Douglas E. Schaubel

The Survival Benefit of Liver Transplantation

Demand for liver transplantation continues to exceed donor organ supply. Comparing recipient survival to that of comparable candidates without a transplant can improve understanding of transplant survival benefit. Waiting list and post‐transplant mortality was studied among a cohort of 12 996 adult patients placed on the waiting list between 2001 and 2003. Time‐dependent Cox regression models were fitted to determine relative mortality rates for candidates and recipients. Overall, deceased donor transplant recipients had a 79% lower mortality risk than candidates (HR = 0.21; p < 0.001). At Model for End‐stage Liver Disease (MELD) 18–20, mortality risk was 38% lower (p < 0.01) among recipients compared to candidates. Survival benefit increased with increasing MELD score; at the maximum score of 40, recipient mortality risk was 96% lower than that for candidates (p < 0.001). In contrast, at lower MELD scores, recipient mortality risk during the first post‐transplant year was much higher than for candidates (HR = 3.64 at MELD 6–11, HR = 2.35 at MELD 12–14; both p < 0.001). Liver transplant survival benefit at 1 year is concentrated among patients at higher risk of pre‐transplant death. Futile transplants among severely ill patients are not identified under current practice. With 1 year post‐transplant follow‐up, patients at lower risk of pre‐transplant death do not have a demonstrable survival benefit from liver transplant.

Hemodialysis versus peritoneal dialysis: A comparison of adjusted mortality rates

Although kidney transplantation is the preferred treatment method for patients with ESRD, most patients are placed on dialysis either while awaiting transplantation or as their only therapy. The question of which dialytic method provides the best patient survival remains unresolved. Survival analyses comparing hemodialysis and continuous ambulatory peritoneal dialysis/continuous cyclic peritoneal dialysis (CAPD/CCPD), a newer and less costly dialytic modality, have yielded conflicting results. Using data obtained from the Canadian Organ Replacement Register, we compared mortality rates between hemodialysis and CAPD/CCPD among 11,970 ESRD patients who initiated treatment between 1990 and 1994 and were followed-up for a maximum of 5 years. Factors controlled for include age, primary renal diagnosis, center size, and predialysis comorbid conditions. The mortality rate ratio (RR) for CAPD/CCPD relative to hemodialysis, as estimated by Poisson regression, was 0.73 (95% confidence interval: 0.68 to 0.78). No such relationship was found when an intent-to-treat Cox regression model was fit. Decreased covariable-adjusted mortality for CAPD/CCPD held within all subgroups defined by age and diabetes status, although the RRs increased with age and diabetes prevalence. The increased mortality on hemodialysis compared with CAPD/CCPD was concentrated in the first 2 years of follow-up. Although continuous peritoneal dialysis was associated with significantly lower mortality rates relative to hemodialysis after adjusting for known prognostic factors, the potential impact of unmeasured patient characteristics must be considered. Notwithstanding, we present evidence that CAPD/CCPD, a newer and less costly method of renal replacement therapy, is not associated with increased mortality rates relative to hemodialysis.

A comprehensive risk quantification score for deceased donor kidneys: the kidney donor risk index.

Background. We propose a continuous kidney donor risk index (KDRI) for deceased donor kidneys, combining donor and transplant variables to quantify graft failure risk. Methods. By using national data from 1995 to 2005, we analyzed 69,440 first-time, kidney-only, deceased donor adult transplants. Cox regression was used to model the risk of death or graft loss, based on donor and transplant factors, adjusting for recipient factors. The proposed KDRI includes 14 donor and transplant factors, each found to be independently associated with graft failure or death: donor age, race, history of hypertension, history of diabetes, serum creatinine, cerebrovascular cause of death, height, weight, donation after cardiac death, hepatitis C virus status, human leukocyte antigen-B and DR mismatch, cold ischemia time, and double or en bloc transplant. The KDRI reflects the rate of graft failure relative to that of a healthy 40-year-old donor. Results. Transplants of kidneys in the highest KDRI quintile (>1.45) had an adjusted 5-year graft survival of 63%, compared with 82% and 79% in the two lowest KDRI quintiles (<0.79 and 0.79–<0.96, respectively). There is a considerable overlap in the KDRI distribution by expanded and nonexpanded criteria donor classification. Conclusions. The graded impact of KDRI on graft outcome makes it a useful decision-making tool at the time of the deceased donor kidney offer.

