Evidence map›Paper›PMID 35747522›Full record

ArticleTransplantation direct2022

Clinical Utility in Adopting Race-free Kidney Donor Risk Index.

Mona D Doshi, Douglas E Schaubel, Yuwen Xu, Panduranga S Rao, Randall S Sung

Open access · goldAbstract read
In one paragraph

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 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 6% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Evaluation of kidney procurement biopsy and machine perfusion on allograft outcomes: A retrospective cohort study of the Organ Procurement and Transplantation Network database.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2026
    Article
  4. Article
  5. Enhancing Clinical Decision Support in Nephrology: Addressing Algorithmic Bias Through Artificial Intelligence Governance.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2024
    Review
  6. Article
  7. Article
  8. Eliminating Race From eGFR Calculations: Impact on Living Donor Programs.Transplant international : official journal of the European Society for Organ Transplantation · 2022
    Article
  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Mona D DoshiDivision of Nephrology, Department of Medicine, University of Michigan, Ann Arbor, MI.
Douglas E SchaubelDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Yuwen XuDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Panduranga S RaoDivision of Nephrology, Department of Medicine, University of Michigan, Ann Arbor, MI.
Randall S SungDepartment of Surgery, University of Michigan, Ann Arbor, MI.
University of Michigan–Ann Arbor · USUniversity of Pennsylvania · US

Funding

Survival Analysis Methods for Organ Failure DataR01DK070869 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI DOUGLAS EARL SCHAUBEL · 2005 to 2026
$4.7M
NIDDK NIH HHS R01 DK070869
6 · The paper itself

Abstract

Recent events of racial injustice prompted us to study potential impact of removing race from kidney donor risk index (KDRI) calculator. Methods: We used Scientific Registry for Transplant Recipients data to analyze outcomes of 66 987 deceased-donor kidney transplants performed in the United States between 2010 and 2016. Graft failure (GF) was defined as death or return to dialysis or requiring repeat transplant. We compared original KDRI and a race-free KDRI (Black donor coefficient zeroed out in the KDRI formula) with respect to recategorization of perceived GF risk (based on KDPI categories: ≤20, 21-34, 35-85, ≥86)' risk discrimination (using the C statistic) and predictive accuracy (using Brier score), and GF risk prediction (using Cox regression on time-to-GF). We used logistic regression to study the impact of donor race on discard probability. Results: There were 10 949 (16.3% of recipients) GF, and 1893 (17% of GFs) were among recipients of kidneys from Black donors. The use of race-free KDRI resulted in reclassification of 49% of kidneys from Black donors into lower GF risk categories. The impact on GF risk discrimination was minimal, with a relative decrease in C statistic of 0.16% and a change in GF predictive accuracy of 0.07%. For a given recipient/donor combination, transplants from Black (compared with non-Black) donors are estimated to decrease predicted graft survival at 1-y by 0.3%-3%, and 5-y by 1%-6%. Kidneys from Black donors are significantly more likely to be discarded (odds ratio adjusted for KDRI except race = 1.24). We estimate that an equal discard probability for Black and non-Black donors would yield 70 additional kidney transplants annually from Black donors. Conclusions: Use of race-free KDRI did not impact GF risk discrimination or predictive accuracy and may lower discard of kidneys from Black donors. We recommend use of race-free KDRI calculator acknowledging the possibility of miscalculation of GF risk in small proportion of kidneys from Black donors.

Identifiers

PMID35747522
PMCPMC9208880
OpenAlexW4283028410

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.