Объем хороида-плексуса в множестве склероза: систематический обзор и метаанализ формирующегося биомаркера изображений.

Introduction

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disorder within the central nervous system (CNS) with heterogeneous neurological symptoms and disability progression [ 1 ]. The most common subtype of MS, known as relapsing–remitting MS (RRMS), is characterized by relapses linked to the formation of inflammatory lesions affecting the CNS [ 2 , 3 ]. Approximately 30 years after disease onset, approximately half of the people with RRMS have a transition into a later stage of the disease, which is defined by a gradual but steadily progressive clinical course of neurological deterioration, independent of the occasional relapses. This phase is secondary progressive MS (SPMS) [ 4 , 5 ]. Likewise, primary progressive MS (PPMS) is characterized by insidious and steadily progressive accumulation of disability at much faster rates than seen in RRMS [ 6 ]. The enlargement of chronic MS lesions, resulting from sustained inflammation at the lesion periphery, is considered a predominant driving factor in the progression of MS [ 7 – 10 ]. Previous studies have shown that lesion enlargement is particularly noticeable near the ventricles, suggesting a correlation between prolonged inflammation and CSF [ 11 ]. The recent studies suggest that the choroid plexus (CP), a crucial component of the ventricular system, may play a role in this inflammatory environment and serve as a potential biomarker for MS progression. When considering the challenge in the prognosis of MS, pursuing an appropriate biomarker to predict its progression is ongoing.

The blood–cerebrospinal fluid barrier (BCSFB) is established by the arachnoid membrane and CP epithelial cells. These cells correspond to highly vascularized, veil-like structures that are within the brain ventricles. They participate in the clearance of solutes from the brain in the CNS and are gateways of neuroimmune regulation [ 12 , 13 ]. In terms of developmental considerations, the CP emerges early in gestation and is critical to brain development by secreting cerebrospinal fluid (CSF), which facilitates cerebral expansion through the establishment of colloid osmotic pressure [ 14 ].

Alterations in CP morphometry are suggested to reflect inflammatory processes and differentiation and may differ between MS and its mimics at the group level [ 15 – 17 ], The CP may hold promise as a possible biomarker of neuroinflammation. Magnetic resonance imaging (MRI), owing to its superior spatial resolution and tissue contrast, has emerged as the modality of choice to assess CP morphology in inflammatory and non-inflammatory neurological conditions [ 18 , 19 ]. Compared to healthy controls (HCs), PwMS exhibit increased 30% CP enlargement, particularly those with RRMS with inflammatory profiles [ 16 , 20 ]. Based on this, CP changes appear to be a surrogate biomarker of neuroinflammation in MRI [ 16 ].

Although some imaging studies have investigated CP morphological alterations and their association with inflammatory markers, the evidence remains inconclusive regarding the relationship between CP architectural or permeability changes and immune cell infiltration [ 21 ]. This enlargement indicates heightened inflammatory activity [ 16 ] and correlates with disease severity measures, including lesion load and brain atrophy [ 22 – 24 ]. These results demonstrate that the CP is a dynamic participant in CNS immune surveillance and may be a source of mechanistic and prognostic biomarkers for MS.

In terms of clinical aspects, one of the primary assessments of disability in MS to examine both motor and neurological function is the expanded disability status scale (EDSS) [ 25 , 26 ]. Studies have shown that in PwMS, greater CP volume (CPV) correlated positively with white matter lesion volume and with EDSS score [ 20 ]. These results suggest that CPV may be a useful imaging and clinical biomarker of MS-related disease and disability progression over time.

Yet, the results between studies have been variable. Some have found no correlation between CPV and clinical or radiologic disease burden measures. For instance, in RRMS and PMS cohorts, CP size did not correlate with EDSS scores, and no correlation was seen in pediatric-onset MS between normalized CPV and EDSS or lesion counts [ 27 ]. Other studies, however, did find positive correlations, with larger CPV being associated with larger lesion loads and greater disability scores in MS [ 20 , 28 ]. Such discordant findings present a gap in the literature and a need for clarification, which this systematic review and meta-analysis aims to provide.

Previous studies did not provide a comprehensive systematic review and meta-analysis, which has impeded the ability to establish a robust conclusion concerning the role of CP in PwMS. This systematic review and meta-analysis was conducted to examine differences in CPV between PwMS and HCs, as well as the correlation with MRI metrics and disability scores.

