Estimated impact of ECHELON-1 overall survival on productivity costs in stage III/IV classical Hodgkin lymphoma in the United States.

BACKGROUND: A 2010 study on the impact of cancer mortality on productivity costs found Hodgkin lymphoma to have the second largest productivity cost lost per death in the United States. The ECHELON-1 trial demonstrated that frontline brentuximab vedotin, doxorubicin, vinblastine, and dacarbazine (A+AVD) improves overall survival (OS) vs doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) in stage III/IV classical Hodgkin lymphoma (cHL), reducing the risk of death to 41% (hazard ratio = 0.59; 95% CI = 0.40-0.88; P = 0.009). OBJECTIVES: To assess the estimated impact of frontline treatment choice on mortality and productivity using an oncology simulation model informed by ECHELON-1 data. METHODS: Individual productivity was estimated using the human capital approach and reported via present value lifetime earnings (PVLE) estimates. Deaths avoided and lifeyears saved without and with A+AVD were calculated using a model informed by realworld treatment use, treatment-specific OS, and expert clinicians' opinions. A+AVD use in the base case was 27% (range: 0%-80%). Stage III/IV cHL prevalence over a 10-year period was estimated; downstream lifetime productivity costs were projected without and with A+AVD. RESULTS: In 2031, 3,645 patients were estimated to be newly diagnosed with stage III/IV cHL. Over 10 years with 27% A+AVD vs no A+AVD use, estimates predicted 14% fewer deaths (2,290 vs 2,650) and 14% less total PVLE losses ($1.438 vs $1.664 billion). Results from scenario analyses (40%-80% vs no A+AVD use) showed 20% to 32% decreases in PVLE losses ($1.331-$1.137 billion vs $1.664 billion), saving up to $527 million over 10 years. CONCLUSIONS: Productivity cost losses due to mortality in stage III/IV cHL are high. Increasing A+AVD use for patients with stage III/IV cHL would reduce productivity cost losses as deaths are avoided, based on ECHELON-1 OS results.

Benchmarking Maintenance Therapy Survival in First-Line Platinum-Based Chemotherapy-Treated Patients with Advanced Urothelial Carcinoma Using Simulated Disease Modeling.

Objective: First-line (1L) maintenance avelumab prolonged overall survival (OS) in patients with advanced urothelial carcinoma (aUC) in JAVELIN Bladder 100. OS was measured from maintenance initiation in patients with disease control following 1L platinum-based therapy (PBT). The OS impact of maintenance for the 1L PBT-treated population is unknown since it was not measured from 1L initiation, nor can it be benchmarked with other 1L therapies. To characterize the OS impact of maintenance avelumab, we used an oncology simulation model to estimate the OS of maintenance-eligible and -ineligible patients with aUC from 1L PBT initiation. Methods: We developed a simulated cohort of 1L PBT-treated patients with aUC, including those who did and did not receive maintenance avelumab. Eligibility was assessed at 5.6 months post 1L PBT initiation based on the JAVELIN trial design. Among the 1L-treated population, 58% (95% credible interval [CrI] 49-67%) were projected to be eligible (calculated from contemporary phase 3 trials); of those, 85% were assumed to receive maintenance. The model estimated median OS (mOS) among a maintenance-ineligible simulated cohort which when combined with the maintenance-eligible cohort yielded an estimated OS in the overall maintenance- intended population from 1L PBT initiation. Results: Approximately half of the modeled 1L PBT-treated population received maintenance. Estimated mOS was 10.1 months (95% CrI 7.5-13.5) for the maintenance-ineligible cohort, 29.3 months (95% CrI 24.8-33.9) for the maintenance-eligible, received maintenance cohort, and 15.9 months (95% CrI 13.2-19.1) in the overall maintenance-intended, 1L PBT-treated population, including those eligible and ineligible for maintenance. Conclusion: The model shows that maintenance avelumab has a modest impact on OS in the overall 1L PBT-treated population of patients with aUC. While maintenance avelumab improves OS for eligible patients, a large proportion of the maintenance-intended population may not receive maintenance due to ineligibility or physician/patient choice.

Estimating long-term outcomes in classic Hodgkin lymphoma: a United States population-based oncology simulation model based on overall survival from the ECHELON-1 trial.

The six-year ECHELON-1 update showed a survival advantage for frontline (1 L) A + AVD (brentuximab vedotin, doxorubicin, vinblastine, dacarbazine) vs ABVD (doxorubicin, bleomycin, vinblastine, dacarbazine) for stage III/IV classic Hodgkin lymphoma (cHL). As clinical trials have limited ability to track patients for extended periods, we developed an oncology simulation model using ECHELON-1 data to estimate population-based cHL outcomes in the US over 10 years (through 2031). The model included a scenario without (64.5% ABVD, 35.5% PET-adapted ABVD utilization) and scenarios with 1 L A + AVD (27%-80%k utilization). At 27%-80% A + AVD utilization, the model estimated 13.6%-31.7% fewer deaths, 2.4%-6.3% more patients ≥5 years progression free, 9.4%-24.4% fewer stem cell transplants (SCTs), and 7.8%-22.5% fewer second cancers over 10 years. These results suggest that the improved outcomes observed in the ECHELON-1 update with A + AVD vs ABVD may translate to more patients alive and fewer with primary relapsed/refractory cHL, SCTs, and second cancers.

