Factors Associated With Switching From Injectable to Oral Disease Modifying Agents Among Patients With Multiple Sclerosis

Assessing treatment switch among patients with multiple sclerosis: A machine learning approach

“…This finding is consistent with previous studies that recognize the importance of age on the treatment patterns in MS patients. 13 , 16 , 17 , 18 A systematic review found that age could impact MS progression, immunosenescence, and DMA selection and engagement. 66 Also, the progression of the disease is observed to be slower among older MS patients than among young and middle-aged MS patients, which might decrease the need for treatment switching among older patients.…”

“…Moreover, the type of index medication and the year of the index date were observed as the other two top important factors in predicting treatment switching, which could be explained by the introduction of the first oral DMA in 2010. 18 This might also be due to the prescriber's experience and the availability of oral DMAs on the market. Many MS patients switched from injectable to oral DMAs after the launch of oral DMAs.…”

“…Secondly, though the rate of treatment switching was low compared to prior research using claims data, the study finding was consistent with previous analyses using electronic medical records. 18 Thirdly, this study developed and compared models in predicting any DMA switching among patients with MS; future studies should compare the treatment switching with different types of DMAs to improve MS care. Fourth, this study evaluated the model performance with an internal validation dataset; more work is needed applying those models with an external dataset to implement the model when predicting treatment switching.…”

“…A total of 72 variables were selected for training the ML modelbased on a review of existing literature that identified factors assocated with treatment switching in MS. 13 , 18 , 31 , 35 These factors were further conceptualized based on the Andersen Behavioral Model (ABM) of Health Services Use, which provides a strong conceptual foundation for predicting treatment switching. 36 According to the ABM, healthcare utilization depends on predisposing, enabling, and need factors.…”

“… 11 Moreover, previous studies based on the traditional regression models identified that age, sex, year of index, relapse, and MS severity were associated with treatment switching among MS patients. 16 , 17 , 18 …”