ArticleTransplantation direct2022
Short Report: Race and Ethnicity Misclassification in Kidney Transplantation Research.
Article in Transplantation direct, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Residential and Transplant Center Neighborhood Segregation and Live Donor Liver Transplant.JAMA network open · 2026Article
- Components of Residential Neighborhood Deprivation and Their Impact on the Likelihood of Live-Donor and Preemptive Kidney Transplantation.Clinical transplantation · 2024Article
- Barriers to Timely Diagnosis of Eosinophilic Gastrointestinal Diseases.The journal of allergy and clinical immunology. In practice · 2024Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Recently, the misuse of race as a biological variable, rather than a social construct, in biomedical research has received national attention for its contributions to medical bias. In national transplant registry data, bias may arise from measurement imprecision because of the collection of provider-perceived race rather than patients' own self-report. Methods: We linked Scientific Registry of Transplant Recipients data to a prospective, multicenter cohort study of adult kidney transplant patients (December 2008-February 2020) that collects patient-reported race. We computed Cohen's kappa statistic to estimate agreement between provider-perceived and patient-reported race in the 2 data sources. We used an unadjusted generalized linear model to examine changes in agreement over time. Results: Among 2942 kidney transplant patients, there was almost perfect agreement among Asian (kappa = 0.88, 95% confidence interval [CI], 0.84-0.92), Black (kappa = 0.97, 95% CI, 0.96-0.98), and White categories (kappa = 0.95, 95% CI, 0.93-0.96) and worse agreement among Hispanic/Latino (kappa = 0.66, 95% CI, 0.57-0.74) and Native Hawaiian/Other Pacific Islander categories (kappa = 0.40, 95% CI, 0.01-0.78). The percent agreement decreased over time (difference in percent agreement = -0.55, 95% CI, -0.75 to -0.34). However, there were differences in these trends by race: -0.07/y, 95% CI, -0.21 to 0.07 for Asian; -0.06/y, 95% CI, -0.28 to 0.16 for Black; -0.01/y, 95% CI, -0.21 to 0.19 for Hispanic/Latino; -0.43/y, 95% CI, -0.58 to -0.28 for White categories. Conclusions: Race misclassification has likely led to increasingly biased research estimates over time, especially for Asian, Hispanic/Latino, and Native Hawaiian/Other Pacific Islander study populations. Improvements to race measurement include mandating patient-reported race, expanding race categories to better reflect contemporary US demographics, and allowing write-ins on data collection forms, as well as supplementing data with qualitative interviews or validated measures of cultural identity, ancestry, and discrimination.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.