Screening for chronic kidney disease: a systematic review of emerging evidence and perspectives

Abstract

Objective

The study aims to summarize the most recent evidence on the cost-effectiveness of chronic kidney disease (CKD) screening, identify the most cost-effective strategies under various conditions, and compare methodologies used in current health economics evaluations. The findings provide insights to support the implementation of appropriate screening strategies, particularly in low- and middle-income countries.

Methods

The final search was conducted between January 1, 2010, and July 1, 2024. Studies were screened for inclusion, and data were extracted, recalculated, and subjected to quality assessment.

Results

Of the 786 articles identified, 24 studies met the inclusion criteria. The probability of screening being cost-effective was 100% for diabetic populations, 75% for those with hypertension, and 72% for the general population. Key drivers of the cost-effectiveness models included drug efficacy, discount rates, and CKD progression probabilities. For diabetic populations, initiating at around age 50 with intervals of 5 to 10 years was generally found to be appropriate. The overall quality of the included studies was high.

Conclusions

CKD screening is cost-effective in high-risk groups such as those with diabetes or hypertension, while general population screening depends on prevalence, methods, and frequency. In resource-limited settings, phased implementation starting with high-risk groups, integration into existing care pathways, and pilot programs using digital tools may enhance feasibility. Future research should refine optimal methods, timing, and intervals, and compare multiple strategies rather than only against standard care.

Introduction

Chronic kidney disease (CKD), defined by a sustained reduction in estimated glomerular filtration rate (eGFR < 60 mL/min/1.73 m²) or markers of kidney damage for over three months [1], is increasingly prevalent with age, particularly in those over 70 [2]. Diabetes is the leading cause of CKD in high-income countries, while hypertension is another major risk factor for the development and eventual progression to kidney failure [3]. Between 1990 and 2017, CKD prevalence rose by 29.3%, and mortality by 41.5%, resulting in 35.8 million disability-adjusted life years (DALYs) [4]. CKD affects approximately 10% of adults in Europe [5] and places a substantial burden on global health systems [6,7].

CKD is often asymptomatic, and in regions with inadequate primary care, nine out of ten patients are unaware of their condition and do not seek treatment [8]. Early screening is therefore critical: it can slow disease progression, prevent cardiovascular complications, reduce dialysis need, and lower treatment costs [8–10]. However, there is no universally accepted CKD screening strategy. The KDIGO conference [11] recommended screening for individuals with hypertension or diabetes, while population-wide screening programs face challenges due to high costs and implementation difficulties. Although experts agree on the target populations for screening, there is still debate regarding the methods, frequency, and age range. Meanwhile, the cost-effectiveness of screening programs often depends on model assumptions [12].

With increasing interest in health economic evaluations, recent studies have examined both general population and high-risk screening strategies. While general population screening may be cost-effective under specific thresholds [13], targeted approaches often yield better cost-benefit ratios. However, some studies may underestimate the effectiveness of intervention by simplifying their models, often omitting the effectiveness of treatment on cardiovascular outcomes.

Two recent systematic reviews have explored the health economics evaluations of CKD screening, but neither fully captures the diversity of current screening strategies. For example, Rokhman et al. [14], did not consider treatment regimens that include sodium-glucose cotransporter 2 (SGLT2) inhibitors, which can reduce kidney failure risk by 30–40% in patients with diabetes and proteinuria [15], and show promise in non-diabetic CKD [11]. Additionally, the review focused solely on the cost-effectiveness of screening versus ‘do nothing’, without comparing the relative benefits of different screening methods. Another review published in 2014 [12] only included studies up to June 2012, resulting in a now outdated evidence on biomarkers and risk-based screening approaches.

This review, therefore, focuses on economic evaluations of CKD screening published over the past 14 years. By examining and comparing the methodologies of these studies, we aim to lay the groundwork for future modeling research as well as offer insights for developing models that are applicable to low- and middle-income countries.

