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Abstract

Objective

In this study, we aimed to perform a comprehensive analysis to assess the prognostic value of neutrophil-to-lymphocyte ratio (NLR) levels in patients diagnosed with thyroid cancer.

Methods

We systematically searched multiple databases, including PubMed, the Cochrane Library, EMBASE, and Google Scholar, up until March 30, 2023, to identify relevant articles. The clinical outcomes evaluated in this study included overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), and cause-specific survival (CSS).

Results

This analysis includes 21 articles with 5187 patients in total. The pooled results revealed that patients with high NLR levels had significantly poorer OS (HR: 2.578, 95% CI: 2.050-3.242, P < 0.001), PFS (HR: 2.143, 95% CI: 1.616-2.843, P < 0.001), DFS (HR: 1.377, 95% CI: 1.045-1.816, P = 0.023), and CSS (HR: 2.842, 95% CI: 1.334-6.053, P = 0.007). The subgroup analyses were performed based on different study regions, treatment modalities, cancer types, and NLR cut-off values, and the above conclusion remained consistent in the majority of subgroup analyses. The stability and reliability of the aforementioned results were supported by the sensitivity analysis and publication bias test.

Conclusion

The baseline NLR levels were useful predictors of outcomes in patients with thyroid cancer.

Keywords

neutrophil-to-lymphocyte ratio thyroid cancer prognosis surgery sorafenib lenvatinib

Introduction

Thyroid cancer (TC) is the most prevalent endocrine malignancy globally.¹ GLOBOCAN 2020 data indicates that it ranked eighth among all malignancies diagnosed worldwide in 2020, with a lower death rate than other malignancies (43 646 deaths in 586 202 new cases diagnosed in all ages and genders).¹ The incidence of thyroid cancer increased from 3.6 cases per 100 000 people in 1973 to 8.7 cases per 100 000 people in 2002, which resulted in a 2.4-fold increase in the number of diagnosed cases each year.² This increase was primarily due to an increase in papillary thyroid cancer (PTC).³ Although the incidence of tumors of approximately 2-4 cm in diameter remained stable, the increase in diagnosis was likely due to the more frequent detection of subclinical tumors using medical imaging.⁴ Nonetheless, rates for larger TC with regional and distant spread are also on the rise.⁵ Consequently, TC mortality has increased by 1.1% each year from 1994 to 2013.⁶

Systemic hematological indicators may be able to predict worse outcomes in several cancers, according to numerous studies.^7,8 The baseline neutrophil-to-lymphocyte ratio (NLR), which represents the proportion of neutrophil and lymphocyte counts in the peripheral circulation, deserves special attention. As an inflammation marker, an elevated NLR has been linked to poor outcomes in numerous cancers, including the breast, colon, and liver.^7,9-11

As for thyroid cancer, many studies have investigated the association between NLR levels and patient prognosis; however, the differences derived from different studies are large. This study sought to establish a systematic understanding of the relationship between NLR and patient outcomes, and the results of this research could be used to evaluate prognosis and create efficient treatment plans.

Methods

Literature Search Strategies

The current investigation adhered to the PRISMA statement¹² and was registered in PROSPERO (CRD42024595510). On March 30, 2023, an exhaustive exploration of literature sources was conducted via PubMed, EMBASE, and the Cochrane Library. The search inquiry included terms such as “neutrophil to lymphocyte ratio”, “neutrophil-to-lymphocyte ratio”, “neutrophil-lymphocyte ratio”, “neutrophil/lymphocyte ratio”, “NLR”, “thyroid neoplasms [Mesh]”, “thyroid adenomas”, “thyroid cancer”, and “thyroid carcinomas”. Moreover, Google Scholar was consulted for grey literature, and the reference lists of eligible publications were manually retrieved. Further details of the search strategies are presented in Supplemental Material 1.

