Diagnostic and prognostic markers for thyroid cancer

dc.contributor.authorPathak, Kumar Alok
dc.contributor.examiningcommitteeLeslie, William (Internal Medicine) Nason, Richard (Surgery) Coombs, Kevin (Medical Microbiology and Infectious Diseases) Rao, Pulivarthi (Baylor College of Medicine)en_US
dc.contributor.supervisorKlonisch, Thomas (Human Anatomy and Cell Science)en_US
dc.date.accessioned2017-08-25T14:42:14Z
dc.date.available2017-08-25T14:42:14Z
dc.date.issued2014
dc.degree.disciplineHuman Anatomy and Cell Scienceen_US
dc.degree.levelDoctor of Philosophy (Ph.D.)en_US
dc.description.abstractStatement of the problem: The objectives of our study were to evaluate the debatable diagnostic role of FDG-PET/CT in predicting the risk of malignancy in follicular neoplasm and to build prognostic models to predict the risks of relapse and death from thyroid cancer, as there is no universally acceptable model valid for different histological types of thyroid cancers. Methods: The efficacy of FDG-PET/CT scan for predicting the risk of malignancy was assessed in a prospective cohort of 50 follicular neoplasms. Disease specific and relapse free survivals of a 2306-patient Manitoba thyroid cancer cohort were estimated by the Kaplan-Meier method and the independent influence of various prognostic factors was assessed by Cox Proportional Hazard models. Cumulative incidence of deaths and relapses from thyroid cancer was calculated by competing risk analysis, and was used to develop and validate prognostic nomograms, using R version 2.13.2 (www.r-project.org). A web-based prognostic model was developed to predict the disease specific survival, and validated internally and externally on an independent patient cohort from London, Ontario. Results: FDG PET/CT had an overall accuracy of 81% in predicting risk of malignancy in non-Hürthle follicular cell neoplasms and 87% accuracy in distinguishing follicular and Hürthle cell adenomas. The age standardized incidence of thyroid cancer in Manitoba increased by 373% from 1970 to 2010, with the proportion of papillary cancers increasing from 58% to 85.9%, and that of anaplastic cancer falling from 5.7% to 2.1% (p<0.001). The disease specific survival was adversely influenced by anaplastic histology, male gender, stage IV disease, incomplete surgical resection and age at diagnosis, during a median follow-up of 11.5 years. Prognostic nomograms were designed to predict the individualized 10-year risks of death and relapse from thyroid cancer, with their respective concordance indices of 0.92 and 0.76. A web-based model was successfully developed and externally validated with excellent discrimination. It compared favorably with the existing staging/risk stratification systems. Conclusions: FDGPET/CT has a very good accuracy of predicting risk of malignancy in non-Hürthle follicular cell neoplasms. We have successfully developed and validated prognostic nomograms and a web model for predicting oncological outcome of thyroid cancer.en_US
dc.description.noteOctober 2017en_US
dc.identifier.urihttp://hdl.handle.net/1993/32375
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectThyroid Canceren_US
dc.subjectPrognosticen_US
dc.subjectDiagnosisen_US
dc.titleDiagnostic and prognostic markers for thyroid canceren_US
dc.typedoctoral thesisen_US
local.subject.manitobayesen_US
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