Cost-effectiveness analysis of multiple gastric cancer screening strategies in Northwest China based on a population program: a Markov modeling study

doi:10.21203/rs.3.rs-2081719/v1

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Cost-effectiveness analysis of multiple gastric cancer screening strategies in Northwest China based on a population program: a Markov modeling study

https://doi.org/10.21203/rs.3.rs-2081719/v1

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Background

Gastric cancer remains a significant global health problem and poses heavy public health and economic burdens on the health system. This study aimed to compare cost-effectiveness among multiple gastric cancer screening strategies and identify the most cost-effective one in Northwest China based on a population-based cohort study using a Markov model.

Methods

Based on the real-world data, a Markov model was developed to evaluate the cost-effectiveness of 21 screening strategies with various screening methods, starting ages, stopping ages, and screening intervals versus no screening for a high-risk gastric cancer population in China. The primary outcomes were quality-adjusted life-years (QALY), costs, effectiveness, and the incremental cost-effectiveness ratio (ICER). One-way and probabilistic sensitivity analyses explored uncertainty.

Results

Our baseline model of annual endoscopic screening for individuals aged 40 to 75 years was the cost-effective strategy, with an ICER of US$ 545.79/QALY compared with no screening. In the scenario analysis, only the H. pylori screen-and-treat from 20 years strategy was non-dominated, with an ICER of US$ 157.41/QALY, and all other systems were dominated (providing less benefit but higher cost). Using the US$ 15,000 per QALY, all selected screening strategies for gastric cancer were cost-effective in the high-risk region of Northwest China. One-way and probabilistic sensitivity analyses demonstrated that the results are robust.

Conclusions

This modelling study provides evidence for the cost-effectiveness of an endoscopic screening program for gastric cancer in the high-risk region of China. Primary prevention appears more cost-effective than secondary prevention strategies. If primary prevention is not an option, secondary prevention strategies should be considered. All selected screening strategies seem to be cost-effective in the high-incidence area of Northwest China.

gastric cancer

screening

cost-effectiveness

Helicobacter pylori antibody

Gastric cancer remained a significant global health problem and was responsible for over one million new cases in 2018 and an estimated 783,000 deaths, making it the fifth most frequently diagnosed cancer and the third leading cause of cancer death [1, 2]. The incidence and mortality rates of gastric cancer in China were 2–3 times above the world average [3]. Due to the lack of a standardized screening system, most GC patients were found in the advanced stages, and the diagnosis and treatment rate of early gastric cancer (EGC) in China was only 14%-21% [4, 5]. Therefore, it is critical to screen and diagnose the disease at an early stage for a radical cure to be possible. However, there is a big gap between urban and rural medical services in China, and there are geographical differences in cancer survival and incidence rate [6]. Selecting a suitable screening strategy according to the local population characteristics is an important measurement to improve the early diagnosis and treatment rate of gastric cancer in China.

Both primary and secondary prevention strategies for gastric cancer minimize cancer incidence and mortality rates [7]. Helicobacter pylori (H.pylori) is regarded as a Group I carcinogen and trigger of the gastric cancer cascade. The screening and eradication of H. pylori infection have been suggested as the primary prevention strategy for gastric cancer [8, 9]. Upper endoscopy and serological testing screening are the main secondary prevention strategies that can be adopted. Gastroscopy, in combination with gastric mucosa biopsies, is regarded as the gold standard model for diagnosing gastric cancer [10]. The currently available noninvasive serological screening tests commonly used to identify the high-risk group of gastric cancer patients are serum pepsinogen (PG) screening and a combination of serum PG and H. pylori IgG antibody (HPA) screening, named the ABC method [11]. However, until now, which gastric cancer screening strategy is the most cost-effective and should be adopted in China, especially in high-risk regions like the Northwest, remains ambiguous.

In 2013, with support from China’s National Science and Technology Program for Public Wellbeing, a large-scale endoscopic screening project for gastric cancer in the general population in the Wuwei region in China, where the gastric cancer incidence and mortality rates were very high, “Wuwei Cohort” was conducted [12]). The endoscopic screening was performed on 21,345 subjects. Among them, the majority also tested for H. pylori infection with the ¹⁴C urea breath test (UBT), and a small subset also tested for PG and H. pylori serological antibodies. These provided the base-case data for the cost-effectiveness analysis and offered a unique opportunity to compare the long-term cost-effectiveness of these strategies in the same population. The main aims of this study were to use the Markov model: a) to evaluate the cost-effectiveness of the endoscopic screening program applied in Wuwei, China; and b) to test the hypothesis of whether screening and treating H. pylori infection would be a better alternative in high-incidence areas in China.

