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Record W2600686060 · doi:10.2215/cjn.02180217

Donor Quality in the Eye of the Beholder: Interactions between Nonimmunologic Recipient and Donor Factors as Determinants of Graft Survival

2017· letter· en· W2600686060 on OpenAlexaff
Bethany J. Foster, Indra R. Gupta

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2017
Typeletter
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsMcGill University Health CentreMontreal Children's Hospital
Fundersnot available
KeywordsMedicineQuality (philosophy)Intensive care medicine

Abstract

fetched live from OpenAlex

Nonimmunologic factors have been increasingly recognized as relevant determinants of graft survival. The Kidney Donor Profile Index (KDPI), used in organ allocation in the United States, takes nonimmunologic donor characteristics known to be associated with graft survival into consideration in the allocation of donor kidneys (1); these include donor age, height, weight, race, history of hypertension, diabetes, hepatitis C, cause of death, serum creatinine, and donation after cardiac death status. Recipient-related factors are not included in the KDPI. The goal of the KDPI is to optimize graft life across all recipients by ensuring that organs with the greatest graft survival potential are allocated to patients with the longest estimated post-transplant survival (“longevity matching”). Therefore, candidates are prioritized for allocation on the basis of the concordance between donor quality (as measured by KDPI) and recipient estimated post-transplant survival: candidates in the top 20th estimated post-transplant survival percentile are prioritized to receive kidneys from donors with the lowest (best) 20th percentile KDPI score (1). Additional prioritization is given for highly sensitized recipients, 0 HLA mismatch, pediatric status, waiting time, and 0 or 1 HLA DR mismatch. This allocation strategy improves on past strategies by including important nonimmunologic factors in allocation decisions. In this issue of the Clinical Journal of the American Society of Nephrology, Miller et al. (2) consider the possibility that donor quality may depend, at least in part, on the recipient. A differing impact of donor quality by recipient race, age, and diabetes status was observed in the past (3). Miller et al.’s analysis of the Scientific Registry of Transplant Recipients database focuses on the importance of donor and recipient body size and donor and recipient sex on graft outcomes. Previous studies have examined associations between graft survival and each of donor–recipient sex mismatch (4–6) and donor–recipient body size mismatch (7–9). The novelty of this study lies in their examination of the combined effects of donor–recipient body size and sex mismatch. A body size mismatch between donor and recipient, wherein the donor is smaller than the recipient, has been previously demonstrated to be associated with poorer outcomes than when donor and recipient are of similar size or the donor is larger than the recipient (9). Miller et al. confirm this association. Importantly, they show no particular advantage to having a donor substantially larger than the recipient. Although larger donors do tend to offer better outcomes than smaller donors, this is likely because an important size mismatch between donor and recipient is unlikely when the donor is large. Recall, however, that the KDPI calculation only factors in the donor’s height and weight; the recipient’s body size is not part of the calculation. This means that smaller donors will have a higher (poorer) KDPI score than larger donors, even though a smaller donor’s organ may perform as well as an organ from a larger donor when transplanted into a small recipient. Donor–recipient sex-mismatched transplants have also been demonstrated in previous studies to be associated with poorer graft survival than sex-matched transplants (4,6,10). Some previous studies concluded that men who receive donor kidneys from women have poorer graft survival than all other donor–recipient sex combinations—believed to be due to the lower nephron “dose” provided by a female than a male kidney (10). In contrast, when Miller et al. compared the graft outcomes of 20 different donor–recipient sex and body size combinations, they found female recipients weighing >30 kg more than their male donor had the worst outcomes of all donor–recipient sex and body size combinations, with hazards for graft failure 1.5 times higher than male recipients of a size-matched male donor. Male recipients weighing >30 kg more than their female donor had the next worst outcomes, with hazards for graft failure 1.35 times higher than male recipients of a size-matched male donor. These findings, along with the observation that even within each donor–recipient sex combination, size mismatch plays a role in graft outcome, force a careful consideration of the mechanisms underlying the observed associations. Recipient body size, as estimated with weight, height, or