Inclusion and Exclusion Criteria

We limited our investigation to research articles that met the following criteria: patients diagnosed with TC and evaluations of the predictive capability of NLR. Additionally, the articles had to report at least 1 of the following outcomes: overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), or cause-specific survival (CSS). Case studies, conference abstracts, and comments were not included. We only chose the articles with the most thorough information and rigorous methods where trials showed overlapping patient populations.¹³

Data Extraction and Quality Assessment

We collected a range of data points, encompassing author, publication year, study region, study design, study period, sample size, age, gender distribution, treatment, cancer types, the cut-off of NLR, and outcomes. Whenever possible, we gave priority to extracting multivariate analyses of HR over univariate analyses.¹⁴ The quality of observational studies was assessed using the Newcastle-Ottawa Scale (NOS) score, and we regarded literature with a score of 6 or higher as high-quality.¹⁵

Statistical Methods

Stata 15.0 was used for the statistical analysis. Using the chi-squared test, statistical heterogeneity was assessed. A random effect model was utilized when P < 0.1 and I² > 50%; otherwise, a fixed effect model was used. Publication bias was evaluated through the Egger and Begg tests. To evaluate the potential impact of publication bias on the pooled results, we employed the trim-and-fill method. Furthermore, a sensitivity analysis was conducted by independently excluding each study to evaluate the robustness of the findings.

Results

Characteristics of Studies

After the initial search, 88 studies that were found to be duplicates were excluded. Following that, a thorough examination of the titles and abstracts resulted in the removal of 358 articles. The remaining 37 articles were then scrutinized for their full texts. Ultimately, we selected 21 articles^16-36 that included a total of 5187 patients for analysis. Figure 1 displays the PRISMA flow diagram, which outlines the selection process. Table 1 summarizes the primary characteristics of the included studies. The NOS scores of all articles ranged from 6 to 8, indicating a low risk of bias.

Figure 1.

The flow diagram of identifying eligible studies.

Table 1.

Main Characteristics of the Studies Included.

Study	Study Region	Study Design	Study Period	Sample Size	Male/Female	Age (Years)	Treatment	Cancer Types	Cut-Off	Out Comes	NOS Score
Jin et al 2023¹⁶	Korea	R	-	70	22/48	65.2 (57-73)^a	Sorafenib	RR-TC	2.2	OS, PFS	7
Treistman et al 2023¹⁵	Brazil	R	09/1993-01/2021	172	55/117	61.5 (24-85)^b	RAI	RR-DTC	3	OS, CSS	8
Huang et al 2022¹⁷	China	R	08/2017-01/2021	382	81/301	46.64 ± 13.70^c	Surgery	PTC	2.70	DFS	8
Fukuda et al 2022¹⁸	Japan	R	01/2012-04/2021	59	22/37	68 (22-83)^b	Lenvatinib	RR-DTC	3.00	OS, PFS	6
Oba et al 2021²⁴	Japan	R	2002-2012	28	15/13	20/8^d	Surgery	PDTC	2.88	OS, CSS	6
Offi et al 2021²³	Italy	R	03/2012-12/2019	116	17/99	36/80^d	Surgery	DTC	-	DFS	7
Ohkuwa et al 2021²²	Japan	R	01/2000-12/2018	123	33/90	41 (4-77)^b	RAI	DTC	2.60	CSS	7
Ito et al, 2021 (1)²⁶	Japan	R	03/2005-07/2019	312	-	241/71^d	RAI	DTC	3.00	CSS	7
Ito et al, 2021 (2)²⁵	Japan	R	06/2014-07/2020	21	7/14	70 (54-87)^b	Sorafenib	RR-DTC	3.00	OS, PFS	6
Ito et al, 2021 (3)²⁵	Japan	R	06/2014-07/2020	18	4/14	73 (29-81)^b	Lenvatinib	RR-DTC	3.00	OS, PFS	6
Park et al 2021²¹	Korea	R	11/1995-05/2020	40	15/25	-	Radiotherapy	ATC	3.47	OS	7
Taylor et al 2021¹⁹	Multi-center	PH	08/2011-10/2012	261	-	-	Lenvatinib	RR-DTC	3.00	OS, PFS	7
Riguetto et al 2022²⁰	Brazil	R	01/2000-01/2019	390	66/324	46.65 ± 15.41^c	Surgery	DTC	-	DFS	7
Fukuda et al 2020³⁰	Japan	R	12/2012-06/2019	13	4/9	68 (39-80)^b	Lenvatinib	ATC	8.00	OS, PFS	6
Yamazaki et al 2020²⁹	Japan	R	04/2006-08/2019	55	18/37	68.2 ± 10.30^c	Multimodal therapy	ATC	3.60	OS	7
Yokota et al 2020²⁸	Japan	R	04/2006-03/2018	570	146/424	339/231^d	Surgery	PTC	2.00	DFS	8
Zhang et al, 2020 (1)²⁷	China	R	2010-2019	101	23/78	63.98 ± 5.72^c	Surgery	DTC	2.53	OS, DFS	6
Zhang et al, 2020 (2)²⁷	China	R	2010-2019	22	6/16	58.77 ± 12.65^c	Multimodal therapy	ATC	3.19	OS	6
Lee et al, 2019 (1)³²	Korea	R	01/2008-01/2012	914	218/696	<45	Surgery	PTC	2.10	DFS	7
Lee et al, 2019 (2)³²	Korea	R	01/2008-01/2012	932	163/769	≥45	Surgery	PTC	2.10	DFS	7
Takahashi et al 2019³¹	Japan	P	09/2012-07/2015	51	21/30	61 (21 - 84)^b	Lenvatinib	RR-DTC, MTC, ATC	3	PFS	6
Jiang et al 2017³³	China	R	05/2009-09/2016	78	34/44	47.30 ± 13.80^c	Surgery	MTC	2.70	DFS	6
Lang et al 2014³⁴	China	R	01/2004-10/2012	191	40/151	47.90 ± 15.80^c	Surgery	PTC	-	DFS	7
Kim et al 2014³⁵	Korea	R	03/2005-09/2012	268	-	-	Surgery	PTC	1.50	DFS	7

