0.62)0.53 (0.35–0.70)1.060.94
47HA33514/2917/340.12 (0.04–0.29)0.67 (0.52–0.79)1.360.31
48IB35420/356/360.00 (0.00–0.10)0.86 (0.71–0.94)01.16
29ID and ELISA603411/495/290.18 (0.10–0.31)0.85 (0.68–0.94)1.200.96
77ID8816141/4736/1250.47 (0.36–0.57)0.78 (0.70–0.84)2.140.68
 Total, range  5106070.00–0.500.53–0.86  
 REM pooled    0.28 (0.18–0.41)0.74 (0.65–0.81)  

Anti-Sm for predicting lupus nephritis.

Of the 8 grade-A articles (Table 8, Figure 3) analyzing the association between anti-Sm antibodies and lupus nephritis, the weighted mean for sensitivity was 25%, the weighted mean for specificity was 85%, and the median positive LR was 1.3; thus, the presence of a positive test result for anti-Sm antibodies generated differences that were seldom clinically important for the diagnosis of lupus nephritis. Furthermore, a negative test result erroneously missed many patients who had the disease (many false negative results) and alone did not predict renal disease. A positive test result, however, might capture those with disease although false positives are possible. The corresponding SROC (Figure 3) shows the uselessness of the test in predicting lupus nephritis, because most points are scattered around the diagonal line.

Figure 3.

Summary receiver operating curve for anti-Sm antibodies in prognosis: lupus nephritis versus no nephritis. Each study is represented by an ellipse (numbers correspond to references). The area of the ellipse shows the relative size of each study. Ellipses are elongated in proportion to the relative contribution within each study of subjects with lupus nephritis (vertical elongation) versus no nephritis (horizontal elongation).

Five grade-B articles (from which data for positive LRs were not available) analyzed the correlation between anti-Sm and lupus nephritis. In 3 studies (25, 30, 46) among 30, 273, and 11 SLE patients, no statistically significant correlation (P > 0.05) between anti-Sm (detected by ID, ELISA, or HA, respectively) and renal involvement was observed. However, in the study done by Field et al (45), membranous glomerulonephritis correlated with anti-Sm antibodies (P < 0.05). In a fifth grade-B study (27), only 1 of 23 SLE patients with Sm antibodies detected by all HA, ID, and CIE techniques had diffuse proliferative glomerulonephritis; 18 patients had changes of mesangial, membranous, or focal nephritis and 4 had normal biopsy results. It remains unclear whether the Sm antibody system may identify a subset of SLE patients with milder renal disease. In addition, one grade-A article (47) analyzed renal disease activity and showed a positive LR of 0.92.

In conclusion, the anti-Sm antibodies were useless in aiding the diagnosis of lupus nephritis.

Anti-Sm for predicting lupus central nervous system involvement.

Only 2 grade-A (29, 48) and 6 grade-B (25, 27, 30, 43, 47–49) articles studied the association between central nervous system (CNS) involvement and anti-Sm antibodies among SLE patients. One of the grade-A articles (48) compared 17 SLE patients with CNS involvement with 60 SLE patients without CNS involvement. The sensitivity was 0, specificity was 0.90, and positive LR was 0. The other grade-A study (29) compared 9 SLE patients with active CNS involvement with 85 SLE patients without CNS involvement. The sensitivity was 0.77, specificity 0.80, and the positive LR was 3.85.

Among the grade-B articles, only 1 study (30) showed a significant correlation between anti-Sm and CNS involvement. All others found no such association (P > 0.05).

From these studies, it was not possible to develop any guidelines regarding utility of anti-Sm in predicting CNS involvement.

Anti-Sm for predicting other systemic manifestations of SLE.

Three analyses from 2 grade-A articles assessed the utility of anti-Sm antibodies in predicting pleuropulmonary involvement (measured by CIE, immunoblotting [IB], and ID, respectively; sensitivity: 14%, 19%, and 82%; specificity: 95%, 68%, and 87%; positive LR: 2.8, 0.6, and 6.3) (48, 49). Two analyses from 1 article assessed the utility of anti-Sm antibodies in predicting cutaneous involvement (measured by CIE and IB, respectively; sensitivity: 12% and 31%; specificity: 97% and 74%; positive LR: 4.0 and 1.2) (48). One article assessed its utility regarding hematologic involvement (measured by CIE and IB, respectively; sensitivity: 11% and 20%; specificity: 97% and 58%; positive LR: 3.7 and 0.5) (48). One article assessed its utility regarding articular involvement (sensitivity: 42%; specificity: 76%; positive LR: 1.8) (42)

Two analyses from 1 grade-A article analyzed the association of anti-Sm with anticardiolipin antibodies (measured by CIE and ELISA, respectively; sensitivity: 16% and 49%; specificity: 97% and 72%; positive LR: 5.3 and 1.8) (50). That same study analyzed the association of anti-Sm with thrombosis (measured by CIE and ELISA respectively; sensitivity: 23% and 55%; specificity: 92% and 62%; positive LR: 2.9 and 1.5) (50).

