Background and Objective The Surveillance, Epidemiology, and End Results Program (SEER) program and the National Program of Cancer Registries (NPCR), are authoritative sources for population cancer surveillance and research in the US. An increasing number of recent oncology studies are based on the electronic health record (EHR)-derived de-identified databases created and maintained by Flatiron Health. This report describes the differences in the originating sources and data development processes, and compares baseline demographic characteristics in the cancer-specific databases from Flatiron Health, SEER, and NPCR, to facilitate interpretation of research findings based on these sources. Methods Patients with documented care from January 1, 2011 through May 31, 2019 in a series of EHR-derived Flatiron Health de-identified databases covering multiple tumor types were included. SEER incidence data (obtained from the SEER 18 database) and NPCR incidence data (obtained from the US Cancer Statistics public use database) for malignant cases diagnosed from January 1, 2011 to December 31, 2016 were included. Comparisons of demographic variables were performed across all disease-specific databases, for all patients and for the subset diagnosed with advanced-stage disease. Results As of May 2019, a total of 201,570 patients with 19 different cancer types were included in Flatiron Health datasets. In an overall comparison to national cancer registries, patients in the Flatiron Health databases had similar sex and geographic distributions, but appeared to be diagnosed with later stages of disease and their age distribution differs from the other datasets. For variables such as stage and race, Flatiron Health databases had a greater degree of incompleteness. There are variations in these trends by cancer types. Conclusions These three databases present general similarities in demographic and geographic distribution, but there are overarching differences across the populations they cover. Differences in data sourcing (medical oncology EHRs vs cancer registries), and disparities in sampling approaches and rules of data acquisition may explain some of these divergences. Furthermore, unlike the steady information flow entered into registries, the availability of medical oncology EHR-derived information reflects the extent of involvement of medical oncology clinics at different points in the specialty management of individual diseases, resulting in inter-disease variability. These differences should be considered when interpreting study results obtained with these databases.

The performance of Covid-19 diagnostic tests must continue to be reassessed with new variants of concern. The objective of this study was to describe the discordance in saliva SARS-CoV-2 PCR and nasal rapid antigen test results during the early infectious period. We identified a high-risk occupational case cohort of 30 individuals with daily testing during an Omicron outbreak in December 2021. Based on viral load and transmissions confirmed through epidemiological investigation, most Omicron cases were infectious for several days before being detectable by rapid antigen tests.

Because immune checkpoint inhibitor therapies (CPI) lack the toxicities of chemotherapy, oncologists may prescribe CPI to patients at the end of life. This article describes real‐world patterns of CPI initiation near the end of life among individuals with metastatic urothelial cell carcinoma.

A multicomponent, mentored research experience that engages medical students from underrepresented communities and is organized within a clinical trials network may expand the pool of diverse public health scientists. Efforts to sustain scholar interest over time and track career trajectories are warranted.

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LBA1 Background: Racial disparities in cancer outcomes remain a societal challenge. The ACA sought to improve equity in healthcare access and outcomes by permitting states to expand Medicaid and providing subsidies for purchase of private insurance. We assessed the impact of Medicaid expansions on racial disparities in time to treatment among patients (pts) with advanced cancer. Methods: We selected pts ages 18-64 years with advanced or metastatic cancer (NSCLC, breast, urothelial, gastric, colorectal, renal cell, prostate, and melanoma), diagnosed between Jan 1, 2011 and Dec 31, 2018, from the nationwide Flatiron Health electronic health record-derived database. We assigned expansion status based on whether the pts’ state of residence had expanded Medicaid as of the diagnosis date. We estimated Medicaid expansion-related changes in the rate of “timely treatment,” an outcome defined as first-line treatment start within 30 days of advanced or metastatic diagnosis. Regression model covariates included race (White, African American, Asian, and Other race), age, sex, practice type, cancer type, stage, and unemployment rate, using time and state fixed-effects. Regression results present predictive margins. Results: The study included 34,067 pts (median age 57 years; 12% African American). Racial disparities were observed pre-expansion: African American pts were 4.9 percentage points (%pt) less likely to receive timely treatment (Table). Regardless of race, Medicaid expansion trended toward an increase in timely treatment overall (p = 0.05). Expansion was associated with a differential benefit for African American vs white pts (6.9 %pt and 1.8 %pt). Prior racial disparities were no longer observed after Medicaid expansion. Conclusions: Implementation of Medicaid expansions as part of the ACA differentially improved African American cancer pts’ receipt of timely treatment, reducing racial disparities in access to care.[Table: see text]