Materials and methods

Study design

This systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 29 ]. The study protocol was formally registered in PROSPERO (CRD42024586066).

Search strategy

Four major electronic databases (PubMed/MEDLINE, Embase, Scopus, and Web of Science) were systematically searched from inception to January 25, 2025. The search strategy encompassed relevant MeSH terms for MS and CP, customized for each database. Further studies were identified through a manual review of the reference lists of relevant articles and reviews. The details of the customized search strategy are available in Supplementary 1.

Study selection

The results of the literature search were transferred to EndNote software (EndNote X21, Thomson Reuters, New York) for storage and screening purposes [ 30 ]. Two reviewers (MYP and EMG) independently assessed the titles and abstracts for eligibility. After the initial screening, the identified articles were subjected to a comprehensive full-text review using the predefined inclusion and exclusion criteria. Disagreements that emerged during the screening and full-text review stages were discussed with a third reviewer (OM) and were resolved. The level of agreement between the two independent reviewers for the study selection phase was high (Cohen’s κ = 0.86), indicating almost perfect agreement.

Inclusion and exclusion criteria

To be included in this systematic review and meta-analysis, studies were required to meet the predetermined inclusion criteria, including;

Published in English;

Peer-reviewed studies;

Study design of case–control, cross-sectional, and cohort;

Participants consist of adults aged 18 years or older with a confirmed diagnosis of MS by McDonald criteria [ 31 ];

Quantify the CPV using the structural conventional MRI with validated MR acquisition protocols, including three-dimensional (3D) T1-weighted, 3D T2-weighted, or 3D Fluid Attenuated Inversion Recovery (FLAIR) sequences;

Comparing CPV between PwMS and HCs or exploring the associations of CPV with clinical features or MRI indices of PwMS.

Exclusion criteria were applied to studies that reported on;

Non-English articles;

Case reports or case series;

Animal and in vitro studies;

Conference abstract, editorials, letters, protocols, and review studies;

Lacking adequate or precise information on CPV, clinical assessments, and MRI metrics in PwMS;

Not providing data suitable for extracting or calculating effect sizes for meta-analysis.

Data extraction

Two reviewers (MYP and EMG) independently extracted the main characteristics of the included studies. These characteristics encompassed study details (e.g., first author, publication year, study design), demographic data (e.g., sample size, sex, age), clinical particulars (e.g., MS subtype, disease duration, disability status), details of CP measurement (e.g., tools, software, method used), and the effect estimate utilized for meta-analysis. The extracted data were compared, and any discrepancies were addressed through consultation and discussion with a senior reviewer (OM) to achieve consensus. The inter-rater agreement for data extraction was strong (Cohen’s κ = 0.82).

Risk of bias assessment (ROB)

Two reviewers (MYP and EMG) independently assessed the risk of bias in the included studies utilizing the Newcastle–Ottawa Scale (NOS) 10-point checklist for case–control studies [ 32 ]. Any discrepancies that arose during this process were resolved through discussion with the third reviewer (OM) to achieve consensus. The agreement between the two reviewers for the risk of bias assessment was substantial (Cohen’s κ = 0.79).

Data analysis

The meta-analysis was executed in two discrete stages to assess two outcomes. First, the meta-analysis was conducted on the standardized mean difference (SMD) of normalized CPV (nCPV) between PwMS and HCs. The subtypes of MS were taken into account when pooling the results. A subgroup analysis was conducted using studies that specified the MS subtype as either (RRMS, progressive MS (PMS), or mixed MS subtypes (including both RRMS and PMS)). In cases where studies provided effect sizes categorized by subtype of MS (RRMS or PMS), these were individually incorporated into the analysis. Otherwise, when studies did not differentiate their findings by MS subtype but reported a combined analysis including both RRMS and PMS, we categorized those results under a mixed MS subtypes group. It is essential to clarify that PMS includes all progressive forms of MS, such as SPMS and PPMS, and that the term"mixed MS subtypes"refers to data from studies that included both RRMS and PMS patients without separating the results.

Then, the meta-analysis was carried out on the correlations between nCPV and disability and MRI metrics. For this analysis, the correlations were converted into Fisher's z scores. Subsequently, these values were retransformed into correlation coefficients (r) for ease of visualization and interpretation.