A grade-A article by Beaufils et al (49) demonstrated severe manifestations of cutaneous vasculitis (vascular purpura in nonthrombocytopenic patients or cutaneous necroses, mainly located in the fingers) among 6 of 12 SLE patients with both anti-DNA and anti-Sm antibodies (group 1) compared with 1 of 22 SLE patients who had anti-DNA antibody with no antibody to an extractable nuclear antigen (group 2; P < 0.01). This same study showed cardiac manifestations (pericarditis, myocarditis, endocarditis, heart block) in 8 of 12 SLE patients in group I compared with 4 of 22 in group 2 (P < 0.01).

No grade-A articles were available to study the utility of anti-Sm antibodies in predicting disease severity in SLE. Among the grade-B studies, 2 (45, 51) showed no correlation between anti-Sm and skin lesion, arthritis, or serositis. Another study (52) concluded that anti-Sm does not appear to be useful in predicting damage in SLE, as measured by the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index (SLICC/ACR DI). Another (30) showed that hematologic involvement seemed less common in patients with anti-Sm alone. One grade-B study (53) showed that anti-Sm antibody occurred less frequently in patients with mild SLE (n = 16, prevalence 12.5%) when compared with those with moderate or severe disease (n = 21, prevalence 47.5%; P < 0.01).

Anti-RNP for predicting lupus nephritis.

Eight grade-A studies (Table 9 and Figure 4) analyzed the utility of anti-RNP antibodies in the diagnosis of lupus nephritis. The weighted mean for sensitivity was 28% and for specificity 74%; the median positive LR was 1.1. These findings suggest the uselessness of the test in the diagnosis of lupus nephritis, evidenced by the agglomeration of the data points around the diagonal line in the SROC (Figure 4).

Figure 4.

Summary receiver operating curve for anti-RNP antibodies in prognosis: lupus nephritis versus no nephritis. Each study is represented by an ellipse (numbers correspond to references). The area of the ellipse shows the relative size of each study. Ellipses are elongated in proportion to the relative contribution within each study of subjects with lupus nephritis (vertical elongation) versus no nephritis (horizontal elongation).

Anti-RNP for predicting lupus CNS involvement.

Only 2 grade-A (29, 48) and 3 grade-B (30, 51, 54) articles studied the association between the presence of CNS involvement and anti-RNP antibodies among SLE patients. Of these 6 studies, none showed a correlation between anti-RNP and CNS involvement. It is not possible from these studies to formulate guidelines because of the lack of grade-A or -B articles.

Anti-RNP for predicting other systemic manifestations.

Only 1 grade-A article (48) was available to calculate a positive LR between anti-RNP antibodies and the presence of pulmonary involvement (measured by CIE and IB, respectively; sensitivity: 10% and 5%; specificity: 84% and 91%; positive LR: 0.6 and 0.6), cutaneous involvement (by CIE and IB, respectively; sensitivity: 14% and 10%; specificity: 86% and 94%; positive LR: 1.0 and 1.7), and hematologic involvement (measured by CIE and IB, respectively; sensitivity: 13% and 7%; specificity: 84% and 90%; positive LR: 0.8 and 0.7). One grade-A article showed the association with articular involvement (sensitivity: 58%; specificity: 24%; positive LR: 0.8) (55). Among grade-B articles, 1 study (51) showed no correlation between anti-RNP and the occurrence of skin lesions, arthritis, and serositis; another study (52) concluded that anti-RNP does not appear to be useful in predicting damage in SLE as measured by the SLICC/ACR DI.

Recommendations for the use of anti-Sm and anti-RNP antibodies in predicting prognosis of rheumatic diseases.

Grade-A studies are needed to develop adequate guidelines for the utility of anti-Sm and anti-RNP antibodies on helping to determine the prognosis of SLE. However, anti-Sm and anti-RNP add little to the prediction of renal disease in SLE. Little information is available as to the utility of these tests in differentiating active renal disease from inactive and in diagnosing CNS involvement or other systemic manifestations of SLE.

Using anti-Sm and anti-RNP for longitudinal assessment.

No Grade-A article, but 6 Grade-B articles were available for assessing the correlation between anti-Sm and anti-RNP antibodies and some measure of disease activity longitudinally in patients with SLE (25, 46, 56–59). Barada et al (25) studied 30 patients with SLE over a 2.5-year period. The group was divided into 14 patients with antibodies to Sm and a control group, which failed to exhibit antibodies to Sm over the study period. Antibodies to Sm were titered 135 times in the 14 patients and the titer of antibodies fluctuated in all 14. They observed significant correlations between the titer of antibodies to Sm and disease activity (60%); the geometric mean titer rose to 3.6 with exacerbation of disease, whereas during remission the geometric mean titer was 1.0 (P < 0.05). These authors also analyzed 29 disease flares in the 14 patients because the previous analysis was biased toward the most severe episode in each patient, and showed that the geometric mean titer of antibodies to Sm during the 29 flares was 3.2, and that during quiescent periods the titer fell to 1.8 (P < 0.001). Furthermore, a rising titer of antibodies to Sm predicted a flare of disease in 5 of 10 patients (50%).

