Outreach and Connection to Care for Chronic Kidney Disease in a Workplace Wellness Setting: A Cost-Effectiveness Analysis

Abstract

Because chronic kidney disease (CKD) is underdiagnosed, many patients do not receive care that could slow or prevent progression. Potential CKD patients can be identified during employee wellness events and referred into care by a CKD outreach program. This study assessed the health and economic benefits associated with a CKD outreach program. A model-based cost-effectiveness analysis was conducted for a cohort of patients at risk for CKD under 2 scenarios: wellness events with a CKD outreach program and wellness events without outreach. The outreach program identified potential CKD patients based on estimated glomerular filtration rates. Health outcomes and total cost to payers were estimated with Markov models using 1-year cycles. Because outreach could be offered to either patients with diabetes or to all potential CKD patients, these groups were modeled separately. The authors assumed 40% percent of potential CKD patients accepted the invitation to participate in the CKD outreach program. Model parameters were taken from peer-reviewed literature. The study was conducted from the perspective of self-insured employers over a 5-year time horizon. The study found that the CKD outreach program resulted in a gain of 2.3 quality-adjusted life-years and saved $500,211 when 1000 potential CKD patients with diabetes were invited. When potential CKD patients were invited without regard for diabetes status, 0.8 quality-adjusted life-years were gained at a cost savings of $34,161. The authors concluded that CKD outreach programs can improve health outcomes for patients with CKD and save costs for payers.

Introduction

Chronic kidney disease (CKD) is a common, underdiagnosed condition because patients may be asymptomatic until late in the disease process—30 million people in the United States are living with CKD,¹ yet more than 90% of them are unaware of their condition.² Early recognition of CKD, followed by referral of patients to appropriate care, can help slow progression of the disease and delay or prevent the onset of end-stage renal disease (ESRD), a stage associated with substantially increased health care costs and a lower quality of life. Employer spending on CKD-related health care increases with disease progression, culminating in dialysis that can cost $120,000 annually.³

Early detection of CKD can be provided by workforce wellness programs offered by employers to employees and their spouses. Some of these programs include serum creatinine testing and provide an estimated glomerular filtration rate (eGFR) as an assessment of kidney function. Although albuminuria can be used to identify CKD patients who would not have been identified by eGFR levels, albuminuria testing is not always practical at workplace wellness events, which are frequently conducted in public spaces.

Referral of patients into appropriate care is needed to fully benefit from the results of eGFR-based screening. Although some patients will self-refer, many of those who participate in annual employee wellness events do not take appropriate action after they receive results. CKD outreach programs have been designed to improve post-testing engagement. In such programs, individuals at risk based on a low eGFR are offered a telemedicine consultation and referral into care. For example, angiotensin-converting enzyme inhibitors (ACEIs) can be used to slow the progression of CKD, especially for patients with proteinuria.⁴

To build on previous studies that suggest CKD screening is cost-effective, the research team has modeled the costs and health benefits of adding CKD outreach programs to wellness events that report eGFR. Because type 2 diabetes is a strong risk factor for CKD and outreach could be offered either to all individuals with a low eGFR or only to those who also have diabetes, these approaches were modeled separately. This study was undertaken from the perspective of self-insured employers.

Methods

Ethical approval and informed consent

No patient-level data were used in this study.

CKD outreach program

Typically, participants in wellness programs receive a report of their results that contains a discussion of how the level of each analyte measured relates to their health. If that analyte is out of the healthy range, the participant is advised to discuss the result with her/his health care provider. However, some people do not follow this advice. For this reason, a CKD outreach program was developed to identify those at risk for CKD and to more actively refer them into care. In this outreach program, participants who had had an eGFR <60 mL/min/1.73m² in the previous year's annual wellness event were invited to participate in a CKD outreach program during the sign-up phase of the current year's wellness event. Those who agreed to participate in the program were offered a telemedicine consultation to discuss their results, encouraged to see a physician about their results, and offered assistance in finding a primary care provider, if needed.

Model

The model assessed the cost-effectiveness of adding a CKD outreach program to annual employee wellness events that report eGFR values. A decision model with Markov nodes was developed to estimate the cost and health outcomes of individuals eligible for CKD outreach programs based on eGFR testing results from annual employee wellness events at Quest Diagnostics (Fig. 1 and Supplementary Fig. S1).

FIG. 1.

