The prognostic value of lymph node to primary tumor standardized uptake value ratio in cancer patients: A meta-analysis

The prognostic value of lymph node to primary tumor standardized uptake value ratio in cancer patients: A meta-analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The prognostic value of lymph node to primary tumor standardized uptake value ratio in cancer patients: A meta-analysis Wing-Keen Yap, Ken-Hao Hsu, Ting-Hao Wang, Chia-Hsin Lin, Chung-Jan Kang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4152387/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 May, 2024 Read the published version in Annals of Nuclear Medicine → Version 1 posted 4 You are reading this latest preprint version Abstract Objective: The lymph node to primary tumor standardized uptake value ratio (NTR) is an innovative parameter derived from positron emission tomography (PET) scans that captures the intricate relationship between primary tumors and associated lymph nodes. This meta-analysis aimed to investigate the prognostic value of NTR in cancer patients. Methods: A systematic search of PubMed, Cochrane, and Embase databases was conducted to identify studies investigating the association between NTR and survival outcomes in cancer patients. The pooled adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) were calculated using a random-effects model. Results: Twelve studies comprising a total of 2037 patients were included in the meta-analysis. Elevated NTR was significantly associated with worse overall survival aHR (2.21, 95% CI 1.63 to 2.99), disease-free survival aHR (3.27, 95% CI 2.12 to 5.05), and distant metastasis-free survival aHR (2.07, 95% CI 1.55 to 2.78) in cancer patients. Subgroup analyses by cancer type showed consistent results across various malignancies, including head and neck squamous cell carcinoma, endometrial carcinoma, lung cancer, breast cancer, and nasopharyngeal carcinoma. Conclusions: This meta-analysis provides evidence for a significant association between elevated NTR and worse survival outcomes in cancer patients. Elevated NTR may serve as a useful prognostic biomarker for cancer patients, and could potentially be used to guide treatment decisions and monitor disease progression. Future studies should aim to validate these findings in larger and more diverse patient populations, and investigate the underlying mechanisms for the observed association between NTR and survival outcomes. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Cancer stands as a prominent contributor to global mortality, accounting for nearly 10 million deaths annually(1, 2). Approximately one in five individuals experiences a cancer diagnosis during their lifetime, and in 2020 alone, an estimated 19.3 million new cases were identified(1, 2). Despite notable progress in early detection, surgical interventions, chemotherapy protocols, radiotherapy, immunotherapies, and comprehensive multidisciplinary approaches, cancer patients persistently grapple with suboptimal prognoses, as evidenced by a mortality rate of 1 in 10 individuals succumbing to the disease(1, 2). Thus, in the realm of oncology, the continuous pursuit of refined prognostic markers is imperative for tailoring treatment strategies and optimizing patient outcomes. Within this context, the Standardized Uptake Value (SUV) derived from positron emission tomography (PET) scans has emerged as a promising metric for characterizing tumor metabolic activity, and has been shown to have significant prognostic implication across diverse cancer types(3-9). Recently, attention has turned towards evaluating the prognostic significance of the Lymph Node to Primary Tumor Standardized Uptake Value Ratio (NTR) – an innovative parameter capturing the intricate relationship between primary tumors and associated lymph nodes(10-22). The rationale for focusing on NTR lies in its ability to provide a detailed insight into tumor behavior. Instead of just looking at the primary tumor SUV, considering lymph node involvement adds complexity and may reveal crucial information about the aggressiveness and progression of the disease. While individual investigations have explored the potential prognostic implications of NTR across diverse cancer types, a comprehensive synthesis of existing evidence is notably absent. This meta-analysis seeks to address this critical gap by systematically reviewing and quantitatively analyzing collective findings from a spectrum of studies investigating the prognostic role of NTR in cancer patients. Through synthesizing data from diverse studies, our aim is to elucidate the collective impact of NTR on predicting outcomes such as overall survival, disease-free survival, and distant metastasis-free survival across various malignancies. METHODS The comprehensive meta-analysis was carried out meticulously, adhering strictly to the guidelines outlined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (23) . Additionally, it was appropriately registered on PROSPERO. Search Strategy A thorough and systematic exploration was conducted across electronic databases, specifically PubMed, EMBASE, and the Cochrane Library, encompassing studies published from their inception until November 2023. The search strategy was developed by incorporating relevant keywords such as “lymph node to primary tumor,” “node to primary tumor,” “node to tumor,” “cancer,” “carcinoma,” “metastasis,” “tumor,” “tumour,” and “neoplasms.” These keywords were combined using appropriate Boolean operators. The complete details of the search can be found in Supplementary Table S1. Subsequently, a comprehensive evaluation of the full texts of the studies was carried out for inclusion. Moreover, the bibliographies of previous systematic reviews were scrutinized, and eligible studies were examined to identify potentially relevant reports. To prevent duplication of articles, the gathered studies were imported into a citation manager (Endnote, version X9.3.3, Clarivate Analytics, Philadelphia, PA). Eligibility assessment Two reviewers independently initiated searches within the databases, evaluating the titles and abstracts of identified studies in a double-blind manner to ensure impartiality. Subsequently, a detailed assessment of full texts followed, relying on the consensus reached by the reviewers concerning the selected abstracts. In instances of uncertainties or discrepancies, the senior author played a crucial role in making the ultimate judgment on eligibility. Overall, a unanimous agreement among all reviewers was pivotal in establishing eligibility. The process of selecting studies adhered to a meticulously defined set of inclusion and exclusion criteria, detailed as follows: Inclusion Criteria: 1. Enrollment of patients with diverse cancer types. 2. Investigation of the association between the NTR and survival outcomes. 3. Provision of hazard ratios (aHRs) accompanied by 95% confidence intervals (CIs) or presenting adequate information to facilitate their calculation. Exclusion Criteria: Studies not published in the English language. Studies that lacked the provision of relevant information. Reviews, meta-analyses, conference abstracts, case reports, letters, or commentaries Data extraction The independent execution of data extraction was carried out by two investigators. The extracted data encompassed various crucial elements, including primary author, publication year, patient recruitment period, study methodology, sample size, cancer staging, geographic location, aHR along with its corresponding 95% confidence CI for the primary endpoints of Overall Survival (OS), Disease-Free Survival (DFS), and Distant Metastasis-Free Survival (DMFS). Additionally, the duration of follow-up, SUV of the primary tumor or metastatic node (SUV-T, SUV-L), and the cut-off value of the NTR were also included. Data synthesis Following retrieval, the obtained data underwent comprehensive qualitative and quantitative analyses. The demographic and interventional characteristics of all incorporated studies were systematically compiled and presented in tabular format, subsequently undergoing a thorough analysis. Dichotomous outcomes, including OS, DFS, and DMFS, were represented as aHR with corresponding confidence intervals (CI). These outcomes were further subjected to a meta-analysis. In instances where there was an overlap in study populations, priority was accorded to more recent studies for the purpose of data synthesis. Appraisal of study quality The assessment of bias employed the Newcastle-Ottawa Scale for the studies included in the analysis. This