Methods

We adhered to the PRISMA guidelines for systematic reviews and meta-analyses. To identify studies on the cost and effectiveness of CKD screening, we retrieved information from the following databases such as PubMed, CNKI, and Wanfang Database. Our search ranged from January 2010 to July 2024. Also, references of the study were screened to compensate for any limitations in our electronic searches. The search strategy was a combination of keywords such as chronic kidney disease, renal kidney failure, mass screening, cost, cost-effectiveness, and cost-utility. We restricted our search to studies published in English or Chinese.

We followed three predefined inclusion criteria:

1. Studies used health economics evaluation methods and related to CKD screening;

2. Studies clarified CKD screening methods, such as eGFR-based screening and proteinuria-based screening;

3. Studies detailed specific treatments post-screening and analyzed the associated costs and effectiveness of healthcare measures.

Exclusion criteria included:

1. Studies contained only budget impact analysis rather than comprehensive methods such as cost-effectiveness analysis, cost-utility analysis, cost-benefit analysis, and cost minimization analysis;

2. Literature reviews, case reports, letters, and editorials.

Data extraction

Two independent reviewers screened studies in three stages: titles, abstracts, and full texts, based on the criteria mentioned above. Any disagreements during the review were resolved via discussion with senior authors.

We developed data extraction tables to collect the following information:

1. Study characteristics: This includes authors, country, year of publication, target population, and screening methods;

2. Health economics evaluation: This covers the evaluation methods, perspectives, range of costs, discounts, the comparator considered, and the models taken for analysis;

3. Health economics evaluation results: We gathered data on quality-adjusted life years (QALYs), calculated by multiplying the health-related quality of life value by the number of years living in the health state [16]. We simultaneously incorporated the incremental cost-effectiveness ratio (ICER), which is determined by dividing the increment of the costs of two healthcare services by the increment of the effectiveness achieved. In this study, we expressed ICER as cost per QALY;

4. Other critical factors: Such as thresholds, model validation, sensitivity analysis, as well as scenario analysis.

Currencies were converted to U.S. dollars at the prevailing exchange rate.

Assessment of quality

We evaluated the included studies using the Quality of Health Economic Studies (QHES) tool. The QHES guideline assesses the quality of health economics implementation through 16 items, each assigned a different weighted score and answered with ‘Yes,’ ‘No,’ ‘Partial,’ or ‘Not applicable.’ The total score was calculated by summing the scores of all questions answered ‘Yes,’ with a score above 75 generally indicating good quality literature [17]. We recalibrated the scoring based on the relevance of each entry for each study, using the formula: total score = actual score in each item of the article/(full score: 100 - total score for weighting of inapplicable entries) × 100.

Results

Study selection and characteristics

We retrieved a total of 786 articles. After removing duplicates and screening titles, 55 full-text articles were reviewed, with 24 studies meeting the inclusion criteria (Figure 1). Of these, 20 studies focused on high-income countries (United States: 7, Europe: 6, East Asia: 4), while only four studies addressed middle-income countries (China, India, Thailand). Two studies targeted pediatric populations [18,19], while the rest focused on adults—six on general population, ten on high-risk individuals, and eight comparing both (Table 1).

Figure 1.

Study selection process.

Table 1.

Characteristics of the included studies.

