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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

Objective

To define inactive disease (ID) and clinical remission (CR) and to delineate variables that can be used to measure ID/CR in childhood-onset systemic lupus erythematosus (cSLE).

Methods

Delphi questionnaires were sent to an international group of pediatric rheumatologists. Respondents provided information about variables to be used in future algorithms to measure ID/CR. The usefulness of these variables was assessed in 35 children with ID and 31 children with minimally active lupus (MAL).

Results

While ID reflects cSLE status at a specific point in time, CR requires the presence of ID for >6 months and considers treatment. There was consensus that patients in ID/CR can have <2 mild nonlimiting symptoms (i.e., fatigue, arthralgia, headaches, or myalgia) but not Raynaud's phenomenon, chest pain, or objective physical signs of cSLE; antinuclear antibody positivity and erythrocyte sedimentation rate elevation can be present. Complete blood count, renal function testing, and complement C3 all must be within the normal range. Based on consensus, only damage-related laboratory or clinical findings of cSLE are permissible with ID. The above parameters were suitable to differentiate children with ID/CR from those with MAL (area under the receiver operating characteristic curve >0.85). Disease activity scores with or without the physician global assessment of disease activity and patient symptoms were well suited to differentiate children with ID from those with MAL.

Conclusion

Consensus has been reached on common definitions of ID/CR with cSLE and relevant patient characteristics with ID/CR. Further studies must assess the usefulness of the data-driven candidate criteria for ID in cSLE.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

Systemic lupus erythematosus (SLE) is a complex, chronic, multisystem, autoimmune, inflammatory disease that primarily targets young women of nonwhite ancestry (1, 2). Up to 20% of patients are diagnosed during childhood (cSLE) and their disease has a less favorable prognosis than those with adult-onset SLE, particularly with respect to multiorgan and kidney involvement (3–5). The course of cSLE is characterized by episodes of disease flares, followed by periods of improvement, which are generally the result of more intensive drug therapy (6, 7). As in other adult and pediatric rheumatic diseases, it is hoped that advances in the treatment of cSLE yield a state of inactive disease (ID) or even clinical remission (CR) (8, 9). To permit comparability of future studies addressing ID and CR, it is advisable to develop common definitions and algorithms or criteria for measuring ID/CR in cSLE.

The objectives of this project were to apply consensus formation methodology to define ID/CR in cSLE, identify variables to be considered in future criteria of ID/CR for cSLE, and derive data-driven candidate criteria for ID.

Significance & Innovations

  • This study newly defines internationally accepted constructs of inactive disease and clinical remission in childhood-onset systemic lupus erythematosus (cSLE).

  • Inactive disease and clinical remission in cSLE require the absence of laboratory evidence compatible with active lupus nephritis and objective physical findings of cSLE activity.

  • Candidate variables to be considered in future criteria are delineated and their validity is confirmed using prospective data.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

The overall approach of the project was based on methodologic strategies successfully employed by the pediatric rheumatology community in the past, following the framework developed by the Classification and Response Criteria Subcommittee of the American College of Rheumatology Committee on Quality Measures (10).

We performed structured consensus formation to define ID/CR and delineate variables (VAR-ID/CR) that can be used in algorithms (or criteria) to measure ID/CR (step 1). Using data from a prospective cohort, we assessed the relevance of the VAR-ID/CR for discriminating patients with ID from patients with minimally active cSLE (MAL) who were not in ID. We also explored data-driven candidate criteria for ID (step 2). The study was approved by the institutional review boards of the participating pediatric rheumatology centers. Informed consent was obtained from all parents and, as appropriate, assent was given by the participants prior to the study procedures.

Step 1: consensus methodology and international Delphi surveys

The goal of the Delphi process (11) was to define ID/CR in cSLE and create a pool of relevant variables (Var-ID/CR) to be considered in candidate criteria. Fundamental to the project was the initial review of the medical literature, addressing the constructs ID/CR with a focus on rheumatology.

The Pediatric Rheumatology Collaborative Study Group, the Childhood Arthritis and Rheumatology Research Alliance, the Pediatric Rheumatology European Society Juvenile Lupus Working Group, the Paediatric Rheumatology International Trials Organisation, and the Pan American League of Associations for Rheumatology were approached and provided access to their membership. Members of these groups have prior experience in using these techniques to develop outcome measures (7, 12, 13). As is commonly done, the level for consensus was set at 80% (8).

Step 2: variable performance and data-driven candidate criteria.

Patients.

As part of a larger study, patients with cSLE ages <18 years (2) were recruited during routine visits at 12 pediatric rheumatology clinics in the US and Canada, and study visits occurred every 3 months thereafter. Some patients entered the study with active cSLE and achieved MAL rather than ID, as rated by the treating physician during followup. Other patients who were considered by their pediatric rheumatologist to “be in remission” were recruited, provided cSLE did not require treatment with systemic corticosteroids. Considering the scores of the Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) (6, 11) and the British Isles Lupus Activity Group (BILAG) index (14), MAL was defined as the absence of BILAG index A scores, 2 or fewer BILAG index B scores, and a SLEDAI-2K score of <5. These cutoffs were chosen based on the results of the Delphi survey and published literature (15). Other patients with cSLE who did not require systemic corticosteroids were also enrolled, provided their managing pediatric rheumatologist considered them to be in ID/CR. Details on the experience of these pediatrics rheumatologists in treating cSLE are described elsewhere (16). In brief, all were board-certified pediatric rheumatologist professionals who see, on average, 20 patients with cSLE weekly at their academic center and have 10 years of experience in treating cSLE.

Outcomes

Findings on physical examination, information about prescribed medications, and standard laboratory testing were obtained, including antinuclear antibodies (ANAs), erythrocyte sedimentation rate (ESR), complete blood count, liver function testing, urinalysis and microscopy, protein:creatinine ratio, complement C3 and C4 levels, anti–double-stranded DNA (anti-dsDNA), and antiphospholipid antibody (aPL) levels. Additionally, we recorded parameters often used for assessing cSLE (7, 17), including physician assessment of overall disease activity (PGA) as measured on a visual analog scale (where 0 = ID and 10 = very active disease), and the scores of several disease activity indices, including the Systemic Lupus Activity Measure (SLAM) (10), SLEDAI-2K (6, 11), and BILAG index (14); scores of 0 indicate ID in all of these indices.