Wuwei cohort and participants

Wuwei, a prefecture-level city located in the eastern region of the Hexi Corridor in Gansu Province, is considered an ideal high-incidence region site for conducting a population-based cohort study for gastric cancer [13]. According to the Wuwei Cohort, 25,000 native residents aged from 35 to 70 years were selected using a cluster sampling method. The final count for gastroscopies performed on these participants was 21,345, and the compliance rate to endoscopy was 85.4%. In addition to gastroscopy, 21,291 participants were tested for H. pylori with UBT, and 9,396 were tested for serum PGⅠ, PGⅡ and HPA using an automated biochemical analyzer (Fig. 1).

Almost 53.0% of the participants were H. pylori-positive as detected by ¹⁴C-UBT, 60.3% were H. pylori IgG positive, and 27.67% were PG-, positive. Individuals who tested positive for the H. pylori infection (including both true and false positive) would recommend receiving standard 14-day bismuth quadruple therapy (20 mg omeprazole, 1 g amoxicillin, 500 mg clarithromycin, twice daily), which was recommended by the Chinese H. pylori guidelines and the Maastricht V conference report. Through 21,345 cases of gastroscopic examinations, 167 GC cases were confirmed by pathological diagnosis, with 103 cases of early gastric cancer and 64 cases of advanced gastric cancer, indicating an overall gastric cancer detection rate of 0.8% and an early GC proportion of 61.7%. Additional details and baseline data of this cohort study are available in Ji et al. [13]. Data characteristics of multiple gastric cancer screening strategies are summarized in Supplementary Table S1. The Ethics Committee of The First Hospital of Lanzhou University approved this study (approval number: LDYYLL2012001).

Markov Model

The Markov model is a process that models random events that occur over time and has been increasingly applied to areas in health economic research in recent years, such as screening for disease, decision analysis of clinical interventions, pharmacoeconomic evaluation, and so on [14, 15]. The principle is to divide the natural course of the disease into several different health states (Markov state) and to stimulate the development of the disease according to the transition probability of each state in a certain period (Markov cycle). This information is combined with each state's health utility values and the public health resource consumption to estimate the outcome and the cost of disease progression through multiple iterations [16].

We synthesized information from regionally representative data sets on demographics, gastric cancer incidence, mortality, survival rate and the Wuwei Cohort database (Table 1). Using these data, we developed a Markov decision model using TreeAge Pro Healthcare 2020 (Tree Age Software, Williamstown, WA, USA) to inform long-term outcomes of 22 strategies with various screening methods, different screening intervals at different starting and stopping ages of gastric cancer, which was representative of the population of Northwest China, a region of high incidence. The natural history of disease progression was simulated based on Correa’s cascade [17] of gastric carcinogenesis of intestinal-type non-cardia gastric adenocarcinoma (NCGA), the primary histologic type of gastric cancer (Fig. 2). As a simulated individual ages, precancerous lesions (atrophy gastritis, intestinal metaplasia, or dysplasia) may develop. Preclinical cancer may either become symptomatic, be detected by screening, or progress to a more advanced preclinical cancerous stage. A healthy individual can transition to atrophy gastritis or remain stay in a normal state. Patients at state atrophy gastritis can progress to intestinal metaplasia, dysplasia, early gastric cancer (EGC) and advanced gastric cancer (AGC) in turn. Patients also can regress to less advanced precancerous lesions before dysplasia develops.

Model assumptions

To simplify the case study, several fundamental assumptions made in this research are: a) the healthy asymptomatic individuals with or without H. pylori infection were in perfect health, with the health-state utility of 1 [9]; b) a Markov process did not reverse the severe state of dysplasia [17, 18]; c) the ABC method plus endoscopy screening was allocated to four Groups (A-D) with different risks of gastric cancer ([19] and the periodic endoscopic examination should be taken for patients in Group B, C, and D at the interval of 3, 2, and 1 year, respectively, except for Group A due to their low-level risk of developing gastric cancer [20]; d) all suspected cases proceeded to biopsy, and all diagnosed cases received treatment; e) all individuals with primary and secondary prevention strategies were undergo screening; f) all individuals could die from causes other than gastric cancer during disease progression, but only patients at state AGC could die from gastric cancer.