Sarcopenia and Mortality after Liver Transplantation

BACKGROUND Surgeons frequently struggle to determine patient suitability for liver transplantation. Objective and comprehensive measures of overall burden of disease, such as sarcopenia, could inform clinicians and help avoid futile transplantations. STUDY DESIGN The cross-sectional area of the psoas muscle was measured on CT scans of 163 liver transplant recipients. After controlling for donor and recipient characteristics using Cox regression models, we described the relationship between psoas area and post-transplantation mortality. RESULTS Psoas area correlated poorly with Model for End-Stage Liver Disease score and serum albumin. Cox regression revealed a strong association between psoas area and post-transplantation mortality (hazard ratio = 3.7/1,000 mm(2) decrease in psoas area; p < 0.0001). When stratified into quartiles based on psoas area (holding donor and recipient characteristics constant), 1-year survival ranged from 49.7% for the quartile with the smallest psoas area to 87.0% for the quartile with the largest. Survival at 3 years among these groups was 26.4% and 77.2%, respectively. The impact of psoas area on survival exceeded that of all other covariates in these models. CONCLUSIONS Central sarcopenia strongly correlates with mortality after liver transplantation. Such objective measures of patient frailty, such as sarcopenia, can inform clinical decision making and, potentially, allocation policy. Additional work is needed develop valid and clinically relevant measures of sarcopenia and frailty in liver transplantation.

The Survival Benefit of Deceased Donor Liver Transplantation as a Function of Candidate Disease Severity and Donor Quality

The survival benefit of liver transplantation depends on candidate disease severity, as measured by MELD score. However, donor liver quality may also affect survival benefit. Using US data from the SRTR on 28 165 adult liver transplant candidates wait‐listed between 2001 and 2005, we estimated survival benefit according to cross‐classifications of candidate MELD score and deceased donor risk index (DRI) using sequential stratification. Covariate‐adjusted hazard ratios (HR) were calculated for each liver transplant recipient at a given MELD with an organ of a given DRI, comparing posttransplant mortality to continued wait‐listing with possible later transplantation using a lower‐DRI organ. High‐DRI organs were more often transplanted into lower‐MELD recipients and vice versa. Compared to waiting for a lower‐DRI organ, the lowest‐MELD category recipients (MELD 6–8) who received high‐DRI organs experienced significantly higher mortality (HR = 3.70; p < 0.0005). All recipients with MELD ≥20 had a significant survival benefit from transplantation, regardless of DRI. Transplantation of high‐DRI organs is effective for high but not low‐MELD candidates. Pairing of high‐DRI livers with lower‐MELD candidates fails to maximize survival benefit and may deny lifesaving organs to high‐MELD candidates who are at high risk of death without transplantation.

Survival Benefit‐Based Deceased‐Donor Liver Allocation

Currently, patients awaiting deceased‐donor liver transplantation are prioritized by medical urgency. Specifically, wait‐listed chronic liver failure patients are sequenced in decreasing order of Model for End‐stage Liver Disease (MELD) score. To maximize lifetime gained through liver transplantation, posttransplant survival should be considered in prioritizing liver waiting list candidates. We evaluate a survival benefit based system for allocating deceased‐donor livers to chronic liver failure patients. Under the proposed system, at the time of offer, the transplant survival benefit score would be computed for each patient active on the waiting list. The proposed score is based on the difference in 5‐year mean lifetime (with vs. without a liver transplant) and accounts for patient and donor characteristics. The rank correlation between benefit score and MELD score is 0.67. There is great overlap in the distribution of benefit scores across MELD categories, since waiting list mortality is significantly affected by several factors. Simulation results indicate that over 2000 life‐years would be saved per year if benefit‐based allocation was implemented. The shortage of donor livers increases the need to maximize the life‐saving capacity of procured livers. Allocation of deceased‐donor livers to chronic liver failure patients would be improved by prioritizing patients by transplant survival benefit.

Cancer Incidence Among Canadian Kidney Transplant Recipients

A number of studies have observed increased cancer incidence rates among individuals who have received renal transplants. Generally, however, these studies have been limited by relatively small sample sizes, short follow‐up intervals or focused on only one cancer site. We conducted a nationwide population‐based study of 11,155 patients who underwent kidney transplantation between 1981 and 1998. Incident cancers were identified up to December 31, 1999, through record linkage to the Canadian Cancer Registry. Patterns of cancer incidence in the cohort were compared to the Canadian general population using standardized incidence ratios (SIRs). We examined variations in risk according time since transplantation, year of transplantation and age at transplantation. In our patient population, we observed a total of 778 incident cancers versus 313.2 expected (SIR = 2.5, 95% CI = 2.3–2.7). Site‐specific SIRs were highest for cancer of the lip (SIR = 31.3, 95% CI = 23.5–40.8), non‐Hodgkins lymphoma (NHL) (SIR = 8.8, 95% CI = 7.4–10.5), and kidney cancer (SIR = 7.3, 95% CI = 5.7–9.2). SIRs for NHL and cancer of the lip and kidney were highest and among transplant patients. This study confirms previous findings of increased risks of posttransplant cancer. Our findings underscore the need for increased vigilance among kidney transplant recipients for cancers at sites where there are no population‐based screening programs in place.

