Economic feasibility analysis of using serum C-reactive protein as a screening tool for high-risk people with diabetes complications in the community: an empirical analysis using CHARLS data

doi:10.21203/rs.3.rs-2702708/v1

Download PDF

Research Article

Economic feasibility analysis of using serum C-reactive protein as a screening tool for high-risk people with diabetes complications in the community: an empirical analysis using CHARLS data

https://doi.org/10.21203/rs.3.rs-2702708/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Objectives: To explore the economic feasibility of using serum C-reactive protein as a screening tool for groups at high risk of diabetes-related complications in Chinese communities.

Methods: In this study, we use data from China Health and Retirement Longitudinal Survey (CHARLS) in 2015. Thenthe Markov model was used to explore the economic feasibility of using serum C-reactive protein as a screening tool for high-risk groups of diabetic complications in Chinese communities.

Results: In our study，27.8% of patients with serum C-reactive protein were at high risk. According to the Markov, it predict that using serum C-reactive as a screening tool for high risk groups of diabetes will reduce the economic burden by ¥50,350.01 per individual compared with the control group . According to the current population proportion of diabetes in China, it estimate that will reduce the economic burden by ¥5840.6 billion（$837.58 billion）,the mortality rate by 8.3% , and the incidence rate of myocardial infarction by 42.2% in five years .This is equivalent to saving 9.628 million lives of diabetes patients and reducing myocardial infarction events by 48.72 million and the economic burden by ¥3134.84 billion ($449.6 billion).

Conclusions: In this study, It is economically feasible to use serum C-reactive protein as a screening tool for high risk groups of diabetes complications in the China community.

C-reactive protein

Diabetes Complications

Screening

Economic burden

Markov

Diabetes has become a global concern. The International Diabetes Federation(IDF)[1] calculates that the prevalence of diagnosed and undiagnosed diabetes in 2019 was 9.3% (463 million people) and will rise to 10.9% (700 million people) in 2045. Currently, there are 116 million diabetes cases in China, accounting for a quarter of global diabetes, it estimated that the number of people with diabetes will rank first in the world by 2045, reaching 174.4 million[2]. Diabetes is accompanied by sever complications, and its mortality and complications bring enormous economic burdens to patients and society. In 2015, the direct medical expenses of the diabetic population in China were estimated to be 141.58 billion dollars, accounting for 1.3% of the GDP [3]. According to the statistics of the International Diabetes Federation [4], the global health expenditure caused by diabetes in 2021 is about 966 billion dollars, and the economic burden of diabetes is expected to account for 2.2% of the global GDP in 2030 [5]. In 2009, China required primary health care institutions to conduct health management for diabetic patients [6]. However, the survey showed that the standard management rate of diabetes was only 40.1%[7]. At present, traditional screening methods are used to detect diabetes in the community, including fasting glucose, glycosylated hemoglobin, etc. The results are likely to be affected by multiple factors that reduce their accuracy [8], which cannot be used as a marker for possible complications in diabetic patients.

In recent years, researchers have discovered several biomarkers for which screening can compensate for the shortcomings of traditional screening methods. Serum C-reactive protein (CRP), as a biomarker of inflammation, has received much attention due to its role in the pathogenesis of type 2 diabetes(T2DM). Based on many prospective studies [9–11], CRP can be used as an effective biomarker to predict diabetes complications and cardiovascular diseases, and is positively correlated with the incidence of long-term complications [12, 13]. To further verify its relationship with the risk of diabetes, Chinese scholars [14] used Mendelian randomization (MR) analysis and showed that CRP levels significantly suggested the risk of T2DM. Therefore, it is theoretically feasible to use CRP as a screening tool for community people at high risk of diabetes complications. This study explored the health economics feasibility of using CRP as a screening tool for high-risk groups of diabetic patients in Chinese community.

2.1 Demographic analysis

2.1.1Data source and demographic analysis

The study used data from China Health and Retirement Longitudinal Survey (CHARLS) in 2015, which involved 150 counties and 450 communities (villages) in 28 provinces (autonomous regions and municipalities directly under the Central Government) in China, with a sample of 23,000 respondents from 12,400 households. The survey objects are mainly microdata of families and individuals aged 45 and above in China. The participants were interviewed face-to-face in their homes through computer-assisted personal interviewing (CAPI) technology.The CHARLS datasets can be downloaded at the CHARLS home page at http://charls. pku.edu.cn/en.

