Treatment preferences of groups (e.g., clinical centers) have often been proposed as instruments to control for unmeasured confounding‐by‐indication in instrumental variable (IV) analyses. However, formal evaluations of these group‐preference‐based instruments are lacking. Unique challenges include the following: (i) correlations between outcomes within groups; (ii) the multi‐value nature of the instruments; (iii) unmeasured confounding occurring between and within groups. We introduce the framework of between‐group and within‐group confounding to assess assumptions required for the group‐preference‐based IV analyses. Our work illustrates that, when unmeasured confounding effects exist only within groups but not between groups, preference‐based IVs can satisfy assumptions required for valid instruments. We then derive a closed‐form expression of asymptotic bias of the two‐stage generalized ordinary least squares estimator when the IVs are valid. Simulations demonstrate that the asymptotic bias formula approximates bias in finite samples quite well, particularly when the number of groups is moderate to large. The bias formula shows that when the cluster size is finite, the IV estimator is asymptotically biased; only when both the number of groups and cluster size go to infinity, the bias disappears. However, the IV estimator remains advantageous in reducing bias from confounding‐by‐indication. The bias assessment provides practical guidance for preference‐based IV analyses. To increase their performance, one should adjust for as many measured confounders as possible, consider groups that have the most random variation in treatment assignment and increase cluster size. To minimize the likelihood for these IVs to be invalid, one should minimize unmeasured between‐group confounding. Copyright © 2014 John Wiley & Sons, Ltd.

Standardized mortality ratios (SMRs) reported by Medicare compare mortality at individual dialysis facilities with the national average, and are currently adjusted for race. However, whether the adjustment for race obscures or clarifies disparities in quality of care for minority groups is unknown. Cox model-based SMRs were computed with and without adjustment for patient race for 5920 facilities in the United States during 2010. The study population included virtually all patients treated with dialysis during this period. Without race adjustment, facilities with higher proportions of black patients had better survival outcomes; facilities with the highest percentage of black patients (top 10%) had overall mortality rates approximately 7% lower than expected. After adjusting for within-facility racial differences, facilities with higher proportions of black patients had poorer survival outcomes among black and non-black patients; facilities with the highest percentage of black patients (top 10%) had mortality rates approximately 6% worse than expected. In conclusion, accounting for within-facility racial differences in the computation of SMR helps to clarify disparities in quality of health care among patients with ESRD. The adjustment that accommodates within-facility comparisons is key, because it could also clarify relationships between patient characteristics and health care provider outcomes in other settings.

An issue of substantial importance is the monitoring and improvement of health care facilities such as hospitals, nursing homes, dialysis units or surgical wards. In addressing this, there is a need for appropriate methods for monitoring health outcomes. On the one hand, statistical tools are needed to aid centers in instituting and evaluating quality improvement programs and, on the other hand, to aid overseers and payers in identifying and addressing sub-standard performance. In the latter case, the aim is to identify situations where there is evidence that the facility's outcomes are outside of normal expectations; such facilities would be flagged and perhaps audited for potential difficulties or censured in some way. Methods in use are based on models where the center effects are taken as fixed or random. We take a systematic approach to assessing the merits of these methods when the patient outcome of interest arises from a linear model. We argue that methods based on fixed effects are more appropriate for the task of identifying extreme outcomes by providing better accuracy when the true facility effect is far from that of the average facility and avoiding confounding issues that arise in the random effects models when the patient risks are correlated with facility effects. Finally, we consider approaches to flagging that are based on the Z-statistics arising from the fixed effects model, but which account in a robust way for the intrinsic variation between facilities as contemplated in the standard random effects model. We provide an illustration in monitoring survival outcomes of dialysis facilities in the US.

BACKGROUND AND OBJECTIVES:When hemodialysis dose is scaled to body water (V), women typically receive a greater dose than men, but their survival is not better given a similar dose. This study sought to determine whether rescaling dose to body surface area (SA) might reveal different associations among dose, sex, and mortality. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS:Single-pool Kt/V (spKt/V), equilibrated Kt/V, and standard Kt/V (stdKt/V) were computed using urea kinetic modeling on a prevalent cohort of 7229 patients undergoing thrice-weekly hemodialysis. Data were obtained from the Centers for Medicare & Medicaid Services 2008 ESRD Clinical Performance Measures Project. SA-normalized stdKt/V (SAN-stdKt/V) was calculated as stdKt/V × ratio of anthropometric volume to SA/17.5. Patients were grouped into sex-specific dose quintiles (reference: quintile 1 for men). Adjusted hazard ratios (HRs) for 1-year mortality were calculated using Cox regression. RESULTS:spKt/V was higher in women (1.7 ± 0.3) than in men (1.5 ± 0.2; P<0.001), but SAN-stdKt/V was lower (women: 2.3 ± 0.2; men: 2.5 ± 0.3; P<0.001). For both sexes, mortality decreased as spKt/V increased, until spKt/V was 1.6-1.7 (quintile 4 for men: HR, 0.62; quintile 3 for women: HR, 0.64); no benefit was observed with higher spKt/V. HR for mortality decreased further at higher SAN-stdKt/V in both sexes (quintile 5 for men: HR, 0.69; quintile 5 for women: HR, 0.60). CONCLUSIONS:SA-based dialysis dose results in dose-mortality relationships substantially different from those with volume-based dosing. SAN-stdKt/V analyses suggest women may be relatively underdosed when treated by V-based dosing. SAN-stdKt/V as a measure for dialysis dose may warrant further study.

