Michelle Petri1, Daniel W Goldman1, Graciela S Alarcón2, Caroline Gordon3, Joan T Merrill4, Paul R Fortin5, Ian N Bruce6, David Isenberg7, Daniel Wallace8, Ola Nived9, Rosalind Ramsey-Goldman10, Sang-Cheol Bae11, John G Hanly12, Jorge Sanchez-Guerrero13, Ann E Clarke14, Cynthia Aranow15, Susan Manzi16, Murray Urowitz13, Dafna D Gladman13, Ken Kalunian17, Victoria P Werth18, Asad Zoma19, Sasha Bernatsky20, Munther Khamashta21, Søren Jacobsen22, Jill P Buyon23, Mary Anne Dooley24, Ronald van Vollenhoven25, Ellen Ginzler26, Thomas Stoll27, Christine Peschken28, Joseph L Jorizzo29, Jeffery P Callen30, Sam Lim31, Murat Inanç32, Diane L Kamen33, Anisur Rahman7, Kristjan Steinsson34, Andrew G Franks23, Laurence S Magder35. 1. Johns Hopkins University, Baltimore, Maryland. 2. University of Alabama at Birmingham. 3. University of Birmingham, Birmingham, UK. 4. Oklahoma Medical Research Foundation, Oklahoma City. 5. CHU de Québec - Université Laval, Quebec City, Quebec, Canada. 6. The University of Manchester and Manchester University Hospital NHS Foundation Trust, Manchester Academic Health Science Center, Manchester, UK. 7. University College, London, UK. 8. Cedars-Sinai and University of California, Los Angeles. 9. Lund University, Lund, Sweden. 10. Northwestern University, Chicago, Illinois. 11. Hanyang University Hospital for Rheumatic Diseases, Seoul, Republic of Korea. 12. Queen Elizabeth II Health Sciences Centre and Dalhousie University, Halifax, Nova Scotia, Canada. 13. Centre for Prognosis Studies in the Rheumatic Diseases, Toronto Western Hospital and University of Toronto, Toronto, Ontario, Canada. 14. University of Calgary, Calgary, Alberta, Canada. 15. Feinstein Institute for Medical Research, Manhasset, New York. 16. Allegheny Health Network, Pittsburgh, Pennsylvania. 17. University of California at San Diego, La Jolla. 18. Hospital of the University of Pennsylvania and Department of Veterans Affairs Medical Center, Philadelphia. 19. Lanarkshire Centre for Rheumatology, Hairmyres Hospital, East Kilbride, Scotland, UK. 20. McGill University Health Centre, Montreal, Quebec, Canada. 21. The Rayne Institute, St Thomas' Hospital, King's College London, London, UK. 22. Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark. 23. New York University, New York, New York. 24. University of North Carolina, Chapel Hill. 25. Amsterdam University Medical Centres, University of Amsterdam, Free University, and Amsterdam Rheumatology and Immunology Center, Amsterdam, The Netherlands. 26. State University of New York Downstate Medical Center, Brooklyn. 27. Kantonsspital, Schaffhausen, Switzerland. 28. University of Manitoba, Winnipeg, Manitoba, Canada. 29. Wake Forest University, Winston-Salem, North Carolina, and Weill Cornell Medicine, New York, New York. 30. University of Louisville, Louisville, Kentucky. 31. Emory University, Atlanta, Georgia. 32. Istanbul University, Istanbul, Turkey. 33. Medical University of South Carolina, Charleston. 34. Fossvogur Landspitali University Hospital, Reyjkavik, Iceland. 35. University of Maryland, Baltimore.
Abstract
OBJECTIVE: The Systemic Lupus International Collaborating Clinics (SLICC) 2012 systemic lupus erythematosus (SLE) classification criteria and the revised American College of Rheumatology (ACR) 1997 criteria are list based, counting each SLE manifestation equally. We derived a classification rule based on giving variable weights to the SLICC criteria and compared its performance to the revised ACR 1997, the unweighted SLICC 2012, and the newly reported European Alliance of Associations for Rheumatology (EULAR)/ACR 2019 criteria sets. METHODS: The physician-rated patient scenarios used to develop the SLICC 2012 classification criteria were reemployed to devise a new weighted classification rule using multiple linear regression. The performance of the rule was evaluated on an independent set of expert-diagnosed patient scenarios and compared to the performance of the previously reported classification rules. RESULTS: The weighted SLICC criteria and the EULAR/ACR 2019 criteria had less sensitivity but better specificity compared to the list-based revised ACR 1997 and SLICC 2012 classification criteria. There were no statistically significant differences between any pair of rules with respect to overall agreement with the physician diagnosis. CONCLUSION: The 2 new weighted classification rules did not perform better than the existing list-based rules in terms of overall agreement on a data set originally generated to assess the SLICC criteria. Given the added complexity of summing weights, researchers may prefer the unweighted SLICC criteria. However, the performance of a classification rule will always depend on the populations from which the cases and non-cases are derived and whether the goal is to prioritize sensitivity or specificity.
OBJECTIVE: The Systemic Lupus International Collaborating Clinics (SLICC) 2012 systemic lupus erythematosus (SLE) classification criteria and the revised American College of Rheumatology (ACR) 1997 criteria are list based, counting each SLE manifestation equally. We derived a classification rule based on giving variable weights to the SLICC criteria and compared its performance to the revised ACR 1997, the unweighted SLICC 2012, and the newly reported European Alliance of Associations for Rheumatology (EULAR)/ACR 2019 criteria sets. METHODS: The physician-rated patient scenarios used to develop the SLICC 2012 classification criteria were reemployed to devise a new weighted classification rule using multiple linear regression. The performance of the rule was evaluated on an independent set of expert-diagnosed patient scenarios and compared to the performance of the previously reported classification rules. RESULTS: The weighted SLICC criteria and the EULAR/ACR 2019 criteria had less sensitivity but better specificity compared to the list-based revised ACR 1997 and SLICC 2012 classification criteria. There were no statistically significant differences between any pair of rules with respect to overall agreement with the physician diagnosis. CONCLUSION: The 2 new weighted classification rules did not perform better than the existing list-based rules in terms of overall agreement on a data set originally generated to assess the SLICC criteria. Given the added complexity of summing weights, researchers may prefer the unweighted SLICC criteria. However, the performance of a classification rule will always depend on the populations from which the cases and non-cases are derived and whether the goal is to prioritize sensitivity or specificity.