Estimating the Productivity Impact of Acute Myeloid Leukemia in Australia Between 2020 and 2029, Using a Novel Work Utility Measure: The Productivity-Adjusted Life Year (PALY)

Abstract

PURPOSE: Acute myeloid leukemia (AML) is a rare hematologic malignancy accounting for 0.8% of new cancer diagnoses in Australia. High mortality and morbidity affect work productivity through workforce dropout and premature death. This study sought to estimate the productivity loss attributable to AML in the Australian population over 10 years and to estimate the costs of this productivity loss. Productivity was measured using productivity-adjusted life years (PALYs), a similar concept to quality-adjusted life years, but adjusts for the productivity loss attributable to disease, rather than impaired health. MATERIALS AND METHODS: Dynamic life tables modeled the Australian working population (age 15-65 years) between 2020 and 2029. The model population had two cohorts: those with and without AML. Differences in life years, PALYs, and costs represented the health and productivity impact of AML. Secondary analyses evaluated the impact of different scenarios. RESULTS: Over the next 10 years, there will be 7,600 years of life lost and 7,337 PALYs lost because of AML, amounting to Australian dollars (AU$) 1.43 billion in lost gross domestic product ($971 million in US dollars). Secondary analyses highlight potential savings of approximately AU$52 million if survival rates were improved by 20% and almost AU$118 million in savings if the return-to-work rates increased by 20% on the current estimates. CONCLUSION: Our study demonstrates that even in low-incidence cancer, high mortality and morbidity translate to profound impacts on years of life, productivity, and the broader economy. Better treatment strategies are likely to result in significant economic gains. This highlights the value of investing in research for improved therapies.

Economic Impact of Screening on Postdiagnosis Work Productivity in Japanese Women with Breast Cancer – A Life-Table Modeling Approach

“…The impact of BC screening on life-years, PALYs, and gross domestic product (GDP) over the subsequent 5 years was examined using dynamic life table modeling [29] in female patients aged 40 to 64 years diagnosed with BC in Japan in 2019. This target age range was chosen because the target age for BC screening is 40 and above and the current full-time employment period in companies ends at age 65 in Japan.…”

“…PA LY s are calculated by multiplying the 'productivity index' from 0 (not productive at all) to 1 (fully productive) by the number of life-years lived [24]. Several studies have reported work productivity using PALY, including studies on osteoarthritis, type 2 diabetes, hypertension, depression, and acute myeloid leukemia [25][26][27][28][29]. The novelty of the current study lies in the use of PALY to calculate the benefits of increased screening-detected BC and work productivity from an economic perspective in Japan.…”