KDOQI practice guidelines recommend predialysis blood pressure <140/90 mm Hg; however, most prior studies had found elevated mortality with low, not high, systolic blood pressure. This is possibly due to unmeasured confounders affecting systolic blood pressure and mortality. To lessen this bias, we analyzed 24,525 patients by Cox regression models adjusted for patient and facility characteristics. Compared with predialysis systolic blood pressure of 130-159 mm Hg, mortality was 13% higher in facilities with 20% more patients at systolic blood pressure of 110-129 mm Hg and 16% higher in facilities with 20% more patients at systolic blood pressure of ≥160 mm Hg. For patient-level systolic blood pressure, mortality was elevated at low (<130 mm Hg), not high (≥180 mm Hg), systolic blood pressure. For predialysis diastolic blood pressure, mortality was lowest at 60-99 mm Hg, a wide range implying less chance to improve outcomes. Higher mortality at systolic blood pressure of <130 mm Hg is consistent with prior studies and may be due to excessive blood pressure lowering during dialysis. The lowest risk facility systolic blood pressure of 130-159 mm Hg indicates this range may be optimal, but may have been influenced by unmeasured facility practices. While additional study is needed, our findings contrast with KDOQI blood pressure targets, and provide guidance on optimal blood pressure range in the absence of definitive clinical trial data.

The Organ Procurement and Transplantation Network has proposed new concepts for the allocation of kidneys from deceased donors that would introduce an element of matching of the estimated future survival of transplanted kidneys and with that of recipients.

In 2003, the US kidney allocation system was changed to eliminate priority for HLA-B similarity. We report outcomes from before and after this change using data from the Scientific Registry of Transplant Recipients (SRTR). Analyses were based on 108 701 solitary deceased donor kidney recipients during the 6 years before and after the policy change. Racial/ethnic distributions of recipients in the two periods were compared (chi-square); graft failures were analyzed using Cox models. In the 6 years before and after the policy change, the overall number of deceased donor transplants rose 23%, with a larger increase for minorities (40%) and a smaller increase for non-Hispanic whites (whites) (8%). The increase in the proportion of transplants for non-whites versus whites was highly significant (p < 0.0001). Two-year graft survival improved for all racial/ethnic groups after implementation of this new policy. Findings confirmed prior SRTR predictions. Following elimination of allocation priority for HLA-B similarity, the deficit in transplantation rates among minorities compared with that for whites was reduced but not eliminated; furthermore, there was no adverse effect on graft survival.

