Trends in financial payments from industry to US cancer centers, 2014-2021.

BACKGROUND: Industry payments to US cancer centers are poorly understood. METHODS: US National Cancer Institute (NCI)-designated comprehensive cancer centers were identified (n = 51). Industry payments to NCI-designated comprehensive cancer centers from 2014 to 2021 were obtained from Open Payments and National Institutes of Health (NIH) grant funding from NIH Research Portfolio Online Reporting Tools (RePORT). Given our focus on cancer centers, we measured the subset of industry payments related to cancer drugs specifically and the subset of NIH funding from the NCI. RESULTS: Despite a pandemic-related decline in 2020-2021, cancer-related industry payments to NCI-designated comprehensive cancer centers increased from $482 million in 2014 to $972 million in 2021. Over the same period, NCI research grant funding increased from $2 481  million to $2 724  million. The large majority of nonresearch payments were royalties and licensing payments. CONCLUSION: Industry payments to NCI-designated comprehensive cancer centers increased substantially more than NCI funding in recent years but were also more variable. These trends raise concerns regarding the influence and instability of industry payments.

Industry Payments to Physicians Endorsing Drugs and Devices on a Social Media Platform.

This study evaluates adherence to industry and professional standards among physicians endorsing drugs and devices on a social media platform.

Costs to Medicare of Nonrecommended Bone-Modifying Agent Use for Castration-Sensitive Prostate Cancer.

PURPOSE: Bone-modifying agents (BMAs) do not prevent skeletal-related events among patients with castration-sensitive prostate cancer (CSPC), but many patients receive BMAs unnecessarily. The costs to Medicare from overuse have not been assessed. METHODS: We used linked SEER-Medicare data 2011-2015 to measure the frequency and number of doses of zoledronic acid (ZA) and denosumab received during CSPC (between diagnosis and initiation of metastatic, castration resistant prostate cancer therapy). We estimated excess BMA among patients who received BMA therapy for CSPC and did not have an indication for osteoporosis fracture prevention. We used the Medicare fee schedule for drug prices and peer-reviewed sources to estimate adverse event frequencies and costs. RESULTS: Median CSPC duration was 387 days (IQR, 253-573), during which time 42% of patients received ≥one dose of denosumab (mean doses, 7) and 18% received ≥one dose of ZA (mean doses, 7). Thirty-eight percent of those receiving denosumab and 47% of those receiving ZA had a history of osteoporosis, osteopenia, spine or hip fracture, or hypercalcemia. The estimated, annual excess BMA cost to Medicare was $44,105,041 in US dollars (USD), composed of $43,303,078 USD and $45,512 USD in drug costs for denosumab and ZA, respectively, and $682,865 USD and $75,585 USD in adverse event costs, respectively. In one-way sensitivity analysis, the estimate was most sensitive to denosumab dosing frequency (estimate range, $28,469,237 USD-$98,830,351 USD) and duration of CSPC (estimate range, $36,823,311 USD-$99,015,908 USD). CONCLUSION: BMA overuse in CSPC incurs substantial cost to Medicare, largely because of denosumab drug costs. Excess costs may be reduced by greater adherence to guideline-concordant BMA use.

Methods for retrospectively improving race/ethnicity data quality: a scoping review.

Improving race and ethnicity (hereafter, race/ethnicity) data quality is imperative to ensure underserved populations are represented in data sets used to identify health disparities and inform health care policy. We performed a scoping review of methods that retrospectively improve race/ethnicity classification in secondary data sets. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, searches were conducted in the MEDLINE, Embase, and Web of Science Core Collection databases in July 2022. A total of 2 441 abstracts were dually screened, 453 full-text articles were reviewed, and 120 articles were included. Study characteristics were extracted and described in a narrative analysis. Six main method types for improving race/ethnicity data were identified: expert review (n = 9; 8%), name lists (n = 27, 23%), name algorithms (n = 55, 46%), machine learning (n = 14, 12%), data linkage (n = 9, 8%), and other (n = 6, 5%). The main racial/ethnic groups targeted for classification were Asian (n = 56, 47%) and White (n = 51, 43%). Some form of validation evaluation was included in 86 articles (72%). We discuss the strengths and limitations of different method types and potential harms of identified methods. Innovative methods are needed to better identify racial/ethnic subgroups and further validation studies. Accurately collecting and reporting disaggregated data by race/ethnicity are critical to address the systematic missingness of relevant demographic data that can erroneously guide policymaking and hinder the effectiveness of health care practices and intervention.