^aMedians with inter-quartile range.

^bMedians with range.

^cMean ± standard deviation.

^d>55 vs <55.

Multicenter, includes American, European, Asian and Australian populations; R, retrospective; P, prospective; PH, post hoc analyses; PTC, papillary thyroid carcinoma; DTC, differentiated thyroid cancer; ATC, anaplastic thyroid carcinoma; MTC, medullary thyroid carcinoma; PDTC, poorly differentiated thyroid cancer; RR-DTC, radioactive iodine refractory differentiated thyroid cancer; RR-TC, radioactive iodine refractory thyroid cancer ; RAI, radioactive iodine; OS, overall survival; PFS, progression-free survival; DFS, disease-free survival; CSS, cause-specific survival.

Baseline NLR Levels and OS

We explored the association between baseline NLR levels and OS in patients with TC, based on survival data from 12 studies with 860 participants. A fixed-effects model was applied given the insignificant heterogeneity across the studies (I² = 23.3%, P = 0.214). The findings revealed that TC patients with high NLR levels had a significantly worse OS (HR: 2.578, 95% CI: 2.050-3.242, P < 0.001) compared to those with low NLR levels (Figure 2).

Figure 2.

Forest plots of the relationship between baseline NLR levels and overall survival in patients with thyroid cancer. HR, hazard ratio; CL, confidence interval.

We then conducted subgroup analyses based on different study regions, treatment modalities, cancer types, and NLR cut-off values. We found that the above conclusion remained consistent in the majority of subgroup analyses (Table 2). Notably, the relationship between NLR levels and OS was at a critical statistical level (P = 0.052) in the subgroup analysis of ATC patients or cut-off >3 (Table 2).

Table 2.

Subgroup Analysis of the Association Between NLR and Prognosis in Patients With Thyroid Cancer.