Study	Country	Perspective	Age	Population	Methods	Comparator	Interval
Zafarnejad et al. [20] (2024)	USA	Healthcare payer	aged 30 years	Proteinuria, DM or HTN	Cumulative eGFR based statistic	1. No screening and usual care 2. annual or biennial 3. age of 30 years or 60 years 4. general patients, DM,HTN	Annual
Pouwels et al. [13] (2024)	Netherlands	Healthcare payer	aged 45–80 years	General population	ACR	No screening and usual care	One-time
Honda et al. [18] (2024)	Japan	Healthcare payer	aged 6 years followed up through junior and high school	School-Aged Children	Hematuria	No screening	Annual
Kumar et al. [21] (2023)	India	Societal	aged over 40 years	DM(normotensive)	Microalbuminuria	No screening	Annual, 5- and 10-year
Cusick et al. [22] (2023)	USA	Healthcare payer	aged 35–75 years	General population	Microalbuminuria	No screening and usual care	One-time, 5- and 10-year
Kairys et al. [23] (2022)	Germany	Healthcare payer	aged 30–90 years or death	General population, DM or HTN	Microalbuminuria(ACR)	No screening	Every 2 years
Ishida et al. [24] (2022)	Japan	Societal	aged over 40 years	Hematuria	Novel biomarkers	Conventional screening	One-time
Shore et al. [25] (2020)	UK	Healthcare payer	aged 18 years	DM	ACR	No screening and usual care	1-, 5-, or 10-year
Snider et al. [26] (2019)	USA	Societal	aged over 50 years	DM	Novel biomarkers	No screening and usual care	Every 2 years
GO et al. [27] (2019)	Korea	Societal	aged 20–120 years or death	General population, DM or HTN	Urinalysis with dipstick and eGFR	No screening	1-, 2-, or 3-year
Wu et al. [28] (2018)	China	Healthcare payer	aged 51 years	DM	Microalbuminuria	No screening	One-time
Critselis et al. [29] (2018)	Europe	Healthcare payer	aged 50 years	DM	Urinary peptide classifier (CKD273)	Annual UAE-based screening	Annual
Wang et al. [30] (2017)	China	Societal	aged over 45 years	Proteinuria, DM or HTN	ACR	1. DAY-1 2. Random 3. DAY-1 + Random 4. DAY-1 + DAY-2 + Random	Annual
Yarnoff et al. [31] (2017)	USA	Healthcare payer	aged over 30 years	General population	CKD risk scores and ACR	1. No screening 2. different risk scores 3. different intervals 4. different thresholds	1-, 2-, and 5-year
Ferguson et al. [32] (2017)	Canada	Healthcare payer	aged over 18 years	Rural Canadian indigenous	eGFR and ACR	No screening and usual care	One-time
Srisubat et al. [33] (2014)	Thailand	Societal	aged 45–75 years	DM(normotensive)	Microalbuminuria	No screening	Annual
Kondo et al. [34] (2012)	Japan	Societal	aged 40–74 years	General population	Proteinuria only, serum creatinine only or both	No screening	Annual
Kessler et al. [35] (2012)	Switzerland	Healthcare payer	aged 50–90 years or death	General population, DM or HTN	Microalbuminuria	No screening and usual care	1-, 2-, 5- or 10-year
Hoerger et al. [36] (2012)	USA	Healthcare payer	aged 50 years	General population, DM or HTN	Microalbuminuria	No screening and usual care	1-, 2-, 5- or 10-year
Sekhar et al. [19] (2010)	USA	Primary care practitioner	aged 8–15 years	School-Aged Children	Urinalysis with dipstick(proteinuri-a or hematuria)	No screening	–
Manns et al. [37] (2010)	Canada	Healthcare payer	–	General population, DM or HTN	eGFR	No screening	One-time
Howard et al. [38] (2010)	Australia	Healthcare payer	aged 50–69 years	Proteinuria, DM or HTN	Urinalysis with dipstick(ACR)	No screening and usual care	Annual
Cornelis et al. [39] (2010)	Netherlands	Healthcare payer	aged 28–75 years	General population	Microalbuminuria	No screening	One-time
Hoerger et al. [40] (2010)	USA	Healthcare payer	aged 50 –90 years or death	General population, DM or HTN	Microalbuminuria	No screening	1-, 2-, 5-, or 10-year

Notes: DM: diabetes mellitus, HTN: hypertension, ACR: albumin-creatinine ratio, eGFR: estimated glomerular filtration rate, UAE: urinary albumin excretion.

Screening strategies, comparators, and frequencies

Screening methods included urine-based tests (n = 13 microalbuminuria, n = 3 dipstick, others using novel biomarkers or classifiers), eGFR, and combined strategies. Eleven studies used usual care as a comparator, eight used no screening, and the rest compared different screening intervals, starting ages, sampling methods, or risk algorithms. Most studies adopted a healthcare payer perspective (n = 16), while seven used a societal perspective, and one represented a primary care provider view. Screening intervals ranged from one-time to annual, biennial, 5- or 10-year intervals. Less frequent screening (e.g. every 5–10 years) was often found to maintain effectiveness while improving cost-effectiveness, especially in low-risk populations or general population screening [18,21,25,30].