evaluation tool covered three critical domains—selection, comparability, and outcome—comprising a total of eight questions. Employing the established scoring framework, the studies were categorized into three tiers reflecting their quality levels. Specifically, studies scoring ≤3 were classified as low-quality, those scoring between 4 and 6 were designated as fair-quality, and studies with a score of ≥7 were acknowledged as high-quality(24). Statistical analysis The present meta-analysis utilized Comprehensive Meta-Analysis software, version 4 (Biostat, Englewood, NJ, USA). To compare the impact of different treatments on survival outcomes, aHRs with their corresponding 95% CIs were synthesized employing a random-effects model. This model was chosen to evenly distribute the influence of heterogeneity across the diverse studies incorporated in the analysis. The presence of heterogeneity among studies was assessed using both the Cochran Q-statistic and I 2 tests. Notably, substantial heterogeneity was defined as a Q-test p-value of <0.05 or an I 2 value exceeding 50%. Sensitivity analysis by one-study-removed method was performed to confirm the robustness of these results. To evaluate the potential for publication bias, funnel plots and Egger's linear regression test were employed, with a significance threshold set at p < 0.05. If the results from Egger's test suggested the presence of publication bias, the trim-and-fill method was employed to adjust for this bias. All statistical analyses were conducted with two-tailed tests, and statistical significance was defined as p < 0.05. RESULTS Literature search and study identification The initial exploration of databases yielded a total of 53 entries, comprising 22 from PubMed, 1 from Cochrane, 30 from Embase and 1 from additional source. A visual representation of the selection progression is provided in Figure 1, while the search methodology and algorithm are detailed in Supplementary Table S1. Upon the removal of duplicates, 2 studies were excluded based on title, and an additional 11 were excluded based on abstract assessments. Subsequently, 21 studies underwent a thorough review of their full texts, resulting in the exclusion of 9 study due to specific reasons as outlined in Supplementary Table S2. Ultimately, 13 studies were considered suitable for qualitative analysis and 12 studies met the criteria for quantitative analysis.(11-22, 25) Characteristics of the included studies Table 1 provides a succinct overview of the studies included in this meta-analysis (including one for qualitative analysis). It is noteworthy that all the studies incorporated in this analysis adopted a retrospective research design. Furthermore, all these studies were conducted in Asian countries, specifically in Japan, Taiwan, China, and Korea, with the exception of one study from Morocco. The publication dates of these studies span a decade, ranging from 2013 to 2024. In total, the quantitative analysis involved 2037 patients recruited across studies within a recruitment timeline spanning from 2000 to 2020. The mean age of the patients varied from 43.2 to 66.5 years, with the male population constituting a proportion ranging from 0% to 97.3%. The duration of follow-up spanned from 10 to 62 months. The meta-analysis encompassed multiple cancer types, including 2 oral squamous cell carcinoma, 4 nasopharyngeal carcinoma, 1 esophageal cancer, 1 endometrioid endometrial carcinoma, 1 uterine cervix invasive squamous cell carcinoma, and 2 non-small cell lung carcinomas. A total of 8 studies reported cancer stage according to the AJCC TNM staging system, while 2 studies reported stage according to the International Federation of Gynecology and Obstetrics Staging System. All studies focused on the association between pretreatment NTR and survival outcomes. The reported aHR with 95% CIs for survival outcomes, including OS, DFS, and DMFS, were directly extracted from the included studies. (Table 2) Quality Assessment The present meta-analysis encompassed a comprehensive compilation of 13 studies, each undergoing meticulous scrutiny for methodological rigor utilizing the Newcastle-Ottawa scale. The results of this evaluation revealed that 10 out of the 13 eligible studies achieved scores equal to or exceeding 7 points, indicating fair quality across the majority of the studies. The remaining three studies received 5-6 points on the scale. Supplementary Figure S1 offers a more detailed visualization of the insights derived from the studies included in this analysis. Meta-analysis results Overall Survival Seven studies provided aHRs relevant to OS.(13, 14, 16, 17, 19, 21, 26) The outcomes of the meta-analysis revealed a significant association, indicating that higher NTR was correlated with worse OS (aHR 2.21, 95% CI 1.63 to 2.99) in a low-heterogeneity context (I 2 = 10.15%, p = 0.35; Figure 2). Although overall heterogeneity was low, subgroup analyses were still conducted to explore the impact of NTR in different tumor types. For nasopharyngeal carcinoma, NTR was significantly associated with worse OS (aHR 2.64, 95% CI 1.38 to 5.05; Figure 2) with low heterogeneity (I 2 = 0%, p = 0.76; Figure 2).(13, 21) In studies focusing on patients with oral cavity SCC, NTR was significantly associated with worse OS (aHR 4.60, 95% CI 2.03 to 10.47; Figure 2) with minimal heterogeneity (I 2 = 0%, p = 0.87; Figure 2).(14, 17) In each subgroup, heterogeneity was even lower, and the pooled hazard ratio remained consistent when classified by different cancer types. The results of various stratified analyses (including region, NTR cut-off values, median SUV-L, median SUV-T) for the impact of NTR on overall survival were shown in Table 3. Disease-free survival Incorporating data from 7 studies that offered aHRs pertinent to DFS, the outcomes of the meta-analysis unveiled a significant correlation.(11-14, 18, 19, 21) Specifically, the meta-analysis showcased that NTR was also notably linked to worse DFS (aHR 3.27, 95% CI 2.12 to 5.05; Figure 3) (I 2 = 23.71%, p = 0.25; Figure 3). Distant metastasis-free survival Incorporating data from five studies that provided aHRs relevant to DMFS, the outcomes of the meta-analysis revealed a significant and affirmative correlation.(15, 16, 20, 21, 25) Specifically, the meta-analysis demonstrated that NTR was notably linked to worse DMFS (aHR 2.07, 95% CI 1.55 to 2.78), with minimal heterogeneity (I 2 = 0%, p = 0.62; Figure 4). While the overall heterogeneity was low, subgroup analyses were conducted to explore the impact of NTR in different tumor types. In studies focusing on patients with nasopharyngeal carcinoma, NTR was significantly associated with worse DMFS (aHR 2.21, 95% CI 1.48 to 3.30; Figure 4) with minimal heterogeneity (I 2 = 0%, p = 0.51; Figure 4).(15, 21, 25) Publication bias and Sensitivity Analysis Funnel plots and Egger’s test were conducted to examine publication bias (Figure S2-S4). Publication bias existed in the analysis of OS (p = 0.001) DFS (p= 0.01). By the Trim and Fill test, three potential missing studies were found in the OS analysis, and the recalculated pooled HR for OS was 1.95 (95% CI: 1.36–2.79); two potential missing studies were identified in the analysis of DFS and the recalculated pooled HR was 3.09 (95% CI: 2.00, 4.77) (Figure S2-S4). The results of these tests indicated that publication bias did not influence the final results of the meta-analysis. The results of the sensitivity analysis showed that removing individual studies did not affect the results of the meta-analysis during the analysis of the relationship between NTR and OS, DFS, DMFS (Figure 5), indicating the reliability of our results. DISCUSSION This meta-analysis extracted the aHR of OS from 7 studies (778 patients) and determined a statistically significant association between the NTR and OS of cancer patient. Low heterogeneity assessed by Cochran Q-statistic and I 2 tests imply that the diverse background conditions of patients did not have a statistically significant impact on the association between the NTR and overall survival (OS). Subgroup analysis results demonstrated that the prognostic significance of the NTR for OS remained consistent across different cancer types, patient number, NTR cut-off values, median SUV-L, median SUV-T and research regions. In addition, after adjusting the synthesized outcome for publication bias via Trim and Fill test, the adjusted pooled aHR remained significant, reinforcing the reliability and robustness of our results. Similarly, a high NTR in cancer patients served as an unfavorable prognostic