CONTEXT Solid organ transplant recipients have elevated cancer risk due to immunosuppression and oncogenic viral infections. Because most prior research has concerned kidney recipients, large studies that include recipients of differing organs can inform cancer etiology. OBJECTIVE To describe the overall pattern of cancer following solid organ transplantation. DESIGN, SETTING, AND PARTICIPANTS Cohort study using linked data on solid organ transplant recipients from the US Scientific Registry of Transplant Recipients (1987-2008) and 13 state and regional cancer registries. MAIN OUTCOME MEASURES Standardized incidence ratios (SIRs) and excess absolute risks (EARs) assessing relative and absolute cancer risk in transplant recipients compared with the general population. RESULTS The registry linkages yielded data on 175,732 solid organ transplants (58.4% for kidney, 21.6% for liver, 10.0% for heart, and 4.0% for lung). The overall cancer risk was elevated with 10,656 cases and an incidence of 1375 per 100,000 person-years (SIR, 2.10 [95% CI, 2.06-2.14]; EAR, 719.3 [95% CI, 693.3-745.6] per 100,000 person-years). Risk was increased for 32 different malignancies, some related to known infections (eg, anal cancer, Kaposi sarcoma) and others unrelated (eg, melanoma, thyroid and lip cancers). The most common malignancies with elevated risk were non-Hodgkin lymphoma (n = 1504; incidence: 194.0 per 100,000 person-years; SIR, 7.54 [95% CI, 7.17-7.93]; EAR, 168.3 [95% CI, 158.6-178.4] per 100,000 person-years) and cancers of the lung (n = 1344; incidence: 173.4 per 100,000 person-years; SIR, 1.97 [95% CI, 1.86-2.08]; EAR, 85.3 [95% CI, 76.2-94.8] per 100,000 person-years), liver (n = 930; incidence: 120.0 per 100,000 person-years; SIR, 11.56 [95% CI, 10.83-12.33]; EAR, 109.6 [95% CI, 102.0-117.6] per 100,000 person-years), and kidney (n = 752; incidence: 97.0 per 100,000 person-years; SIR, 4.65 [95% CI, 4.32-4.99]; EAR, 76.1 [95% CI, 69.3-83.3] per 100,000 person-years). Lung cancer risk was most elevated in lung recipients (SIR, 6.13 [95% CI, 5.18-7.21]) but also increased among other recipients (kidney: SIR, 1.46 [95% CI, 1.34-1.59]; liver: SIR, 1.95 [95% CI, 1.74-2.19]; and heart: SIR, 2.67 [95% CI, 2.40-2.95]). Liver cancer risk was elevated only among liver recipients (SIR, 43.83 [95% CI, 40.90-46.91]), who manifested exceptional risk in the first 6 months (SIR, 508.97 [95% CI, 474.16-545.66]) and a 2-fold excess risk for 10 to 15 years thereafter (SIR, 2.22 [95% CI, 1.57-3.04]). Among kidney recipients, kidney cancer risk was elevated (SIR, 6.66 [95% CI, 6.12-7.23]) and bimodal in onset time. Kidney cancer risk also was increased in liver recipients (SIR, 1.80 [95% CI, 1.40-2.29]) and heart recipients (SIR, 2.90 [95% CI, 2.32-3.59]). CONCLUSION Compared with the general population, recipients of a kidney, liver, heart, or lung transplant have an increased risk for diverse infection-related and unrelated cancers.

In light of continued uncertainty regarding postkidney donation medical, psychosocial and socioeconomic outcomes for traditional living donors and especially for donors meeting more relaxed acceptance criteria, a meeting was held in September 2010 to (1) review limitations of existing data on outcomes of living kidney donors; (2) assess and define the need for long-term follow-up of living kidney donors; (3) identify the potential system requirements, infrastructure and costs of long-term follow-up for living kidney donor outcomes in the United States and (4) explore practical options for future development and funding of United States living kidney donor data collection, metrics and endpoints. Conference participants included prior kidney donors, physicians, surgeons, medical ethicists, social scientists, donor coordinators, social workers, independent donor advocates and representatives of payer organizations and the federal government. The findings and recommendations generated at this meeting are presented.

BACKGROUND Hemodialysis patients with larger hemoglobin level fluctuations have higher mortality rates. We describe facility-level interpatient hemoglobin variability, its relation to patient mortality, and factors associated with facility-level hemoglobin variability or achieving hemoglobin levels of 10.5-12.0 g/dL. Facility-level hemoglobin variability may reflect within-patient hemoglobin variability and facility-level anemia-control practices. STUDY DESIGN Prospective cohort study. SETTING & PARTICIPANTS Data from the Dialysis Outcomes and Practice Patterns Study (DOPPS; 26,510 hemodialysis patients, 930 facilities, 12 countries, 1996-2008) and from the Centers for Medicare & Medicaid Services (CMS; 193,291 hemodialysis patients, 3,741 US facilities, 2002). PREDICTORS Standard deviation (SD) in single-measurement hemoglobin levels in hemodialysis patients in facility cross-sections (facility-level hemoglobin SD); patient characteristics; facility practices. OUTCOMES Patient-level mortality; additionally, facility practices correlated with facility-level hemoglobin SD or patient hemoglobin levels of 10.5-12.0 g/dL. RESULTS Facility-level hemoglobin SD varied more than 5-fold across DOPPS facilities (range, 0.5-2.7 g/dL; mean, 1.3 g/dL) and by country (range, 1.1 in Japan-DOPPS [2005/2006] to 1.7 g/dL in Spain-DOPPS [1998/1999]), with substantial decreases seen in many countries from 1998 to 2007. Facility-level hemoglobin SD was related inversely to patient age, but was associated minimally with more than 30 other patient characteristics and facility mean hemoglobin levels. Several anemia management practices were associated strongly with facility-level hemoglobin SD and having a hemoglobin level of 10.5-12.0 g/dL. When examined in CMS data, facility-level hemoglobin SD was positively associated with within-patient hemoglobin SD during the prior 6 months. Patient mortality rates were higher with greater facility-level hemoglobin SD (DOPPS: HR, 1.08 per 0.5-g/dL greater facility-level hemoglobin SD [95% CI, 1.02-1.15; P = 0.006]; CMS: HR, 1.16 per 0.5-g/dL greater facility-level hemoglobin SD [95% CI, 1.11-1.21; P < 0. 001]). LIMITATIONS Residual confounding. CONCLUSIONS Facility-level hemoglobin SD was associated strongly and positively with patient mortality, not tightly linked to numerous patient characteristics, but related strongly to facility anemia management practices. Facility-level hemoglobin variability may be modifiable and its optimization may improve hemodialysis patient survival.

