Assessment of kidney health: implications for living kidney donors and beyond

This thesis focusses on assessment of kidney health by investigating different aspects of living kidney donation. In the first part, we found that exact measurement of kidney function (“measured GFR: mGFR”) in all potential donors does not result in acceptation of more kidney donors compared to estimation of kidney function (“estimated GFR: eGFR”). Therefore, eGFR will be sufficient for the decision to accept a potential donor in the majority of donor candidates. Moreover, we showed that the CKD-EPI equation for eGFR based on both plasma creatinine and cystatin C, instead of either one of these markers, most accurately and precisely estimates GFR in donor candidates. For the prediction of post-donation GFR, we developed a new equation.During the transplantation procedure, biopsies are taken from the donor kidney. For part two of this thesis, we studied the density of capillaries in relation to pre- and post-donation kidney function. In healthy kidneys, there seems to be no relation between capillary density and kidney function.Shortly after donation, the remaining kidney compensates for the loss of functioning kidney mass. Previously it has been thought that this compensatory response could be harmful over time, resulting in poor long-term outcomes. However, we found that more compensation predicts better, instead of worse, long-term outcomes in living kidney donors

Optimization and Machine Learning Methods for Diagnostic Testing of Prostate Cancer

Technological advances in biomarkers and imaging tests are creating new avenues to advance precision health for early detection of cancer. These advances have resulted in multiple layers of information that can be used to make clinical decisions, but how to best use these multiple sources of information is a challenging engineering problem due to the high cost and imperfect sensitivity and specificity of these tests. Questions that need to be addressed include which diagnostic tests to choose and how to best integrate them, in order to optimally balance the competing goals of early disease detection and minimal cost and harm from unnecessary testing. To study these research questions, we present new optimization-based models and data-driven analytic methods in three parts to improve early detection of prostate cancer (PCa). In the first part, we develop and validate predictive models to assess individual PCa risk using known clinical risk factors. Because not all men with newly-diagnosed PCa received imaging at diagnosis, we use an established method to correct for verification bias to evaluate the accuracy of published imaging guidelines. In addition to the published guidelines, we implement advanced classification modeling techniques to develop accurate classification rules identifying which patients should receive imaging. We propose a new algorithm for a classification model that considers information of patients with unverified disease and the high cost of misclassifying a metastatic patient. We summarize our development and implementation of state-wide, evidence-based imaging criteria that weigh the benefits and harms of radiological imaging for detection of metastatic PCa. In the second part of this thesis, we combine optimization and machine learning approaches into a robust optimization framework to design imaging guidelines that can account for imperfect calibration of predictions. We investigate efficient and effective ways to combine multiple medical diagnostic tests where the result of one test may be used to predict the outcome of another. We analyze the properties of the proposed optimization models from the perspectives of multiple stakeholders, and we present the results of fast approximation methods that we show can be used to solve large-scale models. In the third and final part of this thesis, we investigate the optimal design of composite multi-biomarker tests to achieve early detection of prostate cancer. Biomarker tests vary significantly in cost, and cause false positive and false negative results, leading to serious health implications for patients. Since no single biomarker on its own is considered satisfactory, we utilize simulation and statistical methods to develop the optimal diagnosis procedure for early detection of PCa consisting of a sequence of biomarker tests, balancing the benefits of early detection, such as increased survival, with the harms of testing, such as unnecessary prostate biopsies. In this dissertation, we identify new principles and methods to guide the design of early detection protocols for PCa using new diagnostic technologies. We provide important clinical evidence that can be used to improve health outcomes of patients while reducing wasteful application of diagnostic tests to patients for whom they are not effective. Moreover, some of the findings of this dissertation have been implemented directly into clinical practice in the state of Michigan. The models and methodologies we present in this thesis are not limited to PCa, and can be applied to a broad range of chronic diseases for which diagnostic tests are available.PHDIndustrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143976/1/smerdan_1.pd