Modelling strategies

As gastric cancer is commonly seen in an old population, we used an annual endoscopic screening frequency from 40 to 75 years as the baseline. We also explored 20 other scenarios compared with no screening, in addition to seven strategies with endoscopic screening varying starting ages (40 and 50 years), screening intervals (1, 2, and 3 years) and stopping periods (75 and 80 years). We also evaluated three strategies with H. pylori screen-and-treat varying starting ages (20, 30, and 40 years) and with the same stopping ages of 80 years; seven techniques with the serum PG method varying starting ages (40 and 50 years), screening intervals (1, 2, and 3 years) and stopping periods (75 and 80 years); and four strategies with the serum ABC method varying starting ages (40 and 50 years) and stopping ages (75 and 80 years).

Input parameters

The epidemiologic parameters, state-transition probabilities, health-state utility, and treatment cost used in the model are listed in Table 1. We obtained the age-specific gastric cancer incidence from Chinese literature about the 2012 cancer incidence analysis of Wuwei Municipality, Gansu Province, China [21]. We employed H. pylori prevalence according to an all-age population-based cross-sectional study in the Wuwei region [22]. The initial distributions of the cost-effectiveness analysis in different Markov states were determined from the Wuwei Cohort epidemiologic database (Supplementary Table S2). We calculated age-specific mortalities from other causes by subtracting age-specific GC mortality rates from the corresponding age-specific all-cause mortality rates of rural residents in 2019 from the China Health Statistics Yearbook 2020 [23].

Table 1

Key input model parameters included in our study
Parameters	Baseline	Range	Distribution	References
Clinical and epidemiologic variables
Age at screening initiation (years old) (PG/ABC/Endoscopy)	40, 50	40–70	Uniform	Assumption
Age at screening initiation (years old) (H. pylori screening)	20, 30, 40	20–60	Uniform	Assumption
Age-specific all-cause mortality (per 100,000)	37.72-7668.76^a	Fixed	Fixed	[23]
Age-specific incidence of gastric cancer (per 100,000)	6.44-616.30^a	Fixed	Fixed	[21]
Age-specific mortality due to gastric cancer (per 100,000)	0.29-175.33^a	Fixed	Fixed	[23]
Age-specific prevalence rates of H. pylori (%)
20-	36.4	Fixed	Fixed	[22]
30-	50.3	Fixed	Fixed	[22]
40-	56.3	Fixed	Fixed	[22]
Annual H. pylori infection rate (%)	1	0.25-4	Beta	[41]
Annual H. pylori reinfection rate after eradicated (%)	1	0.6–1.4	Beta	([38]
Eradication rate of bismuth quadruple therapy (%)	85.51	74.71–96.41	Beta	([44]
Relative risk of gastric cancer development with H pylori infection	2.36	1.98–2.81	Lognormal	[45]
Relative risk of gastric cancer development with H pylori eradication	0.66	0.46–0.95	Lognormal	[46]
Serum pepsinogen positive rate (%)	27.67	Fixed	Fixed	[47]
Transition probabilities of disease progression
Normal to atrophy gastritis	0.017	Fixed	Fixed	[25, 48]
Atrophy gastritis to intestinal metaplasia	0.079	Fixed	Fixed	([25, 48]
Intestinal metaplasia to dysplasia	0.040	Fixed	Fixed	[48]
Dysplasia to early gastric cancer	0.380	Fixed	Fixed	[48]
Early gastric cancer to advanced gastric cancer	0.429	Fixed	Fixed	[25]
Advanced gastric cancer to death	0.214	Fixed	Fixed	[49]
Transition probabilities of disease regression
Atrophy gastritis to normal	0.016	Fixed	Fixed	[48]
Intestinal metaplasia to atrophy gastritis	0.037	Fixed	Fixed	[48]
Quality of life utility
Health	1	Fixed	Fixed	Assumption
Gastric precancerous lesion (AG, IM, dysplasia)	0.90	0.77–0.90	Beta	[50] Wuwei Cohort
Early gastric cancer	0.87	0.63–0.92	Beta	[50] Wuwei Cohort
Advanced gastric cancer	0.83	0.55–0.83	Beta	[50] Wuwei Cohort
Death	0	Fixed	Fixed	Assumption
Costs (US dollars)
Screening cost
Endoscopic screening with biopsy	100	90–160	Gamma	[24] Wuwei Cohort
H pylori screening test (UBT)	15	12.04–40.14	Gamma	[26] Wuwei Cohort
PG test	15	12–40	Gamma	[26]) Wuwei Cohort
PG and HPA test	30	14–42	Gamma	[24] Wuwei Cohort
Treatment cost
H pylori eradication treatment	28.27	9.78–59.23	Gamma	[9]
Endoscopic submucosal dissection	3,700	1400-23,570	Gamma	[26, 51]
Surgery	7,692	4069-18,578	Gamma	[52]
Chemotherapy treatment for advanced gastric cancer totally	5,256	3169-9,728	Gamma	[52]
Palliative care for annual cost of illness	4,331	2587-10,770	Gamma	[52]
Discount rate (%)	3			[29]

