| Literature DB >> 35185364 |
Christian Morath1, Salim S Hayek2, Bernd Döhler3, Christian Nusshag1, Claudia Sommerer1, Martin Zeier1, Jochen Reiser4, Caner Süsal3,5.
Abstract
Main problem: Soluble urokinase plasminogen activator receptor (suPAR) is an immunological risk factor for kidney disease and a prognostic marker for cardiovascular events.Entities:
Keywords: cardiovascular; kidney; mortality; suPAR; transplantation
Mesh:
Substances:
Year: 2022 PMID: 35185364 PMCID: PMC8842271 DOI: 10.3389/ti.2021.10071
Source DB: PubMed Journal: Transpl Int ISSN: 0934-0874 Impact factor: 3.782
Demographics of study patients, n (%).
| Characteristic | Unknown (%) | Cohort 1 | Cohort 2 |
|
|---|---|---|---|---|
| Geographical region | – | – | ||
| Europe | 242 (51%) | 549 (100%) | ||
| North America | 168 (35%) | – | ||
| Other | 64 (14%) | – | ||
| Transplant year | – | – | ||
| Range | 1988–2010 | 2006–2015 | ||
| Median | 2003 | 2011 | ||
| Transplant number | – | 0.12 | ||
| First transplant | 402 (85%) | 484 (88%) | ||
| Retransplant | 72 (15%) | 65 (12%) | ||
| Donor relationship | – | <0.001 | ||
| Living | 120 (25%) | 217 (40%) | ||
| Deceased | 354 (75%) | 332 (60%) | ||
| Recipient sex | – | 0.001 | ||
| Female | 155 (33%) | 233 (42%) | ||
| Male | 319 (67%) | 316 (58%) | ||
| Recipient age (years) | – | <0.001 | ||
| <18 | 52 (11%) | – | ||
| 18–59 | 342 (72%) | 403 (73%) | ||
| ≥60 | 80 (17%) | 146 (27%) | ||
| Mean ± SD | 41.8 ± 17.0 | 48.4 ± 14.1 | <0.001 | |
| Donor age (years) | 0.3 | <0.001 | ||
| <18 | 18 (8%) | 13 (2%) | ||
| 18–59 | 364 (77%) | 360 (66%) | ||
| ≥60 | 69 (15%) | 176 (32%) | ||
| Mean ± SD | 42.2 ± 16.1 | 52.2 ± 14.8 | <0.001 | |
| suPAR (ng/ml) | – | |||
| Range | 1.0–26.4 | 1.1–18.1 | ||
| Median (Tertiles) | 5.7 (4.9; 6.7) | 6.2 (5.2; 7.2) |
SD, standard deviation.
FIGURE 1Kaplan-Meier curves demonstrating the impact of suPAR (ng/ml) on 5-year mortality post-transplant in cohort 1 (A) and after serum collection date in cohort 2 (B). The categories “Low,” “Medium,” and “High” are defined by the tertiles of suPAR in each cohort. Log rank p values for trend are shown.
Results of the multivariable Cox regression analysis for influence of suPAR on mortality after serum collection date.
| Subpopulation | N | HR | 95% CI |
|
|---|---|---|---|---|
| All study patients | 1,023 | 2.14 | 1.48–3.08 |
|
| Death due to CVD | 4.24 | 1.81–9.96 |
| |
| Death due to infection | 2.20 | 0.90–5.39 | 0.083 | |
| Death due to cancer | 1.61 | 0.53–4.91 | 0.40 | |
| Cohort 1 | 474 | 1.92 | 1.20–3.08 |
|
| Cohort 2 | 549 | 2.78 | 1.51–5.13 |
|
| Good kidney function | 255 | 5.40 | 1.42–20.5 |
|
| Female patients | 388 | 1.91 | 0.97–3.76 | 0.061 |
| Male patients | 635 | 2.41 | 1.56–3.73 |
|
| Young patients <50 years | 584 | 3.38 | 1.81–6.34 |
|
| Elderly patients ≥50 years | 439 | 1.73 | 1.10–2.71 |
|
Hazard ratios (HR) with 95% confidence interval (CI) of patients with high suPAR values (≥upper tertile) are shown. Significant p-values marked bold.
FIGURE 2Kaplan-Meier curves demonstrating the impact of suPAR (ng/ml) above the upper tertile (“High”) against suPAR values below the upper tertile (“Normal”) on 5-year mortality after serum collection date. Log rank p value is shown.
FIGURE 3Kaplan-Meier curves demonstrating the impact of suPAR (ng/ml) on death with a functioning graft in the following 5 years after serum collection date as stratified by cause of death. Log rank p value is shown. (A) Due to CVD. (B) Due to infection. (C) Due to cancer.
FIGURE 4Kaplan-Meier curves demonstrating the impact of suPAR (ng/ml) on 5-years mortality after serum collection date as stratified by recipient sex (A,B) and recipient age (C,D). Log rank p value is shown.