Cost-effectiveness findings

Table 2 presents the ICER values from the included studies, and ranges by population subgroup are provided in Supplementary Figure S1. Figure 2 summarizes the overall cost-effectiveness conclusions across studies. Additionally, Supplementary Table S1 provides a comparative summary of screening strategies, target populations, recommended frequencies, and cost-effectiveness outcomes, including contextual factors such as country income level and healthcare setting.

Table 2.

Comparison of ICERs.

Study	Indicators	Currency	ICER			Threshold
			General	DM	HTN
Zafarnejad et al. [20] (2024)	DALYs QALYs ICER	US $, 2019	Start age = 30, Annual vs No screening: 15,614	25,148	27,671	50,000–100,000
Pouwels et al. [13] (2024)	QALYs ICER	Euros, 2020	9225($10295)	–	–	20,000($22,343)
Honda et al. [18] (2024)	QALYs ICER	US $, 2020	39,127	–	–	70,093
Kumar et al. [21] (2023)	QALYs ICER	US $, 2021	–	With the dipstick point of care test vs No screening: 308 With the gold standard ACR and a serum creatinine test vs No screening: 196	–	1,826
Cusick et al. [22] (2023)	QALYs ICER	US $	One-time screening and ACEI/ARB + SGLT2 inhibitorvs No screening: 86,300 Screening every 10 y until age 75 y and ACEI/ARB + SGLT2 inhibitorvs No screening: 92,500 Screening every 5 y until age 75 y and ACEI/ARB + SGLT2 inhibitor vs No screening: 121,100	–	–	100,000–150,000
Kairys et al. [23] (2022)	QALYs ICER Lifetime prevalence Average age at the start of RRT Average age at death Rate of false-positive	Euros, 2016	Cost-saving	Cost-saving	Cost-saving	–
Ishida et al. [24] (2022)	Incremental expected number of dialysis participants Incremental expected dialysis period Incremental expected diagnosed IgAN	US $	Cost-saving	–	–	–
Hoerger et al. [40] (2010)	QALYs ICER Lifetime incidence of ESRD	US $, 2006	73,000	21,000	55,000	50,000
Shore et al. [25] (2020)	Total CKD diagnoses Total number of people with ESRD	Euros, 2017	–	Cost-saving	–	–
GO et al. [27] (2019)	QALYs ICER	US $, 2016	66 874.29	37,812.92	40,787.17	25,000(Korean) 80,000(International)
Wu et al. [28] (2018)	QALYs ICER Life years gained ESRD incidence	US $, 2014	–	Screening vs No screening: Cost-saving Screening vs Usual care: 30087	–	7,380-22,140
Critselis et al. [29] (2018)	Life years gained QALYs ICER	GBP	–	23,903($31,858)	–	25,600($34,120)
Snider et al. [26] (2019)	Prevalence of DKD Prevalence of diabetes with stage 5 chronic kidney disease Life years gained QALYs ICER	US $, 2015	–	25,842	–	50,000
Wang et al. [30] (2017)	QALYs ICER	CNY	DAY-1vs Random: 8134.69($1,151) DAY-1 vs DAY-1 + Random: 112335.88($15,899) DAY-1 vs DAY-1 + DAY-2 + Random: 10327.99($1,461)	–	–	100,000(14,716)
Yarnoff et al. [31] (2017)	QALYs ICER	US $, 2016	19,116	–	–	50,000
Ferguson et al. [32] (2017)	QALYs ICER Life expectancy	US $, 2013	23,700	–	–	50,000
Srisubat et al. [33] (2014)	QALYs ICER Life years gained	THB, 2011	–	3,035($91)	–	150,000($4,540)
Kondo et al. [34] (2012)	QALYs ICER	US $, 2009	Dipstick test only: 12,660 Serum Cr assay only: 90,250 Both: 91,505	–	–	128,000
Kessler et al. [35] (2012)	QALYs ICER Lifetime incidence of ESRD	CHF, 2010	66,000($77,923)	29,000($34,238)	40,000($47,226)	71,000($83,784)
Hoerger et al. [36] (2012)	QALYs ICER Lifetime incidence of ESRD	US $, 2006	33,000	19,000	21,000	–
Sekhar et al. [19] (2010)	Rate of diagnoses of CKD ICER	US $	2,779.50	–	–	–
Manns et al. [37] (2010)	Number of end stage renal disease QALYs ICER	CAD, 2009	104,900($77,328)	22,600($16,659)	334,000 ($242,588)	50,000
Howard et al. [38] (2010)	QALYs ICER	AUD, 2008	4,781($3,259)	13,781($9,396)	491($334)	50,000($34,078)
Cornelis et al. [39] (2010)	Life years gained ICER	Euros, 2008	22,000/LYG($24,715)	–	–	20,000–80,000/LYG ($22,335-$89,343)