Notes: ^a Values were age-specific from age of 20 to age of 80+; PG, pepsinogen; ABC, a combination of serum PG and H. pylori IgG antibody (HPA); H. pylori, Helicobacter pylori; the cutoff of ABC method, PG I ≤ 60 ng/ml, and PG I/II ratio of ≤ 3.0; AG, atrophy gastritis; IM, intestinal metaplasia.

Transition Probabilities

The transition probability (p) of an event occurring over a specific time interval (t) was calculated using an incidence rate (r) (p = 1-exp(-rt)) [24]. Regarding the progression rates between different Markov states and the relative death risk of AGC, we obtained data from the studies whose data were derived from a community-based screening program for gastric cancer in the Matzu region of Taiwan also has a very high incidence rate of GC [25, 26] and assumed that the parameters applied to Northwest China.

Costs

Cost data directly or indirectly related to gastric cancer screening were collected from the project audit information, the internal accounts of hospital screening units, and published studies. The cost data of the other expenditures for different stage gastric cancer treatments were obtained from the hospital information system of local hospitals.

Utilities

The generic health status and health-related quality of life (HRQoL) were expressed by health utility weights (HUWs). HUWs are valued between 0 and 1 according to how individuals perceive or her health status. Quality-adjusted life-years (QALY), which reflects both length of life and health-related quality of life, was calculated as the product of the utility score of a particular state of health, defined as a dimensionless number between 1 (perfect health) and 0 (death), and the number of years lived [27]. We identified the utility scores for patients from a cross-sectional study also carried out in Wuwei region as part of the screening program, in which before patients underwent upper endoscopy (n = 1908) using the EQ-5D-5L quality of life questionnaire. The main patient characteristics and utilities according to stages of the gastric cancer cascade are summarized in Supplementary Table S3. To calculate QALYs, we assumed that healthy asymptomatic individuals were in perfect health, with a health-state utility of 1.

Other parameters

Willingness To Pay (WTP)

In a developing country, the maximum price of one year of a healthy life is around threefold the annual earning per capital [28]. The gross domestic product (GDP) per capita in Gansu, China in 2018 was US$ 5,000. The maximum WTP for a QALY gained in this study of about US 15,000 was estimated based on the above approach.

Cost-effectiveness analysis

In agreement with the China Guidelines for Pharmacoeconomic Evaluations, we discounted all costs and clinical consequences by 3% annually [29]. For the cost-effectiveness analysis, all results were scaled to 10 million individuals. To evaluate the relative performance of each strategy, we estimated the lifetime costs of screening and its effects in terms of QALY. We calculated the incremental cost-effectiveness ratios (ICERs), defined as the additional cost of a specific strategy divided by its additional clinical benefit, compared with no screening strategy, and expressed as cost per QALY. A strategy was dominated if it was more costly but yielded fewer QALYs than its adjacent strategy or had a higher ICER than a more effective strategy. All costs are reported in 2018 US dollars (1 U.S.$=6.7 RMB). An ICER of less than US$ 15,000/QALY is therefore an indication that the screening strategy for high-risk Chinese, compared with no screening, is cost-effective.