Estimating long-term progression-free and overall survival in patients with peripheral T-cell lymphoma: A US population-based oncology simulation model based on 5-year results from the ECHELON-2 trial.

BACKGROUND: The ECHELON-2 5-year update showed continued clinically meaningful improvements in progression-free survival (PFS) and overall survival with frontline (1L) A+CHP (brentuximab vedotin in combination with cyclophosphamide, doxorubicin, prednisone) vs CHOP (cyclophosphamide, doxorubicin, vincristine, prednisone) in CD30-expressing peripheral T-cell lymphomas (PTCLs). OBJECTIVE: To estimate PTCL annual prevalence in the United States in 2031 without and with A+CHP using data from the ECHELON-2 5-year update. METHODS: Population-level outcomes were estimated using a dynamic oncology simulation model. Utilization of 1L CHOP (65% utilization) and CHOP plus etoposide (35% utilization) were varied over time and compared with scenarios incorporating 1L A+CHP (20%-50% utilization; base case: 40% utilization) per expert clinicians' opinion. Additional inputs included PTCL incidence and PFS for consolidation and post-1L therapies from published sources. PFS (51.4% [95% CI = 42.8%-59.4%] vs 43.0% [35.8%-50.0%]) and overall survival (hazard ratio = 0.72 [0.53-0.99]) for A+CHP and CHOP came from ECHELON-2. RESULTS: In 2031, an estimated 2,082 patients will be diagnosed with PTCL. Approximately 1,412 additional patients will be alive and progression free, and 106 fewer patients will require second-line therapy with 40% A+CHP utilization vs no A+CHP utilization. Varying 1L A+CHP utilization from 20%-50% vs no 1L A+CHP utilization added 732 to 1,752 patients alive and progression free. CONCLUSIONS: In this oncology simulation model, the improvements in survival outcomes seen with A+CHP vs CHOP in the ECHELON-2 5-year results translated into more estimated patients with PTCL progression free and alive for at least 5 years following 1L A+CHP vs CHOP and a decreased need for post-1L therapy. DISCLOSURES: This study was funded by Seagen Inc. Dr Liu and Dr Yu are employees and shareholders of Seagen Inc. Mr Bloudek is and Dr Mordi was an employee of Curta Health, which received funding from Seagen Inc. for the conduct of this study. Dr Burke received consulting fees from Genentech/Roche, AbbVie, Seattle Genetics, Bayer, AstraZeneca, Adaptive Biotechnologies, Verastem, MorphoSys, Kura, Epizyme, BeiGene, Kymera, Novartis, Bristol Myers Squibb, TG Therapeutics, Lilly, and Nurix; and received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events in speakers bureaus for BeiGene and Seagen Inc. Dr Phillips received consulting fees from AstraZeneca, MorphoSys, Epizyme, Roche/Genentech, Epizyme Eli Lilly, AbbVie, BeiGene, Pharmacyclics, Bristol Myers Squibb, Xencor, Seagen Inc., TG Therapeutics, Bayer, Incyte, and Gilead; and received payment for honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Epizyme and Seagen Inc.

Oncology Simulation Model: A Comprehensive and Innovative Approach to Estimate and Project Prevalence and Survival in Oncology.

Objective: We demonstrate a new model framework as an innovative approach to more accurately estimate and project prevalence and survival outcomes in oncology. Methods: We developed an oncology simulation model (OSM) framework that offers a customizable, dynamic simulation model to generate population-level, country-specific estimates of prevalence, incidence of patients progressing from earlier stages (progression-based incidence), and survival in oncology. The framework, a continuous dynamic Markov cohort model, was implemented in Microsoft Excel. The simulation runs continuously through a prespecified calendar time range. Time-varying incidence, treatment patterns, treatment rates, and treatment pathways are specified by year to account for guideline-directed changes in standard of care and real-world trends, as well as newly approved clinical treatments. Patient cohorts transition between defined health states, with transitions informed by progression-free survival and overall survival as reported in published literature. Results: Model outputs include point prevalence and period prevalence, with options for highly granular prevalence predictions by disease stage, treatment pathway, or time of diagnosis. As a use case, we leveraged the OSM framework to estimate the prevalence of bladder cancer in the United States. Conclusion: The OSM is a robust model that builds upon existing modeling practices to offer an innovative, transparent approach in estimating prevalence, progression-based incidence, and survival for oncologic conditions. The OSM combines and extends the capabilities of other common health-economic modeling approaches to provide a detailed and comprehensive modeling framework to estimate prevalence in oncology using simulation modeling and to assess the impacts of new treatments on prevalence over time.