E. Chow

Lifetime Incidence of CKD Stages 3-5 in the United States

BACKGROUND Lifetime risk estimates of chronic kidney disease (CKD) can motivate preventative behaviors at the individual level and forecast disease burden and health care use at the population level. STUDY DESIGN Markov Monte Carlo model simulation study. SETTING & POPULATION Current US black and white population. MODEL, PERSPECTIVE, & TIMEFRAME Markov models simulating kidney disease development, using an individual perspective and lifetime horizon. OUTCOMES Age-, sex-, and race-specific residual lifetime risks of CKD stages 3a+ (estimated glomerular filtration rate [eGFR] <60 mL/min/1.73 m²), 3b+ (eGFR <45 mL/min/1.73 m²), 4+ (eGFR <30 mL/min/1.73 m²), and end-stage renal disease (ESRD). MEASUREMENTS State transition probabilities of developing CKD and of dying prior to its development were modeled using: (1) mortality rates from the National Vital Statistics Report, (2) mortality risk estimates from a 2-million person meta-analysis, and (3) CKD prevalence from National Health and Nutrition Examination Surveys. Incidence, prevalence, and mortality related to ESRD were supplied by the US Renal Data System. RESULTS At birth, the overall lifetime risks of CKD stages 3a+, 3b+, 4+, and ESRD were 59.1%, 33.6%, 11.5%, and 3.6%, respectively. Women experienced greater CKD risk yet lower ESRD risk than men; blacks of both sexes had markedly higher CKD stage 4+ and ESRD risks (lifetime risks for white men, white women, black men, and black women, respectively: CKD stage 3a+, 53.6%, 64.9%, 51.8%, and 63.6%; CKD stage 3b+, 29.0%, 36.7%, 33.7%, and 40.2%; CKD stage 4+, 9.3%, 11.4%, 15.8%, and 18.5%; and ESRD, 3.3%, 2.2%, 8.5%, and 7.8%). Risk of CKD increased with age, with approximately one-half the CKD stage 3a+ cases developing after 70 years of age. LIMITATIONS CKD incidence was modeled from prevalence estimates in the US population. CONCLUSIONS In the United States, the lifetime risk of developing CKD stage 3a+ is high, emphasizing the importance of primary prevention and effective therapy to reduce CKD-related morbidity and mortality.

Frailty and Early Hospital Readmission After Kidney Transplantation

Early hospital readmission (EHR) after kidney transplantation (KT) is associated with increased morbidity and higher costs. Registry‐based recipient, transplant and center‐level predictors of EHR are limited, and novel predictors are needed. We hypothesized that frailty, a measure of physiologic reserve initially described and validated in geriatrics and recently associated with early KT outcomes, might serve as a novel, independent predictor of EHR in KT recipients of all ages. We measured frailty in 383 KT recipients at Johns Hopkins Hospital. EHR was ascertained from medical records as ≥1 hospitalization within 30 days of initial post‐KT discharge. Frail KT recipients were much more likely to experience EHR (45.8% vs. 28.0%, p = 0.005), regardless of age. After adjusting for previously described registry‐based risk factors, frailty independently predicted 61% higher risk of EHR (adjusted RR = 1.61, 95% CI: 1.18–2.19, p = 0.002). In addition, frailty improved EHR risk prediction by improving the area under the receiver operating characteristic curve (p = 0.01) as well as the net reclassification index (p = 0.04). Identifying frail KT recipients for targeted outpatient monitoring and intervention may reduce EHR rates.

Kidney Failure Risk Projection for the Living Kidney Donor Candidate

BACKGROUND Evaluation of candidates to serve as living kidney donors relies on screening for individual risk factors for end-stage renal disease (ESRD). To support an empirical approach to donor selection, we developed a tool that simultaneously incorporates multiple health characteristics to estimate a persons probable long-term risk of ESRD if that person does not donate a kidney. METHODS We used risk associations from a meta-analysis of seven general population cohorts, calibrated to the population-level incidence of ESRD and mortality in the United States, to project the estimated long-term incidence of ESRD among persons who do not donate a kidney, according to 10 demographic and health characteristics. We then compared 15-year projections with the observed risk among 52,998 living kidney donors in the United States. RESULTS A total of 4,933,314 participants from seven cohorts were followed for a median of 4 to 16 years. For a 40-year-old person with health characteristics that were similar to those of age-matched kidney donors, the 15-year projections of the risk of ESRD in the absence of donation varied according to race and sex; the risk was 0.24% among black men, 0.15% among black women, 0.06% among white men, and 0.04% among white women. Risk projections were higher in the presence of a lower estimated glomerular filtration rate, higher albuminuria, hypertension, current or former smoking, diabetes, and obesity. In the model-based lifetime projections, the risk of ESRD was highest among persons in the youngest age group, particularly among young blacks. The 15-year observed risks after donation among kidney donors in the United States were 3.5 to 5.3 times as high as the projected risks in the absence of donation. CONCLUSIONS Multiple demographic and health characteristics may be used together to estimate the projected long-term risk of ESRD among living kidney-donor candidates and to inform acceptance criteria for kidney donors. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases and others.).