Sensitivity analyses

We conducted one-way and probabilistic sensitivity analyses to explore the effect of parameter uncertainty [30–32]. In the one-way sensitivity analyses, we used the minimum and maximum estimates for all key parameters, testing the influence of extreme variations in each parameter on the overall results. We varied each parameter individually to assess its impact on overall results. Probabilistic sensitivity analyses were done with a Monte Carlo simulation to investigate the effect of parameter uncertainty on the cost-effectiveness results. The input variables were specified as distributions: costs have a gamma distribution, and utility values follow lognormal distributions, as suggested in the literature [33]. we performed 1000 second-order Monte Carlo simulations to explore the influence of uncertainty on those key parameters. In addition, we generated cost-effectiveness acceptability curves for all competing strategies. The definition of cost-effectiveness acceptability curves was the probability that a strategy was most cost-effective among all alternatives given a wide range of WTP thresholds.

Base-case analysis

The Markov model simulated the gastric cancer primarily and secondary prevention strategies and the no-screening strategy and all selected strategies were compared against no screening. Table 2 reports the discounted lifetime costs, QALYs gained and ICERs. Overall, compared with no GC screening, the baseline model of annual endoscopy screening from 40 to 75 years yielded higher QALYs compared with no screening (55.55 QALYs versus 0 QALYs), but was more expensive than no screening (US$ 30317.21 versus US$ 2357.83 per individual). The baseline discounted ICER was US$ 545.79/QALY, far below the US$ 15,000/QALY threshold, indicating that the endoscopic gastric cancer screening program is cost-effective.

Table 2

Estimated cost-effectiveness ratios of gastric cancer screening strategies
Strategy	Lifetime costs percase, US$	Incremental cost, US$	Effectiveness QALYs	Incremental effectiveness (QALYs)	ICER (US$/QALY)
Baseline analysis
No screen	2357.83	-	-	-	-
Annual endoscopic screening from 40y to 75y	30317.21	27959.38	55.55	55.55	545.79
Alterative screening strategies versus no screening
Screening once only
Hp screen-and-treat screening from 20y	17307.17	14949.34	109.95	109.95	157.41
Hp screen-and-treat screening from 30y	17384.80	15026.97	91.36	91.36	190.30
Hp screen-and-treat screening from 40y	15874.61	13516.78	73.29	73.29	216.61
Annually screening
PG with endoscopic screening (40- 80y)	12297.80	9939.97	18.07	18.07	680.75
PG with endoscopic screening (40- 75y)	11169.19	8811.36	16.10	16.10	693.61
PG with endoscopic screening (50-80y)	10398.76	8040.94	13.06	13.06	796.31
Endoscopic screening (40-80y)	33163.42	30805.59	62.67	62.67	529.22
Endoscopic screening (50-80y)	29040.20	26682.37	47.40	47.40	612.71
ABC with endoscopic screening (40-75y)	17274.41	14916.58	61.93	61.93	278.92
ABC with endoscopic screening (40-80y)	18341.84	15984.01	66.76	66.76	274.75
ABC with endoscopic screening (50-75y)	13560.54	11202.71	41.71	41.71	325.10
ABC with endoscopic screening (50-80y)	15582.67	13224.84	51.24	51.24	304.08
Biennial screening
PG with endoscopic screening (50-80y)	14609.68	12251.85	12.45	12.45	1173.73
PG with endoscopic screening (40-80y)	16781.98	14424.15	14.86	14.86	1129.11
Endoscopic screening (40-80y)	52566.68	50208.85	51.93	51.93	1012.34
Endoscopic screening (50-80y)	46753.11	44395.28	40.11	40.11	1165.68
Triennial screening
PG with endoscopic screening (40-80y)	14530.53	12172.70	13.51	13.51	1075.61
PG with endoscopic screening (50-80y)	13212.40	10854.57	10.02	10.02	1319.14
Endoscopic screening (40-80y)	57719.87	55362.05	47.82	47.82	1207.13
Endoscopic screening (50-80y)	52012.01	49654.18	37.88	37.88	1373.20

Notes: Hp, Helicobacter pylori; PG, pepsinogen; ABC, a combination of serum PG and H. pylori IgG antibody (HPA); ICER, incremental cost-effectiveness ratio; QALY, quality-adjusted life year; US$, United States dollar; Cost and QALY were discounted at 3% per year.