All statistical analyses were carried out using R software version 4.3.2. and package “meta” [ 33 ]. Results were pooled and presented in forest plots when three or more comparative studies reported the effect sizes. Standardized mean difference (SMD) and 95% confidence interval (CI) using Cohen's d [ 34 ], as well as pooled correlation coefficients with 95% CI, were used as effect sizes of the meta-analysis. Due to the possible methodological heterogeneity among the included studies, the random-effects model was used to perform the meta-analyses. Heterogeneity among the included studies was evaluated using Cochran's Q test and the inconsistency index (I 2 ) [ 35 ].

Sensitivity analyses were performed to identify potential outliers that might have influenced the overall outcome [ 36 ]. Publication bias was evaluated by utilizing funnel plots, and the symmetry of these plots was assessed using both Egger and Begg tests [ 37 , 38 ]. In addition, studies with potentially overlapping cohorts were reviewed in detail, and in cases of participant duplication, only the most comprehensive dataset was retained in the meta-analysis to avoid duplication bias. Analyses were deemed significant if the p value ≤ 0.05.

Results

Literature search and study selection

A total of 1431 records were retrieved from the literature of the four databases. Following the duplicate removal of 448 records, 983 articles were screened based on title and abstract. After the screening, 152 studies remained, and their full-text versions were assessed. Consequently, 27 studies were included in the qualitative part of our study and 23 studies were included in the quantitative analysis. (Fig. 1 ).

Study characteristics

The included studies comprised data on 2,975 PwMS, with a female‐to‐male ratio of 2.04:1, and 1,191 HCs with a female‐to‐male ratio of about 1.51:1. PwMS demonstrated a mean (SD) age of 40.8 years and a disease duration of 13.1 years. The MS subtypes included RRMS with 2,434 patients and PMS with 490 patients. The mean (SD) age of HCs was 37.2 years. The studies included in our research predominantly came from the United States and Italy (Table 1 ).

Quantitative summary

Comparing normalized CPV between people with multiple sclerosis and healthy controls

The meta-analysis of 21 case–control studies on 1420 PwMS and 1282 HCs indicated that nCPV was significantly higher in PwMS than HCs (SMD = 1.12, 95% CI 0.68 to 1.56, p value < 0.01) (Fig. 2 ).

The subgroup analysis was conducted concerning the subtypes of MS, including RRMS, PMS, and a mixed subtype (RRMS and PMS). The result of subgroup analysis revealed that nCPV of 743 RRMS (SMD = 1.05, 95% CI 0.34 to 1.76, p value < 0.05) and 178 PMS patients (SMD = 0.85, 95% CI 0.58 to 1.12, p value < 0.05) also was significantly higher as compared to 667 and 256 HCs, respectively (Fig. 2 ).

Correlations of nCPV with disability and MRI measures among PwMS

The meta-analysis of six studies on 818 PwMS indicated a significant and direct pooled correlation of 0.23 (95%CI 0.16 to 0.31, p value < 0.01) between nCPV and EDSS (Table 2 ).

Among pooled correlations, higher nCPV was significantly associated with increased normalized ventricular volume (r = 0.59, 95%CI 0.5 to 0.68, p value < 0.01, PwMS = 516) and T2 lesion volume (r = 0.34, 95%CI 0.26 to 0.42, p value < 0.01, PwMS = 547).

Moreover, nCPV had inverse relationships with normalized brain volume (r = − 0.32, 95%CI − 0.41 to − 0.24, p value < 0.01, PwMS = 451), normalized gray matter volume (r = − 0.41, 95%CI − 0.57 to − 0.24, p value < 0.01, PwMS = 303) and normalized thalamic volume (r = − 0.38, 95%CI − 0.46 to − 0.3, p value < 0.01, PwMS = 516) (Table 2 ).

Sensitivity analysis

We conducted leave-one-out sensitivity analyses, systematically omitting each study to examine its influence on the overall pooled estimate. The results showed that removal of any single study did not alter the statistical significance or direction of the pooled effect size, identifying no outliers with significant influence. These results indicated that our findings are robust and not driven by a single influential study. Details of the sensitivity analysis results for all analyses are presented in Supplementary 2.