Variable	Included Studies	Test of Association			Test of Heterogeneity
Variable	Included Studies	HR	95%CI	P value	Modal	I²	P value
Overall survival
Study region
Japan	6	2.030	1.255-3.285	0.004	F	45.5%	0.102
Korea	2	2.447	1.371-4.366	0.002	F	0.0%	0.541
China	2	6.069	2.221-16.589	<0.001	F	0.0%	0.904
Other	2	2.661	1.962-3.611	<0.001	F	0.0%	0.323
Treatment
Lenvatinib	4	2.271	1.611-3.201	<0.001	F	0.0%	0.684
Sorafenib	2	2.470	1.293-4.720	0.006	F	0.0%	0.339
Surgery	2	5.874	2.093-16.484	0.001	F	0.0%	0.944
Other	4	2.562	1.195-5.494	0.016	R	66.1%	0.031
Cancer types
RR-DTC	5	2.568	1.945-3.391	<0.001	F	0.0%	0.526
ATC	4	2.587	0.992-6.749	0.052	R	63.8%	0.040
Other	3	2.967	1.659-5.306	<0.001	F	19.0%	0.291
Cut-off
NLR = 3	5	2.568	1.945-3.391	<0.001	F	0.0%	0.526
NLR = 2-3	3	2.967	1.659-5.306	<0.001	F	19.0%	0.291
NLR >3	4	2.587	0.992-6.749	0.052	R	63.8%	0.040
Progression-free survival
Study region
Japan	5	2.149	1.373-3.364	0.001	F	32.3%	0.206
Other	2	2.139	1.486-3.078	<0.001	F	0.0%	0.871
Treatment
Lenvatinib	5	2.004	1.423-2.822	<0.001	F	3.6%	0.386
Sorafenib	2	2.474	1.500-4.082	<0.001	F	24.7%	0.249
Cancer types
RR-DTC	4	2.154	1.466-3.166	<0.001	F	39.1%	0.177
Other	3	2.130	1.405-3.229	<0.001	F	0.0%	0.602
Cut-off
NLR = 3	5	2.045	1.451-2.882	<0.001	F	24.1%	0.261
Other	2	2.366	1.438-3.891	0.001	F	0.0%	0.504
Disease-free survival
Study region
China	4	1.189	0.989-1.429	0.065	F	52.0%	0.100
Korea	3	1.784	0.334-9.526	0.498	R	77.9%	0.011
Other	3	1.128	0.965-1.318	0.132	F	48.6%	0.143
Treatment
Surgery	10	1.378	1.045-1.819	0.023	R	55.1%	0.018
Cancer types
PTC	6	1.322	0.783-2.233	0.296	R	50.3%	0.074
DTC	3	1.482	0.886-2.479	0.134	R	67.6%	0.046
MTC	1	-	-	-	-	-	-
Cut-off
2-3	6	1.683	0.835-3.389	0.145	R	54.1%	0.054
Other	4	1.220	0.960-1.551	0.103	R	57.0%	0.073
Cause-specific survival
Study region
Japan	3	3.822	2.079-7.028	<0.001	F	0.0%	0.431
Brazil	1	-	-	-	-	-	-
Treatment
RAI	3	2.595	1.104-6.102	0.029	R	72.4%	0.027
Surgery	1	-	-	-	-	-	-
Cancer types
DTC	3	2.595	1.104-6.102	0.029	R	72.4%	0.027
PDTC	1	-	-	-	-	-	-
Cut-off
NLR = 3	2	1.623	1.126-2.338	0.009	F	56.9%	0.128
NLR = 2-3	2	6.013	2.315-15.619	<0.001	F	0.0%	0.637

RR-DTC, radioactive iodine refractory differentiated thyroid cancer; PDTC, poorly differentiated thyroid cancer; ATC, anaplastic thyroid carcinoma; PTC, papillary thyroid carcinoma; DTC, differentiated thyroid cancer; MTC, medullary thyroid carcinoma; RAI, radioactive iodine; HR, risk ratio; CI: Confidence interval; NLR, neutrophil to lymphocyte ratio.

Baseline NLR Levels and PFS

We investigated the association between baseline NLR levels and PFS in TC patients using data from 7 studies with a total of 493 patients. The pooled HR indicated that high levels increased the risk of progression by 114.3% (HR: 2.143, 95% CI: 1.616-2.843, P < 0.001, Figure 3). Given the absence of significant heterogeneity, we utilized a fixed-effects model for analysis (I² = 0%, P = 0.430, Figure 3).

Figure 3.

Forest plots of the relationship between baseline NLR levels and progression-free survival in patients with thyroid cancer. HR, hazard ratio; CL, confidence interval.

Subgroup analyses were performed based on varying factors such as study regions, treatment modalities, cancer types, and NLR cut-off values. All of the subgroup analyses demonstrated consistent results, as shown in Table 2.

Baseline NLR Levels and DFS

A total of 10 studies involving 3942 participants were included to investigate the association between baseline NLR and DFS in TC patients. Interestingly, all of these patients underwent surgical treatment. Given the presence of significant heterogeneity among the included studies (I² = 55.1%, P = 0.018, Figure 4), a random-effects model was applied. The findings demonstrated that high NLR was associated with shorter DFS compared to low NLR (HR: 1.377, 95% CI: 1.045-1.816, P = 0.023, Figure 4).

