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  • Author: Zachary A. P. Wintrob x
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Razelle Kurzrock, Robert Goldberg, Alice C. Ceacareanu and Zachary A. P. Wintrob

Background: It is sometimes suggested that newly-approved cancer treatments have only marginal effectiveness, which raises questions concerning their cost-vs-benefit ratio. Such concerns appear at odds with the lower cancer-related hospitalization rate and improved survival. However, such cost-effectiveness analyses rely on population-based averages obtained from the analysis of clinical trial data. By failing to analyze data from longitudinal datasets, such assessments are unable to account for real-world patient conditions and treatment patterns in evaluating clinical and cost-effectiveness. Longitudinally surveyed clinical data has the potential to objectively reveal any association between patient outcomes and new cancer treatment utilization. Methods: We investigated the effect of being prescribed a higher proportion of new oncology drugs on quality of life, medical services use, and productivity measures as reported by the Medical Expenditure Panel Survey (MEPS, 1996–2015). General linear models with Taylor series variance estimation were applied. New oncology drugs were defined as cancer treatments marketed after the year 2000. Included subjects (N=16,677) had a solid or hematologic malignancy diagnosis (CCCodex 11–47) and available prescription data. Individual age and employment status were accounted for as covariates. All analyses were performed using SAS version 9.4 (Cary, NC). Results: Unadjusted regression data show that individuals using newer oncology treatments missed on average 2.5 (±0.3 SE) fewer days of work or school per year as compared to patients using older drugs (43% improved productivity, P<.0001). The effect persisted even after adjusting for the magnitude of the effect (P<.0001). Accounting for age, the use of newer drugs was, on average, associated with ∼35% fewer missed work or school days. Cancer patients using newer treatments had 0.06 (±0.01 SE) fewer hospital admissions/year compared to patients using older treatments (P<.0001) and spent less time in the emergency room (P<.0411) with ∼45% fewer hospitalizations. Patients using newer medicines also had fewer health-related visits (P<.0001). Conclusion: Analysis of longitudinal real-world evidence gives a more comprehensive and reliable view of the clinical and economic impact of new oncology treatments. Our data suggests significant reductions in lost work/school days, hospitalizations, and use of medical services in general.