{"id":1355,"date":"2012-11-11T06:17:39","date_gmt":"2012-11-11T06:17:39","guid":{"rendered":"http:\/\/mathematicalneurooncology.org\/?p=1355"},"modified":"2012-11-16T17:16:16","modified_gmt":"2012-11-16T17:16:16","slug":"discriminating-time-to-progression-and-survival-using-a-response-metric-tuned-to-patient-specific-glioblastoma-kinetics","status":"publish","type":"post","link":"https:\/\/mathematicalneurooncology.org\/?p=1355","title":{"rendered":"Discriminating time to progression and survival using a response metric tuned to patient-specific glioblastoma kinetics"},"content":{"rendered":"<p>New manuscript published in PLoS ONE (in press).<\/p>\n<p style=\"text-align: center;\"><strong>Discriminating time to progression and survival using a response metric tuned to patient-specific glioblastoma kinetics<\/strong><\/p>\n<p style=\"text-align: center;\">Neal ML, Trister AD, Cloke T, Sodt R, Ahn S, Baldock AL, Bridge CA, Boone A, Rockne R, Swanson KR.<\/p>\n<p style=\"text-align: left;\">Accurate clinical assessment of a patient\u2019s response to treatment for glioblastoma multiforme (GBM), the most malignant type of primary brain tumor, is undermined by the wide patient-to-patient variability in GBM dynamics and responsiveness to therapy. Using computational models that account for the unique geometry and kinetics of individual patients\u2019 tumors, we developed a method for assessing response that discriminates progression-free and overall survival following therapy for GBM. Applying these models as untreated virtual controls, we generate a patient-specific \u201cDays Gained\u201d response metric that estimates the number of days a therapy delayed imageable tumor progression. We assessed treatment response in terms of Days Gained scores for 33 patients at the time of their first MRI scan following first-line radiation therapy. Based on Kaplan-Meier analyses, patients with significant treatment response (characterized by Days Gained scores of 100 or more) had improved progression-free survival and improved overall survival. Our results demonstrate that the Days Gained response metric calculated at the routinely acquired first post-radiation treatment time point provides prognostic information regarding progression and survival outcomes. Applied prospectively, our model-based approach has the potential to improve GBM treatment by accounting for patient-to-patient heterogeneity in GBM dynamics and responses to therapy.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>New manuscript published in PLoS ONE (in press). Discriminating time to progression and survival using a response metric tuned to patient-specific glioblastoma kinetics Neal ML, Trister AD, Cloke T, Sodt R, Ahn S, Baldock AL, Bridge CA, Boone A, Rockne R, Swanson KR. Accurate clinical assessment of a patient\u2019s response to treatment for glioblastoma multiforme &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/mathematicalneurooncology.org\/?p=1355\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Discriminating time to progression and survival using a response metric tuned to patient-specific glioblastoma kinetics&#8221;<\/span><\/a><\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[4,1],"tags":[],"_links":{"self":[{"href":"https:\/\/mathematicalneurooncology.org\/index.php?rest_route=\/wp\/v2\/posts\/1355"}],"collection":[{"href":"https:\/\/mathematicalneurooncology.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mathematicalneurooncology.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mathematicalneurooncology.org\/index.php?rest_route=\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/mathematicalneurooncology.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1355"}],"version-history":[{"count":5,"href":"https:\/\/mathematicalneurooncology.org\/index.php?rest_route=\/wp\/v2\/posts\/1355\/revisions"}],"predecessor-version":[{"id":1358,"href":"https:\/\/mathematicalneurooncology.org\/index.php?rest_route=\/wp\/v2\/posts\/1355\/revisions\/1358"}],"wp:attachment":[{"href":"https:\/\/mathematicalneurooncology.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1355"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mathematicalneurooncology.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1355"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mathematicalneurooncology.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1355"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}