TUESDAY AFTERNOON - MINI ORAL ABSTRACTS: Clinical Strategies and Outcomes in Kidney Transplantation: PDF Only

The effect of demand for kidney transplantation, measured by end-stage renal disease (ESRD) incidence, on access to transplantation is unknown. Using data from the U.S. Census Bureau, Centers for Medicare & Medicaid Services (CMS) and the Organ Procurement and Transplantation Network/Scientific Registry of Transplant Recipients (OPTN/SRTR) from 2000 to 2008, we performed donation service area (DSA) and patient-level regression analyses to assess the effect of ESRD incidence on access to the kidney waiting list and deceased donor kidney transplantation. In DSAs, ESRD incidence increased with greater density of high ESRD incidence racial groups (African Americans and Native Americans). Wait-list and transplant rates were relatively lower in high ESRD incidence DSAs, but wait-list rates were not drastically affected by ESRD incidence at the patient level. Compared to low ESRD areas, high ESRD areas were associated with lower adjusted transplant rates among all ESRD patients (RR 0.68, 95% CI 0.66-0.70). Patients living in medium and high ESRD areas had lower transplant rates from the waiting list compared to those in low ESRD areas (medium: RR 0.68,95% CI 0.66-0.69; high: RR 0.63, 95% CI 0.61-0.65). Geographic variation in access to kidney transplant is in part mediated by local ESRD incidence, which has implications for allocation policy development.

Pancreas allograft acceptance is markedly more selective than other solid organs. The number of pancreata recovered is insufficient to meet the demand for pancreas transplants (PTx), particularly for patients awaiting simultaneous kidney-pancreas (SPK) transplant. Development of a pancreas donor risk index (PDRI) to identify factors associated with an increased risk of allograft failure in the context of SPK, pancreas after kidney (PAK) or pancreas transplant alone (PTA), and to assess variation in allograft utilization by geography and center volume was undertaken. Retrospective analysis of all PTx performed from 2000 to 2006 (n = 9401) was performed using Cox regression controlling for donor and recipient characteristics. Ten donor variables and one transplant factor (ischemia time) were subsequently combined into the PDRI. Increased PDRI was associated with a significant, graded reduction in 1-year pancreas graft survival. Recipients of PTAs or PAKs whose organs came from donors with an elevated PDRI (1.57-2.11) experienced a lower rate of 1-year graft survival (77%) compared with SPK transplant recipients (88%). Pancreas allograft acceptance varied significantly by region particularly for PAK/PTA transplants (p < 0.0001). This analysis demonstrates the potential value of the PDRI to inform organ acceptance and potentially improve the utilization of higher risk organs in appropriate clinical settings.

This article highlights trends and changes in lung and heart-lung transplantation in the United States from 1999 to 2008. While adult lung transplantation grew significantly over the past decade, rates of heart-lung and pediatric lung transplantation have remained low. Since implementation of the lung allocation score (LAS) donor allocation system in 2005, decreases in the number of active waiting list patients, waiting times for lung transplantation and death rates on the waiting list have occurred. However, characteristics of recipients transplanted in the LAS era differed from those transplanted earlier. The proportion of candidates undergoing lung transplantation for chronic obstructive pulmonary disease decreased, while increasing for those with pulmonary fibrosis. In the LAS era, older, sicker and previously transplanted candidates underwent transplantation more frequently compared with the previous era. Despite these changes, when compared with the pre-LAS era, 1-year survival after lung transplantation did not significantly change after LAS inception. The long-term effects of the change in the characteristics of lung transplant recipients on overall outcomes for lung transplantation remain unknown. Continued surveillance and refinements to the LAS system will affect the distribution and types of candidates transplanted and hopefully lead to improved system efficiency and outcomes.

Background. We propose a continuous kidney do nor 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.

'Life years from transplant' (LYFT) is the extra years of life that a candidate can expect to achieve with a kidney transplant as compared to never receiving a kidney transplant at all. The LYFT component survival models (patient lifetimes with and without transplant, and graft lifetime) are comparable to or better predictors of long-term survival than are other predictive equations currently in use for organ allocation. Furthermore, these models are progressively more successful at predicting which of two patients will live longer as their medical characteristics (and thus predicted lifetimes) diverge. The C-statistics and the correlations for the three LYFT component equations have been validated using independent, nonoverlapping split-half random samples. Allocation policies based on these survival models could lead to substantial increases in the number of life years gained from the current donor pool.