2022
DOI: 10.1001/jamanetworkopen.2022.2312
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Predicting Probability of Response to Tumor Necrosis Factor Inhibitors for Individual Patients With Ankylosing Spondylitis

Abstract: IMPORTANCETumor necrosis factor inhibitors (TNFis) have revolutionized the management of ankylosing spondylitis (AS); however, the lack of notable clinical responses in approximately one-half of patients suggests important heterogeneity in treatment response. Identifying patients likely to respond or not respond to TNFis could provide opportunities to personalize treatment strategies. OBJECTIVE To develop models of the probability of short-term response to TNFi treatment in individual patients with active AS. … Show more

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Cited by 14 publications
(10 citation statements)
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“…As all these additional parameters seem differently expressed in the B27+ vs. B27− population, B27− patients might be discriminated a priori, if both genotype and phenotype-related parameters are considered. In a more recent attempt to predict probability of response to TNFi for individual patients using machine learning algorithms, the HLA-B27 genotype ranked relatively low for predicting major response if specific baseline characteristics, including CRP levels, were taken into account [18]. Classification as nonradiographic vs. radiographic axSpA had no significant impact on TNFi retention or response in our analysis, confirming data from another cohort [19].…”
Section: Discussionsupporting
confidence: 80%
“…As all these additional parameters seem differently expressed in the B27+ vs. B27− population, B27− patients might be discriminated a priori, if both genotype and phenotype-related parameters are considered. In a more recent attempt to predict probability of response to TNFi for individual patients using machine learning algorithms, the HLA-B27 genotype ranked relatively low for predicting major response if specific baseline characteristics, including CRP levels, were taken into account [18]. Classification as nonradiographic vs. radiographic axSpA had no significant impact on TNFi retention or response in our analysis, confirming data from another cohort [19].…”
Section: Discussionsupporting
confidence: 80%
“…Nevertheless, it may mitigate overfitting problems compared with the 1-stage modeling approach . Moreover, because the stage 1 risk model can be replaced by alternative models, future studies with ample sample sizes can explore advanced machine learning methods . In addition, although a bayesian framework could have been used at stage 1, we adopted a frequentist framework to leverage available penalization options in existing R packages.…”
Section: Discussionmentioning
confidence: 99%
“…IL-17 production of mucosal-associated invariant cells (MAIT) cells is mediated by IL-7 rather than IL-23 or antigenic stimulation [129]. As to TNF-α, it attributes to microvascular dysfunction and systemic inflammatory reaction [130], and TNF inhibitors could alleviate symptoms and comorbidities [131,132]. Both two pathways could inhibit bone formation, but the connection and hierarchical order between them remains elusive [127].…”
Section: Pyroptosis and Asmentioning
confidence: 99%