Publication bias

Table 2 illustrates a funnel plot, plotting observed SMDs against standard errors (SE) representing precision. This plot estimate exhibits a symmetrical distribution around the vertical dashed line, indicating the pooled effect estimate and forming a funnel shape. Furthermore, the results of the Egger test (bias = 2.47, p value = 0.26) and the Begg test (Z = 1.7, p value = 0.09) confirm no evidence of asymmetry in the funnel plot.

Regarding the pooled correlation coefficients, Begg and Egger tests revealed no publication bias in all meta-analyses (Table 2 ).

Risk of bias assessment

Quality assessment summary scores are illustrated in Table 1 (QA column). Among the 27 included studies, 14 (51.9%) scored above 6, indicating high quality and low risk of bias; 12 (44.4%) scored between 5 and 6, reflecting moderate quality and risk of bias; and 1 study (3.7%) scored below 5, indicating low quality and a high risk of bias.

Discussion

This systematic review and meta-analysis demonstrated a significant increase in the CPV in PwMS, as compared to HCs. Furthermore, CPV showed significant correlations with clinical and imaging markers in PwMS, including ventricular volume, gray matter volume, thalamic volume, T2 lesion volume, brain volume, and EDSS.

Recently, the role of the CP has attracted significant research attention. The CPV rise has been linked to increased clinical disability and injury to brain structures in neurological disease processes [ 61 , 62 ]. Neuroimaging studies in PwMS have reported significant hypertrophy as well as inflammation of the CP, specifically in those categorized as having the highly inflammatory profile [ 16 ]. The CP dysregulation may indicate shared but not yet defined pathways in the pathophysiology of neurodegenerative disorders [ 56 ]. In fact, CP enlargement precedes CNS pathological changes and is considered a recent marker of genetically or environmentally driven susceptibility to neuroinflammation [ 41 , 57 , 62 ]. In PwMS, CP enlargement is already one of the earliest signs of brain pathology [ 21 , 63 , 64 ]. A study in pediatric MS patients by Margoni et al. [ 63 ] also showed increased CPV, especially in female patients.

The results of the current meta-analysis revealed an increase in CPV in PwMS relative to HCs. Jankowska et al. [ 65 ] suggested that CPs undergo varying degrees of enlargement, with this varying in proportion to MS phase and activity. Akaishi et al. [ 66 ] found a significant association between CP enlargement and lesion load, and cerebral white matter atrophy, after controlling for lateral ventricle volume. Their study, however, noted that only lateral ventricle enlargement, and not CP enlargement, was related to total gray matter volume. However, given that most brain atrophy in MS was found to result from gray matter loss, which histological investigations use as an index of neurodegeneration [ 54 ], a hypothesis was forwarded that CP enlargement was an index of neuroinflammation, not neurodegeneration [ 66 ]. Morozumi et al. [ 53 ] proposed that CPV increase may result from MS inflammatory characteristics, with these having effects on CP morphology. However some prior studies reached a contrary conclusion. Recent studies revealed a relationship between an enlarged CP and neurodegenerative changes, including cortical atrophy [ 22 ], chronic lesion expansion, and central brain atrophy in PwMS [ 23 ]. Also, greater nCPV was found to independently predict decreased normalized brain, gray matter, and thalamic volumes in people with RRMS and PMS [ 53 ]. Differentiation between neuroinflammatory and neurodegenerative changes in MS remains a challenging task [ 66 ]. The inflammatory aspect of MS pathology may appear both focally or diffusely and thereby result in consequent neurodegeneration [ 67 ]. Also, with the multiple roles of CP, the exact source and role of volume enlargement, even during normal aging, still presents a challenge [ 68 ]. According to a study by Millward et al. [ 69 ], the lateral ventricle volume may change significantly in PwMS, with changes including both irreversible enlargement due to neurodegeneration and reversible enlargement due to changes due to neuroinflammation.