Figure 4.

Forest plots of the relationship between baseline NLR levels and disease-free survival in patients with thyroid cancer. HR, hazard ratio; CL, confidence interval.

We performed subgroup analyses categorized by various factors, such as study regions, cancer types, and NLR cut-off values. However, we found no statistically significant relationship between NLR levels and PFS in TC patients in the different subgroup analyses (Table 2).

Baseline NLR Levels and CSS

We analyzed data from 4 studies involving 635 patients with TC to estimate the relationship between NLR and CSS. The results showed that high NLR was associated with a 184.2% increased risk of cause-specific mortality (HR: 2.842, 95% CI: 1.334-6.053, P = 0.007), as demonstrated in Figure 5. The included studies had high heterogeneity, so we used a random-effects model (I² = 66.1%, P = 0.031).

Figure 5.

Forest plots of the relationship between baseline NLR levels and cause-specific survival in patients with thyroid cancer. HR, hazard ratio; CL, confidence interval.

We conducted subgroup analyses stratified by different factors, including study regions, treatment modalities, cancer types, and NLR cut-off values. The findings of all subgroup analyses were consistent, as presented in Table 2.

Sensitivity Analysis and Publication Bias

We performed a sensitivity analysis using the leave-one-out method to determine the influence of each study on the combined results. The results showed that the combined HR for OS was not significantly affected by the exclusion of any individual study. The HR ranged from 2.412 (95% CI: 1.854-3.138) after excluding Treistman et al 2023 to 2.706 (95% CI: 2.048-3.575) after excluding Taylor et al 2021, as illustrated in Figure 6. The sensitivity analysis also showed no significant difference in the pooled HR for PFS (Figure 7A), with a range of pooled HRs from 2.118 (95% CI: 1.519-2.953, after excluding Jin et al 2023) to 2.282 (95% CI: 1.678-3.104, after excluding Fukuda et al 2022), and DFS (Figure 7B), with a range of pooled HRs from 1.299 (95% CI: 1.002-1.737, after excluding Offi et al 2021) to 1.610 (95% CI: 1.040-2.490, after excluding Lang et al 2014).

Figure 6.

Sensitivity analysis of the association between baseline NLR levels and overall survival. CL, confidence interval.

Figure 7.

Sensitivity analysis of the association between baseline NLR levels and progression-free survival (A) and disease-free survival (B). CL, confidence interval.

We conducted Begg’s and Egger’s tests to evaluate the presence of publication bias in our analysis. The results revealed no significant publication bias in OS (Egger’s test: P = 0.369; Begg’s test: P = 0.340), PFS (Egger’s test: P = 0.061; Begg’s test: P = 0.072), and DFS (Egger’s test: P = 0.066; Begg’s test: P = 0.210).

Discussion

The effect of NLR on patient prognosis has been applied to patients with liver cancer, colorectal cancer, and stomach cancer.^7,37,38 Our study aimed to explore the prognostic significance of NLR in patients with TC. The analysis revealed a strong association between high NLR levels and shorter OS, PFS, DFS, and CSS in TC patients. As NLR is a commonly available clinical parameter, its measurement before initiating treatment can assist physicians in predicting clinical outcomes with greater accuracy and efficiency. This information can aid in prompt treatment adjustments, further increasing therapeutic benefit rates.

Previously Feng et al³⁹ also implemented a meta-analysis of NLR and prognosis in thyroid cancer, however, they only analysed the effect of NLR on DFS. They combined 5 studies and found that elevated NLR was not significantly associated with overall unfavourable DFS. Russo et al also conducted a study to investigate the relationship between the NLR and DFS in patients with TC and concluded that NLR did not predict DFS in these patients.⁴⁰ And we came to significantly opposite conclusions from a pooled analysis of 21 studies. The biomarker known as the NLR reflects the interaction of 2 important faces of the immune system, namely the innate immune response driven by neutrophils and the adaptive immune response facilitated by lymphocytes.⁴¹ NLR is computed by taking the ratio of neutrophil and lymphocyte counts measured in peripheral blood, thereby providing a straightforward and reliable metric to assess immune function.⁴² While there are no established fixed threshold values for the NLR, fluctuations in NLR levels still indicate abnormalities in the immune system.

