A Flare Risk Index Informed by Select Immune Mediators in Systemic Lupus Erythematosus.
Journal
Arthritis & rheumatology (Hoboken, N.J.)
ISSN: 2326-5205
Titre abrégé: Arthritis Rheumatol
Pays: United States
ID NLM: 101623795
Informations de publication
Date de publication:
05 2023
05 2023
Historique:
revised:
09
09
2022
received:
07
07
2021
accepted:
06
10
2022
pmc-release:
01
05
2024
medline:
17
5
2023
pubmed:
18
10
2022
entrez:
17
10
2022
Statut:
ppublish
Résumé
Systemic lupus erythematosus (SLE) is marked by immune dysregulation linked to varied clinical disease activity. Using a unique longitudinal cohort of SLE patients, this study sought to identify optimal immune mediators informing an empirically refined flare risk index (FRI) reflecting altered immunity prior to clinical disease flare. Thirty-seven SLE-associated plasma mediators were evaluated by microfluidic immunoassay in 46 samples obtained in SLE patients with an imminent clinical disease flare (preflare) and 53 samples obtained in SLE patients without a flare over a corresponding period (pre-nonflare). SLE patients were selected from a unique longitudinal cohort of 106 patients with classified SLE (meeting the American College of Rheumatology 1997 revised criteria for SLE or the Systemic Lupus International Collaborating Clinics 2012 revised criteria for SLE). Autoantibody specificities, hybrid SLE Disease Activity Index (hSLEDAI) scores, clinical features, and medication usage were also compared at preflare (mean ± SD 111 ± 47 days prior to flare) versus pre-nonflare (99 ± 21 days prior to nonflare) time points. Variable importance was determined by random forest analysis with logistic regression subsequently applied to determine the optimal number and type of analytes informing a refined FRI. Preflare versus pre-nonflare differences were not associated with demographics, autoantibody specificities, hSLEDAI scores, clinical features, nor medication usage. Forward selection and backward elimination of mediators ranked by variable importance resulted in 17 plasma mediator candidates differentiating preflare from pre-nonflare visits. A final combination of 11 mediators best informed a newly refined FRI, which achieved a maximum sensitivity of 97% and maximum specificity of 98% after applying decision curve analysis to define low, medium, and high FRI scores. We verified altered immune mediators associated with imminent disease flare, and a subset of these mediators improved the FRI to identify SLE patients at risk of imminent flare. This molecularly informed, proactive management approach could be critical in prospective clinical trials and the clinical management of lupus.
Identifiants
pubmed: 36245261
doi: 10.1002/art.42389
pmc: PMC10106527
mid: NIHMS1843086
doi:
Substances chimiques
Immunologic Factors
0
Autoantibodies
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
723-735Subventions
Organisme : NIGMS NIH HHS
ID : U54 GM104938
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI144292
Pays : United States
Organisme : NIAMS NIH HHS
ID : P30 AR073750
Pays : United States
Organisme : NIAID NIH HHS
ID : R44 AI142967
Pays : United States
Organisme : NIAMS NIH HHS
ID : R01 AR077518
Pays : United States
Informations de copyright
© 2022 American College of Rheumatology.
Références
Bruce IN, O'Keeffe AG, Farewell V, et al. Factors associated with damage accrual in patients with systemic lupus erythematosus: results from the Systemic Lupus International Collaborating Clinics (SLICC) Inception Cohort. Ann Rheum Dis 2015;74:1706-13.
Steiman AJ, Gladman DD, Ibañez D, et al. Prolonged serologically active clinically quiescent systemic lupus erythematosus: frequency and outcome. J Rheumatol 2010;37:1822-7.
Koelmeyer R, Nim HT, Nikpour M, et al. High disease activity status suggests more severe disease and damage accrual in systemic lupus erythematosus. Lupus Sci Med 2020;7:e000372.
Kan HJ, Song X, Johnson BH, et al. Healthcare utilization and costs of systemic lupus erythematosus in Medicaid. BioMed Res Int 2013;2013:808391.
Thanou A, Jupe E, Purushothaman M, et al. Clinical disease activity and flare in SLE: current concepts and novel biomarkers [review]. J Autoimmun 2021;119:102615.
Munroe ME, Vista ES, Guthridge JM, et al. Proinflammatory adaptive cytokines and shed tumor necrosis factor receptors are elevated preceding systemic lupus erythematosus disease flare. Arthritis Rheumatol 2014;66:1888-99.
Munroe ME, Vista ES, Merrill JT, et al. Pathways of impending disease flare in African-American systemic lupus erythematosus patients. J Autoimmun 2017;78:70-8.
Hochberg MC, for the Diagnostic and Therapeutic Criteria Committee of the American College of Rheumatology. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus [letter]. Arthritis Rheum 1997;40:1725.
Petri M, Orbai AM, Alarcon GS, et al. Derivation and validation of the Systemic Lupus International Collaborating Clinics classification criteria for systemic lupus erythematosus. Arthritis Rheum 2012;64:2677-86.
Thanou A, Stavrakis S, Dyer JW, et al. Impact of heart rate variability, a marker for cardiac health, on lupus disease activity. Arthritis Res Ther 2016;18:197.
Buyon JP, Petri MA, Kim MY, et al. The effect of combined estrogen and progesterone hormone replacement therapy on disease activity in systemic lupus erythematosus: a randomized trial. Ann Intern Med 2005;142:953-62.