Prior research has suggested several hypothetical mechanisms for CP enlargement in PwMS compared to HCs. CPV was proposed as an imaging biomarker of lymphocyte infiltration into the brain, inflammatory demyelination, and neurodegeneration without being a clinical severity marker [ 20 , 60 ]. While CPV may serve as an imaging biomarker of immune cell trafficking into the CNS, it may not be directly relevant as an imaging biomarker of SPMS [ 70 ]. In contrast to the blood–brain barrier (BBB), the consistent production of adhesion factors and chemokines by the CP makes possible leukocyte trans-epithelial trafficking [ 71 ]. Integrin receptors, such as intercellular adhesion molecule-1 (ICAM-1), are expressed on the apical surface of the CP, facilitating the migration of leukocytes from the basal spaces to the apical spaces of CP epithelium [ 72 ]. CP hypertrophy may cause infiltration of peripheral immune cells. In response to signals derived from damaged tissue, immune cells might pass through CP epithelium and infiltrate through CNS [ 73 ]. According to a study by Fleischer et al. [ 73 ], it has been shown a strong link between enlarged CP and enhanced microglia and astrocyte activation which can lead to a chronic inflammatory state [ 7 , 74 , 58 ]. Breakdown of the BCSFB in the CP due to inflammatory changes allows inflammatory mediators and immune cells to migrate into brain tissue, providing to the lesions in MS [ 75 , 76 ]. There is evidence of a gradient of periventricular chronic active lesions, where white matter lesions located near the ventricles are associated with increased inflammatory activity and closely related to enlarged CP [ 11 , 23 ].

Based on the current meta-analysis, there is a significant positive correlation of CPV with ventricular volume, T2 lesion volume, and EDSS, whereas a significant inverse correlation was observed between CPV and brain volume, gray matter volume, and thalamic volume in PwMS. The strongest correlation observed was between CPV and ventricular volume (r = 0.59). While CP enlargement is widely viewed as an indicator of neuroinflammation, this particularly strong association with ventricular volume, an established marker of brain atrophy, raises the possibility that CP changes may also reflect secondary structural effects. Given the CP’s pliable nature and proximity to the ventricles, mechanical displacement or passive expansion resulting from periventricular atrophy may contribute to the observed volumetric changes, especially in later disease stages. When viewed alongside other associations reported in our study, including gray matter volume (r = − 0.41), thalamic volume (r = − 0.38), and EDSS (r = 0.23), the CPV-ventricular volume relationship appears unusually strong. This contrast highlights the complexity of CPV interpretation, as CPV may not exclusively represent inflammatory activity.

Unlike some previous studies[ 16 , 20 , 23 , 77 ], which confirmed CPV as significantly associated with plaque volume, Margoni et al. [ 63 ] study revealed an inverse correlation between CPV and thalamic volume. Wang et al. [ 20 ] found a significant association between CP enlargement and structural deep gray matter atrophy and both brain lesion load. Previous studies have demonstrated that enlarged CP is accompanied by a greater number and volume of white matter lesions [ 16 , 77 ]. Thalamic atrophy appears to originate at the interface between the CSF and the thalamus, potentially due to deleterious pro-inflammatory and cytotoxic factors present in the CSF [ 78 ].

These discrepancies, in the context of findings in the studies that investigated the relationships between CPV and MRI measures in PwMS, are likely to be explained by differences in patient demographics, clinical measures, and spinal cord involvement. Increased CPV has volumetric correlates, and interestingly, it indicates that neurodegeneration happens at the interface of CSF and the brain [ 53 ]. This phenomenon could be attributed to detrimental pro-inflammatory and cytotoxic soluble factors within the CSF [ 53 ].

The outcome of the current meta-analysis identified a statistically significant positive correlation between CPV and EDSS in PwMS. CP may serve as an anatomical biomarker of MS disease activity [ 73 ]. However, one study by Bergsland et al. [ 61 ] was not in line with the findings of the current meta-analysis where nCPV did not correlate with EDSS but CP pseudo T2 (pT2) performance did correlate with EDSS throughout the course of the study. There was also no significant association between nCPV and relapse rate or the number of enhancing lesions. An investigation on the clinical significance of CP enlargement in pediatric MS [ 63 ] and a study on adult PwMS [ 16 ] revealed no correlation with the EDSS or disease duration. These disparities could be attributed to the limited disease duration and low EDSS observed in the pediatric PwMS, the lesser degree of spinal cord involvement, and the absence of comorbid conditions that substantially contribute to disability in adult PwMS may also play a role [ 63 ].