Malapure et al⁴³ demonstrated that NLR levels were significantly lower in differentiated TC patients who achieved complete disease clearance following surgery and radioactive iodine (RAI) treatment compared to those with incomplete clearance. Jin et al³⁶ revealed that low NLR levels were significant predictors of longer PFS and OS in patients with RAI-refractory TC treated with sorafenib. Ge et al⁴⁴ further confirmed that elevated pre-ablation NLR was significantly associated with distant metastasis in differentiated TC patients. Recent studies indicated that serum NLR levels in differentiated TC patients significantly increased following treatment with ¹²⁵I particles, with the high-dose group exhibiting higher NLR levels than the low-dose group.⁴⁵ NLR is also considered to be a simple and repeatable biomarker of inflammation that can improve the accuracy of preoperative malignancy prediction.^43,46 Cao et al showed that NLR was poor in identifying the rate of response to radioiodine therapy in patients with papillary TC.⁴⁷

Inflammation has a crucial role in the pathogenesis of several solid and hematopoietic cancers.^48,49 Individuals who are sensitive to persistent infections, immunological problems, and aging experience a chronic pathological response that results in carcinogenesis. The “cancer-elicited inflammation” that is triggered by this process is characterized by a pro-inflammatory cytokine and chemokine storm. To continue the growth of tumors, immune cells are attracted, angiogenesis is produced, and a change from the promoting phase takes place.^48,50 According to the literature, oncogenes that cause TC transformation, such as RET and PTC1, can activate a pro-inflammatory transcriptional program, which in turn forms the inflammatory, pro-tumorigenic microenvironment.⁵¹ The mechanisms that facilitate tumor growth through inflammation are multifaceted and intricate. They entail enhanced cell proliferation, increased cell survival, angiogenesis activation, and metastasis. Additionally, cytokines and chemokines production results in the attraction of various immune cell populations, such as macrophages, T cells, B cells, and NK cells, which enter tumor tissues and produce a distinctive microenvironment.^52-54

As the initial cells involved in the inflammatory response, neutrophils have the potential to release circulating VEGF, chemokines, and proteases that encourage angiogenesis. These inflammatory cytokines could create a favorable environment for tumor growth and progression.^55,56 In addition, an increased number of neutrophils can trigger immunosuppression by suppressing the activity of natural killer cells and activated T cells.^57,58 Various types of lymphocytes play distinct roles in cancer initiation and progression. For example, CD8⁺ T lymphocytes are recognized for their ability to eliminate tumor cells and have become an important focus in the field of immunotherapy.^51,59,60 For the reasons mentioned above, a high NLR may indicate an ineffective immune response or an unbalanced inflammatory condition that may promote disease progression and poorer outcomes, which significantly supports our findings. That is, a high NLR is associated with a poor prognosis in TC patients, whether they undergo surgery, radiotherapy, or targeted therapy.

Undoubtedly, this analysis still has some limitations. The majority of the articles examined were retrospective cohort studies, which could have affected their statistical efficacy. Moreover, the lack of consistency in the cut-off values for NLR across studies may have resulted in aggregated survival outcomes deviating from the actual values. Looking ahead, future studies should focus on establishing standardized NLR cut-off values to enhance the comparability of results across different populations. Prospective cohort studies with larger sample sizes are warranted to further validate the prognostic significance of NLR in various therapeutic contexts.

Conclusion

The baseline NLR levels were useful predictors of outcomes in patients with thyroid cancer.

Supplemental Material

Supplemental Material - Neutrophil-To-Lymphocyte Ratio as a Prognostic Indicator in Thyroid Cancer

Supplemental Material for Neutrophil-To-Lymphocyte Ratio as a Prognostic Indicator in Thyroid Cancer by Qiangang Gao, Mingming Quan, Lilong Zhang, Yanyun Ran, Jijun Zhong, and Bin Wang in Cancer Control.

Footnotes

Authors’ contributions

QGG and WB conceived and designed the study. QGG, QMM, RYY, ZLL, ZJJ, and WB were responsible for data collection and organization, data analysis and interpretation, and writing of the manuscript.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Medical Science and Technology Project of Zhejiang Province (No. 2024KY1817).

Ethical Statement

ORCID iD

Bin Wang

Supplemental Material

Supplemental material for this article is available online.

Appendix

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