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AB0759 (2024)
USING MACHINE LEARNING TO PREDICT SUSTAINED REMISSION IN RHEUMATOID ARTHRITIS PATIENTS TREATED WITH BIOLOGIC THERAPIES
Keywords: Remission, Biological DMARD, Artificial Intelligence
F. Z. Aharrane1, F. E. Abourazzak2, T. Fatima Zahrae2, A. Amar3, I. Hmamouchi4, I. El Bouchti5, Z. Baba6, F. Allali7, R. Bahiri7, A. Bezza8, A. El Maghraoui9, I. Ghozlani10, H. Hassikou11, T. Harzy12, I. Linda13, S. Janani14, R. Niamane15, R. Abouqal16
1Mohammed VI University Hospital Center, Rheumatology, Tangier, Morocco
2Mohammed VI University Hospital Center, Rheumatology, Tangier, Morocco
3Al Akhawayn University, School of Sciences and Engineering, Ifrane, Morocco
4International University of Rabat (UIR), Faculty of Medicine, Health Sciences Research Center (CReSS), Rabat, Morocco
5Mohammed VI University Hospital Center, Rheumatology, Marrakech, Morocco
6Mohammed VI University Hospital Center, Rheumatology, Marrakech, Morocco
7Al Ayachi Hospital, Rheumatology, Salé, Morocco
8Military Hospital Mohammed V, Rheumatology, Rabat, Morocco
9Military Hospital Mohammed V, Rheumatology, Rabat, Morocco
10University Hospital Center of Agadir, Rheumatology, Agadir, Morocco
11Military Hospital Moulay Ismail, Rheumatology, Meknes, Morocco
12Hassan II University Hospital Center, Rheumatology, Fez, Morocco
13Mohammed VI University Hospital Center, Rheumatology, Oujda, Morocco
14Ibn Rochd University Hospital Center, Rheumatology, Casablanca, Morocco
15Military Hospital Avicenne, Rheumatology, Marrakech, Morocco
16Faculty of Medicine and Pharmacy, Mohammed V University, Laboratory of Biostatistics, Clinical Research and Epidemiology, Rabat, Morocco

Background: Sustained remission is the primary therapeutic goal for patients with rheumatoid arthritis (RA). Although several studies have identified factors associated with treatment response in rheumatoid arthritis (RA), there are no precise predictive models for sustained remission in patients treated with biologic therapies.


Objectives: Evaluating the performance of machine learning to predict short-term sustained remission in rheumatoid arthritis patients under biological disease modifying antireumatic drugs (bDMARDS).


Methods: We included patients with rheumatoid arthritis, who started biological disease modifying antireumatic drugs, from the Moroccan registry of biological therapies, with a follow-up of at least 1 year and an evaluation in at least two consecutive visits with an interval of 6 months. Sustained remission was defined as DAS28 < 2.6 on two consecutive visits. Demographic and clinical characteristics were collected at treatment baseline, 6-month, and 12-month follow-up. Four different machine-learning algorithms, namely, logistic regression, Random Forest, K Nearest Neighbors and AdaBoost, were trained and validated to predict remission at 12 months. The algorithms performance was then compared by assessing accuracy, precision and recall.


Results: We included 130 patients (88.5% female); mean age ± SD was 51.52 ± 10.86 years. 38 patients (29.2%) achieved sustained remission. The set of variables used to train the algorithms included initial DAS 28, rheumatoid factor and anti-citrullinated peptides antibodies positivity, Health Assessment Questionnaire-Disability Index, type and number of biotherapies, Methotrexate use, as well as several clinical features. Adaboost showed the best performance (accuracy, 75%; precision, 75%; recall, 100%), outperforming Random Forest (accuracy, 57%; precision, 75%; recall, 60%), K-nearest neighbors (accuracy, 57%; precision, 33%; recall, 100%) and logistic regression (accuracy, 29%; precision, 33%; recall, 25%).


Conclusion: Machine-learning models can be used to predict sustained remission in rheumatoid arthritis patients on biotherapy.


REFERENCES: NIL.


Acknowledgements: NIL.


Disclosure of Interests: None declared.

DOI: 10.1136/annrheumdis-2024-eular.2367
Keywords: Remission, Biological DMARD, Artificial Intelligence
Citation: , volume 83, supplement 1, year 2024, page 1671
Session: Rheumatoid arthritis (Publication Only)