Patient symptoms

A standardized questionnaire was completed at each visit by the patient (14). This questionnaire captures symptoms often associated with cSLE, including their severity (mild = not limiting activities, moderate or severe = limiting activities). The symptoms reported on this questionnaire were reviewed by the treating pediatric rheumatologist for correctness and clinical relevance prior to consideration of these symptoms in the subsequent analyses.

Measures of cSLE course

During followup visits, the managing pediatric rheumatologist rated the disease course on 2 separate scales: 1) in response to the sentence, “Compared to the last study visit 3 months ago, the patient's overall disease is still in ID/CR,” the physicians answered yes or no, and 2) in response to the sentence stem, “Compared to the last study visit three months ago, the patient's overall disease shows,” the pediatric rheumatologist rated the disease course on a 5-point Likert scale: major flare of disease, minor flare of disease, no change in disease, minor improvement of disease, or major improvement of disease. The pediatric rheumatologists (n = 23) who provided the above ratings were all board-certified pediatric rheumatologists and had, on average, 13 years of experience in managing cSLE.

Statistical analyses

Delphi responses were assessed for consensus at 80%. We tested whether there were systematic differences in the responses provided by Delphi respondents from different geographic regions or with varying professional experience as measured by the duration of medical practice. Agreement among raters was assessed using kappa statistics. A kappa value can be interpreted as follows: 0–0.20 = slight, 0.21–0.40 = fair, 0.41–0.60 = moderate, 0.61–0.80 = substantial, and 0.81–1 = almost perfect agreement (18).

We compared patients with ID/CR to those with MAL for differences in the frequency or values of the Var-ID/CR, using contingency table analysis and a 2-sample t-test, respectively. A patient symptom score (range 0–4) was calculated from the sum of the following symptoms: myalgias, arthralgias, fatigue, and headaches.

To correct for multiple comparisons between groups, only Bonferroni-corrected P values less than 0.005 were considered statistically significant (19). Furthermore, we examined the Var-ID/CR for redundancy using Pearson's correlation coefficients (r). High values (r = >0.6) support redundancy or indicate that algorithms containing both predictors may cause unstable estimates, i.e., whether the patient truly has ID/CR or not. For these analyses, we used the first observation available for each patient, i.e., the enrollment visit for patients with ID/CR and the first visit when MAL was reached in the others.

Lastly, in exploratory analysis to derive data-driven criteria for ID, we performed logistic regression to predict ID (outcome variable) considering the Var-ID/CR as predictors. Given our recruitment strategy, the duration of followup, and the number of patients enrolled, we focused on ID and not on CR in these exploratory analyses. For each model, we estimated the rescaled R2 value as a generalized measure of the model fit (14) and calculated the area under the receiver operating characteristic curve (AUC) as a measure of diagnostic accuracy for distinguishing ID from MAL. The accuracy (AUC) can be interpreted as follows: 0.9–1.0 = excellent, 0.81–0.91 = good, 0.71–0.80 = moderate, 0.61–0.70 = fair, and ≤0.60 = poor (20).

Open-source online survey software, LimeSurvey, was used for Delphi response management and as a presentation layer (online at http://www.limesurvey.org/). All analyses were done using SAS software, version 9.2.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

Literature review

A detailed literature search was performed. The identified articles were screened independently by 2 authors (RM, HIB) and assessed for relevance to the project. All articles considered relevant for defining ID/CR by at least 1 were reviewed in detail by both of these authors. Relevance assessment included the provision of a definition, development of criteria, or the delineation of items considered with ID/CR. The 37 articles deemed useful for defining ID/CR were summarized for presentation to participants in the Delphi process (for details on the literature search strategy and results, see Supplementary Appendix A, available in the online version of this article at http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2151-4658).

Delphi survey participants

In 2009, the initial Delphi survey was sent to 137 pediatric rheumatologists who indicated their willingness to participate in this project during the consensus process for the cSLE flare criteria (14). The response rate for the first Delphi questionnaire (concerning ID/CR) was 77%.

In early 2011, the second survey was sent to 598 members of the participating organizations. There were 362 respondents to the survey (61% survey response rate), and based on the information provided, there were 240 pediatric rheumatologists among the respondents, who treated a minimum of 3 cSLE patients per month. On average, these physicians had 15.5 years (range 4–27 years) of experience treating cSLE and assessed 12 patients per month (range 3–80). Most of these respondents worked in the US or Canada (46%), Europe (34%), and Central and South America (15%), followed by Asia, Africa, and Australia (5%). Responses from these 240 pediatric rheumatologists were used in the analyses, while the feedback from all other respondents was not further considered. Therefore, only responses of pediatric rheumatologists were included in the analysis.

Ratings from physicians in North America were comparable to those in Europe and Central and South America (all κ = >0.72) for Var-ID/CR, for which consensus was achieved, and there were no parameters for which consensus was reached in only 1 geographic region. Likewise, there were no significant differences among respondents with different experience. This supports the fact that there were no systematic differences in the opinion of the survey respondents from different geographic areas or different levels of experience.

Definition of the constructs

Consensus was reached in several key findings that are summarized in the following. ID and CR must be discriminated from “cure” or “minimally clinically active cSLE.” Furthermore, “inactive disease” (ID) refers to a certain point in time, whereas “clinical remission” (CR) constitutes a time period during which a patient is considered to have ID (consensus 91%). While the use of medication was deemed irrelevant in ID, this was not the case with CR. Respondents' consensus suggests 3 levels of CR, considering both the duration of ID and the medications prescribed for cSLE (Table 1).

Table 1. Definitions of ID and CR in cSLE*
ConstructTimeframeMedication usage
Point in timeMinimal time interval, monthsCorticosteroidsImmuno- suppressivesPreventive medicationsMedications to treat damage
  • *

    ID = inactive disease; CR = clinical remission; cSLE = childhood-onset systemic lupus erythematosus.