Decision tree and Markov model. In the decision tree (Panel A), the square indicates the decision node; the empty circle indicates the chance node; and the M-circles indicate the Markov model. In the Markov model (Panel B), the arrows indicate the transitions allowed (see Table 1 for transition probabilities). The unidirectional arrows indicate that the model considers CKD to be an irreversible disease. Patients were not allowed to remain in the untreated microalbuminuria or untreated macroalbuminuria state when they accept CKD outreach (ie, the thick red arrows do not apply to these patients). For patients who either were not offered CKD outreach or who declined to participate in CKD outreach, a fraction of those eligible for guideline-supported ACEI therapy are assumed to refer themselves to physician care for testing and treatment (Table 1). The double headed arrows allow for loss of adherence to ACEI therapy: patients who became nonadherent to ACEI therapy remained nonadherent for all remaining cycles. ACEI, angiotensin-converting enzyme inhibitor; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; ESRD, end-stage renal disease; Rx, ACEI therapy. Color images are available online.

The decision tree (Fig. 1 Panel A) compared 2 scenarios for individuals with an eGFR <60 mL/min/1.73m² in an annual wellness event: one with the offer of the CKD outreach program and the other without the offer of the CKD outreach program. Those who agreed to participate in the program were encouraged to see their primary care provider about their results; and the patient's primary care provider was assumed to order confirmatory tests for serum creatinine, albuminuria, and urine creatinine. Based on the resulting eGFR and albumin/creatinine ratio (ACR), patients would then receive an ACEI therapy according to the Kidney Disease Improving Global Outcomes guidelines.⁴ Thus, the research team assumed that ACEI therapy would be provided for CKD patients with diabetes with microalbuminuria (ie, moderately increased albuminuria—ACR from 30 to 300 mg/g) or macroalbuminuria (ie, severely increased albuminuria—ACR >300 mg/g) and also for non-diabetic CKD patients with macroalbuminuria. It was assumed that patients with normoalbuminuria (ie, normal to mildly increased albuminuria—ACR <30 mg/g) and non-diabetic CKD patients with microalbuminuria were not treated with ACEI; these patients were assumed to be retested annually and treated in subsequent years if indicated.

Based on a CKD outreach program conducted at Quest Diagnostics, the research team assumed that 40% of those invited accepted invitations to participate in the outreach program. For patients who either were not offered CKD outreach or who declined to participate in CKD outreach, the team assumed that 9.2% of those eligible for guideline-supported ACEI therapy would have referred themselves to physician care for testing and treatment (Table 1).

Table 1.

Model Parameters

Parameters	Base case value	Range	Reference
Rates and probabilities (annual)
Prevalence of:
Macroalbuminuria (DM)	0.081	±30%	Garg et al⁶
Macroalbuminuria (ND)	0.029	±30%	Garg et al⁶
Microalbuminuria (DM)	0.426	±30%	Garg et al⁶
Microalbuminuria (ND)	0.180	±30%	Garg et al⁶
Transition from:
Micro- to macroalbuminuria (DM)	0.0284	±30%	Hoerger et al⁷
Micro- to macroalbuminuria (ND)	0.0142	±30%	Footnote 1
Normo- to microalbuminuria (DM)	0.0200	±30%	Hoerger et al⁷
Normo- to microalbuminuria (ND)	0.0100	±30%	Footnote 1
Macroalbuminuria to ESRD (DM)	0.0531	±30%	Manns et al⁹
Macroalbuminuria to ESRD (ND)	0.0342	±30%	Manns et al⁹
Microalbuminuria to ESRD (DM)	0.0030	±30%	Adler et al⁸
Microalbuminuria to ESRD (ND)	0.0015	±30%	Footnote 1
Mortality from:
ESRD	0.1450	±30%	den Hartog et al¹²
Macroalbuminuria (DM)	0.0489	±30%	Manns et al⁹
Macroalbuminuria (ND)	0.0257	±30%	Manns et al⁹
Normo- or microalbuminuria (DM)	0.0242	±30%	Manns et al⁹
Normo- or microalbuminuria (ND)	0.0085	±30%	Manns et al⁹
RRR of:
ESRD from proteinuria by ACEI (DM)	0.36	±30%	Manns et al⁹
ESRD from proteinuria by ACEI (ND)	0.41	±30%	Manns et al⁹
Macroalbuminuria from microalbuminuria by ACEI	0.55	±30%	Strippoli et al¹³
Mortality from proteinuria by ACEI (DM)	0.21	±30%	Strippoli et al¹³
Mortality from proteinuria by ACEI (ND)	0	0 to 0.05	Manns et al⁹
Fraction of outreach invitations accepted	0.40	0.10 to 0.70	Footnote 2
Fraction with DM	0.30	±30%	Footnote 2
Fraction of ACEI-eligible patients who self-refer	0.092	±30%	Assumption
Rate of adherence to ACEI therapy	0.90	0.85 to 0.95	Assumption
Cost of: ($)
CKD outreach	50	±30%	Footnote 3
ACR and eGFR tests	22.06	±30%	Footnote 4
PCP visit	123	±30%	HDMS 2018
ACEI	84	±30%	Footnote 5
ACEI monitoring	200	±30%	Footnote 6
ESRD year 1 and 2	156,584	±30%	Footnote 7
ESRD year 3	83,812	±30%	Footnote 7
ESRD year 4 and 5	11,040	±30%	Footnote 7
Utility of:
CKD	0.850	Not done	Manns et al⁹
ESRD	0.639	Not done	Manns et al⁹
Disutility of ACEI	0.010	Not done	Boulware et al²¹