Notes: DALYs: disability adjusted life years, QALYs: quality-adjusted life years, ICER: incremental cost-effectiveness ratio.

Figure 2.

Color-coded heatmap decision matrix of cost-effectiveness by region and population subgroup. Pink cells represent cost-effective findings, yellow cells represent not cost-effective findings, and grey cells indicate empty placeholders with no study. Studies within dashed boxes represent analyses conducted in low- and middle-income countries (LMICs); all other studies were conducted in high-income countries.

By population subgroup, all 14 studies (100%) found screening strategies in diabetic populations to be cost-effective. Among hypertensive individuals, 6 out of 8 studies (75%) supported cost-effectiveness, while 2 reported conflicting results. For the general population, findings were more heterogeneous: two studies (11%) found screening cost-saving, 13 (72%) deemed it cost-effective, and three (17%) concluded it was not cost-effective. Among pediatric populations, the two studies reached opposite conclusions.

Age and frequency patterns influenced cost-effectiveness results. In diabetic populations, screening individuals around age 50 appeared to optimize cost-effectiveness compared to broader age groups [25,37,38]. Most studies found that increasing screening frequency led to higher ICERs, whereas extending the interval (e.g. to 5 or 10 years) reduced costs with minimal health tradeoffs [21,30]. In the general population, for earlier starting ages (e.g. 30–45 years), less frequent strategies (such as one-time or 10-year intervals) were generally more cost-effective. In contrast, for later starting ages (e.g. after 50 years), more frequent screening (every 5 years or even shorter intervals) tended to be more favorable in terms of cost-effectiveness.

Three recent studies (published after 2022) incorporated SGLT2 inhibitors alongside ACEIs/ARBs and consistently reported improved cost-effectiveness [13,20,22]. In contrast, eight earlier studies incorporated CVEs, but only three explicitly modeled both CVE-related costs and benefits [13,25,39], while others did so indirectly or acknowledged it as a limitation. Consequently, some of these studies may have concluded screening was not cost-effective [37] or only under restrictive conditions [35,40]. One even assumed no benefit from CKD monitoring in patients without diabetes or hypertension [34], further weakening the value of screening.

Input parameters

CKD prevalence ranged from 6.2% to 11% [21,29], with most studies using albuminuria as a proxy. Among diabetic patients, microalbuminuria prevalence reached 21.9% [28,41], while in the general population it ranged from 6.3% to 14.3%, highest among African Americans [36]. Screening adherence varied between 50% and 91%, averaging around 72%. One smartphone-based home testing study reported only 32% participation [25]. Two studies reported background detection outside of screening (0.22 and 0.05) [18,36].

Screening sensitivity ranged from 0.31 (urine dipstick) [27] to 0.95 (novel peptide classifier CKD273) [29], and specificity from 0.44 to 0.97. Many studies used values from a systematic review by Wu et al. with sensitivity and specificity of 0.87 and 0.88, respectively [42].