  • Preventive medications include systemic medications that can be used to prevent disease damage, such as statins, aspirin, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, bisphosphonates, vitamin D, and ω-3 fatty acids.

  • Medication exposure is not considered.

IDYesPermissiblePermissiblePermissiblePermissible
CR      
 CR on medication for cSLENo6PermissiblePermissiblePermissiblePermissible
 CR on preventive medicationNo6NoNoPermissiblePermissible
 CR off medication for cSLENo12NoNoNoPermissible

Even patients considered to have “CR off medications” were anticipated to continue mediations to treat non–cSLE-related comorbid conditions or organ damage, but not medications, probiotics, or nutritional supplements that are used as prophylaxis of cSLE-related disease damage or progression. These “preventive” medications include (based on consensus) statins, aspirin, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, bisphosphonates, vitamin D, and ω-3 fatty acids. Notably, there was no consensus regarding whether antimalarials or daily nonsteroidal antiinflammatory drugs (NSAIDs) should be considered as preventive medications or not.

Details on ID with cSLE

Additionally, respondents achieved consensus that patients with ID/CR must have a normal physical examination but may have select laboratory abnormalities (Table 2). With ID, there may be up to 2 mild nonlimiting symptoms (myalgia, arthralgia, fatigue, and/or headaches).

Table 2. Details on permissible signs, symptoms, and laboratory abnormalities of patients with inactive disease*
DescriptorsPermissible even if potentially due to cSLE activityNot permissible, unless due to disease damage
  • *

    cSLE = childhood-onset systemic lupus erythematosus; EKG = electrocardiogram; ANA = antinuclear antibody; aPL = antiphospholipid antibodies; ULN = upper limit of normal range; ESR = erythrocyte sedimentation rate.

  • On physical examination or by credible patient report.

  • Urine sediment with white blood cells >5 cells/high-power field (hpf), red blood cells >5 cells/hpf, or cellular casts.

Signs of cSLE activity on physical examinationNoneMalar rash Livedo reticularis Raynaud's phenomenon Alopecia
Symptoms associated with cSLE activity  
 Types of symptomsFatigue Arthralgia Myalgia HeadachesIntermittent chest pain without radiologic or EKG abnormalities
 Number of symptoms≤23 or 4
 Severity of symptomsMild and nonlimiting≥1 are moderate/severe
Laboratory abnormalitiesANA positivity Any damage-related laboratory abnormalities, including proteinuria and decreased creatinine clearance Abnormally low levels of complement C4 if presumed to be due to null allele Abnormal but stable levels of aPL ≤2 × ULN ESR ≤2 × ULNAbnormal urinary sediment due to lupus nephritis Abnormal liver function testing Abnormally low complement C3 or CH50 levels Anemia, leukopenia, lymphopenia, neutropenia, and thrombocytopenia

Respondents achieved consensus that permissible laboratory abnormalities include ANA positivity and stable levels of aPL that do not exceed twice the upper limit of normal (ULN; 2 × ULN). The majority of the survey respondents stated that stable low levels of anti-dsDNA antibodies (73%) are permissible with ID/CR.

There was consensus that ESR elevation should be considered with ID/CR, and the majority of the raters stated that ESR levels not exceeding 2 × ULN (66%) were acceptable with ID/CR. Based on previous suggestions, since there are various methods for measuring the ESR (with different ULNs) and clinical laboratory facilities often change assays, ESR values >50 mm/hour were considered to be >2 × ULN in the subsequent analyses (14).

Based on consensus, C4 hypocomplementemia was permissible, provided that the low serum levels were due to genetic variability rather than active cSLE. In brief, there are more than 40 different human polymorphic allotypes of the 2 distinct major gene product isotypes, C4A and C4B (21). Among others, serum levels of C4 are moderately correlated with the C4 gene copy numbers (22, 23). Because formal genetic testing for clinical purposes of C4 gene copy numbers is unavailable, clinicians deduce that a genetic variation must be present if C4 levels do not normalize, despite apparently well-controlled cSLE.

The PGA and the scores of disease activity indices were deemed important for determining ID/CR. Consensus was also reached that, irrespective of the measure considered (SLAM, SLEDAI-2K, or BILAG index), the scores of a disease activity index alone were insufficient to identify ID/CR, and that ID/CR could be present even if the disease activity scores were >0.

VAR-ID/CR in patients considered to be in ID/CR by the managing pediatric rheumatologists

There were 35 patients with ID/CR and 31 patients with MAL, as rated by their pediatric rheumatologist (Table 3). The groups differed significantly in the frequency of abnormal findings on physical examination. Leukopenia, lymphopenia, neutropenia, anemia, and C3 hypocomplementemia were less common with ID/CR than with MAL. Of note, the groups were comparable for low levels of C4, ESR values exceeding 2 × ULN, and positivity of anti-dsDNA antibodies (Table 4).

Table 3. Patients with ID by the treating pediatric rheumatologist*
Patient characteristicsIDMAL
  • *

    Values are the number of patients unless otherwise indicated. ID = inactive disease; MAL = minimally active lupus; SDI = Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index; SLE = systemic lupus erythematosus.

  • Systemic Lupus Erythematosus Disease Activity Index 2000 score ≤5 and ≤2 B scores without A British Isles Lupus Assessment Group (BILAG) index scores.

  • Based on items that are scored by the BILAG index.

Demographics  
 Sex  
  Female2820
  Male711
 Race  
  White2815
  African American511
  Asian25
 Age at onset, mean ± SD years12.6 ± 2.814.8 ± 3.2
 Disease duration, mean ± SD years4.2 ± 2.21.4 ± 2.6
Disease damage  
 SDI, mean ± SD (range)0.2 ± 0.6 (0–3)0.5 ± 0.9 (0–3)
Prior SLE organ involvement  
 Lupus nephritis  
  Yes1417
  No2114
 Neuropsychiatric lupus  
  Yes1122
  No249
Table 4. Differences between patient with ID and minimally active stable disease activity*
cSLE characteristicsPresent with ID (n = 35), no. (%)Present with MAL (n = 31), no. (%)P
  • *

    ID = inactive disease; cSLE = childhood-onset systemic lupus erythematosus; MAL = minimally active lupus; NS = not significant; EKG = electrocardiogram; ANA = antinuclear antibody; anti-dsDNA = anti–double-stranded DNA; aPL = antiphospholipid antibodies; ESR = erythrocyte sedimentation rate.