Measuring the Efficiency of the Living Kidney Donor Candidate Evaluation Process

Background: Living kidney donation is the ideal treatment for many patients with kidney failure. However, the living donor evaluation process has been criticized by patients and healthcare providers as inefficient. In the present research, we evaluated the inefficiency of the living donor evaluation process. Methods: We conducted a scoping review of the literature and obtained data from large administrative datasets (1256 living donors) and medical chart review (849 prospectively recruited living donors across 12 transplant centres plus retrospective analysis of 1065 living donor candidates from a single centre). Results: The median time to complete the entire evaluation was 9-11 months for donors and 4.3 months for candidates who were declined or withdrew from the evaluation. Up to 35% of recipients who could potentially have received a pre-emptive transplant (avoided dialysis entirely) started dialysis before transplantation, costing the healthcare system $8.1M for dialysis alone. Shortening the evaluation time by only 10$1.3M in Ontario due to averted dialysis costs and up to 38 intended recipients each year could have received a transplant they otherwise did not receive (17% increase in living donor transplantation). The cost to the healthcare system was $3,641 for the donor evaluation,$11,695 for the donor surgery (including perioperative costs), and $933 for the first year post-donation. There are many reasons that may contribute to a longer living donor evaluation. Donation through kidney paired donation prolonged the time until donation by 6 months. The evaluation time was doubled if the intended recipient started dialysis part-way through the donors’ evaluation. Finally, every month delay in the recipient referral extended the time until donation by 0.4-0.9 months and increased the likelihood that the recipient would start dialysis before transplant. Between-centre differences were observed for evaluation times and donation costs. Conclusions: The living donor evaluation is time-consuming, resulting in potentially avoidable unintended adverse consequences to donor candidates, their intended recipient, and the healthcares system. Potential strategies to improve the efficiency of this process include eliminating unnecessary or redundant tests, evaluating multiple donor candidates simultaneously, performing 1-day evaluations, and promoting earlier recipient referrals

Barriers to Blood Availability Within the New Orleans Area

An adequate and reliable supply of blood and blood components is becoming an increasing public health concern. Over the past decade, researchers have indicated a continued decline in the collection of blood products. An insufficient blood supply may present a risk to both patients and reserves for emergencies and disasters. The purpose of this quantitative, cross-sectional study was to determine whether gender, age group, ethnicity, year, serological tests, and discard factors were associated with the availability of the donated blood supply throughout the New Orleans region. The donated blood supply chain model guided this study. Secondary data were retrieved from The Blood Center of New Orleans, Louisiana. A simple random sample technique was used to select the sample, consisting of 286,625 allogeneic blood donors. Bivariate logistic regression and multiple logistic regression were used to analyze data collected between 2008 and 2017. The bivariate logistic regression showed a statistically significant association (p = .000) between gender (OR = .760; 95% CI .753 – .767), age group (OR = 1.554; 95% CI 1.522 – 1.588), ethnicity (OR = .635; 95% CI .627 – .643), year (OR = .713; 95% CI .696 – .731), and available blood. Similarly, the multiple logistic regression also revealed a statistically significant association (p = .000) between gender (OR = .796; 95% CI .789 – .804), age group (OR = 1.426; 95% CI 1.395 – 1.458), ethnicity (OR = .672; 95% CI .664 – .681), year (OR = .726; 95% CI .708 – .744), and available blood. The knowledge presented in this study promotes positive social change by guiding blood center practitioners on ways to improve current work practices to increase the available donated blood supply and maintain a satisfactory blood inventory

Blood Supply Chain Networks in Healthcare: Game Theory Models and Numerical Case Studies