A recent similar systematic review and meta-analysis by Kolahi et al. [ 79 ] addressed changes in CPV in PwMS compared to HCs and described moderate correlations with disability and various imaging metrics. Although their study highlighted the promise of CPV as a biomarker, it is not without several methodological limitations that the present study aimed to overcome. Specifically, Kolahi et al.’s. analysis lacked subgroup stratification by MS subtype, included fewer studies and smaller sample sizes, and included limited correlations with MRI measurements. In addition, segmentation methods and normalization approaches used across the included studies were not standardized, and publication bias and heterogeneity were only minimally examined. In contrast, our analysis included 27 studies, with an increased overall sample size, subgroup meta-analyses based on clinical characteristics (RRMS, PMS, and mixed MS populations), and a comprehensive array of nCPV associations with other clinical-imaging outcomes evaluated (EDSS, brain volume, gray matter, thalamic, ventricular and T2 lesion load) for which to date, we have analyzed separately for the MS population as a whole and by MS subtype. Normalization procedures were also standardized; sensitivity analysis and publication bias testing by funnel plots and Egger/Begg were performed. These have strength methodologies that greatly enhance the robustness, reproducibility, and clinical applicability of our findings.

Strengths and limitations

This study is a systematic review and meta-analysis that compared the CPV between PwMS and HCs, as well as assessed its relationships with disability and MRI parameters in PwMS. Our search strategy had several notable strengths, especially its comprehensive nature (including the absence of temporal publication restrictions), reproducibility, and efficiency. In addition, to enhance the results accuracy by reducing heterogeneity of the analysis, we conducted subgroup meta-analyses based on MS subtypes. Given the influence of age and sex on nCPV [ 63 , 80 ], most of the included studies employed age and sex matching and used CPV as a ratio of total intracranial volume to mitigate the impact of these covariates. The findings of this study should be interpreted with caution, given its limitations. However, differences in MRI devices, Tesla strength, MR acquisition metrics, software to image the region of interest, or methods of describing CP ensure this consideration based on findings in studies that need to be made in future follow-up studies. In addition, the lack of standardization in CP segmentation methods, including variability in software packages, segmentation approach, and normalization procedures, may have introduced heterogeneity in reported CP volumes. As not all studies clearly described their segmentation approaches, we were unable to assess how methodological differences influenced effect sizes. A few studies included in this review assessed CPV only from the lateral ventricles and excluded CPV from the third and fourth ventricles. Lastly, this study did not consider the influence of different disease-modifying therapies (DMTs) on CPV. Other reasons can be influenced by age, sex, and body mass index on the CPV [ 63 , 81 ]. With inconsistencies in the control of these covariates in studies in this review, it is highly imperative in future studies to take these factors into careful consideration in order to reach meaningful conclusions. The paucity of comprehensive studies limits the effective comparison of CPV in RRMS and PMS patients. Owing to the small number of studies in this review, especially in the meta-analysis of correlation coefficients, the findings of this systematic review and meta-analysis should be interpreted with caution.

Conclusion

In conclusion, this study showed a significant increase in CPV in PwMS compared with HCs. Moreover, there is a substantial association between CPV and disability score and various MRI metrics of the brain structure of PwMS. These findings of this study suggest an association between CPV and the prognostic and disease activity biomarker in PwMS, indicating that CPV may serve as a potentially useful additional radiological biomarker for the monitoring and assessment of disease progression in MS, which will have to be verified in larger longitudinal imaging studies.

Supplementary Information

Additional file 1

Additional file 2

Additional file 3

Acknowledgements

None.

Author contributions

Conceptualization: (MYP) and (OM); Data curation: (MYP), (EMG), and (SV); Formal analysis: (MYP), (FM) and (OM): Investigation: (FM), (VS), and (OM); Methodology: (EMG) and (OM); Writing—original draft preparation: (OM), (MYP) and (EMG); Writing—review and editing: (EMG), (VS), (FN), and (OM); Supervision: (OM), (EMG), and (FN); Validation: (VS) and (OM); Visualization: (MYP).

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

This article is based on the previously conducted studies and does not contain any new studies with human participants or animals per formed by any of the authors.

Patient and public involvement

Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Patient consent for publication

Not required.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

Supplementary Materials

Additional file 1

Additional file 2

Additional file 3

Data Availability Statement

No datasets were generated or analysed during the current study.