  • Based on chi-square test with Yates' correction or Fischer's exact test, when appropriate.

  • By history or on physical examination.

  • §

    As interpreted and scored on the Systemic Lupus Activity Measure (SLAM) or British Isles Lupus Assessment Group index.

  • Only available in a subset of patients.

  • #

    Urine sediment or protein:creatinine ratio >0.2.

  • **

    Abnormal values as per the SLAM.

Abnormal physical examination3 (9)13 (42)< 0.001
Raynaud's phenomenon2 (6)3 (10)NS
Symptoms associated with cSLE activity   
 Intermittent chest pain without radiologic or EKG abnormalities01 (3)NS
  Fatigue§2 (6)7 (23)0.072
  Arthralgia§4 (11)6 (19)NS
  Myalgia§1 (3)1 (3)NS
  Headaches§1 (3)8 (26)0.01
 Absence of any of the above symptoms28 (80)19 (61)NS
Laboratory assessment   
 ANA positivity35 (100)31 (100)NS
 Anti-dsDNA antibodies16 (46)17 (55)NS
 Elevated levels of aPL7 (44)5 (50)NS
 ESR >50 mm/hour5 (14)1 (3)NS
 Urine abnormalities due to lupus#02 (6)< 0.001
  Abnormal liver function testing01 (3)NS
  Abnormally low complement C3 levels, mg/dl2 (6)6 (19)NS
  Abnormally low complement C4 levels, mg/dl15 (43)14 (45)NS
  Abnormal complete blood count**   
   Anemia, hemoglobin <10 gm/dl4 (11)9 (29)NS
   Leukopenia, <3,500/mm32 (6)4 (13)NS
   Thrombocytopenia, <150,000/mm301 (3)NS
   Lymphopenia, <1,500/mm313 (37)21 (68)0.016
   Neutropenia, <1,500/mm31 (3)3 (10)NS

With the exception of the white blood cell and absolute neutrophil counts (r = 0.92), none of the other Var-ID/CR were more than moderately correlated with each other. Details of the results of laboratory testing are provided in Table 5. We did not have access to aPL levels. Therefore, we excluded aPL from the pool of VAR-ID/CR in the subsequent analyses.

Table 5. Differences in variables considered important for assessing ID in cSLE*
 Present with ID (n = 35)Present with MAL (n = 31)P
  • *

    Values are the mean ± SD (range) unless otherwise indicated. ID = inactive disease; cSLE = childhood-onset systemic lupus erythematosus; MAL = minimally active lupus; VAS = visual analog scale; PGA = physician global assessment of disease activity; SLAM = Systemic Lupus Activity Measure; SLEDAI-2K = Systemic Lupus Erythematosus Disease Activity Index 2000; BILAG = British Isles Lupus Activity Group; NS = not significant; ESR = erythrocyte sedimentation rate; WBCs = white blood cells.

  • By 2-sample t-test.

Sum of symptoms of fatigue, arthralgia, myalgia, and headaches0.22 ± 0.38 (0–2)0.71 ± 1.04 (0–3)0.0233
 Disease activity   
  10-cm VAS of PGA0.37 ± 0.73 (0–3)2.03 ± 1.14 (0–5)< 0.001
  SLAM score1.63 ± 1.70 (0–5)3.26 ± 2.67 (0–9)0.0050
  SLEDAI-2K score1.97 ± 1.47 (0–3)2.65 ± 1.56 (0–4)0.075
  BILAG index, mean ± SD1.03 ± 1.182.51 ± 2.010.0008
  BILAG index C scores0.83 ± 0.92 (0–3)1.13 ± 1.12 (0–4)NS
  Maximum no. of BILAG C scores43 
  BILAG index B scores0.06 ± 0.24 (0–1)0.42 ± 0.10 (0–2)< 0.009
  Maximum no. of B scores21 
Laboratory testing   
 ESR, mm/hour21.5 ± 20.9 (1–77)19.2 ± 14.0 (4–61)NS
 WBCs, 1,000/mm35,820 ± 1,690 (2,900–10,700)6,240 ± 2,450 (2,300–10,900)NS
 Hemoglobin, mg/dl13.4 ± 1.34 (10.7–15.8)12.4 ± 1.46 (8.2–15.4)NS
 Absolute lymphocyte count, 1,000/mm31,840 ± 720 (930–3,900)1,250 ± 500 (500–2,250)0.0002
 Absolute neutrophil count, 1,000/mm34,030 ± 1,350 (940–7,260)4,570 ± 2,390 (800–9,060)0.0214
 Platelets, 1,000/mm3261,000 ± 78,000 (176,000–471,000)274,000 ± 63,000 (178,000–411,000)NS
 Complement C3, mg/dl107 ± 17.6 (73–146)97.3 ± 31.2 (20 – 165)NS
 Complement C4, mg/dl17.7 ± 6.60 (2–34)15.5 ± 8.56 (2 – 41)NS

Construct validity of the definition of ID/CR

The ability of all Var-ID/CR to discriminate patients with ID (n = 35) from those with MAL (n = 31) was explored. These analyses focused only on the patient phenotype with ID (or CR) and not on the concomitant use of medications. Assuming that, as is shown in Table 2, all Var-ID/CR deemed permissible but none of those considered unacceptable can be present with ID/CR, we tested the agreement between the treating pediatric rheumatologists and the consensus achieved via Delphi surveys (Table 6).