factor for DFS and DMFS. Notably, this study is the first meta-analysis to demonstrate the prognostic role of the NTR with respect to survival outcomes in cancer patients. Our meta-analysis provides a consolidated perspective that goes beyond individual cancer types, contributing to a more unified understanding of NTR’s prognostic relevance. These insights hold promise for informing clinical decision-making, facilitating personalized therapeutic interventions, and contribute to advancements in cancer care. The rationale for focusing on NTR lies in its potential to offer a nuanced understanding of tumor behavior. Beyond assessing primary tumor SUV in isolation, considering lymph node involvement introduces a layer of complexity that may harbor pivotal insights into disease aggressiveness and progression. The underlying mechanisms for the association of higher NTR and worse survival outcomes are not fully understood, but it has been suggested that higher NTR may reflect a state of more aggressive tumor behavior, which can promote tumor growth and metastasis(17). In a surgical series investigating oral squamous cell carcinoma, Ishibashi-Kanno et al. observed a notable association between histopathological diagnosis of LN metastasis and elevated NTR(17). Furthermore, their findings revealed a significant correlation between the presence of extracapsular spread and elevated NTR(17). Similarly, in a surgical series study of endometrioid endometrial carcinoma, Chung et al. showed a positive association of NTR with stage, lymph node metastasis, lymph vascular space invasion, tumor grade, and recurrence in endometrioid endometrial carcinoma patients(12). The study suggests that the relative metabolic activity of lymph nodes serves as a valuable surrogate functional marker indicative of tumor aggressiveness(12). This argument is further supported by 4 previous studies on different cancer types demonstrating a significant association between elevated NTR and distant metastatic potential, and ultimately, poor prognosis(10, 15, 16, 20). Although pretreatment lymph node SUVmax as a sole parameter has been shown to be a significant prognosticator in various cancer types(8, 9, 27–31), there are some well-known drawbacks of using nonnormalized SUV, e.g., partial volume effect, uptake time dependence of the SUV, and interstudy variability of image acquisition and reconstruction parameters, which could possibly undermine the reliability of the SUVmax values(12, 32–34). The strength of NTR is that by normalizing the lymph node SUVmax to the primary tumor SUVmax, NTR may be less susceptible to the inter-scanner variability, and may have better generalizability(20, 35–41). In a study on esophageal squamous cell carcinoma patients, Lin et al. assessed the potential impact of employing different PET/CT scanners on the NTR and lymph node SUVmax, and demonstrated that the variation of the optimal cutoff values and the interquartile range of the NTR obtained by the two different PET/CT scanners was minimal, while the non-normalized lymph node SUVmax suffered significantly greater inter-scanner variability(20). Limitations of the study It is noteworthy that the included studies in this meta-analysis were all conducted in Asian countries, which may limit the generalizability of the findings to other populations. Additionally, the studies varied in terms of their sample sizes, cancer types, and endpoints measured, which may have contributed to the observed heterogeneity in the meta-analysis. However, the authors employed appropriate statistical methods to account for this heterogeneity and provide a comprehensive synthesis of the available evidence. The quality assessment of the included studies using the Newcastle-Ottawa Scale (NOS) indicated that the majority of the studies were of fair to high quality. This suggests that the findings of this meta-analysis are based on relatively robust evidence. Future studies should aim to validate these findings in larger and more diverse patient populations, and investigate the underlying mechanisms for the observed association between NTR and survival outcomes. CONCLUSIONS In conclusion, this meta-analysis provides evidence for a significant association between elevated NTR and worse survival outcomes in cancer patients. These findings have important implications for further research, and highlight the potential utility of NTR as a prognostic biomarker in cancer. Abbreviations SUV, Standardized Uptake Value; PET, positron emission tomography; NTR, Lymph Node to Primary Tumor Standardized Uptake Value Ratio; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; aHR, adjusted hazard ratio; CI, confidence interval; OS, overall survival; DFS, disease free survival; DMFS distant metastasis-free survival; SCC, squamous cell carcinoma; SUV-T standardized uptake value of the primary tumor; SUV-L standardized uptake value of the lymph node Declarations Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Financial disclosure: None declared. Conflict of interests: None declared. Ethics approval and consent to participate: Not applicable Consent for publication: Not applicable Availability of data and materials: Not applicable Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding: Not applicable Authors' contributions Wing-Keen Yap: Study design, Data acquisition, Quality control of data and algorithms, Data analysis and interpretation, Manuscript preparation, Manuscript editing, Manuscript review Ken-Hao Hsu: Quality control of data and algorithms, Data analysis and interpretation, Manuscript preparation, Manuscript editing, Manuscript review Ting-Hao Wang: Quality control of data and algorithms, Data analysis and interpretation, Manuscript preparation, Manuscript editing, Manuscript review Chia-Hsin Lin: Quality control of data and algorithms, Data analysis and interpretation, Manuscript preparation, Manuscript editing, Manuscript review Chung-Jan Kang: Manuscript preparation, Manuscript editing, Manuscript review Shih-Ming Huang: Manuscript preparation, Manuscript editing, Manuscript review Huan-Chun Lin: Manuscript editing, Manuscript review Tsung-Min Hung: Manuscript editing, Manuscript review Kai-Ping Chang: Study design, Study concept, Data analysis and interpretation, Manuscript preparation, Manuscript editing, Manuscript review Tsung-You Tsai: Study design, Data acquisition, Quality control of data and algorithms, Data analysis and interpretation, Statistical analysis, Manuscript preparation, Manuscript editing, Manuscript review Acknowledgements: Not applicable References Ferlay J, Colombet M, Soerjomataram I, Parkin DM, Piñeros M, Znaor A, et al. 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Shin S, Pak K, Kim IJ, Kim BS, Kim SJ. Prognostic Value of Tumor-to-Blood Standardized Uptake Ratio in Patients with Resectable Non-Small-Cell Lung Cancer. Nucl Med Mol Imaging. 2017;51(3):233-9. Zhang P, Chen W, Zhao K, Qiu X, Li T, Zhu X, et al. Tumor to liver maximum standardized uptake value ratio of FDG-PET/CT parameters predicts tumor treatment response and survival of stage III non-small cell lung cancer. BMC Medical Imaging. 2023;23(1):107. van den Bosch S, Dijkema T, Philippens MEP, Terhaard CHJ, Hoebers FJP, Kaanders J, et al. Tumor to cervical spinal cord standardized uptake ratio (SUR) improves the reproducibility of (18)F-FDG-PET based tumor segmentation in head and neck squamous cell carcinoma in a multicenter setting. Radiother Oncol. 