Competing Risk Modeling with Bivariate Varying Coefficients to Understand the Dynamic Impact of COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic has exerted a profound impact on patients with end-stage renal disease relying on kidney dialysis to sustain their lives. A preliminary analysis of dialysis patient postdischarge hospital readmissions and deaths in 2020 revealed that the COVID-19 effect has varied significantly with postdischarge time and time since the pandemic onset. However, the complex dynamics cannot be characterized by existing varying coefficient models.

BIVARIATE FUNCTIONAL PATTERNS OF LIFETIME MEDICARE COSTS AMONG ESRD PATIENTS.

In this work we study the lifetime Medicare spending patterns of patients with end-stage renal disease (ESRD). We extract the information of patients who started their ESRD services in 2007-2011 from the United States Renal Data System (USRDS). Patients are partitioned into three groups based on their kidney transplant status: 1-unwaitlisted and never transplanted, 2-waitlisted but never transplanted, and 3-waitlisted and then transplanted.

Kernel Estimation of Bivariate Time-varying Coefficient Model for Longitudinal Data with Terminal Event.

We propose a nonparametric bivariate time-varying coefficient model for longitudinal measurements with the occurrence of a terminal event that is subject to right censoring. The time-varying coefficients capture the longitudinal trajectories of covariate effects along with both the followup time and the residual lifetime. The proposed model extends the parametric conditional approach given terminal event time in recent literature, and thus avoids potential model misspecification.

Pitfalls of the concordance index for survival outcomes.

Prognostic models are useful tools for assessing a patient's risk of experiencing adverse health events. In practice, these models must be validated before implementation to ensure that they are clinically useful. The concordance index (C-Index) is a popular statistic that is used for model validation, and it is often applied to models with binary or survival outcome variables.

COVID-19 and Hospitalization Among Maintenance Dialysis Patients: A Retrospective Cohort Study Using Time-Dependent Modeling.

Rationale & Objective: The coronavirus disease 2019 (COVID-19) pandemic has had a profound impact on hospitalizations in general and on dialysis patients in particular. This study modeled the impact of COVID-19 on hospitalizations of dialysis patients in 2020.

Study Design: Retrospective cohort study.

Analysis of hospital readmissions with competing risks.

The 30-day hospital readmission rate has been used in provider profiling for evaluating inter-provider care coordination, medical cost effectiveness, and patient quality of life. Current profiling analyzes use logistic regression to model 30-day readmission as a binary outcome, but one disadvantage of this approach is that this outcome is strongly affected by competing risks (e.g.

The Impact of COVID-19 on Postdischarge Outcomes for Dialysis Patients in the United States: Evidence from Medicare Claims Data.

Background: Recent investigations have shown that, on average, patients hospitalized with coronavirus disease 2019 (COVID-19) have a poorer postdischarge prognosis than those hospitalized without COVID-19, but this effect remains unclear among patients with end-stage kidney disease (ESKD) who are on dialysis.

Methods: Leveraging a national ESKD patient claims database administered by the US Centers for Medicare and Medicaid Services, we conducted a retrospective cohort study that characterized the effects of in-hospital COVID-19 on all-cause unplanned readmission and death within 30 days of discharge for patients on dialysis. Included in this study were 436,745 live acute-care hospital discharges of 222,154 Medicare beneficiaries on dialysis from 7871 Medicare-certified dialysis facilities between January 1 and October 31, 2020.

Concordance indices with left-truncated and right-censored data.

In the context of time-to-event analysis, a primary objective is to model the risk of experiencing a particular event in relation to a set of observed predictors. The Concordance Index (C-Index) is a statistic frequently used in practice to assess how well such models discriminate between various risk levels in a population. However, the properties of conventional C-Index estimators when applied to left-truncated time-to-event data have not been well studied, despite the fact that left-truncation is commonly encountered in observational studies.

Deceased donors as nondirected donors in kidney paired donation.

As proof of concept, we simulate a revised kidney allocation system that includes deceased donor (DD) kidneys as chain-initiating kidneys (DD-CIK) in a kidney paired donation pool (KPDP), and estimate potential increases in number of transplants. We consider chains of length 2 in which the DD-CIK gives to a candidate in the KPDP, and that candidate's incompatible donor donates to theDD waitlist. In simulations, we vary initial pool size, arrival rates of candidate/donor pairs and (living) nondirected donors (NDDs), and delay time from entry to the KPDP until a candidate is eligible to receive a DD-CIK.

The profile inter-unit reliability.

To assess the quality of health care, patient outcomes associated with medical providers (eg, dialysis facilities) are routinely monitored in order to identify poor (or excellent) provider performance. Given the high stakes of such evaluations for payment as well as public reporting of quality, it is important to assess the reliability of quality measures. A commonly used metric is the inter-unit reliability (IUR), which is the proportion of variation in the measure that comes from inter-provider differences.

KPDGUI: An interactive application for optimization and management of a virtual kidney paired donation program.

Background And Objectives: The aim in kidney paired donation (KPD) is typically to maximize the number of transplants achieved through the exchange of donors in a pool comprising incompatible donor-candidate pairs and non-directed (or altruistic) donors. With many possible options in a KPD pool at any given time, the most appropriate set of exchanges cannot be determined by simple inspection. In practice, computer algorithms are used to determine the optimal set of exchanges to pursue.

Inter-Unit Reliability for Quality Measure Testing.

