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dc.contributor.authorParsons, S
dc.contributor.authorKelly, M
dc.contributor.authorCohen, J
dc.contributor.authorCastellino, S
dc.contributor.authorHenderson, T
dc.contributor.authorKelly, K
dc.contributor.authorKeller, F
dc.contributor.authorHenzer, T
dc.contributor.authorKumar, A
dc.contributor.authorJohnson, P
dc.contributor.authorMeyer, R
dc.contributor.authorRadford, John A
dc.contributor.authorRaemaekers, J
dc.contributor.authorHodgson, D
dc.contributor.authorEvens, A
dc.date.accessioned2018-06-04T09:48:45Z
dc.date.available2018-06-04T09:48:45Z
dc.date.issued2018-04-29
dc.identifier.citationEarly-stage Hodgkin lymphoma in the modern era: simulation modelling to delineate long-term patient outcomes. 2018 Br J Haematolen
dc.identifier.issn1365-2141
dc.identifier.pmid29707774
dc.identifier.doi10.1111/bjh.15255
dc.identifier.urihttp://hdl.handle.net/10541/621031
dc.descriptionLymphoma Research Teamen
dc.description.abstractWe developed a novel simulation model integrating multiple data sets to project long-term outcomes with contemporary therapy for early-stage Hodgkin lymphoma (ESHL), namely combined modality therapy (CMT) versus chemotherapy alone (CA) via 18 F-fluorodeoxyglucose positron emission tomography response-adaption. The model incorporated 3-year progression-free survival (PFS), probability of cure with/without relapse, frequency of severe late effects (LEs), and 35-year probability of LEs. Furthermore, we generated estimates for quality-adjusted life years (QALYs) and unadjusted survival (life years, LY) and used model projections to compare outcomes for CMTversusCA for two index patients. Patient 1: a 25-year-old male with favourable ESHL (stage IA); Patient 2: a 25-year-old female with unfavourable ESHL (stage IIB). Sensitivity analyses assessed the impact of alternative assumptions for LE probabilities. For Patient 1, CMT was superior to CA (CMT incremental gain = 0·11 QALYs, 0·21 LYs). For Patient 2, CA was superior to CMT (CA incremental gain = 0·37 QALYs, 0·92 LYs). For Patient 1, the advantage of CMT changed minimally when the proportion of severe LEs was reduced from 20% to 5% (0·15 QALYs, 0·43 LYs), whereas increasing the severity proportion for Patient 2's LEs from 20% to 80% enhanced the advantage of CA (1·1 QALYs, 6·5 LYs). Collectively, this detailed simulation model quantified the long-term impact that varied host factors and alternative contemporary treatments have in ESHL.
dc.language.isoenen
dc.rightsArchived with thanks to British journal of haematologyen
dc.titleEarly-stage Hodgkin lymphoma in the modern era: simulation modelling to delineate long-term patient outcomes.en
dc.typeArticleen
dc.contributor.departmentDepartment of Pediatrics, Tufts University School of Medicine, Boston, MA, USAen
dc.identifier.journalBritish Journal of Haematologyen
refterms.dateFOA2018-12-17T15:25:51Z
html.description.abstractWe developed a novel simulation model integrating multiple data sets to project long-term outcomes with contemporary therapy for early-stage Hodgkin lymphoma (ESHL), namely combined modality therapy (CMT) versus chemotherapy alone (CA) via 18 F-fluorodeoxyglucose positron emission tomography response-adaption. The model incorporated 3-year progression-free survival (PFS), probability of cure with/without relapse, frequency of severe late effects (LEs), and 35-year probability of LEs. Furthermore, we generated estimates for quality-adjusted life years (QALYs) and unadjusted survival (life years, LY) and used model projections to compare outcomes for CMTversusCA for two index patients. Patient 1: a 25-year-old male with favourable ESHL (stage IA); Patient 2: a 25-year-old female with unfavourable ESHL (stage IIB). Sensitivity analyses assessed the impact of alternative assumptions for LE probabilities. For Patient 1, CMT was superior to CA (CMT incremental gain = 0·11 QALYs, 0·21 LYs). For Patient 2, CA was superior to CMT (CA incremental gain = 0·37 QALYs, 0·92 LYs). For Patient 1, the advantage of CMT changed minimally when the proportion of severe LEs was reduced from 20% to 5% (0·15 QALYs, 0·43 LYs), whereas increasing the severity proportion for Patient 2's LEs from 20% to 80% enhanced the advantage of CA (1·1 QALYs, 6·5 LYs). Collectively, this detailed simulation model quantified the long-term impact that varied host factors and alternative contemporary treatments have in ESHL.


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