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P65 Cluster-based propensity score analysis of glucocorticoid usage and lupus remission: a pilot study
  1. Halbert Hernández-Negrin1,2,3,
  2. Diana Paredes-Ruiz3,
  3. Maria Herrero-Galvan4,
  4. Victor Moreno-Torres3,5,6,
  5. Ioana Ruiz-Arruza3,4,
  6. Cedric Leonard7,
  7. Pierre Duffau7,
  8. Christophe Richez7,
  9. Patrick Blanco7,
  10. Estibaliz Lazaro7 and
  11. Guillermo Ruíz-Irastorza3,4
  1. 1Systemic Autoimmune Diseases Unit, Internal Medicine Clinical Management Unit, Hospital Regional Universitario de Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA-Plataforma BIONAND), Malaga, Spain
  2. 2Faculty of Medicine, Universidad de Málaga, Malaga, Spain
  3. 3Autoimmune Diseases Research Unit, Dept. of Internal Medicine, Biocruces Bizkaia Health Research Institute, Hospital Universitario Cruces, Bizkaia, Spain
  4. 4Universidad del País Vasco/Euskal Herriko Unibertsitatea, Bizkaia, Spain
  5. 5UNIR Health Sciences School, Madrid, Spain
  6. 6Systemic Autoimmune Diseases Unit, Internal Medicine Dept., Hospital Universitario Puerta de Hierro Majadahonda, Madrid, Spain
  7. 7Bordeaux Hospital University, FHU ACRONIM, France

Abstract

Objective This study aimed to determine the impact of glucocorticoid (GC) usage patterns within the first year of diagnosis on achieving prolonged remission in patients with systemic lupus erythematosus (SLE).

Methods We conducted an observational study of routine clinical care data of the Lupus Cruces-Bordeaux cohort including those patients with an SLEDAI-2K>4 at diagnosis. Prolonged remission was defined as remission (according to DORIS criteria) achieved within the first year and maintained in five consecutive yearly visits. Clusters of GC usage in the first year of diagnosis were determined, considering the maximum prednisone dosage, cumulative dosage, number of methylprednisolone pulses and the maximum pulse dosage. Hierarchical and k-means clustering techniques were employed for this purpose. Subsequently, binary logistic regression was used to obtain a propensity score for belonging to one of these clusters, incorporating critical clinical and laboratory variables that might influence the choice of one GC usage patterns over another. Propensity score matching was performed, ensuring a 1:1 ratio with a caliper of 0.2. Variables effect sizes in both groups were assessed using standardized difference measures. Generalized linear models were used to determine the association between GC usage patterns and prolonged remission, adjusted for other covariables and treatments.

Results Out of 233 patients in the full cohort. 125 patients with an SLEDAI-2K>4 at diagnosis were selected. Two patterns of GC use were identified, and 33 patients were analyzed in each of them after propensity score matching was performed. Our analysis revealed that a GC usage pattern characterized by a lower cumulative prednisone dosage, reduced maximum prednisone dosage and a higher number of methylprednisolone pulses was associated with an increased likelihood of achieving prolonged remission. The results are presented in detail within table 1 and figure 1.

Conclusions This study underscores the significant impact of early GC management patterns in achieving prolonged remission among SLE patients. Identifying clusters of GC usage provides insights into optimizing treatment strategies and promoting sustained remission. The findings emphasize the importance of tailored GC regimens to improve long-term outcomes in SLE patients.

Acknowledgements Dr. Ruiz-Irastorza was supported by the Department of Education of the Basque Government, research grant IT 1512–22. Dr. Hernandez-Negrin was supported by Consejería de Transformación Económica, Industria, Conocimiento y Universidades. Junta de Andalucía-Sevilla (Spain), research grant PREDOC-00826.

View this table:
Abstract P65 Table 1

Baseline characteristics of study subjects (before and after Propensity Score matching)

Abstract P65 Figure 1
Abstract P65 Figure 1

Forest plot: impact of glucocorticoid pattern on prolonged SLE remission

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/lupus-2024-el.119

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