Purpose Oral targeted therapies represent a significant advance for the treatment of patients with chronic lymphocytic leukemia (CLL); however, their high cost has raised concerns about affordability and the economic impact on society. Our objective was to project the future prevalence and cost burden of CLL in the era of oral targeted therapies in the United States. Methods We developed a simulation model that evaluated the evolving management of CLL from 2011 to 2025: chemoimmunotherapy (CIT) as the standard of care before 2014, oral targeted therapies for patients with del(17p) and relapsed CLL from 2014, and for first-line treatment from 2016 onward. A comparator scenario also was simulated where CIT remained the standard of care throughout. Disease progression and survival parameters for each therapy were based on published clinical trials. Results The number of people living with CLL in the United States is projected to increase from 128,000 in 2011 to 199,000 by 2025 (55% increase) due to improved survival; meanwhile, the annual cost of CLL management will increase from $0.74 billion to $5.13 billion (590% increase). The per-patient lifetime cost of CLL treatment will increase from $147,000 to $604,000 (310% increase) as oral targeted therapies become the first-line treatment. For patients enrolled in Medicare, the corresponding total out-of-pocket cost will increase from $9,200 to $57,000 (520% increase). Compared with the CIT scenario, oral targeted therapies resulted in an incremental cost-effectiveness ratio of $189,000 per quality-adjusted life-year. Conclusion The increased benefit and cost of oral targeted therapies is projected to enhance CLL survivorship but can impose a substantial financial burden on both patients and payers. More sustainable pricing strategies for targeted therapies are needed to avoid financial toxicity to patients.

Purpose Oral targeted therapies represent a significant advance for the treatment of patients with chronic lymphocytic leukemia (CLL); however, their high cost has raised concerns about affordability and the economic impact on society. Our objective was to project the future prevalence and cost burden of CLL in the era of oral targeted therapies in the United States. Methods We developed a simulation model that evaluated the evolving management of CLL from 2011 to 2025: chemoimmunotherapy (CIT) as the standard of care before 2014, oral targeted therapies for patients with del(17p) and relapsed CLL from 2014, and for first-line treatment from 2016 onward. A comparator scenario also was simulated where CIT remained the standard of care throughout. Disease progression and survival parameters for each therapy were based on published clinical trials. Results The number of people living with CLL in the United States is projected to increase from 128,000 in 2011 to 199,000 by 2025 (55% increase) due to improved survival; meanwhile, the annual cost of CLL management will increase from $0.74 billion to $5.13 billion (590% increase). The per-patient lifetime cost of CLL treatment will increase from $147,000 to $604,000 (310% increase) as oral targeted therapies become the first-line treatment. For patients enrolled in Medicare, the corresponding total out-of-pocket cost will increase from $9,200 to $57,000 (520% increase). Compared with the CIT scenario, oral targeted therapies resulted in an incremental cost-effectiveness ratio of $189,000 per quality-adjusted life-year. Conclusion The increased benefit and cost of oral targeted therapies is projected to enhance CLL survivorship but can impose a substantial financial burden on both patients and payers. More sustainable pricing strategies for targeted therapies are needed to avoid financial toxicity to patients.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.