In the scenario analysis, we computed ICERs for all screening strategies. We presented the cost-effectiveness frontier in Fig. 3. This frontier was comprised of an H. pylori screen-and-treat strategy from 20 years once only versus no screening. Among all selected screening strategies, only the H. pylori screen-and-treat from 20 years strategy was non-dominated, with an ICER of US$ 157.41/QALY, and all other systems were dominated. The ABC method, regardless of the starting ages of 40 or 50 years and the stopping ages of 75 years to 80 years, yielded higher ICERs (US$ 274.75–325.10/QALY) than the serum PG method or endoscopic screening. All selected gastric cancer screening strategies were cost-effective using a WTP threshold of US$ 15,000 per QALY.

Sensitivity analysis

The one-way sensitivity analysis (Fig. 4) indicated that cost, transition probabilities and utility scores have little individual influence on the cost-effectiveness of the baseline program. We found the ICERs lower than the threshold at both these variables’ upper and lower limits. The results of the probabilistic sensitivity analysis (Fig. 5A) show that at the point of US$ 15,000/QALY, nearly 100% of the simulations indicated that the endoscopic gastric cancer screening program is cost-effective compared with no screening, and the H. pylori screen-and-treat from 20 years strategy was the most cost-effective strategy in 100% of simulations using a WTP threshold of US$ 15,000 per QALY (Fig. 5B).

Massive population-based endoscopic gastric cancer screening was performed in Wuwei Municipality, Gansu Province, China, in 2013. This screening program identified patients with early upper digestive tract cancers who underwent treatment modalities. Our cost-effectiveness analysis indicates that the endoscopic gastric cancer screening program in high-risk regions is cost-effective compared to no screening. We developed a well-calibrated and validated Markov model to simulate a high-risk population under 22 unique screening scenarios. Comprehensive modeling showed that the once-only H. pylori screen-and-treat strategy at the age of 20 years was the most cost-effective strategy for preventing gastric cancer. Primary prevention appears more cost-effective than secondary prevention strategies. In secondary prevention strategies, the ABC method screening is less expensive and more effective than the PG method or endoscopic screening strategies. The results were robust in the sensitivity analysis when we varied the estimates for costs, transition probabilities and utility scores.

Two recent systematic analyses have confirmed the cost-effectiveness of an H. pylori screen-and-treat strategy in preventing gastric cancer, even in areas with low incidences of gastric cancer [34]. From our study, an H. pylori screen-and-treat strategy from 20 years old seems more cost-effective than the screening strategies from 30 or 40 years old. This finding is consistent with some previous studies [26, 35]. Some studies have noticed that severe chronic atrophic gastritis and intestinal metaplasia may be irreversible gastric mucosal changes regardless of whether H. pylori is eradicated [34]. The biological plausibility is upheld by the concept of ‘‘a point of no return,’’ which may account for why the benefit of H. pylori eradication diminishes at the advanced stage when many irreversible molecular changes have developed (24). Therefore, it is essential to eliminate H. pylori infection before irreversible changes occur.

At present, the most commonly used strategy for serologic testing are serum PG and ABC method screening [36]. Both the PG and ABC method has been confirmed by many prospective studies to be effective and convenient risk stratification strategies for gastric cancer [37, 38]. The ABC method involves classifications that are based on serum HPA and serum PG levels: Group A [HPA (-) PG (-)], noninfected cases; Group B [HPA (+) PG (-)], free or mild chronic atrophic gastritis (CAG) with active or acute H. pylori infection; Group C [HPA (+) PG (+)], CAG with chronic inactive H. pylori infection; and Group D [HPA (-) PG (+)], severe CAG with extensive IM and spontaneous diminishment of H. pylori infection [19, 20, 39]. It is generally believed that the risk of gastric cancer is highest in group D, followed by groups C, B, and A, in descending order [40].

Serum levels of PG I and II reflect the functional and morphologic status of the gastric mucosa, and measuring serum PG levels can be used to identify subjects with extensive atrophic gastritis which are at high risk for gastric cancer [41]. The optimal PG cutoff value for atrophic gastritis remains controversial. A serum PG I value of ≤ 70 ng/ml and a serum PG I/II ratio of ≤ 3.0 is defined as the criteria for atrophy in Japan and are currently widely accepted ([42]. However, some studies have disagreed because these criteria are based on endoscopy diagnostic data for only atrophic gastritis and not on histological information. In fact, the best PG cutoff value for gastric atrophy may be higher based on histological examination because the cytological changes of minor gastric atrophy appear before the morphological changes of stomach mucosa endoscopically [43]. In this study, we found that the sensitivity and specificity of the PG method for screening atrophic gastritis obtained from a Chinese study [10] (PG I ≤ 60 ng/ml, and PG I/II ratio of ≤ 3.0) were higher than those calculated from the Japanese cutoff (Supplementary Table S4, S5). Therefore, we used PG cutoff values from China to calculate the ABC method. Several prospective studies have confirmed that the ABC method is an effective and convenient risk stratification pattern for gastric cancer. Our model demonstrated that the ABC method is the most cost-effective in secondary prevention strategies.