Addressing Geographic Disparities in Liver Transplantation Through Redistricting

Severe geographic disparities exist in liver transplantation; for patients with comparable disease severity, 90‐day transplant rates range from 18% to 86% and death rates range from 14% to 82% across donation service areas (DSAs). Broader sharing has been proposed to resolve geographic inequity; however, we hypothesized that the efficacy of broader sharing depends on the geographic partitions used. To determine the potential impact of redistricting on geographic disparity in disease severity at transplantation, we combined existing DSAs into novel regions using mathematical redistricting optimization. Optimized maps and current maps were evaluated using the Liver Simulated Allocation Model. Primary analysis was based on 6700 deceased donors, 28 063 liver transplant candidates, and 242 727 Model of End‐Stage Liver Disease (MELD) changes in 2010. Fully regional sharing within the current regional map would paradoxically worsen geographic disparity (variance in MELD at transplantation increases from 11.2 to 13.5, p = 0.021), although it would decrease waitlist deaths (from 1368 to 1329, p = 0.002). In contrast, regional sharing within an optimized map would significantly reduce geographic disparity (to 7.0, p = 0.002) while achieving a larger decrease in waitlist deaths (to 1307, p = 0.002). Redistricting optimization, but not broader sharing alone, would reduce geographic disparity in allocation of livers for transplant across the United States.

Frailty and Mortality in Kidney Transplant Recipients

We have previously described strong associations between frailty, a measure of physiologic reserve initially described and validated in geriatrics, and early hospital readmission as well as delayed graft function. The goal of this study was to estimate its association with postkidney transplantation (post‐KT) mortality. Frailty was prospectively measured in 537 KT recipients at the time of transplantation between November 2008 and August 2013. Cox proportional hazards models were adjusted for confounders using a novel approach to substantially improve model efficiency and generalizability in single‐center studies. We precisely estimated the confounder coefficients using the large sample size of the Scientific Registry of Transplantation Recipients (n = 37 858) and introduced these into the single‐center model, which then estimated the adjusted frailty coefficient. At 5 years, the survivals were 91.5%, 86.0% and 77.5% for nonfrail, intermediately frail and frail KT recipients, respectively. Frailty was independently associated with a 2.17‐fold (95% CI: 1.01–4.65, p = 0.047) higher risk of death. In conclusion, regardless of age, frailty is a strong, independent risk factor for post‐KT mortality, even after carefully adjusting for many confounders using a novel, efficient statistical approach.

Early Changes in Liver Distribution Following Implementation of Share 35

In June 2013, a change to the liver waitlist priority algorithm was implemented. Under Share 35, regional candidates with MELD ≥ 35 receive higher priority than local candidates with MELD < 35. We compared liver distribution and mortality in the first 12 months of Share 35 to an equivalent time period before. Under Share 35, new listings with MELD ≥ 35 increased slightly from 752 (9.2% of listings) to 820 (9.7%, p = 0.3), but the proportion of deceased‐donor liver transplants (DDLTs) allocated to recipients with MELD ≥ 35 increased from 23.1% to 30.1% (p < 0.001). The proportion of regional shares increased from 18.9% to 30.4% (p < 0.001). Sharing of exports was less clustered among a handful of centers (Gini coefficient decreased from 0.49 to 0.34), but there was no evidence of change in CIT (p = 0.8). Total adult DDLT volume increased from 4133 to 4369, and adjusted odds of discard decreased by 14% (p = 0.03). Waitlist mortality decreased by 30% among patients with baseline MELD > 30 (SHR = 0.70, p < 0.001) with no change for patients with lower baseline MELD (p = 0.9). Posttransplant length‐of‐stay (p = 0.2) and posttransplant mortality (p = 0.9) remained unchanged. In the first 12 months, Share 35 was associated with more transplants, fewer discards, and lower waitlist mortality, but not at the expense of CIT or early posttransplant outcomes.