A crucial component of every healthcare system is the safe and steady supply of the life-saving product, blood. In order to meet the demand for blood consistently, it is imperative to maintain a robust supply chain. The blood banking industry in the United States, faced with emerging challenges, which include, an increase in operating costs, rise in competition among blood centers, insufficient reimbursement from payers such as insurance companies and government programs, in addition to inherent challenges such as donor motivation, seasonal shortages, perishability, is trying to adapt to the changing dynamics to sustain itself economically. The altruistic nature of this industry and the financial implications for its various stakeholders, makes the efficient management of blood supply chains an important and interesting area of study. In this dissertation, I contribute to the existing literature on blood banking by modeling the operational and economic challenges throughout the blood supply chain in the context of competition using game theory. I develop a model for blood service organizations competing for donations where they use service quality levels at collection sites as their strategic variables to increase their collection of blood from voluntary donors. I further construct a competitive blood supply chain network model that captures all major activities as well as perishability along the supply chain from collection of blood to distribution to hospitals. As a crucial extension to the study on blood supply chains, I develop a network framework with multiple tiers of decision-makers including payers, that captures the decentralized nature of the blood banking system in the United States. The solutions from this multi-objective decision-making problem include quantities of blood to be supplied and transfused, given demand is known, as well as the financial transactions between the different tiers of stakeholders. For each model the governing equilibrium conditions are derived, and equivalent variational inequality formulations presented. The models and their relevance are further illustrated through simulated case studies. The results obtained provide valuable insights that can inform healthcare policy makers and regulators

Improving Access and Outcomes in Living Kidney Donor Transplantation

Shortages in deceased organ donation have necessitated widespread acceptance of living donor kidney transplantation, which offers better outcomes in terms of graft survival, life expectancy and quality of life for many patients with end-stage kidney disease, compared with deceased donor kidney transplantation and dialysis. However, there are barriers and challenges that exist in the current practice of living kidney donor transplantation. Overall, the rates of living kidney donor transplantation have decreased or plateaued, with ethic and socio-economic disparities in access to living kidney donation reported in many countries that remain largely unexplained. Living donors must accept risks associated with undergoing nephrectomy, yet the evidence on the long-term risks of living kidney donation remains uncertain. In response, there have been efforts to identify and describe the barriers and disparities in living kidney donor transplantation, improve the pathway for living donors and to assess a range of outcomes for living donors. A comprehensive understanding of the values, beliefs, experiences, priorities and preferences of the key stakeholders, including donors and health professionals involved in their care is needed to ensure that research; clinical practice and policy in living kidney donation address their needs and priorities. This is a thesis by publication containing published and submitted work. The aims of the studies included in this thesis are: 1) To identify and describe the beliefs, attitudes and expectations of patients with CKD regarding living kidney donation. 2) To describe kidney donors’ experiences of the evaluation process, and the motivations and challenges to sustaining commitment prior to donation. 3) To describe nephrologists’ perspectives on barriers to living kidney donation and disparities in access to living kidney donor transplantation. 4) To identify living kidney donors’ priorities for outcomes and describe the reasons for their choices. 5) To determine the characteristics and heterogeneity of outcomes reported in randomised trials and observational studies in adult living kidney donor

Effects of a reduction in GFR on cardiovascular structure and function: a five year follow up study

The inverse association between glomerular filtration rate (GFR) and cardiovascular risk is well recognised but not fully explained. Furthermore, chronic kidney disease is associated with atherosclerosis, arteriosclerosis, left ventricular hypertrophy and myocardial fibrosis. Kidney donation reduces renal function by approximately 30% and allows the study of the cardiovascular effects of a reduced GFR in healthy subjects without confounding comorbidities. This thesis aims to examine the isolated effects of a reduction in GFR as a result of nephrectomy on haemodynamics, blood pressure, cardiovascular structure and function, myocardial tissue characterisation and blood biomarkers. In a multi-centre prospective controlled study, there were no significant changes in peripheral blood pressure or pulse wave velocity in donors compared to controls at 12 months. In a prospective 5 year longitudinal study of donors and controls, no significant differences were observed in left ventricular volumes or mass, strain parameters or ejection fraction at 5 years after nephrectomy. In a cross-sectional comparison of 1:1 age and sex matched donors and controls there were no significant differences in T1 or T2 times, extracellular volume or late gadolinium enhancement. The reduction in GFR after donation does not lead to deleterious changes in cardiovascular structure and function at 5 years