1. Assumed to be half that of DM in the base case and varied from 10% to 70% or that of DM in 1-way sensitivity analysis.

2. Based on a CKD outreach program conducted at Quest Diagnostics.

3. Fee for each potential CKD patient contacted.

4. Cost for tests for blood creatinine (Current Procedural Terminoloty [CPT] 82565), urine albumin (CPT 82043), creatinine (CPT 82570).

5. GoodRX. ACE Inhibitors. https://www.goodrx.com/ace-inhibitors. Accessed April 19, 2018.

6. Approximately 200% of the Medicare reimbursement for 2 level 1 physician visits and 1 follow-up testing.

7. Annual cost to commercial groups as described in Methods.

ACEI, angiotensin-converting enzyme inhibitor; ACR, albumin/creatinine ratio; CKD, chronic kidney disease; DM, diabetes mellitus; eGFR, estimated glomerular filtration rate; ESRD, end-stage renal disease; ND, non-diabetic; PCP, primary care provider; RRR, relative risk reduction.

Markov models (Fig. 1 Panel B) were used to simulate the outcomes for a cohort of 1000 individuals eligible for the CKD outreach program. At every cycle of the Markov model, patients were assumed to be in 1 of the 7 mutually exclusive health states defined by their disease and treatment status: normoalbuminuria, microalbuminuria not treated, microalbuminuria treated, macroalbuminuria not treated, macroalbuminuria treated, ESRD, or dead. CKD was assumed to progress irreversibly from normoalbuminuria, to microalbuminuria, to macroalbuminuria, to ESRD, to death. CKD is usually not reversible, and the assumption of irreversibility of CKD has been made in 86% of CKD cost-effectiveness studies (n = 21) reviewed in Sutton et al.⁵ The model also allowed direct transition from microalbuminuria to ESRD, although the probability of this transition was less than one tenth of the probability of transition from macroalbuminuria to ESRD (Table 1). However, the model did not include the direct transition from normoalbuminuria to macroalbuminuria or ESRD because CKD outreach was not expected to have an impact on these transitions (patients with normoalbuminuria would not receive ACEI therapy) and because transition probabilities from normoalbuminuria to macroalbuminuria or ESRD would be negligible with respect to those from microalbuminuria to macroalbuminuria or ESRD. In addition, the model allowed for loss of adherence to ACEI therapy; patients who became nonadherent to ACEI therapy remained nonadherent for all remaining cycles.

Markov simulations were conducted separately for CKD patients with and without diabetes because treatment criteria and transition probabilities differed between these 2 groups. CKD patients with diabetes did not remain in the untreated microalbuminuria or untreated macroalbuminuria states when they participated in CKD outreach (Fig. 1). Non-diabetic CKD patients did not remain in the untreated macroalbuminuria state when they participated in CKD outreach (Supplementary Fig. S1).

Parameters

Model parameters were based on peer-reviewed literature and engagement rates for outreach programs at Quest Diagnostics (Table 1). The frequencies of macroalbuminuria and microalbuminuria among CKD patients were based on the third National Health and Nutrition Examination Survey study⁶ for patients with eGFR between 30 and 60 mL/min/1.73m²; for non-diabetic CKD patients, the weighted averages of the frequencies reported for hypertensive and non-hypertensive patients were used.

