Appendix_D_online_supp – Supplemental material for Exploring the Benefits of Transformations in Health Utility Mapping

Supplemental material, Appendix_D_online_supp for Exploring the Benefits of Transformations in Health Utility Mapping by Nicholas Mitsakakis, Karen E. Bremner, George Tomlinson and Murray Krahn in Medical Decision Making</p

Appendix_C_online_supp – Supplemental material for Exploring the Benefits of Transformations in Health Utility Mapping

Supplemental material, Appendix_C_online_supp for Exploring the Benefits of Transformations in Health Utility Mapping by Nicholas Mitsakakis, Karen E. Bremner, George Tomlinson and Murray Krahn in Medical Decision Making</p

Estimates for cohort of individuals born after 1964, for years 1999–2013, from model (12), (13) calibrated using data listed in S4 Table and S5 Table.

Blue circles denote observed annual numbers of HCC and hepatitis C diagnoses for this cohort. A: Model estimates of total number of HCC diagnoses. B: Model estimates of total number of hepatitis C diagnoses. C: Model estimates of CHC prevalence rate Rx(t). D: Model estimates of proportion of CHC population undiagnosed .</p

Appendix_B_online_supp – Supplemental material for Exploring the Benefits of Transformations in Health Utility Mapping

Supplemental material, Appendix_B_online_supp for Exploring the Benefits of Transformations in Health Utility Mapping by Nicholas Mitsakakis, Karen E. Bremner, George Tomlinson and Murray Krahn in Medical Decision Making</p

Appendix_A_online_supp – Supplemental material for Exploring the Benefits of Transformations in Health Utility Mapping

Supplemental material, Appendix_A_online_supp for Exploring the Benefits of Transformations in Health Utility Mapping by Nicholas Mitsakakis, Karen E. Bremner, George Tomlinson and Murray Krahn in Medical Decision Making</p

Estimates for cohort of individuals born between 1945 and 1964, for years 1999–2013, from model (12), (13) calibrated using data listed in S4 Table and S5 Table.

Blue circles denote observed annual numbers of HCC and hepatitis C diagnoses for this cohort. A: Model estimates of total number of HCC diagnoses. B: Model estimates of total number of hepatitis C diagnoses. C: Model estimates of CHC prevalence rate Rx(t). D: Model estimates of proportion of CHC population undiagnosed .</p

One-way sensitivity analysis for estimated prevalence rate, averaged over all birth cohorts.

One-way sensitivity analysis for estimated prevalence rate, averaged over all birth cohorts.</p

Cohort-averaged estimates of prevalence rate and proportion of CHC population undiagnosed.

A: Estimates for years 1999–2013 of CHC prevalence rate in Canada rate averaged over all birth cohorts. B: Estimates for years 1999–2013 of proportion of CHC population undiagnosed averaged over all birth cohorts.</p

Estimates for cohort of individuals born before 1945, for years 1999–2013, from model (12), (13) calibrated using data listed in S4 Table and S5 Table.

Blue circles denote observed annual numbers of HCC and hepatitis C diagnoses for this cohort. A: Model estimates of total number of HCC diagnoses. B: Model estimates of total number of hepatitis C diagnoses. C: Model estimates of CHC prevalence rate Rx(t). D: Model estimates of proportion of CHC population undiagnosed .</p

Advanced liver disease state transition model.

Transition probabilities are derived in S1 Appendix. HCC: hepatocellular carcinoma. DC: decompensated cirrhosis. LT: liver transplant. PT: post-liver transplant. LD: liver-related death. SVR: Sustained virologic response.</p