Race-based assumptions in biomedical journal articles.
Background: Criteria for low-dose CT scan lung cancer screening vary across guidelines. Knowledge of the eligible pool across demographic groups can enable policy and programmatic decision-making, particularly for disproportionately affected populations. Research Question: What are the eligibility rates for low-dose CT scan screening according to sex and race or ethnicity and how do these rates relate to corresponding lung cancer incidence rates?
This Comment supports SDGs 3 and 10 by highlighting the need to centre race in the work of the global health community. The authors call on colleagues to meaningully engage with critical race theory, a transdisciplinary intellectual movement to understand and disrupt systemic racism.
This Article supprts SDGs 3 and 10 by assessing the performance of four severity scoring systems used for case-mix determination and benchmarking in intensive care units to identify possible ethnicity-based bias. The study found systemic differences in calibration across ethnicities.
This Comment supports SDGs 3 and 10 by highlighting the role of data scientists in challenging racism and discrimination. The Comment highlights how structural inequalities in society are easily encoded in datasets and in the application of data science, which can reinforce existing injustices.
Our nationwide network of BME women faculty collectively argue that racial funding disparity by the National Institutes of Health (NIH) remains the most insidious barrier to success of Black faculty in our profession. We thus refocus attention on this critical barrier and suggest solutions on how it can be dismantled.
Purpose: Radiation therapy interruption (RTI) worsens cancer outcomes. Our purpose was to benchmark and map RTI across a region in the United States with known cancer outcome disparities. Methods and Materials: All radiation therapy (RT) treatments at our academic center were cataloged. Major RTI was defined as ≥5 unplanned RT appointment cancellations. Univariate and multivariable logistic and linear regression analyses identified associated factors. Major RTI was mapped by patient residence.
There have been several recent studies addressing the genetic architecture of depression. This review serves to take stock of what is known now about the genetics of depression, how it has increased our knowledge and understanding of its mechanisms, and how the information and knowledge can be leveraged to improve the care of people affected.