For CKD patients with diabetes, transition probabilities from normo- to microalbuminuria and from micro- to macroalbuminuria were taken from Hoerger et al,⁷ and the transition probability from microalbuminuria to ESRD was taken from Adler et al.⁸ For non-diabetic CKD patients, these transition probabilities were assumed to be 50% of those for CKD patients with diabetes in the base case; in 1-way sensitivity analysis the research team used a range of 10% to 70% of those for CKD patients with diabetes (Table 1). Transition probabilities from macroalbuminuria to ESRD were estimated using the 5-year event rates for patients younger than age 65 years in Manns et al⁹; the team assumed that CKD patients with macroalbuminuria had the same risk as the proteinuria-positive subgroup in Mann et al who had urine dipstick readings of greater than trace or a urine protein:creatinine ratio greater than 200 mg/g. For CKD patients with diabetes, the transition probability from macroalbuminuria to ESRD thus determined was 0.0531, which is similar to the base case value of 0.056 that Adarkwah et al¹⁰ derived from the Lewis et al study.¹¹

Mortality rates from normo-, micro-, and macroalbuminuria were estimated using the 10-year event rates for patients younger than age 65 in Manns et al⁹; the team assumed that patients with macroalbuminuria had the same risk as the proteinuria-positive subgroup in Mann et al⁹ and that patients with normo- or microalbuminuria had the same risk as the proteinuria-negative subgroup. The mortality rate from ESRD was taken from den Hartog et al.¹² The effectiveness of ACEIs was taken from Manns et al and Strippoli et al.^9,13

Because this study was undertaken from the perspective of self-insured employers, only direct medical costs incurred by the payers were included in modeling. The CKD outreach program was assumed to incur a 1-time fee of $50 for each eligible individual invited to participate whether or not the individual chose to participate in the program. This fee was paid to the third-party administrator that provided the telemedicine consultations and referral to care. Costs for follow-up physician visits and treatment after the telemedicine consultation were included in cost-effectiveness analysis separately. The cost of follow-up testing was for blood creatinine (Current Procedural Terminology [CPT] 82565), urine albumin (CPT 82043), and urine creatinine (CPT 82570) tests.

For patients with ESRD with employer health plan coverage, Medicare becomes the primary payer after a 30-month coordination period (https://www.medicare.gov/coverage/dialysis-services-supplies). Thus, the costs of dialysis are paid by the health plan for the first 30 months and the health plan pays 20% of the Medicare-allowed amount for dialysis thereafter (Medicare covers the rest of the cost). Only dialysis costs covered by the health plan were included in the model. For both the commercial group and Medicare, the ESRD cost was the sum of dialysis cost (Golestaneh et al³) and a proportion of the non-dialysis medical cost (Golestaneh et al³); because ESRD increases the risk of cardiovascular disease and use of specialized health care,¹⁴ the proportion of the non-dialysis medical cost attributed to ESRD was assumed to be 30% in the base case and varied from 10% to 50% in sensitivity analysis. Other costs and health-related utilities are listed in Table 1.

Analyses

Primary outcomes were quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs). The time horizons examined were 5 years, which would be of interest to self-insured employers. All analyses were performed using TreeAge Pro Version 2018 (TreeAge Software, Williamstown, MA). The effect of changes in individual model parameters on the cost-effectiveness outcome was examined by deterministic sensitivity analysis, wherein the upper and lower bounds of the parameter values were adjusted by ±30% from the base case values unless noted otherwise in Table 1. In Markov simulations, an annual 3% discount rate was applied to all future costs in order to discount them to their net present value.

Results

In the high-risk cohort of potential CKD patients with diabetes, the CKD outreach program resulted in better health outcomes and lower total cost than no CKD outreach (Table 2). Inviting 1000 potential CKD patients with diabetes to participate in the CKD outreach program gained 2.3 QALYs and saved $500,211 over a period of 5 years. Thus, the CKD outreach strategy dominated (was cheaper and better than) the no-CKD outreach strategy. Inviting all potential CKD patients (with and without diabetes) to participate in the CKD outreach program also resulted in better health outcomes and lower total costs (Table 2). For both populations, cost savings from the CKD outreach program increased over time (Fig. 2A for patients with diabetes), with CKD outreach for all potential CKD patients becoming cost saving by year 4 (Supplementary Fig. S2).