2019;130:39-45. Hofheinz F, Apostolova I, Oehme L, Kotzerke J, van den Hoff J. Test-Retest Variability in Lesion SUV and Lesion SUR in (18)F-FDG PET: An Analysis of Data from Two Prospective Multicenter Trials. J Nucl Med. 2017;58(11):1770-5. van den Hoff J, Oehme L, Schramm G, Maus J, Lougovski A, Petr J, et al. The PET-derived tumor-to-blood standard uptake ratio (SUR) is superior to tumor SUV as a surrogate parameter of the metabolic rate of FDG. EJNMMI Res. 2013;3(1):77. Hofheinz F, Hoff J, Steffen IG, Lougovski A, Ego K, Amthauer H, et al. Comparative evaluation of SUV, tumor-to-blood standard uptake ratio (SUR), and dual time point measurements for assessment of the metabolic uptake rate in FDG PET. EJNMMI Res. 2016;6(1):53. Tables Tables 1 to 3 are available in the Supplementary Files section. Supplementary Files Tables.docx SupplementaryTables240314.docx NTRfigureS1.pdf Supplementary Figure Legends Supplementary Figure S1: Quality assessment of included studies by NOS. NOS, Newcastle-Ottawa scale. NTRfigureS2.pdf Supplementary Figure S2: Funnel plots of OS. OS, overall survival NTRfigureS3.pdf Supplementary Figure S3: Funnel plots of DFS. DFS, disease-free survival. NTRfigureS4.pdf Supplementary Figure S4: Funnel plots of DMFS. DMFS, distant metastasis-free survival. Cite Share Download PDF Status: Published Journal Publication published 09 May, 2024 Read the published version in Annals of Nuclear Medicine → Version 1 posted Reviewers agreed at journal 29 Mar, 2024 Reviewers invited by journal 27 Mar, 2024 Editor assigned by journal 24 Mar, 2024 First submitted to journal 22 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4152387","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":284505015,"identity":"008300f4-a779-4a28-a7af-3687f9b5c798","order_by":0,"name":"Wing-Keen Yap","email":"","orcid":"","institution":"Chang Gung Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wing-Keen","middleName":"","lastName":"Yap","suffix":""},{"id":284505016,"identity":"3947004b-d865-418f-b6da-f69fb040aa01","order_by":1,"name":"Ken-Hao Hsu","email":"","orcid":"","institution":"Chang Gung Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ken-Hao","middleName":"","lastName":"Hsu","suffix":""},{"id":284505017,"identity":"b6bda901-9a65-4c0d-83f2-b39eba4e775c","order_by":2,"name":"Ting-Hao Wang","email":"","orcid":"","institution":"Chang Gung Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ting-Hao","middleName":"","lastName":"Wang","suffix":""},{"id":284505018,"identity":"8648b6b0-5bf9-411b-8dc0-f1799cbae52d","order_by":3,"name":"Chia-Hsin Lin","email":"","orcid":"","institution":"Chang Gung Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chia-Hsin","middleName":"","lastName":"Lin","suffix":""},{"id":284505019,"identity":"bef7b937-f513-4a86-8693-4ee8b50b9777","order_by":4,"name":"Chung-Jan Kang","email":"","orcid":"","institution":"Chang Gung Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chung-Jan","middleName":"","lastName":"Kang","suffix":""},{"id":284505020,"identity":"f78aeb31-b165-435b-91d0-7955f528bdec","order_by":5,"name":"Shih-Ming Huang","email":"","orcid":"","institution":"Chang Gung Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shih-Ming","middleName":"","lastName":"Huang","suffix":""},{"id":284505021,"identity":"645d95d0-00a1-4f1b-b667-19b2a2721611","order_by":6,"name":"Huan-Chun Lin","email":"","orcid":"","institution":"Chang Gung Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Huan-Chun","middleName":"","lastName":"Lin","suffix":""},{"id":284505022,"identity":"cfa3a940-8270-4d50-a0a2-0f69d6ca6024","order_by":7,"name":"Tsung-Min Hung","email":"","orcid":"","institution":"Chang Gung Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tsung-Min","middleName":"","lastName":"Hung","suffix":""},{"id":284505023,"identity":"be439ac5-155a-4106-9033-a0720b195604","order_by":8,"name":"Kai-Ping Chang MD","email":"","orcid":"","institution":"Chang Gung Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kai-Ping","middleName":"","lastName":"Chang","suffix":"MD"},{"id":284505024,"identity":"617ce220-62aa-4637-888e-7b8837f9131b","order_by":9,"name":"Tsung-You Tsai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIie3PsQrCMBCA4QsH1+W0q0HBV7AInRRfpSI4uQnOhUJdBNd28hlc6iyCoy/QRRfnZhEHQdvq4mDsKJgfkiHk4xIAk+kHE/5zMSHuyxOyKpKWbdEYwMsJVpzUk0t2SwLfCPp4UnEI3Nnx5aiuSbuOIDI10U2grlyXpLZxIi91QgSUcaIhq6MrTk+SNNlLRU4IazriW5cX4XNBBhUIu6J4mAyYCjKsQqYyOgDbSK6MxukoRBFo/+L41lotZjAge3duZL20v5oH20xpSTGK7u+TP9/Pa5f7TXvHZDKZ/r0HN8dGSrwonDwAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-2486-7317","institution":"Chang Gung Memorial Hospital","correspondingAuthor":true,"prefix":"","firstName":"Tsung-You","middleName":"","lastName":"Tsai","suffix":""}],"badges":[],"createdAt":"2024-03-23 01:53:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4152387/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4152387/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12149-024-01933-5","type":"published","date":"2024-05-09T21:17:53+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53956307,"identity":"93a5f72e-5079-465d-8a76-a3115ba07d09","added_by":"auto","created_at":"2024-04-02 17:19:52","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":100091,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA flow diagram.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4152387/v1/f6977f177221d1340e61a36f.jpg"},{"id":53956303,"identity":"e85654ec-2c1f-4f7a-939c-fc8634bf6f76","added_by":"auto","created_at":"2024-04-02 17:19:52","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":125562,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the meta-analysis regarding OS. OS, overall survival. SCC, squamous cell carcinoma. NTR, Lymph Node to Primary Tumor Standardized Uptake Value Ratio.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4152387/v1/254bff0e21336ad8288c58d6.jpg"},{"id":53956312,"identity":"d4e3fae5-67ca-4071-a86c-0310e264f485","added_by":"auto","created_at":"2024-04-02 17:19:52","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":95867,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the meta-analysis regarding DFS. DFS, disease-free survival. SCC, squamous cell carcinoma. NTR, Lymph Node to Primary Tumor Standardized Uptake Value Ratio.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4152387/v1/b05d2cc0445badfc49c87bda.jpg"},{"id":53956309,"identity":"27c70087-374e-4c98-9404-d6277ff86c28","added_by":"auto","created_at":"2024-04-02 17:19:52","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":91570,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the meta-analysis regarding DMFS. DMFS, distant metastasis-free survival. SCC, squamous cell carcinoma. NTR, Lymph Node to Primary Tumor Standardized Uptake Value Ratio.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4152387/v1/57c7bc54c6a9a1ee83cd228a.jpg"},{"id":53956308,"identity":"c59bcf1c-15ed-48e6-9b7a-96b2bcddbee9","added_by":"auto","created_at":"2024-04-02 17:19:52","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":115674,"visible":true,"origin":"","legend":"\u003cp\u003eSensitivity analysis on OS, DFS and DMFS analysis. OS, overall survival. DFS, disease-free survival. DMFS, distant metastasis-free survival. SCC, squamous cell carcinoma. NTR, Lymph Node to Primary Tumor Standardized Uptake Value Ratio.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4152387/v1/b6592f16f92c524af61ef1c7.jpg"},{"id":56488097,"identity":"9e987e12-f5cd-44dc-9044-3e37d0afabdc","added_by":"auto","created_at":"2024-05-14 21:28:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":705477,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4152387/v1/76b2cfed-3b1b-4993-b18c-db807f3673f2.pdf"},{"id":53956302,"identity":"5624798f-a720-4f50-9920-d3a6e4e9a73e","added_by":"auto","created_at":"2024-04-02 17:19:52","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":27849,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-4152387/v1/910f2f7576f223ecd5fecd64.docx"},{"id":53956305,"identity":"1239a8e4-2d1c-4884-bb2f-c33112e75a01","added_by":"auto","created_at":"2024-04-02 17:19:52","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":23544,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplementaryTables240314.docx","url":"https://assets-eu.researchsquare.com/files/rs-4152387/v1/3f6709f8ea9d779cc4eca7e4.docx"},{"id":53956306,"identity":"5adef9fa-4fda-4970-a47a-c84c0a89b6b1","added_by":"auto","created_at":"2024-04-02 17:19:52","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":206515,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure Legends\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary Figure S1: Quality assessment of included studies by NOS. NOS, Newcastle-Ottawa scale.\u003c/p\u003e","description":"","filename":"NTRfigureS1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4152387/v1/6dd56ee5fe7e28f2c7008a8c.pdf"},{"id":53956311,"identity":"de375b54-8dcf-44d7-bbc2-2eb7e6809ab4","added_by":"auto","created_at":"2024-04-02 17:19:52","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":23332,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure S2: Funnel plots of OS. OS, overall survival\u003c/p\u003e","description":"","filename":"NTRfigureS2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4152387/v1/9fa2387af45fadc2921bdda1.pdf"},{"id":53956310,"identity":"9d94e395-d7a4-4984-841c-9ff73595820b","added_by":"auto","created_at":"2024-04-02 17:19:52","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":22358,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure S3: Funnel plots of DFS. \u0026nbsp;DFS, disease-free survival.