Table 6. Performance of disease activity indices as measured by the AUC*
Disease activity indexID does not permit low C4 or ESR >50 mm/hourID permits low C4 but not ESR >50 mm/hourID permits low C4 and ESR >50 mm/hourID as defined by the treating physician
  • *

    Values are the AUC (95% confidence intervals around the AUC estimate) (R value from logistic regression [%]). AUC = area under the receiver operating characteristic curve; ID = inactive disease; ESR = erythrocyte sedimentation rate; SLEDAI-2K = Systemic Lupus Erythematosus Disease Activity Index 2000; PGA = physician global assessment of disease activity; SLAM = Systemic Lupus Activity Measure; BILAG = British Isles Lupus Activity Group.

  • Assuming normal urine sediment and absence of proteinuria due to lupus nephritis activity and stable antiphospholipid antibody titer <2 × upper limit of normal.

  • Considering all parameters listed in Table 2 and the PGA.

  • §

    Sum of mild nonlimiting symptoms of headaches, myalgias, arthralgias, and fatigue.

  • PGA measured on a 10-cm visual analog scale.

All parameters without disease activity measure0.97 (0.94–1.0) (74)0.95 (0.95–1.0) (71)0.85 (0.76–0.95) (49)0.94 (0.87–1.0) (74)
SLEDAI-2K summary score0.86 (0.75–0.97) (40)0.65 (0.51–0.80) (10)0.63 (0.49–0.77) (6)0.63 (0.50–0.77) (8)
SLEDAI-2K summary score, PGA0.71 (0.58–0.84) (18)0.86 (0.74–0.99) (38)0.72 (0.59–0.84) (20)0.91 (0.84–0.98) (59)
SLEDAI-2K summary score, PGA, patient symptom score§0.88 (0.77–0.99) (44)0.74 (0.60–0.94) (22)0.74 (0.62–0.85) (26)0.91 (0.84–0.99) (61)
SLAM summary score0.84 (0.72–0.96) (33)0.85 (0.75–0.95) (43)0.77 (0.65–0.89) (26)0.69 (0.56–0.82) (17)
SLAM summary score, PGA0.85 (0.72–0.97) (34)0.86 (0.76–0.96) (44)0.79 (0.67–0.90) (31)0.90 (0.82–0.99) (61)
BILAG index summary score0.83 (0.72–0.95) (34)0.79 (0.66–0.92) (24)0.85 (0.75–0.95) (40)0.74 (0.62–0.86) (25)
BILAG index summary score, PGA0.82 (0.66–0.96) (35)0.83 (0.71–0.94) (35)0.85 (0.75–0.95) (42)0.92 (0.85–0.99) (65)
BILAG index B and C scores0.88 (0.82–0.94) (50)0.86 (0.74–0.98) (43)0.86 (0.74–0.97) (44)0.71 (0.58–0.84) (25)
BILAG index B and C scores, PGA0.90 (0.83–0.97) (51)0.87 (0.75–0.98) (44)0.88 (0.77–0.99) (48)0.94 (0.88–0.99) (70)
SLEDAI-2K and BILAG index summary scores0.85 (0.75–0.96) (40)0.93 (0.86–1.0) (60)0.86 (0.77–0.96) (44)0.76 (0.63–0.88) (30)
SLEDAI-2K and BILAG index summary scores, PGA0.85 (0.75–0.96) (40)0.95 (0.89–1.0) (62)0.85 (0.76–0.95) (45)0.92 (0.85–0.99) (65)

The agreement between the treating physician and the consensus definition of ID/CR was slight when C4 hypocomplementemia was considered to reflect active cSLE (κ = 0.16). When considering all Var-ID/CR but assuming that C4 hypocomplementemia was due to genetic variability (rather than active cSLE), then the agreement was moderate (κ = 0.44), and agreement further increased (κ = 0.48) when ESR elevation was no longer considered for characterizing patients with ID/CR.

Data-driven candidate criteria for ID

To increase the feasibility of future criteria of ID/CR, it is highly desirable to minimize the number of variables to be included in future criteria of ID/CR. All of the Var-ID/CR (except aPL levels) are items of disease activity indices that are commonly used in cSLE (SLAM, SLEDAI-2K, and BILAG index). Therefore, in exploratory analyses using logistic models, we considered the scores of the disease indices as predictors of ID, under consideration of ESR levels exceeding 2 × ULN (here, >50 mm/hour) and C4 hypocomplementemia (Table 6).

When all Var-ID/CR (except aPL levels) were included in the model, the outcome ID could be predicted very well, irrespective of C4 and ESR status. In conjunction with laboratory testing suggesting inactive lupus nephritis and a normal physical examination, the SLAM and the BILAG index (domain scores or total summary score) were similar in their ability to predict ID. Only when the PGA and patient symptom score were added to the SLEDAI-2K as predictors did the resulting logistic model of ID perform as well (AUC, R2) as the models that included the BILAG index or the SLAM. Conversely, adding the PGA and the patient symptom score to models that contained the SLAM or the BILAG index as predictors of ID did not importantly improve model performance (AUC) or fit (R2).

Thirty-two of the 35 patients in ID/CR at baseline continued to be in ID/CR at the 6-month followup visit. Repetition of the above analyses using the followup data of these 32 patients yielded similar results.

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

Using consensus formation methodology, we developed taxonomy for generally accepted future criteria of ID and CR in cSLE. Additionally, variables deemed central for the measurement of these constructs were delineated, and data-driven candidate criteria for ID were derived.

CR in other conditions such as malignancies (24), infections (25), and rheumatoid arthritis is defined as a time point when the disease is very well controlled (9, 26). Conversely, there was consensus among pediatric rheumatologists that CR in cSLE constitutes a time period. Therefore, the construct of CR in cSLE embraces a concept that is already in use for juvenile idiopathic arthritis (8). Implicit to this concept is the need for an ID construct to define the disease state (or patient phenotype) that is present throughout the CR period.

Different from CR, medication use is not part of the definition of ID in cSLE. This is sensible when considering the proposed use of ID/CR criteria in future clinical trials, where medication adjustments are closely regulated to help delineate the safety and efficacy of the study drug. Concomitant medication usage is only relevant for disease-modifying medications in long-term followup, and this will be captured by the different levels of CR proposed.