Facility-specific quality measures are commonly used to monitor dialysis facilities. To successfully develop, test and validate quality measures, a subset of facilities are often recruited for preliminary evaluations. To ensure that the facility-specific measures will achieve a desirable precision, it is often of interest to determine a minimum number of facilities that should be recruited.

An efficient algorithm to enumerate sets with fallbacks in a kidney paired donation program.

Kidney paired donation is a partial solution to overcoming biological incompatibility preventing kidney transplants. A kidney paired donation (KPD) program consists of altruistic or non-directed donors (NDDs) and pairs, each of which comprises a candidate in need of a kidney transplant and her/his willing but incompatible donor. Potential transplants from NDDs or donors in pairs to compatible candidates in other pairs are determined by computer assessment, though various situations involving either the donor, candidate, or proposed transplant may lead to a potential transplant failing to proceed.

Reevaluation of the Kidney Donor Risk Index.

Background: The Kidney Donor Risk Index (KDRI) is a score applicable to deceased kidney donors which reflects relative graft failure risk associated with deceased donor characteristics. The KDRI is widely used in kidney transplant outcomes research. Moreover, an abbreviated version of KDRI is the basis, for allocation purposes, of the "top 20%" designation for deceased donor kidneys.

Inter-unit reliability for nonlinear models.

In monitoring dialysis facilities, various quality measures are used in order to assess the performance and quality of care. The inter-unit reliability (IUR) describes the proportion of variation in the quality measure that is due to the between-facility variation. If the measure under evaluation is a simple average across normally distributed patient outcomes for each facility, the IUR is based on a one-way analysis of variance (ANOVA).

Valuing Sets of Potential Transplants in a Kidney Paired Donation Network.

In kidney paired donation (KPD), incompatible donor-candidate pairs and non-directed (also known as altruistic) donors are pooled together with the aim of maximizing the total utility of transplants realized via donor exchanges. We consider a setting in which disjoint sets of potential transplants are selected at regular intervals, with fallback options available within each proposed set in the case of individual donor, candidate or match failure. We develop methods for calculating the expected utility for such sets under a realistic probability model for the KPD.

Discussion of "Survival models and health sequences" by Walter Dempsey and Peter McCullagh.

This is a discussion of the paper by Dempsey and McCullagh.

Conditional modeling of longitudinal data with terminal event.

We consider a random effects model for longitudinal data with the occurrence of an informative terminal event that is subject to right censoring. Existing methods for analyzing such data include the joint modeling approach using latent frailty and the marginal estimating equation approach using inverse probability weighting; in both cases the effect of the terminal event on the response variable is not explicit and thus not easily interpreted. In contrast, we treat the terminal event time as a covariate in a conditional model for the longitudinal data, which provides a straight-forward interpretation while keeping the usual relationship of interest between the longitudinally measured response variable and covariates for times that are far from the terminal event.

A Look-Ahead Strategy for Non-Directed Donors in Kidney Paired Donation.

While there is a growing need for kidney transplants to treat end stage kidney disease, the supply of transplantable kidneys is in serious shortage. Kidney paired donation (KPD) programs serve as platforms for candidates with willing but incompatible donors to assess the possibility of exchanging donors, thus opening up new transplant opportunities for these candidates. In recent years, non-directed (or altruistic) donors (NDDs) have been incorporated into KPD programs beginning chains of transplants that benefit many candidates.

A Kidney Graft Survival Calculator that Accounts for Mismatches in Age, Sex, HLA, and Body Size.

Background And Objectives: Outcomes for transplants from living unrelated donors are of particular interest in kidney paired donation (KPD) programs where exchanges can be arranged between incompatible donor-recipient pairs or chains created from nondirected/altruistic donors.

Design, Setting, Participants, & Measurements: Using Scientific Registry of Transplant Recipients data, we analyzed 232,705 recipients of kidney-alone transplants from 1998 to 2012. Graft failure rates were estimated using Cox models for recipients of kidney transplants from living unrelated, living related, and deceased donors.

Variation in infection prevention practices in dialysis facilities: results from the national opportunity to improve infection control in ESRD (End-Stage Renal Disease) project.

OBJECTIVE To observe patient care across hemodialysis facilities enrolled in the National Opportunity to Improve Infection Control in ESRD (end-stage renal disease) (NOTICE) project in order to evaluate adherence to evidence-based practices aimed at prevention of infection. SETTING AND PARTICIPANTS Thirty-four hemodialysis facilities were randomly selected from among 772 facilities in 4 end-stage renal disease participating networks. Facility selection was stratified on dialysis organization affiliation, size, socioeconomic status, and urban/rural status.

Decision Making in Kidney Paired Donation Programs with Altruistic Donors.

In recent years, kidney paired donation (KPD) has been extended to include living non-directed or altruistic donors, in which an altruistic donor donates to the candidate of an incompatible donor-candidate pair with the understanding that the donor in that pair will further donate to the candidate of a second pair, and so on; such a process continues and thus forms an altruistic donor-initiated chain. In this paper, we propose a novel strategy to sequentially allocate the altruistic donor (or bridge donor) so as to maximize the expected utility; analogous to the way a computer plays chess, the idea is to evaluate different allocations for each altruistic donor (or bridge donor) by looking several moves ahead in a derived look-ahead search tree. Simulation studies are provided to illustrate and evaluate our proposed method.