\u003c/p\u003e","description":"","filename":"NTRfigureS3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4152387/v1/84b3dfa0593f271b75ebb942.pdf"},{"id":53956313,"identity":"d6bf36c8-be4f-4aec-be15-b28025ebab12","added_by":"auto","created_at":"2024-04-02 17:19:52","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":22480,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure S4: Funnel plots of DMFS. DMFS, distant metastasis-free survival.\u003c/p\u003e","description":"","filename":"NTRfigureS4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4152387/v1/621c393c2a7c4562547fd214.pdf"}],"financialInterests":"","formattedTitle":"The prognostic value of lymph node to primary tumor standardized uptake value ratio in cancer patients: A meta-analysis","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCancer stands as a prominent contributor to global mortality, accounting for nearly 10 million deaths annually(1, 2). Approximately one in five individuals experiences a cancer diagnosis during their lifetime, and in 2020 alone, an estimated 19.3 million new cases were identified(1, 2). Despite notable progress in early detection, surgical interventions, chemotherapy protocols, radiotherapy, immunotherapies, and comprehensive multidisciplinary approaches, cancer patients persistently grapple with suboptimal prognoses, as evidenced by a mortality rate of 1 in 10 individuals succumbing to the disease(1, 2).\u003c/p\u003e\n\u003cp\u003eThus, in the realm of oncology, the continuous pursuit of refined prognostic markers is imperative for tailoring treatment strategies and optimizing patient outcomes. Within this context, the Standardized Uptake Value (SUV) derived from positron emission tomography (PET) scans has emerged as a promising metric for characterizing tumor metabolic activity, and has been shown to have significant prognostic implication across diverse cancer types(3-9). Recently, attention has turned towards evaluating the prognostic significance of the Lymph Node to Primary Tumor Standardized Uptake Value Ratio (NTR) – an innovative parameter capturing the intricate relationship between primary tumors and associated lymph nodes(10-22). The rationale for focusing on NTR lies in its ability to provide a detailed insight into tumor behavior. Instead of just looking at the primary tumor SUV, considering lymph node involvement adds complexity and may reveal crucial information about the aggressiveness and progression of the disease.\u003c/p\u003e\n\u003cp\u003eWhile individual investigations have explored the potential prognostic implications of NTR across diverse cancer types, a comprehensive synthesis of existing evidence is notably absent. This meta-analysis seeks to address this critical gap by systematically reviewing and quantitatively analyzing collective findings from a spectrum of studies investigating the prognostic role of NTR in cancer patients. Through synthesizing data from diverse studies, our aim is to elucidate the collective impact of NTR on predicting outcomes such as overall survival, disease-free survival, and distant metastasis-free survival across various malignancies.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThe comprehensive meta-analysis was carried out meticulously, adhering strictly to the guidelines outlined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)\u003csup\u003e(23)\u003c/sup\u003e. Additionally, it was appropriately registered on PROSPERO.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSearch Strategy\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA thorough and systematic exploration was conducted across electronic databases, specifically PubMed, EMBASE, and the Cochrane Library, encompassing studies published from their inception until November 2023. The search strategy was developed by incorporating relevant keywords such as “lymph node to primary tumor,” “node to primary tumor,” “node to tumor,” “cancer,” “carcinoma,” “metastasis,” “tumor,” “tumour,” and “neoplasms.” These keywords were combined using appropriate Boolean operators. The complete details of the search can be found in Supplementary Table S1. Subsequently, a comprehensive evaluation of the full texts of the studies was carried out for inclusion.\u003c/p\u003e\n\u003cp\u003eMoreover, the bibliographies of previous systematic reviews were scrutinized, and eligible studies were examined to identify potentially relevant reports. To prevent duplication of articles, the gathered studies were imported into a citation manager (Endnote, version X9.3.3, Clarivate Analytics, Philadelphia, PA).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEligibility assessment\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTwo reviewers independently initiated searches within the databases, evaluating the titles and abstracts of identified studies in a double-blind manner to ensure impartiality. Subsequently, a detailed assessment of full texts followed, relying on the consensus reached by the reviewers concerning the selected abstracts. In instances of uncertainties or discrepancies, the senior author played a crucial role in making the ultimate judgment on eligibility. Overall, a unanimous agreement among all reviewers was pivotal in establishing eligibility.\u003c/p\u003e\n\u003cp\u003eThe process of selecting studies adhered to a meticulously defined set of inclusion and exclusion criteria, detailed as follows:\u003c/p\u003e\n\u003cp\u003eInclusion Criteria:\u003c/p\u003e\n\u003cp\u003e1. Enrollment of patients with diverse cancer types.\u003c/p\u003e\n\u003cp\u003e2. Investigation of the association between the NTR and survival outcomes.\u003c/p\u003e\n\u003cp\u003e3. Provision of hazard ratios (aHRs) accompanied by 95% confidence intervals (CIs) or presenting adequate information to facilitate their calculation.\u003c/p\u003e\n\u003cp\u003eExclusion Criteria:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eStudies not published in the English language.\u003c/li\u003e\n \u003cli\u003eStudies that lacked the provision of relevant information.\u003c/li\u003e\n \u003cli\u003eReviews, meta-analyses, conference abstracts, case reports, letters, or commentaries\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cem\u003eData extraction\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe independent execution of data extraction was carried out by two investigators. The extracted data encompassed various crucial elements, including primary author, publication year, patient recruitment period, study methodology, sample size, cancer staging, geographic location, aHR along with its corresponding 95% confidence CI for the primary endpoints of Overall Survival (OS), Disease-Free Survival (DFS), and Distant Metastasis-Free Survival (DMFS). Additionally, the duration of follow-up, SUV of the primary tumor or metastatic node (SUV-T, SUV-L), and the cut-off value of the NTR were also included.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData synthesis\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFollowing retrieval, the obtained data underwent comprehensive qualitative and quantitative analyses. The demographic and interventional characteristics of all incorporated studies were systematically compiled and presented in tabular format, subsequently undergoing a thorough analysis. Dichotomous outcomes, including OS, DFS, and DMFS, were represented as aHR with corresponding confidence intervals (CI). These outcomes were further subjected to a meta-analysis. In instances where there was an overlap in study populations, priority was accorded to more recent studies for the purpose of data synthesis.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAppraisal of study quality\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe assessment of bias employed the Newcastle-Ottawa Scale for the studies included in the analysis. This evaluation tool covered three critical domains—selection, comparability, and outcome—comprising a total of eight questions. Employing the established scoring framework, the studies were categorized into three tiers reflecting their quality levels. Specifically, studies scoring ≤3 were classified as low-quality, those scoring between 4 and 6 were designated as fair-quality, and studies with a score of ≥7 were acknowledged as high-quality(24).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe present meta-analysis utilized Comprehensive Meta-Analysis software, version 4 (Biostat, Englewood, NJ, USA). To compare the impact of different treatments on survival outcomes, aHRs with their corresponding 95% CIs were synthesized employing a random-effects model. This model was chosen to evenly distribute the influence of heterogeneity across the diverse studies incorporated in the analysis.