Dysinger M, Marusov G, Fraser S. Quantitative analysis of four protein biomarkers: an automated microfluidic cartridge-based method and its comparison to colorimetric ELISA. J Immunol Methods 2017;451:1-10.
Bruner BF, Guthridge JM, Lu R, et al. Comparison of autoantibody specificities between traditional and bead-based assays in a large, diverse collection of patients with systemic lupus erythematosus and family members. Arthritis Rheum 2012;64:3677-86.
Rosner B. Fundamentals of Biostatistics. 7th ed. Boston, MA: Brooks/Cole, Cengage Learning; 2011.
Cohen J. A power primer. Psychol Bull 1992;112:155-9.
Genuer R, Poggi JM, Tuleau-Malot C. Variable selection using random forests. Pattern Recogn Lett 2010;31:2225-36.
Capitaine L, Genuer R, Thiébaut R. Random forests for high-dimensional longitudinal data. Stat Methods Med Res 2021;30:166-84.
Vickers AJ, Cronin AM, Elkin EB, et al. Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers. BMC Med Inform Decis Mak 2008;8:53.
Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Mahwah, NJ: Lawrence Erlbaum Associates; 1988.
Lu R, Guthridge JM, Chen H, et al. Immunologic findings precede rapid lupus flare after transient steroid therapy [published correction appears in Sci Rep 2019;9:17514]. Sci Rep 2019;9:8590.
Leng SX, McElhaney JE, Walston JD, et al. ELISA and multiplex technologies for cytokine measurement in inflammation and aging research [review]. J Gerontol A Biol Sci Med Sci 2008;63:879-84.
Aldo P, Marusov G, Svancara D, et al. Simple Plex(™): a novel multi-analyte, automated microfluidic immunoassay platform for the detection of human and mouse cytokines and chemokines. Am J Reprod Immunol 2016;75:678-93.
Purushothama S, Dysinger M, Chen Y, et al. Emerging technologies for biotherapeutic bioanalysis from a high-throughput and multiplexing perspective: insights from an AAPS emerging technology action program committee. Bioanalysis 2018;10:181-94.
Cao J, Seegmiller J, Hanson NQ, et al. A microfluidic multiplex proteomic immunoassay device for translational research. Clin Proteomics 2015;12:28.
Han S, Guthridge JM, Harley ITW, et al. Osteopontin and systemic lupus erythematosus association: a probable gene-gender interaction. PLoS One 2008;3:e0001757.
Wirestam L, Enocsson H, Skogh T, et al. Osteopontin and disease activity in patients with recent-onset systemic lupus erythematosus: results from the SLICC inception cohort. J Rheumatol 2019;46:492-500.
Wilkinson C, Henderson RB, Jones-Leone AR, et al. The role of baseline BLyS levels and type 1 interferon-inducible gene signature status in determining belimumab response in systemic lupus erythematosus: a post hoc meta-analysis. Arthritis Res Ther 2020;22:102.
Gordon C, Sutcliffe N, Skan J, et al. Definition and treatment of lupus flares measured by the BILAG index. Rheumatology (Oxford) 2003;42:1372-9.
Vickers AJ, Van Calster B, Steyerberg EW. Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests. BMJ 2016;352:i6.
Van Calster B, Wynants L, Verbeek JFM, et al. Reporting and interpreting decision curve analysis: a guide for investigators. Eur Urol 2018;74:796-804.
Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making 2006;26:565-74.
Rousson V, Zumbrunn T. Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies. BMC Med Inform Decis Mak 2011;11:45.
Steyerberg EW, Vickers AJ. Decision curve analysis: a discussion. Med Decis Making 2008;28:146-9.
Collins GS, Reitsma JB, Altman DG, et al. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ 2015;350:g7594.
Pauker SG, Kassirer JP. Therapeutic decision making: a cost-benefit analysis. N Engl J Med 1975;293:229-34.
Adamichou C, Bertsias G. Flares in systemic lupus erythematosus: diagnosis, risk factors and preventive strategies. Mediterr J Rheumatol 2017;28:4-12.
Arnaud L, Tektonidou MG. Long-term outcomes in systemic lupus erythematosus: trends over time and major contributors [review]. Rheumatology (Oxford) 2020;59(Suppl5):v29-38.
Hammond ER, Desta B, Near AM, et al. Frequency, severity and costs of flares increase with disease severity in newly diagnosed systemic lupus erythematosus: a real-world cohort study, United States, 2004-2015. Lupus Sci Med 2021;8:e000504.
Zeng X, Zheng L, Rui H, et al. Risk factors for the flare of systemic lupus erythematosus and its influence on prognosis: a single-center retrospective analysis. Adv Rheumatol 2021;61:43.
Costedoat-Chalumeau N, Houssiau F, Izmirly P, et al. A prospective international study on adherence to treatment in 305 patients with flaring SLE: assessment by drug levels and self-administered questionnaires. Clin Pharmacol Ther 2019;106:374-82.
Hsu CY, Lin YS, Cheng TT, et al. Adherence to hydroxychloroquine improves long-term survival of patients with systemic lupus erythematosus. Rheumatology (Oxford) 2018;57:1743-51.
Marengo MF, Waimann CA, de Achaval S, et al. Measuring therapeutic adherence in systemic lupus erythematosus with electronic monitoring. Lupus 2012;21:1158-65.
Lau CS, Mak A. The socioeconomic burden of SLE [review]. Nat Rev Rheumatol 2009;5:400-4.