There was no consensus regarding whether antimalarials and NSAIDs should be allowed, nor was there consensus to prohibit NSAIDs or antimalarials in patients who are in “CR on preventive medications.” NSAIDs are widely used in the general population “as needed,” whereas regular intake likely suggests the presence of clinically relevant joint inflammation or damage. Antimalarials are antiinflammatory and widely used in cSLE for the prevention of damage (27), and are often continued, irrespective of the patients' disease control. The prospective data collected for this study were not suited to explore medication usage during CR, and additional studies are needed to determine antimalarial and NSAID usage in the context of CR.

Disease activity indices and the PGA have a long history of use to delineate the course of cSLE and SLE (17, 28, 29). The same is true for ID/CR. Both the PGA and disease activity index scores were deemed central to, but not sufficient for, identifying ID/CR in cSLE. There was consensus that any objective abnormalities on physical examination were incompatible with ID/CR. Likewise, several symptoms (arthralgia, myalgia, headaches, and fatigue) that are associated with cSLE activity were considered relevant when classifying a patient to be in ID/CR.

Similar to the cSLE flare criteria, patient well-being and health-related quality of life are not among the candidate variables to be considered for future criteria of ID/CR (8, 17). Instead, there was consensus to consider specific symptoms that are known to have a detrimental impact on health-related quality of life and well-being with cSLE in such criteria.

The presence of aPL was deemed permissible with ID/CR by consensus, provided aPL levels are <2 × ULN. However, aPL testing is not standardized, both in terms of assays and the units used to report levels, making the uniform interpretation of the degree of aPL elevation impossible (30–32). The remaining Var-ID/CR (without aPL) were able to accurately discriminate patients with ID from those with MAL, raising the possibility that aPL levels may not be required to identify patients with ID/CR. This will need confirmation in future studies.

Consensus was reached that complement C4 levels should be normal with ID/CR, unless due to genetic variability. However, clinical testing for the gene copy numbers of C4 is not readily available at present. Based on our exploratory analyses, it is very likely that the elimination of C4 hypocomplementemia from the pool of Var-ID/CR will not significantly change the measurement properties of future criteria of ID/CR. In contrast to C4 not being a critical determinant of the VAR-ID/CR, elimination of the ESR from the pool of VAR-ID/CR considerably decreased the accuracy with which ID was predicted in our data sets. The agreement between the treating rheumatologist and the consensus phenotype with ID was fair to moderate but well in line with what was observed in previous studies (8, 17).

The SLAM and BILAG index scores include subjective symptoms as well as objective abnormal findings, whereas the SLEDAI-2K only scores the latter. In regression models that considered a disease activity index as a predictor, only the SLAM or the BILAG index identified patients with ID with good to excellent accuracy. Conversely, only the combination of the SLEDAI-2K and PGA plus the patient symptom score was comparable in distinguishing patients with ID from those with MAL.

If confirmed in a larger prospective data set, disease activity index scores alone or in combination with the PGA and the patient symptom score appear to accurately identify patients in ID, provided there is a normal physical examination and laboratory testing suggests inactive lupus nephritis.

The Outcome Measures in Rheumatology (OMERACT) filter is used to evaluate the usefulness of criteria for rheumatic diseases (32). The OMERACT filter encompasses 3 components of clinimetrics: truth, discrimination, and feasibility. Truth captures 4 aspects of validity: face, content, criterion, and construct. Discrimination is the second component of the OMERACT filter and asks if the criteria are able to distinguish between states of interest. Feasibility, the third component of the filter, refers to how practical it is for the measurement of the outcome to be carried out quickly and easily, using a simple scoring method and at a minimal cost in a physician's office. The international consensus process that led to the definition of ID/CR and delineated a pool of VAR-ID/CR is in support of the first component, the ability of data-driven candidate criteria to discriminate between ID, and MAL supports the second component, whereas the limited number and type of the parameters considered the candidate criteria are in support of the third component of the OMERACT filter.

A limitation of our study is the limited number of patients studied. However, ID/CR is an exceedingly rare disease state in adults with lupus and occurs even less frequently in children (3, 31). Therefore, the results of the logistic regression models were considered exploratory in nature only.

In summary, a framework for defining and measuring ID and CR in cSLE has been developed. Despite the complexity of cSLE, our research suggests that in patients with a normal physical examination and clinically inactive lupus nephritis, simple algorithms are sufficient to identify patients with ID. The presented data-driven algorithms to measure ID based on the score of a disease activity index, PGA, and ESR will need to be verified in future studies. Specifically, we expect that a consensus conference for additional consensus formation will yield further specification of the ID/CR criteria, preferably using data from clinical trials aimed at achieving ID/CR in cSLE. Next steps in the development of criteria to measure ID/CR will also include further consensus formation around medication usage with CR.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Brunner had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Mina, Giannini, Brunner.

Acquisition of data. Mina, Klein-Gitelman, Ravelli, Beresford, Avcin, Espada, Eberhard, Schanberg, O'Neil, Silva, Higgins, Onel, Singer, von Scheven, Imundo, Nelson, Giannini, Brunner.

Analysis and interpretation of data. Mina, Giannini, Brunner.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

We are indebted to the members of the External Scientific Advisory Committee of this study for their advice in the study implementation, conduction, and statistical analysis: Drs. Carol Wallace, Suzanne Bowyer, Vern Farewell, Rosalind Ramsey-Goldman, Nicola Ruperto, Carlos Rose, and James Witter.