Practical Algorithms for Resource Allocation and Decision Making

Algorithms are widely used today to help make important decisions in a variety of domains, including health care, criminal justice, employment, and education. Designing \emph{practical} algorithms involves balancing a wide variety of criteria. Deployed algorithms should be robust to uncertainty, they should abide by relevant laws and ethical norms, they should be easy to use correctly, they should not adversely impact user behavior, and so on. Finding an appropriate balance of these criteria involves technical analysis, understanding of the broader context, and empirical studies ``in the wild''. Most importantly practical algorithm design involves close collaboration between stakeholders and algorithm developers. The first part of this thesis addresses technical issues of uncertainty and fairness in \emph{kidney exchange}---a real-world matching market facilitated by optimization algorithms. We develop novel algorithms for kidney exchange that are robust to uncertainty in both the quality and the feasibility of potential transplants, and we demonstrate the effect of these algorithms using computational simulations with real kidney exchange data. We also study \emph{fairness} for hard-to-match patients in kidney exchange. We close a previously-open theoretical gap, by bounding the price of fairness in kidney exchange with chains. We also provide matching algorithms that bound the price of fairness in a principled way, while guaranteeing Pareto efficiency. The second part describes two real deployed algorithms---one for kidney exchange, and one for recruiting blood donors. For each application cases we characterize an underlying mathematical problem, and theoretically analyze its difficulty. We then develop practical algorithms for each setting, and we test them in computational simulations. For the blood donor recruitment application we present initial empirical results from a fielded study, in which a simple notification algorithm increases the expected donation rate by $5\%$. The third part of this thesis turns to human aspects of algorithm design. We conduct several survey studies that address several questions of practical algorithm design: How do algorithms impact decision making? What additional information helps people use complex algorithms to make decisions? Do people understand standard algorithmic notions of fairness? We conclude with suggestions for facilitating deeper stakeholder involvement for practical algorithm design, and we outline several areas for future research

Smoking and Second Hand Smoking in Adolescents with Chronic Kidney Disease: A Report from the Chronic Kidney Disease in Children (CKiD) Cohort Study

The goal of this study was to determine the prevalence of smoking and second hand smoking [SHS] in adolescents with CKD and their relationship to baseline parameters at enrollment in the CKiD, observational cohort study of 600 children (aged 1-16 yrs) with Schwartz estimated GFR of 30-90 ml/min/1.73m2. 239 adolescents had self-report survey data on smoking and SHS exposure: 21 [9%] subjects had “ever” smoked a cigarette. Among them, 4 were current and 17 were former smokers. Hypertension was more prevalent in those that had “ever” smoked a cigarette (42%) compared to non-smokers (9%), p\u3c0.01. Among 218 non-smokers, 130 (59%) were male, 142 (65%) were Caucasian; 60 (28%) reported SHS exposure compared to 158 (72%) with no exposure. Non-smoker adolescents with SHS exposure were compared to those without SHS exposure. There was no racial, age, or gender differences between both groups. Baseline creatinine, diastolic hypertension, C reactive protein, lipid profile, GFR and hemoglobin were not statistically different. Significantly higher protein to creatinine ratio (0.90 vs. 0.53, p\u3c0.01) was observed in those exposed to SHS compared to those not exposed. Exposed adolescents were heavier than non-exposed adolescents (85th percentile vs. 55th percentile for BMI, p\u3c 0.01). Uncontrolled casual systolic hypertension was twice as prevalent among those exposed to SHS (16%) compared to those not exposed to SHS (7%), though the difference was not statistically significant (p= 0.07). Adjusted multivariate regression analysis [OR (95% CI)] showed that increased protein to creatinine ratio [1.34 (1.03, 1.75)] and higher BMI [1.14 (1.02, 1.29)] were independently associated with exposure to SHS among non-smoker adolescents. These results reveal that among adolescents with CKD, cigarette use is low and SHS is highly prevalent. The association of smoking with hypertension and SHS with increased proteinuria suggests a possible role of these factors in CKD progression and cardiovascular outcomes