Real-world costing analysis for diffuse large B-cell lymphoma in British Columbia

Abstract

Introduction: Diffuse large B-cell lymphoma (dlbcl) accounts for 30%-40% of all non-Hodgkin lymphomas. Approximately 60% of patients are cured with standard treatment. Targeted treatments are being investigated and might improve disease outcomes; however, their effect on cancer drug budgets will be significant. For the present study, we conducted an analysis of real-world costs for dlbcl patients treated in British Columbia, useful for health care system planning.

Methods: Patient records from a retrospective cohort of patients diagnosed with dlbcl in British Columbia during 2004-2013 were anonymously linked across multiple administrative data sources: systemic therapy, radiotherapy, hospitalizations, oncologist services, outpatient medications, and fee-for-service physician services. Using generalized linear modelling regression, time-dependent costs (in 2015 Canadian dollars) were estimated in 6-month intervals over a 5-year period. The inverse probability weighting method was applied to account for censored observations. Nonparametric bootstrapping was used to estimate standard errors for the mean cost at each time interval.

Results: The cohort consisted of 678 patients (5-year overall survival: 67%). Mean age at diagnosis was 64 ± 14 years; median follow-up was 3.2 years. Mean total cost of care was highest in the first 6 months after diagnosis ($29,120; 95% confidence interval: $28,986 to $29,170) and after disease progression ($18,480; 95% confidence interval: $15,187 to $24,772). Systemic therapy and hospitalization costs were the largest cost drivers. At each time interval, costs were observed to be positively skewed.

Conclusions: Our results depict real-world costs for the treatment of dlbcl patients with standard chop-r therapy. Cost-model parameters are also provided for economic modelling of dlbcl interventions.

Keywords: Diffuse large B-cell lymphoma; censored costing; costs, real-world; inverse probability weighting.

FIGURE 1

Fitted cost model showing censoring-adjusted costs for the cohort, plotted against time (t) in 6-month intervals. (A) Costs for first-line treatment. (B) Costs for second-line treatment. The solid black line indicates the fitted cost model; the dotted lines indicate the 95% confidence limits.