FIG. 2.

Cost-effectiveness results of CKD outreach. (A) Cost savings over 5 years from CKD outreach per 1000 potential CKD patients with diabetes invited. (B) Sensitivity analysis of 5-year cost savings from CKD outreach for potential CKD patients with diabetes. Cost savings at the upper and lower bounds (Table 1) of the model parameters are indicated by red and blue bars, respectively. (C) 5-year cost savings per 1000 potential CKD patients with diabetes invited according to fraction of outreach invitations accepted (★ base case). ACEI, angiotensin-converting enzyme inhibitor; CKD, chronic kidney disease; DM, diabetes mellitus; ESRD, end-stage renal disease; PCP, primary care provider; RRR, relative risk reduction. Color images are available online.

Table 2.

Outcomes for the Chronic Kidney Disease Outreach Programs: Base Case at 5 Years

Group	Strategy	Per patient				ICER
Group	Strategy	$	Incremental $	QALY	Incremental QALY	ICER
Diabetics	No outreach	6948	Ref	3.6858	Ref	Ref
	Outreach	6448	−500	3.6882	0.0023	Dominating
All	No outreach	3178	Ref	3.8083	Ref	Ref
	Outreach	3144	−34	3.8091	0.0008	Dominating

Note that numbers may not sum because of rounding.

ICER, incremental cost-effectiveness ratio ($/QALY gained); QALY, quality-adjusted life-year; Ref, reference.

Cost savings from the CKD outreach program were most sensitive to the fraction of outreach invitations accepted, the cost of treatment for ESRD, the effectiveness of ACEIs in reducing the incidence of ESRD, and progression from and prevalence of macroalbuminuria (Fig. 2B for CKD patients with diabetes). As expected, the higher the fraction of outreach invitations accepted or the higher the cost of treatment for ESRD, the higher the cost savings from the program. For example, the cost savings would reach $1,325,528 if all 1000 potential CKD patients with diabetes invited accepted the invitation (Fig. 2C). On the other hand, the potential cost savings from CKD outreach were affected only modestly by changes in costs associated with testing, medication, and physician consultation (Fig. 2B). Cost savings from CKD outreach also were sensitive to the proportion of non-dialysis medical costs included in the total cost of ESRD (Supplementary Fig. S3).

In addition to QALYs, the number of cases of ESRD prevented can be of interest because ESRD entails substantial morbidity, costs, and risk of mortality. For 1000 individuals with diabetes and potential CKD who accepted outreach invitations, the CKD outreach program would have prevented the occurrence of approximately 6 cases of ESRD at year 5 (Supplementary Fig. S4).

For all potential CKD patients, the cost savings for CKD outreach vs. no CKD outreach was affected by disease progression rate (Supplementary Fig. S5). For example, if transition probabilities from normo- to microalbuminuria and from micro- to macroalbuminuria or ESRD in non-diabetic patients were 20% of those in patients with diabetes, instead of the 50% in the base case, the cost savings would decrease from the base case $34,161 to $25,516 per 1000 patients invited.

Discussion

This analysis indicates that, in the context of employee wellness programs that provide eGFR results, CKD outreach programs have the potential to improve health outcomes for patients with CKD and to save medical costs for self-insured employers. For individuals with diabetes with low eGFR, CKD outreach could reach break-even cost by the second year with increasing cost savings thereafter. If CKD outreach were offered to all individuals with a low eGFR, CKD outreach could become cost saving by year 4. As expected, cost savings from CKD outreach were substantial for CKD patients with diabetes (7.2% of the total costs) but the cost savings for all CKD patients was modest. Thus for the all-CKD patient group, the primary motivation for offering the outreach program is the improved health outcome from the program.

Major health benefits and cost savings of the CKD outreach program result from preventing or delaying ESRD. And because CKD typically takes years to progress to ESRD, the longer time horizons provide more opportunity for ESRD events to be prevented or delayed by the program, resulting in cost savings that increase with time (Fig. 2 and Supplementary Fig. S2).

