UC Davis

Pancreatic cancer is a devastating disease with a 5-year survival rate of only 10%. (1) As many as 57,600 people were diagnosed with pancreatic in 2020 and 47,050 were expected to die from the disease before the end of the year. (2) With this cancer being so aggressive it is often detected late and is difficult to treat. (3) The options for treatment are thus fairly limited to patients depending on the stage of their cancer, and options range from surgery to chemotherapy and radiation. (4) While all cancer care is expensive, pancreatic cancer on average costs $61,700, with the highest costs being associated with hospitalizations and cancer-directed procedures. (5) For those with resectable disease, the costs are typically far greater at $134,700. (5) While these are high costs, there are many different places for patients to seek care that could influence these numbers. These range from local community hospitals to teaching institutions and high-volume pancreatic treatment centers. With so many choices for patients to select from, the costs of each choice matter, as does the quality of care they are to receive. While many hospitals provide a high quality of care, it is important to investigate which hospitals are best for both a patient’s overall health and the payer’s pocketbook. With pancreatic cancer having such high associated costs and mortality rates the quality of treatment, costs, and the outcomes matter. In California, many high-volume treatment centers are also teaching hospitals and it is possible that because these hospitals are heavily invested in teaching and research that care at such a place would incur higher costs. (6,7) It is also possible, however, that these centers provide higher quality care. To payers, maximizing the benefit to cost ratio is extremely important. It is thus imperative to understand not only the costs, but the outcomes patients receive at these various treatment centers. To better understand this relationship at high vs low-volume hospitals, a cost-effectiveness analysis should be used. The following three studies address these pressing questions and gaps in the literature. Studies from the United States have confirmed that high-volume hospitals do provide higher quality of care but have shown inconsistencies in the cost-effectiveness of that care and none to our knowledge have examined the impact of socioeconomic status (SES) on cost-effectiveness. (8) SES is a well-known factor in cancer survival, but it is rarely studied in the context of cost-effectiveness even though it can affect conclusions about value. The first paper investigates the relationship between socioeconomic status (SES) and the cost-effectiveness of surgical treatment at high vs. low-volume centers by conducting a subgroup cost-effectiveness analysis. This study involves the creation of incremental cost-effectiveness ratios (ICERs) and cost-effectiveness acceptability curves (CEACs) that allow payers to easily access information about the probability of cost-effectiveness at varying points that the payer is willing to pay (WTP). The second study demonstrates that cost-effectiveness acceptability curves (CEACs) can mask subgroup differences such as those seen in paper one. This paper also provides an example of where a CEAC for the overall population provides more optimistic findings than CEACs for both of the constituent subgroups. This study aims to show how the findings from overall CEACs can differ from subgroup analysis and how this can affect policy recommendations. The last study investigates the sensitivity of cost-effectiveness findings to analytic assumptions. Analytic assumptions made during the analysis of cost-effectiveness data can affect the findings and potential subsequent policy recommendations. This study investigates the effects of these assumptions through analyzing 6 different models with varying assumptions and comparing their incremental cost-effectiveness ratios (ICERs) along with select cost-effectiveness acceptability curves. Overall, this dissertation provides insight into not only the cost-effectiveness of the surgical treatment of pancreatic at high vs. low-volume centers but also investigates many assumptions and analytic methods of conducting cost-effectiveness analyses. This is done through conducting cost-effectiveness analyses which includes creating ICERs and CEACs. Providing evidence of how analytic assumptions affect cost-effectiveness analyses is important to allow researchers a greater understanding of how methodology can affect not only the outcome of cost-effectiveness analysis but the subsequent policy implications. As the US healthcare system spends an exorbitant amount of money on cancer care, it is imperative that scare resources are allocated as effectively as possible. These studies expand current knowledge in the field in an effort to increase efficiency and lower unnecessary spending in pancreatic cancer care amongst other more global healthcare implications.

References: 1. Survival Rates for Pancreatic Cancer [Internet]. American Cancer Society. 2021 [cited 2021 May 24]. Available from: https://www.cancer.org/cancer/pancreatic-cancer/detection-diagnosis-staging/survival-rates.html 2. Rosenzweig A. Pancreatic Cancer Survival Rate Reaches 10% [Internet]. Pancreatic Cancer Action Network. 2020 [cited 2021 May 24]. Available from: https://www.pancan.org/news/pancreatic-cancer-survival-rate-reaches-10/#:~:text=In%202020%2C%20an%20estimated%2057%2C600,be%20diagnosed%20with%20pancreatic%20cancer. 3. Stallard J. Why Is Pancreatic Cancer So Hard to Treat? [Internet]. Memorial Sloan Kettering Cancer Center. 2016 [cited 2021 May 24]. Available from: https://www.mskcc.org/news/why-pancreatic-cancer-so-hard-treat 4. Pancreatic cancer [Internet]. UC Davis Health Comprehensive Cancer Center. [cited 2021 May 24]. Available from: https://health.ucdavis.edu/cancer/cancer-types/pancreas.html 5. O’Neill CB, Atoria CL, O’Reilly EM, LaFemina J, Henman MC, Elkin EB. Costs and trends in pancreatic cancer treatment. Cancer. 2012 Oct 15;118(20):5132–9. 6. Niphadkar S, Nathan R, Perimbeti S, Liang YY, Marconcini LAL, Lee WM, et al. Emerging trends in pancreatic cancer and diabetes. JCO. 2017 May 20;35(15_suppl):e13077–e13077. 7. Reddy S. High-volume, NCI-designated centers not associated with greater value in pancreatic cancer care [Internet]. HemOnc Today. 2019 [cited 2021 Jun 3]. Available from: https://www.healio.com/news/hematology-oncology/20190823/highvolume-ncidesignated-centers-not-associated-with-greater-value-in-pancreatic-cancer-care 8. Bateni SB, Gingrich AA, Hoch JS, Canter RJ, Bold RJ. Defining Value for Pancreatic Surgery in Early-Stage Pancreatic Cancer. JAMA Surg 2019;154:e193019. https://doi.org/10.1001/jamasurg.2019.3019.