Real-world use of mogamulizumab among patients with mycosis fungoides and Sézary syndrome before and during COVID-19 in the United States

Background: Per label, mogamulizumab (Moga) is administered on days 1, 8, 15, and 22 of the first 28-day cycle (loading) and on days 1 and 15 of each subsequent cycle (maintenance) for adult patients with relapsed or refractory mycosis fungoides (MF) or Sézary syndrome (SS) after ≥1 prior systemic therapy. During the COVID-19 pandemic, professional organizations suggested dosing intervals for systemic cancer therapies be extended to limit in-person visits. This study examined the real-world use of Moga before and during the COVID-19 pandemic in the United States. Methods: Using the Symphony Health Solutions database, adults with ≥1 diagnosis (dx) of MF or SS (ICD-10 CM: C84.0x or C84.1x) and ≥1 Moga claim during 10/1/2018-5/6/2021 were identified. Within the MF (no SS dx) and SS (any SS dx) cohorts, patients were divided into 2 subgroups based on their Moga initiation date: 10/1/2018-3/31/2020 (pre COVID-19) and 4/1/2020-5/6/2021 (COVID-19). Patient characteristics and dosing intervals between Moga doses 1-4 (loading) and between subsequent doses (maintenance) were examined. Results: Overall, 154 MF and 204 SS patients initiated Moga during the study period (mean age: 66.8 and 69.2 years;male: 64% and 55%, respectively). In the MF cohort, 98 and 56 patients were in the “pre COVID-19” and “COVID-19” subgroups. The mean dosing interval was shorter among patients in the “COVID-19” subgroup for both the loading (9.1 vs. 13.2 days) and maintenance doses (15.2 vs. 16.1 days) (Table). In the SS cohort, 121 and 83 patients were in the “pre COVID-19” and “COVID-19” subgroups. Mean loading (9.0 vs. 11.1 days) and maintenance (15.0 vs. 16.8 days) dosing intervals were shorter for patients included in the “COVID-19” subgroup. Conclusions: Among MF and SS patients, dosing intervals for Moga in loading and maintenance were not extended during the 1st year of the COVID-19 compared to pre COVID-19. There was a trend towards closer concordance with the label during COVID-19.

Topic-to-Topic Modeling for COVID-19 Mortality

We examine a cohort of 4307 COVID-19 case fatalities from a de-identified national registry in the U.S. using Latent Dirichlet Allocation and group each patient by topic based on their pre-existing conditions in the years prior to infection and again during the last three weeks of life. We show that certain pre-existing condition topics have strong associations with certain COVID-19 mortality topics suggesting that the major clinical pathways leading to COVID-19 death may be through failures of already weakened organ systems. We then explore the demographics for these groups and generate several insights and hypotheses. © 2021 IEEE.