Investigators: Adam Huber (IWK Health Centre and Dalhousie University, Halifax, Nova Scotia, Canada), Alan Rosenberg (Royal University Hospital, Saskatoon, Saskatchewan, Canada), Alberto Martini (University of Genoa, Genoa, Italy), Alejandra Pringe (Hospital Pedro de Elizalde, Buenos Aires, Argentina), Ali Yalcindag (Rhode Island Hospital, Providence), Amita Aggarwal (SGPGI, Lucknow, India), Anders Fasth (Göteborg University, Göteborg, Sweden), Andrew Lasky (Children's Mercy Hospital, Kansas City, KS), Andrew Zeft (University of Utah, Salt Lake City), Ann Reed (Mayo Clinic, Rochester, MN), Anne Stevens (Seattle Children's Hospital, Seattle, WA), AnneMarie Brescia (DuPont Hospital for Children, Wilmington, DE), Annet Van Royen (Wilhelmina Children's Hospital, Utrecht, The Netherlands), Basil Fathalla (Detroit Medical Center, Detroit, MI), Berit Flatø (RiksHospitalet University Hospital, Oslo, Norway), Blanca Elena Rios Gomes Bica (Federal University of Rio de Janeiro, Rio de Janeiro, Brazil), Brigitte Bader-Meunier (Hôpital Robert Debré, Paris, France), Carmen Laura De Cunto (Hospital Italiano, Buenos Aires, Argentina), Carol Wallace (Children's Hospital and Regional Medical Center, Seattle, WA), Carolina Duarte Salazar (Instituto Nacional de Rehabilitación, Mexico City, Mexico), Cassia M. P. L. Barbosa (UNIFESP, Sao Paulo, Brazil), Cecilia Coto Hermosilla (Hospital Pedro Borras Astorga, Habana, Cuba), Christian Hümer (Abteilung fur Pädiatrie, Vorarlberg, Austria), Christina Boros (University of Adelaide, Adelaide, South Australia, Australia), Claire LeBlanc (University of Alberta, Edmonton, Alberta, Canada), Claudio A. Len (UNIFESP, Sao Paulo, Brazil), Consuelo Modesto (Hospital Vall d'Hebron, Barcelona, Spain), Deborah McCurdy (Mattel Children's Hospital, Los Angeles, CA), Daniel Kingsbury (Legacy Emanuel Children's Hospital, Portland, OR), Daniel Lovell (Children's Hospital of Cincinnati, Cincinnati, OH), David Cabral (British Columbia Children's Hospital, Vancouver, British Columbia, Canada), David Sherry (Children's Hospital of Philadelphia, Philadelphia, PA), Deborah Rothman (Shriner's Hospital for Children, Springfield, MA), Delfor Alberto Giacomone (Hospital de Niños Sor María Ludovica, La Plata, Argentina), Diana Milojevic (University of California, San Francisco), Dorothee Stichweh (Children's Medical Center, Dallas, TX), Dowain Wright (Children's Hospital Central California, Madera), Dolores Teresa Cantera Oceguera (Hospital Pedro Borras Astorga, Habana, Cuba), Edsel Arce (Children's Hospital Central California, Madera), Elizabeth Chalom (Saint Barnabas Medical Center, Livingston, NJ), Emilia Spangenberg (Sociedad Uruguaya de Reumatología, Montevideo, Uruguay), Esi Morgan DeWitt (Children's Hospital of Cincinnati, Cincinnati, OH), Eyal Muscal (Baylor College of Medicine, Houston, TX), Frank Dressler (Medizinische Hochschule Hannover, Hannover, Germany), Gaelle Chedeville (Montreal Children's Hospital, Montreal, Quebec, Canada), Gail Faller (Chris Hani Baragwanath Hospital, Johannesburg, South Africa), Gary Sterba (Hospital J. M. de los Rios, Caracas, Venezuela), Gerd Horneff (Asklepios Klinik für Kinder, Sankt Augustin, Germany), Giovany Beltrán Avendaño (Bogotá, Columbia), Harry L. Gewanter (Pediatric and Adolescent Health Center, Midlothian, VA), Hartmut Michels (Mengel E. Rheumatic Children's Hospital, Garmisch-Partenkirchen, Germany), Germann Girschick (University of Würzburg, Würzburg, Germany), Irama Maldonado (Centro Nacional de Enfermedades Reumáticas, Caracas, Venezuela), Ivan Foeldvari (Kinder- & Jugendrheumatologie, Hamburg, Germany), Jaime de Inocencio (Centro de Salud Jazmín, Madrid, Spain), Janis Dionne (British Columbia Children's Hospital, Vancouver, British Columbia, Canada), Jelena Vojinovic (University of Niš, Serbia), Jennifer Huggins (Children's Hospital of Cincinnati, Cincinnati, OH), Jennifer Weiss (Joseph M. Sanzari Children's Hospital, Hackensack, NJ), Jenny Soep (Children's Hospital Colorado, Aurora), James N. Jarvis (Oklahoma University Health Sciences Center, Oklahoma City), Jing-Long Huang (Chang Gung Children's Hospital, Taoyuang Hsien, Taiwan), Johannes Roth (University Hospital Münster, Münster, Germany), Jordi Antón (Hospital Sant. Joan de Déu, Barcelona, Spain), Jose Goldenberg (Hospital Israelita, Sao Paulo, Brazil), Joyce Hsu (Lucile Packard Children's Hospital, Palo Alto, CA), Judy Olson (Medical College of Wisconsin, Milwaukee), Juliana Sato (Istituto G. Gaslini, Genoa, Italy), Kathleen A. Haines (New York University, New York), Kelly Rouster-Stevens (Wake Forest University Baptist Medical Center, Winston-Salem, NC), Ken Schikler (University of Louisville, Louisville, KY), Isabelle Kone-Paut (Hôpital de Bicêtre, Le Kremlin Bicêtre, France), L. Nandini Moorthy (Robert Wood Johnson Medical School, New Brunswick, NJ), Lawrence Jung (National Children's Hospital, Washington, DC), Lenore Buckley (Virginia Commonwealth University School of Medicine, Richmond), Leonard H. Sigal (Robert Wood Johnson Medical Group, New Brunswick, NJ), Leslie Abramson (Vermont Children's Hospital, Burlington), Linda Wagner-Weiner (University of Chicago, Chicago, IL), Liora Harel (Schneider Children's Medical Center, Petah Tikva, Israel), Lisa Rider (National Institutes of Health, Bethesda, MD), Manuel Ferrandiz (Instituto de Salud del Niño, Lima, Peru), Mara Becker (The Children's Mercy Hospital, Kansas City, MO), Lori Tucker (British Columbia Children's Hospital, Vancouver, British Columbia, Canada), María