Annual eGFR decline was reported as 0.33 and 0.65 mL/min/1.73 m²/year [13,23]. ACEI/ARB therapies showed consistent benefit, with relative risk reductions in CKD progression ranging from 24% to 82% (commonly 67%). Utility values for CKD ranged from 0.85 (stages 1–4) [37,42] to 0.12–0.64 for ESKD [13,21,28,29]. Proteinuria was associated with a utility decrement of 0.01 per year [38].

Unit cost

Screening costs varied from $1.90 to $961 (median: $142), with wide variation depending on test modality and country context. Medication costs for ACEIs/ARBs ranged from $0.22 to $3,846, with a median of $379. SGLT2 inhibitor costs were between $307 and $365 [20,22]. The highest reported costs were typically in studies set in middle-income settings using microalbuminuria tests [21].

Sensitivity analysis

23 studies conducted one-way sensitivity analyses, 21 conducted scenario analyses, and 17 included probabilistic sensitivity analyses. Key variables influencing cost-effectiveness included CKD progression rates (8 studies), adherence (12 studies), and costs related to screening, medications, management, and savings from reduced dialysis patients (16 studies).

Model validation and quality assessment

Only eight studies referenced guideline adherence, with the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) being the most commonly followed (62.5%). Fourteen studies discussed model validation: 10 used external validation with real-world or published data, and two also included internal checks [29,37]. One used the AdViSHE tool [13], while another relied on expert opinion [24].

The QHES scores of included studies ranged from 65 to 95, with a median of 89. 46% (11/24) scored 90 or above, another 46% scored between 80 and 89, and 8% (2/24) scored below 80. The lowest score, 65, was for a study on pediatric CKD screening [19]. In 10 of the reviewed items, over 75% of the studies conducted detailed analyses. For five specific items—selection of analytical perspective (Item 2), source of variable values (Item 3), economic model structure (Item 12), model selection and limitations (Item 13), and funding support (Item 16)—only 2 studies (2.9%) for Items 2 and 3, 15 studies (22%) for Item 12, 16 studies (23.5%) for Item 13, and 14 studies (20.5%) for Item 16 provided clear explanations. When addressing potential bias (Item 14), many authors discussed its direction but ignored the magnitude (Figure 3).

Figure 3.

Study quality score. a. Total score for each study based on the QHES. b. Percentage scores for all studies on each entry.

Discussion

This systematic review synthesized 24 cost-effectiveness studies of CKD screening across varied populations and regions. It found that targeted screening in diabetic groups was consistently cost-effective, whereas findings in hypertensive or general populations were mixed. However, heterogeneity in screening frequency, target populations, and healthcare system contexts limited direct comparisons. The findings inform context-specific CKD screening strategies and highlight key evidence gaps and opportunities for future research.

The incorporation of SGLT2 inhibitors into screening models represents a key turning point. Earlier models often underestimated benefits by omitting cardiovascular complications or assuming limited treatment effects, which led to findings of low or conditional cost-effectiveness [34,35,37,40]. More recently, studies show that adding SGLT2 inhibitors improves cost-effectiveness by delaying CKD progression, reducing cardiovascular events, and lowering ESKD incidence [13,20,22]. This underscores newer treatments like SGLT2 inhibitors as critical drivers of cost-effectiveness outcomes.

Early discussions around CKD screening centered on whether screening should be implemented. However, with increasing awareness of its significant burden, strategies have shifted to include education of high-risk populations, implementation of early detection programs, and incorporation of evidence-based treatments for CKD and related conditions [43]. As a result, the current question is no longer whether to screen, but how to do so effectively.

What to screen: Selecting appropriate and feasible indicators

The choice of screening indicators is central to both the effectiveness and feasibility. Using either albuminuria or eGFR alone has important limitations [44,45]. Current guidelines recommend combining both urine testing and eGFR for CKD detection [46,47], yet among the studies included in this review, only three studies [27,31,32], all from high-income countries, followed this approach.