The results of this analysis are strongly influenced by the relationship between diabetes, proteinuria, and response to ACEI therapy. Patients with diabetes are more likely to have proteinuria than are non-diabetics, and CKD patients with proteinuria are more likely to progress to ESRD and receive greater risk reduction from early diagnosis and ACEI therapy. Because of the higher prevalence of albuminuria in diabetes, the model has 1 out of 2 CKD patients with diabetes who accepted CKD outreach invitations initially receiving ACEI therapy. The effectiveness of outreach to patients with diabetes with proteinuria could become even more effective in the future because an inhibitor of the sodium glucose cotransporter, which resorbs glucose in the kidney, has recently been reported to reduce the risk of CKD progression substantially among these patients, a risk reduction that is in addition to that provided by ACEI.¹⁵

This analysis has a number of limitations. The results depend on model assumptions because this analysis was based on simulation rather than actual patient outcomes. Assumptions that could affect cost-effectiveness outcomes for the CKD outreach program include choice of therapy and ethnicity of the population the CKD outreach targeted. For example, some CKD patients might receive treatment with angiotensin II receptor blockers (ARBs) instead of ACEIs,^16,17 and ARBs may be less effective than ACEI at slowing CKD progression.¹⁸ The population targeted by CKD outreach could differ in ethnic composition from the population from which the model parameters were derived. And because African American CKD patients are at increased risk of developing ESRD compared with non-African Americans,¹⁹ CKD outreach would be expected to become increasingly cost-effective as the fraction of African Americans in the target population increased. This is consistent with a report that screening African Americans for microalbuminuria has a more favorable ICER than that for screening non-African American populations.²⁰

The cost-effectiveness of adding a CKD outreach program also will differ based on other aspects of the populations being considered. For example, the research team has modeled the situation in which a CKD outreach program is added to a wellness program that already includes eGFR screening. If a CKD outreach program were added in a situation that did not already have an ongoing eGFR screening program, the outreach program would be somewhat less cost-effective because the cost of the initial annual eGFR screening for the entire population also would need to be included in the costs. On the other hand, a Medicare population may have more cost savings from delaying CKD because, in contrast to employee health plans, Medicare would be responsible for all future dialysis costs.

The sensitivity analysis highlighted other potential limitations of this model. For example, the cost savings from CKD outreach was strongly affected by the fraction of outreach invitations accepted, the cost of ESRD, the efficacy of ACEIs, and progression from and prevalence of macroalbuminuria. This sensitivity to the fraction of outreach invitations accepted highlights the opportunity to increase the effectiveness of outreach programs by thoughtful combinations of engagement methods, incentives, and education programs. For the cost of ESRD, the research team assumed that 30% of the non-dialysis medical costs were attributable to ESRD. However, if a lower proportion of non-dialysis medical costs were included in the cost of ESRD, cost savings from CKD outreach would have been lower than the base case estimate.

Transition from macroalbuminuria to ESRD also had a large effect on cost-effectiveness outcomes. This transition probability will be a function of the characteristics of the patient population targeted by CKD outreach. The team indirectly derived this transition probability from the Alberta Kidney Disease Patient cohort,⁹ and the value was similar to that derived from the Collaborative Study Group trial¹⁰ (see Methods). If the risk of progression from macroalbuminuria to ESRD in the actual population targeted for outreach is higher or lower, cost savings will be higher or lower than in the base case.

On the other hand, cost savings from CKD outreach was less affected by other costs associated with the program, such as the physician visits, testing, medication, monitoring, and program vendor fee. Consequently, uncertainty on these parameters would have less impact on cost-effectiveness outcomes. As expected, the higher the costs for these items, the lower the cost savings from CKD outreach. Also, the probability of progression to ESRD from microalbuminuria had much less effect on cost savings from CKD outreach than did the probability of progression from macroalbuminuria because the former is only 1/17th of the latter in CKD patients with diabetes (Table 1).

Conclusion

This study found that a CKD outreach program could improve health outcomes for employees with CKD while saving costs for self-insured employers.

Footnotes

Acknowledgments

We thank Dr. Robert Toto of UT Southwestern Medical Center for helpful comments on the model and manuscript, and Andre Arellano for excellent technical assistance.

Author Disclosure Statement

Drs. Li and Devlin are employed by Quest Diagnostics, which funded this study.

Funding Information

This study was funded by Quest Diagnostics.

Supplementary Material

Supplementary Figure S1

Supplementary Figure S2

Supplementary Figure S3

Supplementary Figure S4

Supplementary Figure S5

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Supplementary Material

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