Clinical Characteristics, Treatment Patterns, and Healthcare Costs and Utilization for Hepatocellular Carcinoma (HCC) Patients Treated at a Large Referral Center in Washington State 2007–2018

Abstract

Introduction Though the treatment landscape for hepatocellular carcinoma (HCC) has evolved significantly with the refinement of liver-directed therapy techniques and the introduction of new drugs, few studies have investigated the impact of the changing treatment landscape on lifetime treatment costs, particularly in Barcelona Clinic Liver Cancer (BCLC) stage C disease. We sought to investigate real-world clinical characteristics, treatment patterns, and healthcare costs in a cohort of HCC patients treated at a single high-volume institution in Washington (WA) state. Methods We conducted a retrospective cohort study of patients diagnosed with HCC between 2007 and 2018 using abstracted electronic medical record (EMR) data linked to cancer registry data and health claims from commercial plans, Medicare, and Medicaid. We described clinical and treatment characteristics, including BCLC stage and Child Pugh score. We investigated median survival and mean lifetime treatment costs by BCLC stage using Kaplan–Meier cost estimator methods. A multivariate Cox proportional hazards model was used to investigate factors associated with overall survival. Results The final cohort included 215 patients, the majority of whom were white (71%), male (68%), and with underlying hepatitis C (61%). Mean per patient lifetime costs were highest in BCLC A and BCLC C patients. Mean lifetime costs in BCLC A patients ($292,134) was driven by surgery, hospital, pharmacy, imaging, and outpatient costs. Chemotherapy costs were highest in BCLC C patients, though not the predominant area of spending. Median survival was highest in patients with BCLC 0 and A disease; BCLC stage C and higher area deprivation index (ADI) were associated with poorer survival. Conclusion In a cohort of WA state HCC patients, mean lifetime costs were highest in patients with BCLC A disease, attributable to surgery and hospital costs. As increased utilization of newer and less toxic therapies improves survival in BCLC C patients, mean lifetime costs in this group may also rise.

Demographic, clinical and aetiological characteristics of patients with hepatocellular carcinoma followed between 2012 and 2017 at University Hospital Joseph Raseta Befelatanana, Antananarivo, Madagascar

“…A clear male predominance was observed in our series, consistent with all the data in the Western [ 1 , 13 , 26 ], Asian [ 27 – 32 ] and African [ 8 – 11 , 14 , 17 , 18 – 24 ] literature. Risk factors for HCC such as HBV, HCV, alcoholism and smoking would be more frequent in men than in women [ 1 , 2 , 20 ].…”

“…The same findings had been made in Nigeria [ 21 ], Cameroon [ 23 ], Congo [ 19 ], Burkina Faso [ 24 ] and in the rest of Sub-Saharan African countries [ 8 – 11 , 17 , 18 , 22 ]. Whereas in Western countries, HCC is discovered very early in the majority of cases [ 26 ]. This suggests that an effort is needed for the early diagnosis of HCC in the Malagasy population.…”

Area-Level Socioeconomic Disadvantage and Health Care Spending

“…This may occur if underlying studies involve narrow data or scope. For example, in this review, 3 of the 4 studies that did not find an association between ADI or SVI and spending were single-center studies with relatively small sample sizes . Two of these studies evaluated elective joint replacement surgery, which may not reflect other types of care.…”

“…The most common medical specialty areas for these studies included general adult medicine 12,[16][17][18][19][20] (5 of 14 ADI-based studies and 2 of 10 SVI-based studies) or surgery (5 of 14 ADI-based studies and 5 of 10 SVI-based studies), including general, [21][22][23][24] cardiothoracic, 25 vascular, 26 and orthopedic [27][28][29][30] surgery. A smaller number were more specialty focused on oncology, [31][32][33] cardiology, 34 pediatrics, 35 and COVID-19. 36,37 Nearly half of the studies using national data (4 of 9 level, due to limited availability of these variables in electronic medical records and claims data.…”

Explainable and Personalized Medical Cost Prediction Based on Multitask Learning over Mobile Devices

“…Moreover, due to the different conditions of different patients and the influence of factors such as healing time and degree of recovery, it is difficult to fit medical costs with simple linear models. erefore, the prediction of medical cost requests both the application of various dimensions of data available from mobile ends and feedbacks to users with a deep understanding on the impact of individual and personalized characteristics on healthcare costs [14,15].…”