In contrast, urine dipstick testing remains common in low- and middle-income countries despite its limited accuracy [8,30,48]. Novel biomarkers may offer greater diagnostic precision, but their high cost and limited availability pose major concerns [26,29].

In whom to screen: Prioritizing high-risk and underserved populations

Across adult populations, individuals with diabetes and hypertension benefited most from screening, as supported by cost-effectiveness evidence. Beyond clinical risk, racial disparities also warrant consideration. For example, the prevalence of kidney failure in Indigenous Canadians is 2 to 4 times higher than in non-Indigenous populations [32]. At the same time, African Americans have a higher lifetime incidence of ESRD compared to non-African Americans [36].

Risk stratification remains essential. Ideally, noninvasive risk prediction tools could facilitate CKD screening and predict disease progression, thereby identify individuals most likely to benefit. For example, Yarnoff et al. employed the Bang et al. risk score and found that using a threshold of 0.02 with a two-year screening interval yielded the most cost-effective results [31]. However, such models are often developed in specific populations, and their generalizability remains uncertain. Moreover, while many clinical risk factors used in these models are routinely available and thus more scalable in low- and middle-income countries, the inclusion of costly biomarkers in some models poses practical challenges in resource-limited settings [8,49,50].

Although most evidence focuses on adults, children with certain underlying conditions may also benefit from targeted CKD screening. In China, national guidelines recommend regular CKD screening in pediatric high-risk groups, including those with kidney malformations, a family history of kidney disease in first-degree relatives, or a history of acute kidney injury [51]. In Japan, a 12-year cost-effectiveness study of school-based urine screening found the program economically viable, with early detection of an average of 108.2 CKD cases annually and a nearly 50% reduction in lifetime ESRD incidence [18]. These outcomes may reflect Japan’s long-standing infrastructure for school health programs and follow-up care. By contrast, in the United States, Sekhar et al. [19] reported that the American Academy of Pediatrics discontinued routine urine dipstick screening in 2007, citing low yield and a high prevalence of transient or false-positive results among asymptomatic children. Moreover, the lack of effective pharmacological interventions for early-stage CKD in children limited the clinical utility of early detection, further undermining the rationale for routine screening. Overall, early identification through school-based urine testing or targeted screening in high-risk groups may help delay progression, although the cost-effectiveness of such strategies remains underexplored and highly context-dependent.

With what methods: balancing simplicity, accuracy, and acceptability

Screening methods must balance ease of use, accuracy, and population acceptability. Conventional approaches, such as mobile teams or opportunistic in-hospital screening, have been effective in improving participation [32,52].

Emerging digital health technologies offer alternative or complementary strategies, particularly where geographical limitations hinder access to screening. Evidence suggests they can improve screening uptake and reduce costs [53–55]; however, one study in our review showed low acceptance (32%). Therefore, long-term clinical and economic outcomes remain uncertain. Importantly, such tools can be embedded into routine primary care. Further research should build patient trust and engagement, develop sustainable implementation strategies to realize their potential.

How often to screen: tailoring frequency based on age and resource constraints

Our review suggests that both age at initiation and screening frequency substantially influence cost-effectiveness. Generally, earlier initiation appears more efficient when combined with longer intervals, whereas later initiation benefits from shorter intervals. From a resource perspective, high-income countries may find it cost-effective to start screening earlier and maintain higher frequency, which can prevent a greater number of end-stage kidney disease cases [13,20,23,25]. In contrast, in low- and middle-income settings, less frequent screening, especially when starting at younger ages, may be more appropriate to balance health gains with budget constraints.

In what context to screen: accounting for health system and economic realities

Cost-effectiveness analyses must be region-specific, as the feasibility and value of interventions are shaped by the structure, organization, and funding mechanisms of each healthcare system [56]. Supplementary Table 2 summarizes key health system features and the role of primary care in CKD screening across different regions.

Education plays a critical role in supporting uptake and sustainability. A pilot program among college students in India [57] found that brief educational videos and presentations followed by on-site urine testing, enabled efficient one-time screening and enhanced awareness of CKD’s asymptomatic nature. This underscores the importance of embedding education within screening programs. Policy implications for low- and middle-income countries are summarized in Supplementary Table 3.

