OBJECTIVES: To compare rates of inpatient hospitalizations, outpatient specialist visits, sickness absences, as well as direct and indirect costs, between patients with newly diagnosed light-chain (AL) amyloidosis and those without AL in Sweden.

METHODS: Data came from six Swedish nationwide population-based registers and linked by unique personal identity number. Patients with newly diagnosed AL were identified by having two or more diagnosis codes for amyloidosis and one of the following: receipt of anti-plasma cell therapy, a diagnosis of amyloidosis made in a hematology/oncology clinic, or diagnosis code specific to AL. For each AL case, non-AL individuals were randomly selected and matched with a maximum ratio of 1:5 based on age, sex, calendar year, and county. Outcome measures were compared between the two groups on a per-patient-per-year basis to account for varying lengths of follow-up.

RESULTS: 846 patients with newly diagnosed AL (median age 70yr, 41% female) and 4,227 matched controls were identified. Compared to controls, patients with AL had significantly higher mean Charlson Comorbidity Scores (p<0.001), higher rates of cardiac failure (p<0.001) and renal failure (p<0.001) at baseline. During follow-up, patients with AL had higher PPPY number of hospitalizations (4.6 vs 0.4, p<0.001) and outpatient visits (18.0 vs 2.3, p<0.001); incurred €36,181 (p<0.001) higher average PPPY all-cause costs, with an incremental difference of €31,377 due to medical costs. Among working-age patients (AL: n=280; controls: n=1400), AL patients had 10.4% higher rate of sickness absence (p<0.001) with €3,688 (p=0.004) higher PPPY indirect costs than controls.

CONCLUSIONS: These findings indicate that AL imposed significant healthcare costs to patients, employers, and society with the majority of incremental total costs being attributed to medical care. However, it should be noted that the estimates of prescription drug cost are likely underestimates due to incomplete capture of intravenous and subcutaneous treatments in the data.