\u003c/p\u003e\n\u003cp\u003eThe presence of heterogeneity among studies was assessed using both the Cochran Q-statistic and I\u003csup\u003e2\u003c/sup\u003e tests. Notably, substantial heterogeneity was defined as a Q-test p-value of \u0026lt;0.05 or an I\u003csup\u003e2\u003c/sup\u003e value exceeding 50%.\u0026nbsp;Sensitivity analysis by one-study-removed method was performed to confirm the robustness of these results.\u003c/p\u003e\n\u003cp\u003eTo evaluate the potential for publication bias, funnel plots and Egger's linear regression test were employed, with a significance threshold set at p \u0026lt; 0.05. If the results from Egger's test suggested the presence of publication bias, the trim-and-fill method was employed to adjust for this bias.\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were conducted with two-tailed tests, and statistical significance was defined as p \u0026lt; 0.05.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cem\u003eLiterature search and study identification\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe initial exploration of databases yielded a total of 53 entries, comprising 22 from PubMed, 1 from Cochrane, 30 from Embase\u0026nbsp;and 1 from additional source. A visual representation of the selection progression is provided in Figure 1, while the search methodology and algorithm are detailed in Supplementary Table S1.\u003c/p\u003e\n\u003cp\u003eUpon the removal of duplicates, 2 studies were excluded based on title, and an additional 11 were excluded based on abstract assessments. Subsequently, 21 studies underwent a thorough review of their full texts, resulting in the exclusion of 9 study due to specific reasons as outlined in Supplementary Table S2. Ultimately, 13 studies were considered suitable for qualitative analysis and 12 studies met the criteria for quantitative analysis.(11-22, 25)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCharacteristics of the included studies\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 provides a succinct overview of the studies included in this meta-analysis (including one for qualitative analysis). It is noteworthy that all the studies incorporated in this analysis adopted a retrospective research design. Furthermore, all these studies were conducted in Asian countries, specifically in Japan, Taiwan, China, and Korea, with the exception of one study from Morocco. The publication dates of these studies span a decade, ranging from 2013 to 2024.\u003c/p\u003e\n\u003cp\u003eIn total, the quantitative analysis involved 2037 patients recruited across studies within a recruitment timeline spanning from 2000 to 2020. The mean age of the patients varied from 43.2 to 66.5 years, with the male population constituting a proportion ranging from 0% to 97.3%. The duration of follow-up spanned from 10 to 62 months. The meta-analysis encompassed multiple cancer types, including 2 oral squamous cell carcinoma, 4 nasopharyngeal carcinoma, 1 esophageal cancer, 1 endometrioid endometrial carcinoma, 1 uterine cervix invasive squamous cell carcinoma, and 2 non-small cell lung carcinomas. A total of 8 studies reported cancer stage according to the AJCC TNM staging system, while 2 studies reported stage according to the International Federation of Gynecology and Obstetrics Staging System. All studies focused on the association between pretreatment NTR and survival outcomes. The reported aHR with 95% CIs for survival outcomes, including OS, DFS, and DMFS, were directly extracted from the included studies. (Table 2)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eQuality Assessment\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe present meta-analysis encompassed a comprehensive compilation of 13\u0026nbsp;studies, each undergoing meticulous scrutiny for methodological rigor utilizing the Newcastle-Ottawa scale. The results of this evaluation revealed that\u0026nbsp;10\u0026nbsp;out of the 13\u0026nbsp;eligible studies achieved scores equal to or exceeding 7 points, indicating fair quality across the majority of the studies. The remaining three studies received 5-6 points on the scale. Supplementary Figure S1 offers a more detailed visualization of the insights derived from the studies included in this analysis.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMeta-analysis results\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOverall Survival\u003c/p\u003e\n\u003cp\u003eSeven studies provided aHRs relevant to OS.(13, 14, 16, 17, 19, 21, 26) The outcomes of the meta-analysis revealed a significant association, indicating that higher NTR was correlated with worse OS (aHR 2.21, 95% CI 1.63 to 2.99) in a low-heterogeneity context (I\u003csup\u003e2\u003c/sup\u003e = 10.15%, p = 0.35; Figure 2). Although overall heterogeneity was low, subgroup analyses were still\u0026nbsp;conducted to explore the impact of NTR in different tumor types. For nasopharyngeal carcinoma, NTR was significantly associated with worse OS (aHR 2.64, 95% CI 1.38 to 5.05; Figure 2) with low heterogeneity (I\u003csup\u003e2\u003c/sup\u003e = 0%, p = 0.76; Figure 2).(13, 21) In studies focusing on patients with oral cavity SCC, NTR was significantly associated with worse OS (aHR 4.60, 95% CI 2.03 to 10.47; Figure 2) with minimal heterogeneity (I\u003csup\u003e2\u003c/sup\u003e = 0%, p = 0.87; Figure 2).(14, 17) In each subgroup, heterogeneity was even lower, and the pooled hazard ratio remained consistent when classified by different cancer types. The results of various stratified analyses (including region, NTR cut-off values, median SUV-L, median SUV-T) for the impact of NTR on overall survival were shown in Table 3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDisease-free survival\u003c/p\u003e\n\u003cp\u003eIncorporating data from 7 studies that offered aHRs pertinent to DFS, the outcomes of the meta-analysis unveiled a significant correlation.(11-14, 18, 19, 21) Specifically, the meta-analysis showcased that NTR was also notably linked to worse DFS (aHR 3.27, 95% CI 2.12 to 5.05; Figure 3) (I\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e= 23.71%, p = 0.25; Figure 3).\u003c/p\u003e\n\u003cp\u003eDistant metastasis-free survival\u003c/p\u003e\n\u003cp\u003eIncorporating data from five studies that provided aHRs relevant to DMFS, the outcomes of the meta-analysis revealed a significant and affirmative correlation.(15, 16, 20, 21, 25)\u0026nbsp;Specifically, the meta-analysis demonstrated that NTR was notably linked to worse DMFS (aHR\u0026nbsp;2.07, 95% CI 1.55\u0026nbsp;to 2.78), with minimal heterogeneity (I\u003csup\u003e2\u003c/sup\u003e = 0%, p = 0.62; Figure 4). While the overall heterogeneity was low, subgroup analyses were conducted to explore the impact of NTR in different tumor types. In studies focusing on patients with nasopharyngeal carcinoma, NTR was significantly associated with worse DMFS (aHR 2.21, 95% CI 1.48\u0026nbsp;to 3.30; Figure 4) with minimal heterogeneity (I\u003csup\u003e2\u003c/sup\u003e = 0%, p = 0.51; Figure 4).(15, 21, 25)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublication bias and Sensitivity Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunnel plots and Egger’s test were conducted to examine publication bias (Figure S2-S4). Publication bias existed in the analysis of OS (p = 0.001) DFS (p= 0.01). By the Trim and Fill test, three potential missing studies were found in the OS analysis, and the recalculated pooled HR for OS was 1.95 (95% CI: 1.36–2.79); two potential missing studies were identified in the analysis of DFS and the recalculated pooled HR was 3.09 (95% CI: 2.00, 4.77) (Figure S2-S4). The results of these tests indicated that publication bias did not influence the final results of the meta-analysis. The results of the sensitivity analysis showed that removing individual studies did not affect the results of the meta-analysis during the analysis of the relationship between NTR and OS, DFS, DMFS (Figure 5), indicating the reliability of our results.