To study CRP as a screening tool for diabetes patients at high risk of complications in the community, we limited the sample to respondents who underwent physical examination in 2015, including 20,967 people, and screened patients from the subject sample who were required to meet the following conditions: Detailed data were collected via a standard questionnaire including completion of a complete questionnaire, participation in laboratory examinations, and demographic characteristics. A total of 216 subjects meet the criteria (Fig. 1), underwent serum C-reactive protein detection; Deleted data included no serum C-reactive protein test, heart disease, stroke, and nephropathy disease, and missing data.

2.1.2 Analysis Method

Eligible samples were filtered by using Excel and SPSS25.0 . Using stepwise confirmatory procedure. We relied on self-report diabetes data from each participant. In the present study, 216 eligible subjects were divided into two groups based on CRP≥3mg/L and < 3mg/L [15], including 60 CRP≥3mg/L patients and 156 CRP＜3mg/L patients. Table 1 shows the baseline characteristics of patients in the two groups.

Table 1 Characteristic distribution of patients with CRP≥3mg/L and CRP < 3mg/L.

Characteristic

CRP≥3mg/L

（n=156）

CRP＜3mg/L

（n=60）

t/X²

P-value

Age

57.88±9.9

60.06±10.6

1.434

＞0.05

Gender，n（%）

Male

Female

58（37.2）

98（62.8）

24（40）

36（60）

0.146

＞0.05

BMI，n（%）

＜18.5

18.5-23.9

＞23.9

1（0.6）

55（35.3）

100（64.1）

1（1.6）

19（31.7）

40（66.7）

0.699

＞0.05

CRP serum C-reactive protein

2.2 Economic burden analyses

To keep the analysis concise and stable, the study only analyzed the cost of serum C-reactive proteins screening and direct medical cost to measure financial burden.

2.2.1 Design of health economy model

Patients were divided into an experimental group (CRP screening) and a control group (no CRP screening). According to the natural history Markov state transition model for diabetes (Fig.2), in this study, we analyzed the economic health feasibility of using CRP screening as a tool for high risk groups of diabetic complications patients in China community. In order to ensure correlation between the individual attributes , Tree Pro2019 software is used to establish Markov models. Six different health states were in the model: diabetes, stroke, myocardial infarction, diabetic nephropathy, diabetic foot, and death. At the end of the model (one year), an individual either transitions to a different health state or stays in the same one . The initial state assumes that the target patients entering the model are diabetes with no complications from heart disease, stroke , or nephropathy . Based on the average annual probability of transfer of various disease states in different health states (diabetes, multiple complications, death, etc.) , we calculated the distribution of the various health states throughout the next cycle (by year) (Fig.S1), as well as the value of the screening costs and direct medical expenditures of patients with different health states throughout this cycle. We compared the potential to reduce the economic burden of serum C-reactive protein as a routine screening method for community residents.

2.2.2 Model parameters

This cycle was combined with patients' average age and life expectancy at baseline to determine the total simulation time. The mean age of CHARLS2015 sample patients was 58.4 years, and based on the analysis of the China Statistical Yearbook [16]，the average life expectancy of Chinese residents is projected to rise to 80.88 years by 2030, the simulation cycle for this model is therefore set to 20 years. According to the [17]2021 National Development and Statistics Bulletin of the People's Republic of China, we suggest using a discount rate of 5%, and choosing a discount rate in the range of 3%-8% for the sensitivity analysis. Information on the likelihood of metastasis among various medical conditions in patients with diabetes was obtained from the published literature (see TableS1).

2.2.3 Calculation of economic burden of disease

The cost of each diagnosis and treatment in the model was collected in 2003 [22] , and calculated according to the 2015 Consumer Price Index [23] , the cost of C-reactive protein screening was ¥10 per time [24]. The costs of each item are shown in TableS2.

According to Markov cost analysis, after 20 years, the cumulative cost of the experimental group is ¥109,849, the cumulative cost of the control group is ¥160,338, and the incremental cost is -¥50,488, indicating that the experimental group can reduce the economic burden (see TableS3).