Calculating Life Years from Transplant (LYFT): Methods for Kidney and Kidney-Pancreas Candidates

The Organ Procurement and Transplantation Network (OPTN) Kidney Committee is considering a proposal for a new deceased donor kidney allocation system. Among the components under consideration is a strategy to rank candidates in part by the estimated incremental years of life that are expected to be achieved with a transplant from a specific available deceased donor, computed as the difference in expected median lifespan with that transplant compared with remaining on dialysis. This concept has been termed life years from transplant or LYFT. Median lifespans could be calculated, based on objective medical criteria, for each candidate when a deceased donor kidney becomes available, based on Cox regression models using current candidate and donor medical information. The distribution of the calculated LYFT scores for an average nonexpanded criteria donor kidney is similar across candidate sex, race/ethnicity, insurance status and, with the exception of diabetes, diagnosis. LYFT scores tend to be higher for younger candidates and lower for diabetics receiving a kidney‐alone rather than a simultaneous kidney‐pancreas transplant. Prioritizing candidates with higher LYFT scores for each available kidney could substantially increase total years of life among both transplant candidates and recipients. LYFT is also a powerful metric for assessing trends in allocation outcomes and for comparing alternative allocation systems.

Frailty, core muscle size, and mortality in patients undergoing open abdominal aortic aneurysm repair

OBJECTIVES Determining operative risk in patients undergoing aortic surgery is a difficult process, as multiple variables converge to affect overall mortality. Patient frailty is certainly a contributing factor, but is difficult to measure, with surgeons often relying on subjective or intuitive influences. We sought to use core muscle size as an objective measure of frailty, and determine its utility as a predictor of survival after abdominal aortic aneurysm (AAA) repair. METHODS Four hundred seventy-nine patients underwent elective open AAA repair between 2000 and 2008. Two hundred sixty-two patients (54.7%) had preoperative computed tomography (CT) scans available for analysis. Cross-sectional areas of the psoas muscles at the level of the L4 vertebra were measured. The covariate-adjusted effect of psoas area on postoperative mortality was assessed using Cox regression. RESULTS Of the 262 patients, there were 55 deaths and the mean length of follow-up was 2.3 years. Cox regression revealed a significant association between psoas area and postoperative mortality (P = .003). The effect of psoas area was found to decrease significantly as follow-up time increased (P = .008). Among all covariates included in the Cox models (including predictors of mortality such as American Society of Anesthesiologists [ASA] score), the psoas area was the most significant. CONCLUSION Core muscle size, an objective measure of frailty, correlates strongly with mortality after elective AAA repair. A better understanding of the role of frailty and core muscle size may aid in risk stratification and impact timing of surgical repair, especially in more complex aortic operations.

Rates of solid-organ wait-listing, transplantation, and survival among residents of rural and urban areas

CONTEXT Disparities in access to organ transplantation exist for racial minorities, women, and patients with lower socioeconomic status or inadequate insurance. Rural residents represent another group that may have impaired access to transplant services. OBJECTIVE To assess the association of rural residence with waiting list registration for heart, liver, and kidney transplant and rates of transplantation among wait-listed candidates. DESIGN, SETTING, AND PATIENTS Five-year US cohort of 174,630 patients who were wait-listed and who underwent heart, liver, or kidney transplantation between 1999 and 2004. MAIN OUTCOME MEASURES Rates of new waiting list registrations and transplants per million population for residents of 3 residential classifications (rural/small town population, <10,000; micropolitan, 10,000-50,000; and metropolitan >50,000 or suburb of major city). RESULTS Compared with urban residents, waiting list registration rates for rural/small town residents were significantly lower for heart (covariate-adjusted rate ratio [RR] = 0.91; 95% confidence interval [CI], 0.86-0.96; P<.002), liver (RR = 0.86; 95% CI, 0.83-0.89; P<.001), and kidney transplants (RR = 0.92; 95% CI, 0.90-0.95; P<.001). Compared with residents in urban areas, rural/small town residents had lower relative transplant rates for heart (RR = 0.88; 95% CI, 0.81-0.94; P = .004), liver (RR = 0.80; 95% CI, 0.77-0.84; P<.001), and kidney transplantation (covariate-adjusted RR = 0.90; 95% CI, 0.88-0.93; P<.001). These disparities were consistent across national organ allocation regions. Significantly longer waiting times among rural patients wait-listed for heart transplantation were observed but not for liver and kidney transplantation. There were no significant differences in posttransplantation outcomes between groups. CONCLUSIONS Patients living in rural areas had a lower rate of wait-lisiting and transplant of solid organs, but did not experience significantly different outcomes following transplant. Differences in rates of wait-listing and transplant may be due to variations in the burden of disease between different patient groups or barriers to evaluation and waiting list entry for rural residents with organ failure.