\u0026nbsp;\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis meta-analysis extracted the aHR of OS from 7 studies (778 patients) and determined a statistically significant association between the NTR and OS of cancer patient. Low heterogeneity assessed by Cochran Q-statistic and I\u003csup\u003e2\u003c/sup\u003e tests imply that the diverse background conditions of patients did not have a statistically significant impact on the association between the NTR and overall survival (OS). Subgroup analysis results demonstrated that the prognostic significance of the NTR for OS remained consistent across different cancer types, patient number, NTR cut-off values, median SUV-L, median SUV-T and research regions. In addition, after adjusting the synthesized outcome for publication bias via Trim and Fill test, the adjusted pooled aHR remained significant, reinforcing the reliability and robustness of our results. Similarly, a high NTR in cancer patients served as an unfavorable prognostic factor for DFS and DMFS. Notably, this study is the first meta-analysis to demonstrate the prognostic role of the NTR with respect to survival outcomes in cancer patients. Our meta-analysis provides a consolidated perspective that goes beyond individual cancer types, contributing to a more unified understanding of NTR\u0026rsquo;s prognostic relevance. These insights hold promise for informing clinical decision-making, facilitating personalized therapeutic interventions, and contribute to advancements in cancer care.\u003c/p\u003e \u003cp\u003eThe rationale for focusing on NTR lies in its potential to offer a nuanced understanding of tumor behavior. Beyond assessing primary tumor SUV in isolation, considering lymph node involvement introduces a layer of complexity that may harbor pivotal insights into disease aggressiveness and progression. The underlying mechanisms for the association of higher NTR and worse survival outcomes are not fully understood, but it has been suggested that higher NTR may reflect a state of more aggressive tumor behavior, which can promote tumor growth and metastasis(17). In a surgical series investigating oral squamous cell carcinoma, Ishibashi-Kanno et al. observed a notable association between histopathological diagnosis of LN metastasis and elevated NTR(17). Furthermore, their findings revealed a significant correlation between the presence of extracapsular spread and elevated NTR(17). Similarly, in a surgical series study of endometrioid endometrial carcinoma, Chung et al. showed a positive association of NTR with stage, lymph node metastasis, lymph vascular space invasion, tumor grade, and recurrence in endometrioid endometrial carcinoma patients(12). The study suggests that the relative metabolic activity of lymph nodes serves as a valuable surrogate functional marker indicative of tumor aggressiveness(12). This argument is further supported by 4 previous studies on different cancer types demonstrating a significant association between elevated NTR and distant metastatic potential, and ultimately, poor prognosis(10, 15, 16, 20).\u003c/p\u003e \u003cp\u003eAlthough pretreatment lymph node SUVmax as a sole parameter has been shown to be a significant prognosticator in various cancer types(8, 9, 27\u0026ndash;31), there are some well-known drawbacks of using nonnormalized SUV, e.g., partial volume effect, uptake time dependence of the SUV, and interstudy variability of image acquisition and reconstruction parameters, which could possibly undermine the reliability of the SUVmax values(12, 32\u0026ndash;34). The strength of NTR is that by normalizing the lymph node SUVmax to the primary tumor SUVmax, NTR may be less susceptible to the inter-scanner variability, and may have better generalizability(20, 35\u0026ndash;41). In a study on esophageal squamous cell carcinoma patients, Lin et al. assessed the potential impact of employing different PET/CT scanners on the NTR and lymph node SUVmax, and demonstrated that the variation of the optimal cutoff values and the interquartile range of the NTR obtained by the two different PET/CT scanners was minimal, while the non-normalized lymph node SUVmax suffered significantly greater inter-scanner variability(20).\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eLimitations of the study\u003c/h2\u003e \u003cp\u003eIt is noteworthy that the included studies in this meta-analysis were all conducted in Asian countries, which may limit the generalizability of the findings to other populations. Additionally, the studies varied in terms of their sample sizes, cancer types, and endpoints measured, which may have contributed to the observed heterogeneity in the meta-analysis. However, the authors employed appropriate statistical methods to account for this heterogeneity and provide a comprehensive synthesis of the available evidence. The quality assessment of the included studies using the Newcastle-Ottawa Scale (NOS) indicated that the majority of the studies were of fair to high quality. This suggests that the findings of this meta-analysis are based on relatively robust evidence. Future studies should aim to validate these findings in larger and more diverse patient populations, and investigate the underlying mechanisms for the observed association between NTR and survival outcomes.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIn conclusion, this meta-analysis provides evidence for a significant association between elevated NTR and worse survival outcomes in cancer patients. These findings have important implications for further research, and highlight the potential utility of NTR as a prognostic biomarker in cancer.\u003c/p\u003e"},{"header":"Abbreviations","content":"SUV, Standardized Uptake Value; PET, positron emission tomography; NTR, Lymph Node to Primary Tumor Standardized Uptake Value Ratio; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; aHR, adjusted hazard ratio; CI, confidence interval; OS, overall survival; DFS, disease free survival; DMFS distant metastasis-free survival; SCC, squamous cell carcinoma; SUV-T standardized uptake value of the primary tumor; SUV-L standardized uptake value of the lymph node"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial disclosure:\u0026nbsp;\u003c/strong\u003eNone declared.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interests:\u0026nbsp;\u003c/strong\u003eNone declared.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWing-Keen Yap: Study design, Data acquisition, Quality control of data and algorithms, Data analysis and interpretation, Manuscript preparation, Manuscript editing, Manuscript review\u003c/p\u003e\n\u003cp\u003eKen-Hao Hsu:\u0026nbsp;Quality control of data and algorithms, Data analysis and interpretation, Manuscript preparation, Manuscript editing, Manuscript review\u003c/p\u003e\n\u003cp\u003eTing-Hao Wang: Quality control of data and algorithms, Data analysis and interpretation, Manuscript preparation, Manuscript editing, Manuscript review\u003c/p\u003e\n\u003cp\u003eChia-Hsin Lin:\u0026nbsp;Quality control of data and algorithms, Data analysis and interpretation, Manuscript preparation, Manuscript editing, Manuscript review\u003c/p\u003e\n\u003cp\u003eChung-Jan Kang: Manuscript preparation, Manuscript editing, Manuscript review\u003c/p\u003e\n\u003cp\u003eShih-Ming Huang: Manuscript preparation, Manuscript editing, Manuscript review\u003c/p\u003e\n\u003cp\u003eHuan-Chun Lin: Manuscript editing, Manuscript review\u003c/p\u003e\n\u003cp\u003eTsung-Min Hung: Manuscript editing, Manuscript review\u003c/p\u003e\n\u003cp\u003eKai-Ping Chang: Study design, Study concept, Data analysis and interpretation, Manuscript preparation, Manuscript editing, Manuscript review\u003c/p\u003e\n\u003cp\u003eTsung-You Tsai: Study design, Data acquisition, Quality control of data and algorithms, Data analysis and interpretation, Statistical analysis, Manuscript preparation, Manuscript editing, Manuscript review\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFerlay J, Colombet M, Soerjomataram I, Parkin DM, Pi\u0026ntilde;eros M, Znaor A, et al. 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Radiat Oncol J. 2013;31(3):111-7.\u003c/li\u003e\n\u003cli\u003eIshibashi-Kanno N, Yamagata K, Hara T, Takaoka S, Fukuzawa S, Uchida F, et al. Prognostic prediction using maximum standardized uptake value ratio of lymph node-to-primary tumor in preoperative PET-CT for oral squamous cell carcinoma. J Stomatol Oral Maxillofac Surg. 2023;124(5):101489.\u003c/li\u003e\n\u003cli\u003eKim YH, Yoon HJ, Kim Y, Kim BS. Axillary Lymph Node-to-Primary Tumor Standard Uptake Value Ratio on Preoperative (18)F-FDG PET/CT: A Prognostic Factor for Invasive Ductal Breast Cancer. J Breast Cancer. 2015;18(2):173-80.\u003c/li\u003e\n\u003cli\u003eLi TC, Zhao X, Liu YN, Wang GL, Liu KF, Zhao K. Prognostic value of node-to-primary tumor maximum standardized uptake value ratio in T1-4N1-3M0 non-small cell lung cancer patients treated with concurrent chemo-radiotherapy. Nucl Med Commun. 2022;43(8):901-7.\u003c/li\u003e\n\u003cli\u003eLin CH, Hung TM, Chang YC, Hsieh CH, Shih MC, Huang SM, et al. 