PURPOSE: As immune checkpoint inhibitors (ICIs) have transformed the care of patients with cancer, it is unclear whether treatment at the end of life (EOL) has changed. Because aggressive therapy at the EOL is associated with increased costs and patient distress, we explored the association between the Food and Drug Administration (FDA) approvals of ICIs and treatment patterns at the EOL. METHODS: We conducted a retrospective, observational study using patient-level data from a nationwide electronic health record–derived database. Patients had advanced melanoma, non–small-cell lung cancer (NSCLC; cancer types with an ICI indication), or microsatellite stable (MSS) colon cancer (a cancer type without an ICI indication) and died between 2013 and 2017. We calculated annual proportions of decedents who received systemic cancer therapy in the final 30 days of life, using logistic regression to model the association between the post-ICI FDA approval time and use of systemic therapy at the EOL, adjusting for patient characteristics. We assessed the use of chemotherapy or targeted/biologic therapies at the EOL, before and after FDA approval of ICIs using Pearson chi-square test. RESULTS: There was an increase in use of EOL systemic cancer therapy in the post-ICI approval period for both melanoma (33.9% to 43.2%; P < .001) and NSCLC (37.4% to 40.3%; P < .001), with no significant change in use of systemic therapy in MSS colon cancer. After FDA approval of ICIs, patients with NSCLC and melanoma had a decrease in the use of chemotherapy, with a concomitant increase in use of ICIs at the EOL. CONCLUSION: The adoption of ICIs was associated with a substantive increase in the use of systemic therapy at the EOL in melanoma and a smaller yet significant increase in NSCLC.

Objective: To evaluate the cost-effectiveness of financial incentives for human immunodeficiency virus (HIV) viral suppression compared to standard of care. Study Design: Mathematical model of 2-year intervention offering financial incentives ($70 quarterly) for viral suppression (<400 copies/ml 3 ) based on the HPTN 065 clinical trial with HIV patients in the Bronx, NY and Washington, D.C. Methods: A disease progression model with HIV transmission risk equations was developed following guidelines from the Second Panel on Cost-Effectiveness in Health and Medicine. We used health care sector and societal perspectives, 3% discount rate, and lifetime horizon. Data sources included trial data (baseline N ¼ 16,208 patients), CDC HIV Surveillance data, and published literature. Outcomes were costs (2017 USD), quality-adjusted life years (QALYs), HIV infections prevented, and incremental cost-effectiveness ratio (ICER). Results: Financial incentives for viral suppression were estimated to be costsaving from a societal perspective and cost-effective ($49,877/QALY) from a health care sector perspective. Compared to the standard of care, financial incentives gain 0.06 QALYs and lower discounted lifetime costs by $4210 per patient. The model estimates that incentivized patients transmit 9% fewer infections than the standard-of-care patients. In the sensitivity analysis, ICER 95% credible intervals ranged from cost-saving to $501,610/QALY with 72% of simulations being cost-effective using a $150,000/QALY threshold. Modeling results are limited by uncertainty in efficacy from the clinical trial. Conclusions: Financial incentives, as used in HTPN 065, are estimated to improve quality and length of life, reduce HIV transmissions, and save money from a societal perspective. Financial incentives offer a promising option for enhancing the benefits of medication in the United States.