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MRI was analyzed using semi\u2010automated methods. Correlations of PST score with PROMs and MRI metrics were examined using Spearman\u2019s rho. Wilcoxon rank sum testing compared MRI metrics across PST score quartiles and linear regression models identified predictors of PST performance. Effects of employment and depression were also investigated.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In 721 patients (mean age 47.6\u00a0\u00b1\u00a011.4\u00a0years), PST scores were significantly correlated with all MRI metrics, including cord atrophy and deep gray matter volumes. Linear regression demonstrated self\u2010reported physical disability, cognitive function, fatigue and social domains (adjusted <jats:italic>R<\/jats:italic><jats:sup>2<\/jats:sup><jats:italic>\u00a0=\u00a0<\/jats:italic>0.44, <jats:italic>P<\/jats:italic>\u00a0&lt;\u00a00.001) as the strongest clinical predictors of PST score, whereas that of MRI variables included T2 lesion volume, whole\u2010brain fraction and cord atrophy (adjusted <jats:italic>R<\/jats:italic><jats:sup>2<\/jats:sup><jats:italic>\u00a0=\u00a0<\/jats:italic>0.42, <jats:italic>P<\/jats:italic>\u00a0&lt;\u00a00.001). An inclusive model identified T2 lesion volume, whole\u2010brain fraction, self\u2010reported upper extremity function, cognition and social participation as the strongest predictors of PST score (adjusted <jats:italic>R<\/jats:italic><jats:sup>2<\/jats:sup><jats:italic>\u00a0=\u00a0<\/jats:italic>0.51, <jats:italic>P<\/jats:italic>\u00a0&lt;\u00a00.001). There was significant effect modification by depression on the relationship between self\u2010reported cognition and PST performance. Employment status was associated with PST scores independent of age and physical disability.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The PST score correlates with PROMs, MRI measures of focal and diffuse brain injury, and employment. The PST score is a feasible and meaningful measure for routine multiple sclerosis care.<\/jats:p><\/jats:sec>","DOI":"10.1111\/ene.14239","type":"journal-article","created":{"date-parts":[[2020,3,28]],"date-time":"2020-03-28T08:21:32Z","timestamp":1585383692000},"page":"1238-1249","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Cognitive processing speed in multiple sclerosis clinical practice: association with patient\u2010reported outcomes, employment and magnetic resonance imaging metrics"],"prefix":"10.1111","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7303-2332","authenticated-orcid":false,"given":"G.","family":"Macaron","sequence":"first","affiliation":[{"name":"Mellen Center for Multiple Sclerosis Neurological Institute Cleveland Clinic Cleveland OH USA"},{"name":"Faculty of Medicine Universit\u00e9 Saint Joseph de Beyrouth Beirut Lebanon"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"L. 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