Study limitations

This study has several limitations. First, despite a comprehensive search, there were relatively few studies focusing on non-Western populations, which may introduce publication bias. Most included studies were conducted in high-income countries, limiting the generalizability of findings to low- and middle-income settings, although we provided pragmatic recommendations for resource-limited regions.

Second, substantial heterogeneity existed among included studies in terms of population characteristics, screening indicators, outcome measures, model structures, and willingness-to-pay thresholds, precluding meta-analysis. Reporting inconsistencies and model simplifications, such as excluding potential side effects of ACEI/ARB therapies or mortality risks from transplantation or dialysis, may bias estimates and overestimate net benefits. Moreover, willingness-to-pay thresholds varied widely according to healthcare system contexts, and evidence on thresholds relevant to middle-income countries remains scarce. Together, these factors limit the direct translation of cost-effectiveness findings into real-world policy; in particular, the results cannot be directly applied to prioritize screening programs in resource-limited settings without context-specific evaluation, especially in countries with markedly different healthcare infrastructure and resource availability.

Third, only two studies addressed pediatric populations, limiting applicability of findings to children and adolescents. Nonetheless, we highlighted potential benefits of targeted screening in high-risk pediatric groups, especially in Asian settings.

Finally, although we applied rigorous quality assessment criteria, subjective factors may have influenced study appraisals. Despite these limitations, this systematic review’s methods and findings provide valuable insights into the economic evaluation of CKD screening globally, particularly for regions lacking robust local evidence.

Conclusion and outlook

In summary, the existing health economic evaluations of CKD screening indicate that such programs hold significant public health value and clinical importance. Screening high-risk populations, such as those with diabetes or hypertension, has proven to be cost-effective, while screening the general population depends on the CKD prevalence, methods, and frequency in different regions. It is recommended that more convenient screening methods be adopted that combine age and risk scores. For instance, urine screening every 5–10 years in community settings, alongside supporting primary care facilities to collaborate on establishing regional diagnostic centers, could help reduce the costs of redundant testing. Healthcare decision-makers need to consider the structure of local healthcare systems, propose specific screening strategies, and reallocate medical resources based on reasonable budget analysis to maximize the cost-effectiveness of CKD screening programs and reduce the healthcare burden. In high-income countries like Europe and the U.S., combining UACR and eGFR screening captures both structural and functional kidney damage, improving diagnostic accuracy and reducing follow-up caused by false positives from a single marker. This integrated strategy is both clinically and economically effective.

In resource-limited settings, phased implementation strategies may help balance cost-effectiveness and feasibility. Examples include starting with targeted screening of high-risk groups, expanding coverage as resources permit, and embedding CKD screening into existing diabetes and hypertension care pathways to leverage shared infrastructure and reduce incremental costs. Pilot programs supported by digital tools can be launched in selected regions to generate real-world data and refine protocols before nationwide rollout. Policymakers should also ensure that community health workers receive training in CKD risk assessment and patient education, thereby improving screening uptake and follow-up compliance.

Future research should be based on real-world studies and focus on refining specific screening strategies, including which sampling method is best, when to start, how often between, and when to stop. In addition, it should compare cost-effectiveness across different approaches rather than only against “do nothing” or standard care. Implementing these context-specific strategies can enhance the real-world applicability and policy relevance of CKD screening programs globally.

Funding Statement

This research was funded by Hunan innovative province construction project (Grant No. 2019SK2211), Key research and development project of Hunan Province (Grant No. 2020SK2089), The Natural Science Foundation of Hunan province (Grant Nos 2020JJ4833, 2019SK2211, and XY040019), Hunan Province Key Field R&D Program (Grant No. 2020SK2097), the National Natural Science Foundation of China (Grant No. 82570823), and Horizontal Project (Grant Nos KY080269, KY080262, XY080323, and XY080324).

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No potential conflict of interest was reported by the authors.

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Data availability statement

All data in this systematic review are publicly available.