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Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies: The PRISMA-DTA Statement. Jama. 2018;319(4):388-96.\u003c/li\u003e\n\u003cli\u003eWells G, Shea B, O\u0026apos;Connell J. The Newcastle-Ottawa Scale (NOS) for Assessing The Quality of Nonrandomised Studies in Meta-analyses. Ottawa Health Research Institute Web site. 2014;7.\u003c/li\u003e\n\u003cli\u003eKong FF, Pan GS, Ni MS, Du CR, Hu CS, Ying HM. Prognostic value of lymph node-to-primary tumor ratio of PET standardized uptake value for nasopharyngeal carcinoma: a recursive partitioning risk stratification analysis. Ther Adv Med Oncol. 2024;16:17588359241233235.\u003c/li\u003e\n\u003cli\u003eLiu T, David M, Batstone M, Clark J, Low TH, Goldstein D, et al. The utility of postoperative radiotherapy in intermediate-risk oral squamous cell carcinoma. Int J Oral Maxillofac Surg. 2021;50(2):143-50.\u003c/li\u003e\n\u003cli\u003eHong CM, Park S-H, Chong GO, Lee YH, Jeong JH, Lee S-W, et al. Enhancing prognosis prediction using pre-treatment nodal SUVmax and HPV status in cervical squamous cell carcinoma. Cancer Imaging. 2019;19(1):43.\u003c/li\u003e\n\u003cli\u003eLee SJ, Kay CS, Kim YS, Son SH, Kim M, Lee SW, et al. Prognostic value of nodal SUVmax of 18F-FDG PET/CT in nasopharyngeal carcinoma treated with intensity-modulated radiotherapy. Radiat Oncol J. 2017;35(4):306-16.\u003c/li\u003e\n\u003cli\u003eHsieh CE, Cheng NM, Chou WC, Venkatesulu BP, Chou YC, Liao CT, et al. Pretreatment Primary Tumor and Nodal SUVmax Values on 18F-FDG PET/CT Images Predict Prognosis in Patients With Salivary Gland Carcinoma. Clin Nucl Med. 2018;43(12):869-79.\u003c/li\u003e\n\u003cli\u003eVatankulu B, Şanlı Y, Kaytan Sağlam E, Kuyumcu S, \u0026Ouml;zkan ZG, Yılmaz E, et al. Does Metastatic Lymph Node SUVmax Predict Survival in Patients with Esophageal Cancer? Mol Imaging Radionucl Ther. 2015;24(3):120-7.\u003c/li\u003e\n\u003cli\u003eBong-Il S, Kyoung Sook W. Prognostic value of nodal SUVmax on pretreatment F-18 FDG PET/CT in patients with gastric cancer. Journal of Nuclear Medicine. 2014;55(supplement 1):74.\u003c/li\u003e\n\u003cli\u003eHamberg LM, Hunter GJ, Alpert NM, Choi NC, Babich JW, Fischman AJ. The dose uptake ratio as an index of glucose metabolism: useful parameter or oversimplification? J Nucl Med. 1994;35(8):1308-12.\u003c/li\u003e\n\u003cli\u003eKeyes JW, Jr. SUV: standard uptake or silly useless value? J Nucl Med. 1995;36(10):1836-9.\u003c/li\u003e\n\u003cli\u003eHuang S-C. Anatomy of SUV. Nuclear Medicine and Biology. 2000;27(7):643-6.\u003c/li\u003e\n\u003cli\u003eWang C, Zhao K, Hu S, Huang Y, Ma L, Li M, et al. The PET-Derived Tumor-to-Liver Standard Uptake Ratio (SUV (TLR) ) Is Superior to Tumor SUVmax in Predicting Tumor Response and Survival After Chemoradiotherapy in Patients With Locally Advanced Esophageal Cancer. Front Oncol. 2020;10:1630.\u003c/li\u003e\n\u003cli\u003eShin S, Pak K, Kim IJ, Kim BS, Kim SJ. Prognostic Value of Tumor-to-Blood Standardized Uptake Ratio in Patients with Resectable Non-Small-Cell Lung Cancer. Nucl Med Mol Imaging. 2017;51(3):233-9.\u003c/li\u003e\n\u003cli\u003eZhang P, Chen W, Zhao K, Qiu X, Li T, Zhu X, et al. Tumor to liver maximum standardized uptake value ratio of FDG-PET/CT parameters predicts tumor treatment response and survival of stage III non-small cell lung cancer. BMC Medical Imaging. 2023;23(1):107.\u003c/li\u003e\n\u003cli\u003evan den Bosch S, Dijkema T, Philippens MEP, Terhaard CHJ, Hoebers FJP, Kaanders J, et al. Tumor to cervical spinal cord standardized uptake ratio (SUR) improves the reproducibility of (18)F-FDG-PET based tumor segmentation in head and neck squamous cell carcinoma in a multicenter setting. Radiother Oncol. 2019;130:39-45.\u003c/li\u003e\n\u003cli\u003eHofheinz F, Apostolova I, Oehme L, Kotzerke J, van den Hoff J. Test-Retest Variability in Lesion SUV and Lesion SUR in (18)F-FDG PET: An Analysis of Data from Two Prospective Multicenter Trials. J Nucl Med. 2017;58(11):1770-5.\u003c/li\u003e\n\u003cli\u003evan den Hoff J, Oehme L, Schramm G, Maus J, Lougovski A, Petr J, et al. The PET-derived tumor-to-blood standard uptake ratio (SUR) is superior to tumor SUV as a surrogate parameter of the metabolic rate of FDG. EJNMMI Res. 2013;3(1):77.\u003c/li\u003e\n\u003cli\u003eHofheinz F, Hoff J, Steffen IG, Lougovski A, Ego K, Amthauer H, et al. Comparative evaluation of SUV, tumor-to-blood standard uptake ratio (SUR), and dual time point measurements for assessment of the metabolic uptake rate in FDG PET. EJNMMI Res. 2016;6(1):53.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"annals-of-nuclear-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"anme","sideBox":"Learn more about [Annals of Nuclear Medicine](http://link.springer.com/journal/12149)","snPcode":"12149","submissionUrl":"https://www.editorialmanager.com/anme/default2.aspx","title":"Annals of Nuclear Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4152387/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4152387/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eThe lymph node to primary tumor standardized uptake value ratio (NTR) is an innovative parameter derived from positron emission tomography (PET) scans that captures the intricate relationship between primary tumors and associated lymph nodes. This meta-analysis aimed to investigate the prognostic value of NTR in cancer patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A systematic search of PubMed, Cochrane, and Embase databases was conducted to identify studies investigating the association between NTR and survival outcomes in cancer patients. The pooled adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) were calculated using a random-effects model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Twelve studies comprising a total of 2037 patients were included in the meta-analysis. Elevated NTR was significantly associated with worse overall survival aHR (2.21, 95% CI 1.63 to 2.99), disease-free survival aHR (3.27, 95% CI 2.12 to 5.05), and distant metastasis-free survival aHR (2.07, 95% CI 1.55 to 2.78) in cancer patients. Subgroup analyses by cancer type showed consistent results across various malignancies, including head and neck squamous cell carcinoma, endometrial carcinoma, lung cancer, breast cancer, and nasopharyngeal carcinoma.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e This meta-analysis provides evidence for a significant association between elevated NTR and worse survival outcomes in cancer patients. Elevated NTR may serve as a useful prognostic biomarker for cancer patients, and could potentially be used to guide treatment decisions and monitor disease progression. Future studies should aim to validate these findings in larger and more diverse patient populations, and investigate the underlying mechanisms for the observed association between NTR and survival outcomes.\u003c/p\u003e","manuscriptTitle":"The prognostic value of lymph node to primary tumor standardized uptake value ratio in cancer patients: A meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-02 17:19:47","doi":"10.21203/rs.3.rs-4152387/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-03-30T02:05:21+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-27T11:38:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-25T02:16:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Annals of Nuclear Medicine","date":"2024-03-22T21:52:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"annals-of-nuclear-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"anme","sideBox":"Learn more about [Annals of Nuclear Medicine](http://link.springer.com/journal/12149)","snPcode":"12149","submissionUrl":"https://www.editorialmanager.com/anme/default2.aspx","title":"Annals of Nuclear Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"69455562-1f54-4f24-8ed8-0da7205cf49a","owner":[],"postedDate":"April 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-05-14T21:21:50+00:00","versionOfRecord":{"articleIdentity":"rs-4152387","link":"https://doi.org/10.1007/s12149-024-01933-5","journal":{"identity":"annals-of-nuclear-medicine","isVorOnly":false,"title":"Annals of Nuclear Medicine"},"publishedOn":"2024-05-09 21:17:53","publishedOnDateReadable":"May 9th, 2024"},"versionCreatedAt":"2024-04-02 17:19:47","video":"","vorDoi":"10.1007/s12149-024-01933-5","vorDoiUrl":"https://doi.org/10.1007/s12149-024-01933-5","workflowStages":[]},"version":"v1","identity":"rs-4152387","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4152387","identity":"rs-4152387","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}