Markov cohort analysis was performed for diabetes models of the two groups. The Markov probability distribution of the state (Fig.S2 and Fig.S3) shows that the mortality rate of both groups is increasing year by year, and the mortality rate of the control group at each period is greater than that of the experimental group. The probability distributions for diabetic foot and diabetic nephropathy are not significantly different between the 2 groups. In the control group, the probability of myocardial infarction briefly increased and then slowly declined, however the incidence in the experimental group increased from year to year but the overall incidence was less than that in the control group. There was a gradual increase in the incidence of stroke in both the control and experimental groups.Still the incidence in the control group was greater than that in the experimental group. The prevalence of diabetes in both the control group and the experimental group showed a decreasing trend, and the decreasing trend was faster in the experimental group.

In the present study, 2.5% of eligible patients had diabetes and 1.5% had no heart disease, stroke, or nephropathy, and 27.8% CRP ≥ 3 mg /L. According to the model of Markov, the experimental group with serum C-reactive protein screening has the potential to reduce the economic burden of ¥50, 350.01 per individual compared with the control group. Currently, there are 116 million people with diabetes in China [2], a proportionally estimated reduction of ¥5840.6 million, or $837.58 billion (2022 exchange rate of $1 = ¥697.32). The proportion of patients at high risk for C-reactive protein testing is estimated to be as high as 30 million nationwide. Compared with the control group, a 5-year，there was an 8.3% reduction in mortality and a 42.2% reduction in myocardial infarction , but a decrease in stroke was not anticipated. This equates to 9.628 million lives saved from diabetes in the country as a whole; Myocardial infarction events have decreased by 48.95 million people and the economic burden has decreased by ¥313.484 billion ($44.96 billion) (see TableS4 and Table S5). This substantially reduces the burden on the health economy relative to global health expenditures for diabetes [25] in 2021. Thus, CRP could be implemented nationally as a screening tool for diabetes complications events.

Briefly, based on the changes in the probability distribution of both groups and the specific parameter values related to each round, we can find that, relative to the natural population in the control group, screening measures may delay the progression of diabetes to some degree and reduce economic burden.

Sensitivity Analysis：In the single-factor sensitivity cyclone plot analysis, the range of discount rate variation was between 3% and 8%. The remaining parameters (e.g., utility values for diabetes and each complication, screening costs, probability of transfer, etc.) were taken to be between 20% at the top and the bottom. From Fig.3, it can be seen that the utility value of diabetes has the most significant impact on the increase in economic burden, followed by the utility value of myocardial infarction.

Studies have shown that serum C-reactive protein can predict diabetes and its complications. Using serum C-reactive protein as a screening tool for people at high risk of diabetes in this study could reduce the financial burden by $50,350 per person. If rolled out nationwide, it is expected to save 9.628 million lives, reduce the incidence of 48.95 million myocardial infarction and reduce the health economic burden by 313.484 billion ($44.96 billion) over five years. At present, the traditional screening methods in the community are influenced by many factors, so in recent years, researchers have chosen an economical, convenient, and accurate screening method from the perspective of inflammatory markers to compensate for the deficiency of traditional screening methods. China has entered the aging stage, and rapid aging has resulted in an increased healthcare burden. Diabetes is a common age-related condition [26]. Effective screening of high-risk populations in the diabetic groups is the first step in normalized community management and reduction of complications.

Early screening for chronic diseases and the calculation of financial burdens are favored by most researchers. A study [27]on the economic burden of early screening in patients with atrial fibrillation similarly demonstrated the importance of early screening for chronic diseases not only to save patients' lives but also to reduce the economic burden of the affected patients, and efforts should be made to increase the participation in screening.

A significant strength of this study includes a large sample size from the national survey of Middle and Older People in China, which allows us to identify a unique subgroup. In this study, from the perspective of adverse events, we used the Markov model to compare the incidence of major adverse events and the financial burden of their severity on patients in both scenarios. By calculating the transition probability to predict their changes, it is confirmed that serum C-reactive protein can be used as a screening method for people at high risk of diabetes in the community to reduce the financial burden of residents.