A number of published studies have attempted to evaluate the potential use of anti-Sm and anti-RNP antibodies in the longitudinal assessment of patients with SLE; however, the articles presented data from single or “representative” patients. Because of the substantial risk of reporting bias, such reports presenting only partial data were not considered suitable for this analysis.

There are additional caveats that are critical to the interpretation of studies showing longitudinal data for a more complete population of patients with SLE. Several concerns include 1) the use of diverse definitions of disease activity, 2) the inclusion of anti-Sm antibodies in the definition of disease activity, 3) the potential effects of therapy on disease activity or test results, and 4) possible selection bias in the populations studied. In addition, just as there has been no universal definition of disease activity, there is no universal definition of a flare of SLE. This has considerable impact on the interpretation of data from longitudinal studies; for example, rates of flare vary substantially among the studies. As noted above, the presence of anti-Sm or anti-RNP antibodies correlate with disease activity, and such studies confirm this association but do not provide information on predicting flares or on longitudinal followup.

Differences in trial design preclude compilation of the data, but most of the studies showed a correlation between changes in titers of anti-Sm and anti-RNP antibodies and flare of disease activity. Despite this association, changes in anti-Sm and anti-RNP antibodies are not diagnostic of a flare. Thus, there are individual patients who have flares without changes in anti-Sm or anti-RNP antibody titers, and vice versa. Because the number of articles is limited, there is a need for further research in this area.

Recommendations for using anti-Sm and anti-RNP for longitudinal assessment.

The presence of a positive anti-Sm or anti-RNP antibody result does not predict subsequent flares of disease activity in SLE. Despite the sparse number of relevant studies, rising titers of anti-Sm antibodies antedate or are associated with an increased risk of flares of disease activity. Therefore, longitudinal assessment of anti-Sm antibody titers may be useful in the care of SLE patients; however, subsets of SLE patients have flares without increases in anti-Sm and others have increases in anti-Sm titers without flares. In addition, the correlations between alterations in anti-Sm or anti-RNP and flares of disease tend to be modest. Thus, the data at present do not support the concept of using alterations in anti-Sm or anti-RNP titers to predict or diagnose flare independent of clinical evaluation. Nor are the data sufficiently strong to endorse changes in therapeutic regimens based solely on alterations in anti-Sm or anti-RNP titers (i.e., independent of clinical evaluation). Changes in titers of anti-Sm or anti-RNP should be optimally interpreted in the context of information obtained from the history, physical examination, and other laboratory investigations. There is insufficient data to make recommendations concerning the optimum frequency of testing anti-Sm or anti-RNP in patients with established disease to assess disease activity longitudinally. However, if such testing is performed, the results should be interpreted in the overall clinical context.

Correlations between anti-Sm or anti-RNP antibodies among racially distinct populations.

Several studies have assessed the prevalence of anti-Sm and anti-RNP antibodies in racially distinct populations of SLE patients. Although the prevalence of anti-Sm and anti-RNP antibodies has varied among the populations, both anti-Sm and anti-RNP occurred more frequently in African Americans (19, 60–64) or Afro-Caribbeans (65) when compared with whites. Ward et al (60) and Cooper et al (63) showed an increased prevalence of anti-Sm and anti-RNP antibodies in African Americans, with an adjusted odds ratio (OR) of 2.48 (60) and 5.7 (63) for anti-Sm (P < 0.05) and 1.79 (60) and 15.0 (63) for anti-RNP (P < 0.05) when compared with whites. Arnett et al (61) demonstrated that anti-Sm occurred more frequently in African Americans (25%) than whites (10%; P = 0.02), as did anti-RNP (40% versus 23%; P = 0.03). Field et al (45) showed that 7 of 34 white (21%) SLE patients and 8 of 11 Afro-Caribbeans (73%) were positive for anti-Sm antibodies.

Conclusions

The anti-Sm antibody was highly specific for SLE and it was not found in healthy controls and rarely found in people with other rheumatic diseases. Thus, anti-Sm antibody testing should be performed when one is considering a diagnosis of SLE, but not to aid in the diagnosis of other rheumatic diseases. Anti-Sm antibodies did not correlate with the presence of renal disease in patients with SLE and the LR for this association was very small. This finding reflects the uselessness of anti-Sm antibodies as a predictor of lupus nephritis. Anti-Sm antibodies do not appear to predict disease flares, but studies are sparse.

The anti-RNP antibody is not specific to SLE. Although a positive test result for anti-RNP offers strong support for the diagnosis of MCTD, it does not support a diagnosis of SLE, RA, or SSc. With regard to prognosis, anti-RNP testing is of no value for diagnosing lupus nephritis. Further studies are warranted to make valid conclusions about the association between anti-RNP testing and other rheumatic diseases, SLE manifestations, and disease activity. Anti-Sm and anti-RNP antibodies occur more frequently in African Americans or Afro-Caribbeans when compared with whites.

Acknowledgements

The authors wish to acknowledge the assistance of Dr. Peter Bonis and the excellent analytical and data interpretation support offered by Prof. Joseph Lau during the progress of preparing this article.

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