body surface area, provides an indication of the metabolic demand on the transplanted kidney. Donor body size may provide some indication of nephron dose, which is determined by both nephron number and glomerular/nephron volume. However, nephron number correlates much more strongly with birthweight than with postnatal body size. Nephron formation occurs from week 6–36 of gestation (11); lower birthweight is associated with lower nephron number (12). In one study, a linear relationship between birthweight and nephron number was observed, and predicted 257,426 more glomeruli per kilogram higher birthweight (12). Adult weight is only very weakly correlated with birthweight. Nephron number also decreases with aging, with a mean estimated loss of 4500 glomeruli per kidney per year between 18 and 70 years of age (13). In contrast, glomerular volume increases with somatic growth, and is correlated with body size (12,14). When a kidney from a small donor is transplanted into a large recipient, Miller et al. suggest that the high demands on a kidney with a low nephron dose because of either low nephron number, low glomerular volume, or both, leads to hyperfiltration injury with glomerular hypertension and subsequent damage. If this is the mechanism explaining the observed association between donor–recipient body size mismatch and poor outcome, then it must be a low glomerular volume in the donor kidney that is responsible. Nephron number is poorly correlated with adult body weight; additional nephron formation does not occur after birth, only nephron growth. Nephron number can be predicted with greater accuracy from the birthweight and age of the donor than from body size. The reasons behind the associations between donor–recipient sex combinations and graft outcomes are complex. Male donors offer a slightly greater number of nephrons, and a larger nephron volume, than female donors (12). However, any advantages offered by a male donor are believed to be overwhelmed in female recipients by an immunologic reaction to the HY-antigen that is present in all male tissues (6). It is suggested that the cumulative effects of the overwhelming metabolic demands of a large body on a small donor kidney and the immunologic reaction to the HY antigen explain why large female recipients of small male donors have the worst outcomes of all donor–recipient sex and body size combinations. However, other factors must also be considered. Miller et al. compared outcomes of each donor–recipient sex and body size combination with those of size-matched male recipients of male donors. This analytic approach does not consider the possibility that outcomes may differ between male and female recipients for reasons intrinsic to the recipient and unrelated to the donor (15). Although several studies showed no differences in graft outcomes by sex (5,16), others suggested that there may be differences. Studies focusing on children and young adults <40 years old have consistently shown poorer outcomes among females than males (17,18). Factors that may contribute to recipient sex differences in graft outcomes include sex differences in medication adherence (19–21), and sex-related differences in immune activation—possibly driven by sex hormones. Estrogens tend to enhance immune activation whereas androgens tend to suppress immune activation (22,23). Sex differences in graft outcomes deserve additional study. The magnitude of the combined effects of donor–recipient size mismatch and sex mismatch was large, leading the authors to question whether matching for sex and body size should also be considered in organ allocation algorithms. This idea deserves consideration, but must be approached with a great deal of caution. This would require that a new KDPI-like index include both donor and recipient variables, and therefore that the index be calculated for each possible donor–candidate pair. Whether such complex matching would lead to meaningful improvements in graft survival is not known. More importantly, special care would have to be taken to avoid disadvantaging larger recipients. Restricting transplant options by prioritizing sex matching may also lead to longer waiting times. This may particularly affect women, who are more likely than men to be sensitized, and therefore need a larger pool of donors from which to find a suitable match. Women with a large body size would be particularly disadvantaged by an approach that favored allocation of sex- and body size-matched kidneys. The study by Miller et al. raises interesting questions regarding the possible value of matching donor and recipient not only for HLA and longevity, but also for body size and sex. Future simulation studies may help answer these questions. Disclosures None.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.006
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.143
GPT teacher head0.451
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2017
Admission routes1
Has abstractyes

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