Survival Benefit of Primary Deceased Donor Transplantation With High‐KDPI Kidneys

The Kidney Donor Profile Index (KDPI) has been introduced as an aid to evaluating deceased donor kidney offers, but the relative benefit of high‐KDPI kidney transplantation (KT) versus the clinical alternative (remaining on the waitlist until receipt of a lower KDPI kidney) remains unknown. Using time‐dependent Cox regression, we evaluated the mortality risk associated with high‐KDPI KT (KDPI 71–80, 81–90 or 91–100) versus a conservative, lower KDPI approach (remain on waitlist until receipt of KT with KDPI 0–70, 0–80 or 0–90) in first‐time adult registrants, adjusting for candidate characteristics. High‐KDPI KT was associated with increased short‐term but decreased long‐term mortality risk. Recipients of KDPI 71–80 KT, KDPI 81–90 KT and KDPI 91–100 KT reached a “break‐even point” of cumulative survival at 7.7, 18.0 and 19.8 months post‐KT, respectively, and had a survival benefit thereafter. Cumulative survival at 5 years was better in all three high‐KDPI groups than the conservative approach (p < 0.01 for each comparison). Benefit of high‐KDPI KT was greatest in patients age >50 years and patients at centers with median wait time ≥33 months. Recipients of high‐KDPI KT can enjoy better long‐term survival; a high‐KDPI score does not automatically constitute a reason to reject a deceased donor kidney.

Identifying Appropriate Recipients for CDC Infectious Risk Donor Kidneys

Over 10% of deceased donors in 2011 met PHS/CDC criteria for infectious risk donor (IRD), and discard rates are significantly higher for kidneys from these donors. We hypothesized that patient phenotypes exist for whom the survival benefit outweighs the infectious risk associated with IRDs. A patient‐oriented Markov decision process model was developed and validated, based on SRTR data and meta‐analyses of window period risks among persons with IRD behaviors. The Markov model allows patients to see, for their phenotype, their estimated survival after accepting versus declining an IRD offer, graphed over a 5‐year horizon. Estimated 5‐year survival differences associated with accepting IRDs ranged from −6.4% to +67.3% for a variety of patient phenotypes. Factors most predictive of the survival difference with IRD transplantation were age, PRA, previous transplant, and the expected time until the next non‐IRD deceased donor offer. This study suggests that survival benefit derived from IRD kidneys varies widely by patient phenotype. Furthermore, within the inherent limitations of model‐based prediction, this study demonstrates that it is possible to identify those predicted to benefit from IRD kidneys, and illustrates how estimated survival curves based on a clinical decision can be presented to better inform patient and provider decision‐making.

A Risk Index for Living Donor Kidney Transplantation

Choosing between multiple living kidney donors, or evaluating offers in kidney paired donation, can be challenging because no metric currently exists for living donor quality. Furthermore, some deceased donor (DD) kidneys can result in better outcomes than some living donor kidneys, yet there is no way to compare them on the same scale. To better inform clinical decision‐making, we created a living kidney donor profile index (LKDPI) on the same scale as the DD KDPI, using Cox regression and adjusting for recipient characteristics. Donor age over 50 (hazard ratio [HR] per 10 years = 1.151.241.33), elevated BMI (HR per 10 units = 1.011.091.16), African‐American race (HR = 1.151.251.37), cigarette use (HR = 1.091.161.23), as well as ABO incompatibility (HR = 1.031.271.58), HLA B (HR = 1.031.081.14) mismatches, and DR (HR = 1.041.091.15) mismatches were associated with greater risk of graft loss after living donor transplantation (all p < 0.05). Median (interquartile range) LKDPI score was 13 (1–27); 24.2% of donors had LKDPI < 0 (less risk than any DD kidney), and 4.4% of donors had LKDPI > 50 (more risk than the median DD kidney). The LKDPI is a useful tool for comparing living donor kidneys to each other and to deceased donor kidneys.

Quantifying Postdonation Risk of ESRD in Living Kidney Donors

Studies have estimated the average risk of postdonation ESRD for living kidney donors in the United States, but personalized estimation on the basis of donor characteristics remains unavailable. We studied 133,824 living kidney donors from 1987 to 2015, as reported to the Organ Procurement and Transplantation Network, with ESRD ascertainment via Centers for Medicare and Medicaid Services linkage, using Cox regression with late entries. Black race (hazard ratio [HR], 2.96; 95% confidence interval [95% CI], 2.25 to 3.89; P<0.001) and male sex (HR, 1.88; 95% CI, 1.50 to 2.35; P<0.001) was associated with higher risk of ESRD in donors. Among nonblack donors, older age was associated with greater risk (HR per 10 years, 1.40; 95% CI, 1.23 to 1.59; P<0.001). Among black donors, older age was not significantly associated with risk (HR, 0.88; 95% CI, 0.72 to 1.09; P=0.3). Greater body mass index was associated with higher risk (HR per 5 kg/m2, 1.61; 95% CI, 1.29 to 2.00; P<0.001). Donors who had a first-degree biological relationship to the recipient had increased risk (HR, 1.70; 95% CI, 1.24 to 2.34; P<0.01). C-statistic of the model was 0.71. Predicted 20-year risk of ESRD for the median donor was only 34 cases per 10,000 donors, but 1% of donors had predicted risk exceeding 256 cases per 10,000 donors. Risk estimation is critical for appropriate informed consent and varies substantially across living kidney donors. Greater permissiveness may be warranted in older black candidate donors; young black candidates should be evaluated carefully.