This study has several notable strengths and highlights several important policy implications. Firstly, this was the first study to compare the cost-effectiveness of multiple screening strategies for gastric cancer in the same population using a Markov modeling approach based on the Wuwei Cohort database in the northwest area of China. Secondly, our findings revealed that annual endoscopic screening is the most cost-effective screening frequency compared with screening every 2 years or every three years. However, the latter frequencies decrease total costs significantly, they do not improve the effectiveness significantly. Thirdly, in this analysis, screening strategies initiated regardless of the ABC method or endoscopic technology at 40 years of age were more cost-effective than those initiated at 50 years of age and provided a more favorable option in terms of cost-effectiveness. The incidence of GC increased significantly after the age of 40 years and gradually decreased after reaching the peak value. Together with the burden of disease, screening effectiveness and modeling results, these results indicated that initiating screening at the age of 40 years would be a reasonable option in high-risk regions of China. Lastly, the results of this study indicated that early eradication of H. pylori appeared to be the most cost-effective approach. There have been many cost-effectiveness analyses addressing this topic and the results of this study confirmed previous simulations. Nonetheless, only some of the literature was based on the established population-based program; this study was of importance on the public health policy-making for this high-risk population.

Our study also has some limitations. First, the costs of clinical screening and treatment in this study are derived from the cost accounting of the screening program and hospital information system; other implementation costs, such as the administration of equipment and other ancillary costs, were not included. This may lead to an underestimation of costs and, subsequently, cost-effectiveness. Second, for progression rates between different stages, we used data from other region and assumed that the parameters were applicable to Northwest China. These factors require careful consideration, and further research should be conducted to reduce uncertainty. Last, we used one time GDP per capita as the WTP threshold in our cost-effectiveness analysis. However, GDP-based cost-effectiveness ratios, or other estimates of WTP, do not provide information on affordability, budget impact or the feasibility of implementation. The local policy context must also be considered, and WTP thresholds should not be used alone.

In conclusion, this modeling study provides evidence for the cost-effectiveness of endoscopic screening program for gastric cancer in a high-risk region of China. Primary prevention appears more cost-effective than secondary prevention strategies. If primary prevention is not an option, then secondary prevention strategies should be considered and all selected screening strategies seem to be cost-effective in high-incidence area of Northwest China.

Acknowledgments

The authors are grateful to all the study participants and staff from the collaborating hospitals. We thank the Department of Epidemiology and Statistics, School of Public Health, Lanzhou University.

Authors’ contributions

Rong Liu and Lingshan Zhou contributed equally to this work. Rong Liu and Lingshan Zhou have full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Rong Liu, Ya Zheng, Xiaobin Hu and Yongning Zhou conceived the study. Rong Liu, Lingshan Zhou and Ya Zheng developed, calibrated, and validated the model. Rong Liu, Lingshan Zhou, Peng Nie and Youfa Wang ran simulations, per-formed the analysis, and wrote the manuscript. Yuping Wang, Quanling Guan, Rui Ji, Qinghong Guo, Zhaofeng Chen, Zhiyi Zhang, Zhengqi Wu, Ping Fan, Xiangyi Zan and Linzhi Lu revised the manuscript critically for important intellectual content. All authors approved the final version before submission.

Funding

This work was supported by the National Natural Science Foundation of China [71964021], the National Natural Science Foundations of Gansu Province [18JR3RA336 and 21JR7RA372].

Availability of data and materials

Not applicable

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable

Competing interests

All authors declare no competing interests.

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Cost-effectiveness analysis of multiple gastric cancer screening strategies in Northwest China based on a population program: a Markov modeling study

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Introduction

Methods

Wuwei cohort and participants

Markov Model

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Modelling strategies

Input parameters

Transition Probabilities

Costs

Utilities

Other parameters

Willingness To Pay (WTP)

Cost-effectiveness analysis

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Base-case analysis

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