Martha Katsicas (Hospital de Pediatría “Prof. Dr. Juan P. Garrahan,” Buenos Aires, Argentina), Maria Odete Esteves Hilario (Universidade Federal de São Paulo, São Paulo, Brazil), Maria Teresa Apaz (Universidad Católica Clinica Reina Fabiola, Cordoba, Argentina), Maria Teresa Terreri (Universidade Federal de São Paulo, São Paulo, Brazil), Mario J. Moreno (Hurtado 202 y Machala Edificio Crespo 1er, Ceunca, Ecuador), Mathew Adams (Children's Hospital of Michigan, Detroit), Matthew Stoll (Children's Medical Center Dallas, Dallas, TX), Marilynn Punaro (Texas Scottish Rite Hospital, Dallas), Mauricio Alegria Mendoza (Colonia Médica, San Salvador, El Salvador), Melissa Elder (University of Florida, Gainesville), Michael Henrickson (Children's Hospital of Cincinnati, Cincinnati, OH), Michael S. Borzy (Ohio State University, Columbus), Monica Patricia Velasquez Mendez (Universidad Nacional De Colombia, Bogotá, Columbia), Nico Wulffraat (UMC Utrecht, Utrecht, The Netherlands), Nicola Ruperto (University of Genoa, Genoa, Italy), Norm Ilowite (Children's Hospital at Montefiore, New York, NY), Patricia Woo (Great Ormond Street Children Hospital, London, UK), Pavla Dolezalova (Charles University in Prague, Prague, Czech Republic), Peter Blier (Baystate Children's Hospital, Springfield, MA), Peter Chira (Stanford University, Palo Alto, CA), Pilar Guarnizo (Universidad del Rosario Bogotá, Bogotá, Columbia), Polly Ferguson (University of Iowa, Iowa City), Prieur Anne-Marie (Hôpital Necker-Enfants-Malades, Paris, France), Hans-Iko Huppertz (Hess-Kinderklinik, Bremen, Germany), Pierre Quartier (Hôpital Necker-Enfants Malades, Paris, France), Raju Khubchandani (Jaslok Hospital and Research Center, Mumbai, India), Randy Cron (University of Alabama, Birmingham), Raphael Hirsch (Children's Hospital Pittsburgh, Pittsburgh, PA), Raúl Gutiérrez (Suárez Hospital General de México, México City, México), Ricardo Russo (Hospital de Pediatría “Prof. Dr. Juan P. Garrahan,” Buenos Aires, Argentina), Richard Vehe (University of Minnesota, Minneapolis-St. Paul), Richard Vesely (Detska Fakultna Nemocnica, Košice, Slovakia), Rik Joos (Jan Palfijn Ziekenhuis, Merksem, Belgium), Rita Jerath (Medical College of Georgia, Augusta), Riva Brik (Rambam Medical Center, Haifa, Israel), Rob Nickeson (University of South Florida, Tampa), Robert Sundel (Boston Children's Hospital, Boston, MA), Roberto Carreño Manjarrez (Hospital Infantil de Mexico, Mexico City, Mexico), Rolando Cimaz (AOU Meyer and University of Florence, Florence, Italy), Rosario Jurado (Sanitorio Americano, Montevideo, Uruguay), Rotraud K. Saurenmann (University Children's Hospital, Zurich, Switzerland), Ruben Burgos-Vargas (Hospital General de México, México City, México), Ruben Cuttica (Hospital General de Niños Pedro de Elizalde, Buenos Aires, Argentina), Ruth Eraso (Universidad De Antioquia, Medellín, Colombia), Sheila Knupp Feitosa de Oliveira (Instituto de Puericultura e Pediatria Martagão Gesteira, Rio de Janeiro, Brazil), Shirley Tse (Hospital for Sick Children, Toronto, Ontario, Canada), Silvia Magni-Manzoni (Fondazione IRCCS Policlinico San Matteo, Pavia, Italy), Silvia Meiorin (Hospital de Niños Ricardo Gutierrez, Buenos Aires, Argentina), Stacy Ardoin (Ohio State University, Columbus), Stefan Hagelberg (Karolinska University Hospital, Stockholm, Sweden), Stella M. Garay (Hospital Sor Maria Ludovica, La Plata, Argentina), Susa Benseler (Hospital for Sick Children, Toronto, Ontario, Canada), Susan Nielsen (Juliane Marie Centret, RigsHospitalet, Copenhagen, Denmark), Terry L. Moore (St. Louis University School of Medicine, St. Louis, MO), Thomas Griffin (Children's Hospital of Cincinnati, Cincinnati, OH), Tim Beukelman (University of Alabama, Birmingham), Tracy Ting (Children's Hospital of Cincinnati, Cincinnati, OH), Witske Kuis (Wilhelmina Children's Hospital, Utrecht, The Netherlands), Wineke Armbrust (University Medical Center Groningen, Groningen, The Netherlands), Yosef Uziel (Sapir Medical Center, Kfar Saba, Israel), Yuki Kimura (Hackensack University Medical Center, Hackensack, NJ.)

Other acknowledgments include Joshua Pendl, Jamie Meyers-Eaton (site coordination and database management), Lukasz Itert (survey management), Cincinnati Children's Hospital Medical Center (CCHMC) Biomedical Informatics (web-based data management application development), Jill Segerman (editorial support with the manuscript preparation): CCHMC; Marilynn Punaro (data collection), Shirley Henry (site coordination): Texas Scottish Rite Hospital; Becky Pupluva (site coordination): University of Chicago Comer Children's Hospital; Dina Blair (site coordination): Children's Memorial Hospital; Lori Tucker (data collection), America Uribe (site coordination): British Columbia Children's Hospital; Deborah Levy, Any Eichenfield (data collection): Morgan Stanley Children's Hospital; Elizabeth Brooks, Kabita Nanda, Nellie Coughlin (data collection): MetroHealth Medical Center and Case Western Reserve University; Lauren Kickingbird Walters, Kimberly Benjamin (site coordination): University of Oklahoma Health Sciences Center; and Janet Wooton (site coordination): Duke Medical Center.

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  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

Additional Supporting Information may be found in the online version of this article.

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ACR_21612_sm_SupplData.doc494KSupplementary Data

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