Impact of the COVID-19 pandemic on treatment patterns for US patients with metastatic solid cancer

medRxiv [Preprint]. 2021 Sep 23:2021.09.22.21263964. doi: 10.1101/2021.09.22.21263964.

Abstract

Background: The COVID-19 pandemic has led to delays in patients seeking care for life-threatening conditions; however, its impact on treatment patterns for patients with metastatic cancer is unknown. We assessed the COVID-19 pandemic's impact on time to treatment initiation (TTI) and treatment selection for patients newly diagnosed with metastatic solid cancer.

Methods: We used an electronic health record-derived longitudinal database curated via technology-enabled abstraction to identify 14,136 US patients newly diagnosed with de novo or recurrent metastatic solid cancer between January 1 and July 31 in 2019 or 2020. Patients received care at ∼280 predominantly community-based oncology practices. Controlled interrupted time series analyses assessed the impact of the COVID-19 pandemic period (April-July 2020) on TTI, defined as the number of days from metastatic diagnosis to receipt of first-line systemic therapy, and use of myelosuppressive therapy.

Results: The adjusted probability of treatment within 30 days of diagnosis [95% confidence interval] was similar across periods: January-March 2019 41.7% [32.2%, 51.1%]; April-July 2019 42.6% [32.4%, 52.7%]; January-March 2020 44.5% [30.4%, 58.6%]; April-July 2020 46.8% [34.6%, 59.0%]; adjusted percentage-point difference-in-differences 1.4% [-2.7%, 5.5%]. Among 5,962 patients who received first-line systemic therapy, there was no association between the pandemic period and use of myelosuppressive therapy (adjusted percentage-point difference-in-differences 1.6% [-2.6%, 5.8%]). There was no meaningful effect modification by cancer type, race, or age.

Conclusions: Despite known pandemic-related delays in surveillance and diagnosis, the COVID-19 pandemic did not impact time to treatment initiation or treatment selection for patients with metastatic solid cancers.

Publication types

  • Preprint