Limitations: In the present study, by quantifying different states of naturally occurring diabetes regression, some of the transfer probabilities used were gathered from the published literature, and some of the data were calculated manually; Complications of diabetes set in the model did not include all complications, ignoring other complications such as retinopathy, which may also have an impact on the patient's financial burden; a single factor sensitivity analysis showed that diabetes and myocardial infarction utility values were the most influential factors in the outcomes, and further studies will continue to be carried out to explore the reasons for their influence in this study.

In this study, It is economically feasible to use CRP as a screening tool for high risk groups of diabetes complications in the China community.

CHARLS: China Health and Retirement Longitudinal Study

MI: myocardial infarction

DF: Diabetic Nephropathy

DN: Diabetic Foot

CRP：serum C-reactive protein screening

Ethical Approval

CHARLS was approved by the Ethical Review Committee (IRB) at Peking University, Beijing, China. And we confirmed that the data accessed by the manuscript comply with relevant data protection and privacy regulations.

Competing interests ：None declared.

Authors' contributions

All authors participated in concept and design of this study. Qian Wu: Select a topic, Data analysis, Writing manuscript; Bing Wang: Make overall arrangements, Participate in writing and revising papers; Xiaohong Yang ,Yujia Wang and Li Gao: Paper framework design and revision; Chunli Chen and Yaqin Peng: Conceptualization; Fang Cheng and Wenjun Cai: Collect data and analyze data. The author(s) read and approved the final manuscript.

Funding

This work was supported by The Department of Education of Zhejiang Province (Y202043955).

Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Williams R, Karuranga S, Malanda B, et al. Global and regional estimates and projections of diabetes-related health expenditure: Results from the International Diabetes Federation Diabetes Atlas, 9th edition[J]. Diabetes Res Clin Pract, 2020,162:108072. https://doi.org/ 10.1016/j.diabres.2020.108072
Patterson C C, Karuranga S, Salpea P, et al. Worldwide estimates of incidence, prevalence and mortality of type 1 diabetes in children and adolescents: Results from the International Diabetes Federation Diabetes Atlas, 9th edition[J]. Diabetes Res Clin Pract, 2019,157:107842. https://doi.org/ 10.1016/j.diabres.2019.107842
Ding C, Bao Y, Bai B, et al. An update on the economic burden of type 2 diabetes mellitus in China[J]. Expert Rev Pharmacoecon Outcomes Res, 2022,22 (4) :617-625. https://doi.org/ 10.1080/14737167.2022.2020106
Ogurtsova K, Guariguata L, Barengo N C, et al. IDF diabetes Atlas: Global estimates of undiagnosed diabetes in adults for 2021[J]. Diabetes Res Clin Pract, 2022,183:109118. https://doi.org/10.1016/j.diabres.2021.109118
Bommer C, Sagalova V, Heesemann E, et al. Global Economic Burden of Diabetes in Adults: Projections From 2015 to 2030[J]. Diabetes Care, 2018,41(5):963-970. https://doi.org/ 10.2337/dc17-1962
Notice of the National Health and Family Planning Commission on the issuance of the National Basic Public Health Service Specifications (Third Edition) [J]. Gazette of the National Health Commission of People's Republic of China, 2017 (03) :21. /https://doi.org/
Hu Caihong, Zhang Mei, Zhang Xiao, et al. The management status of diabetes patients (≥35 years old) in communities of China[J]. Chinese Journal of Prevention and Control of Chronic Diseases, 2021,29 (04) :264-267 https://doi.org/ 10.16386/j.cjpccd.issn.1004-6194.2021.04.006
Barry E, Roberts S, Oke J, et al. Efficacy and effectiveness of screen and treat policies in prevention of type 2 diabetes: systematic review and meta-analysis of screening tests and interventions[J]. BMJ, 2017,356: i6538. https://doi.org/ 10.1136/bmj.i6538
Qian X, He S, Wang J, et al. Prediction of 10-year mortality using hs-CRP in Chinese people with hyperglycemia: Findings from the Da Qing diabetes prevention outcomes study[J]. Diabetes Res Clin Pract, 2021,173:108668. https://doi.org/ 10.1016/j.diabres.2021.108668
Chen K, Yan J, Wu L, et al. Relationship Between C-Reactive Protein and Respiratory Diseases in Patients with Type 2 Diabetic Retinopathy[J]. Med Sci Monit, 2022,28: e935807. https://doi.org/ 10.12659/MSM.935807
Duncan B B, Schmidt M I. The epidemiology of low-grade chronic systemic inflammation and type 2 diabetes[J]. Diabetes Technol Ther, 2006,8(1):7-17. https://doi.org/ 10.1089/dia.2006.8.7
Landman G W, Kleefstra N, Groenier K H, et al. Inflammation biomarkers and mortality prediction in patients with type 2 diabetes (ZODIAC-27) [J]. Atherosclerosis, 2016,250:46-51. https://doi.org/ 10.1016/j.atherosclerosis.2016.04.015
Xia M, Zhang C, Gu J, et al. Impact of C-reactive protein on long-term mortality in acute myocardial infarction patients with diabetes and those without[J]. Clin Chim Acta, 2018,480:220-224. https://doi.org/10.1016/j.cca.2018.02.025
Cheng L, Zhuang H, Yang S, et al. Exposing the Causal Effect of C-Reactive Protein on the Risk of Type 2 Diabetes Mellitus: A Mendelian Randomization Study[J]. Front Genet, 2018,9:657. https://doi.org/10.3389/fgene.2018.00657
RUAN X N. Association between C-reactive protein and the risk of diabetes[J]. Chinese Journal of Diabetes Mellitus, 2017, 9(2): 106-111.
Yu Q, Du CJ, Du EY, et al. The Variation and Prediction of Life Expectancy in China Based on the Comparison of Yearbook Data[J]. Chinese Journal of Health Statistics, 2019,36(06):814-817.
Statistical Bulletin on National Economic and Social Development of the People's Republic of China for 2021[J]. China Statistics, 2022(03):9-26.
Wu Jielong.The health economic evaluation of "co-management of doctors of three kinds" of diabetes patients in Xiamen [D]. Xiamen University,2018.
Wang J M, Liu Q P, Zhang M L, et al. [Effectiveness of different screening strategies for type 2 diabete on preventing cardiovascular diseases in a community-based Chinese population using a decision-analytic Markov model] [J]. Beijing Da Xue Xue Bao Yi Xue Ban, 2022,54(3):450-457. https://doi.org/10.19723/j.issn.1671-167X.2022.03.009
Xie X, Vondeling H. Cost-utility analysis of intensive blood glucose control with metformin versus usual care in overweight type 2 diabetes mellitus patients in Beijing, P.R. China[J]. Value Health, 2008,11 Suppl 1: S23-S32. https://doi.org/10.1111/j.1524-4733. 2008. 00363.x
Chao J, Zong M, Xu H, et al. The long-term effect of community-based health management on the elderly with type 2 diabetes by the Markov modeling[J]. Arch Gerontol Geriatr, 2014,59(2):353-359. https://doi.org/10.1016/j.archger.2014.05.006
Xing-bao C, Ling T, Hui-yun C. Assessing the impact of complications on the costs of Type 2 diabetes in urban China[J]. Chinese Journal of Diabetes, 2003, 11(4): 238-241.
China Statistical Yearbook 2020[J]. Statistical Theory and Practice, 2021(01):2.
Zhejiang Provincial Medical Insurance Bureau. Retrieved December 29, 2022 ,from: http://ybj.zj.gov.cn/.
Ogurtsova K, Da R F J, Huang Y, et al. IDF Diabetes Atlas: Global estimates for the prevalence of diabetes for 2015 and 2040[J]. Diabetes Res Clin Pract, 2017,128:40-50. https://doi.org/10.1016/j.diabres.2017.03.024
Campisi J, Kapahi P, Lithgow G J, et al. From discoveries in ageing research to therapeutics for healthy ageing[J]. Nature, 2019,571(7764):183-192. https://doi.org/ 10.1038/s41586-019-1365-2
Lyth J, Svennberg E, Bernfort L, et al. Cost-effectiveness of population screening for atrial fibrillation: the STROKESTOP study[J]. Eur Heart J, 2022. https://doi.org/10.1093/eurheartj/ehac547

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

Economic feasibility analysis of using serum C-reactive protein as a screening tool for high-risk people with diabetes complications in the community: an empirical analysis using CHARLS data

Status:

Version 1

Abstract

Figures

1. Introduction

2. Methods

3. Results

4. Discussion

5. Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1