Clinical usefulness of nutritional and immunological indices to distinguish gallbladder carcinoma from benign disease

Clinical usefulness of nutritional and immunological indices to distinguish gallbladder carcinoma from benign disease | 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 Clinical usefulness of nutritional and immunological indices to distinguish gallbladder carcinoma from benign disease Daisuke Ogawa, Hiromitsu Hayashi, Shinsei Yumoto, Rumi Itoyama, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5786974/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 May, 2025 Read the published version in International Journal of Clinical Oncology → Version 1 posted 5 You are reading this latest preprint version Abstract Background It is challenging to accurately and preoperatively diagnose gallbladder carcinoma (GBC) because patients are often asymptomatic or present with nonspecific symptoms that mimic common benign diseases in radiological findings. In this study, we evaluated the clinical usefulness of nutritional and immunological indices to distinguish GBC from benign disease. Methods This study included 113 patients who underwent surgical resection for suspected GBC (37 benign and 76 GBC cases by pathological diagnosis). As the nutritional and immunological indices, the geriatric nutritional risk index (GNRI), modified Glasgow prognostic score (mGPS), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and prognostic nutrition index (PNI) were examined, and their usefulness in distinguishing GBC from benign disease was determined using logistic regression analyses. Results GBC cases displayed significantly worse nutritional and immunological status in the GNRI, mGPS, NLR, PLR, and PNI compared with those of the benign cases. As the predictive factors to distinguish GBC from benign disease, age > 75 years, GNRI < 101.7, and PLR ≥ 1.76 were identified by multivariate logistic regression analyses. Conclusion Patients with GBC showed poor nutritional or immunological status compared with patients with benign disease, and a low GNRI and high PLR may be noninvasive predictors of GBC. Gallbladder Neoplasm Gallbladder Diseases Nutrition Assessment Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Gallbladder carcinoma (GBC) is one of the common hepatobiliary malignancies, predominantly occurring in certain regions including Eastern Europe, East Asia, Southeast Asia, and Latin America [ 1 , 2 ]. The prognosis of GBC is very poor, with 5-year survival rates of 5–20% even after surgery because of the aggressive tumor biology, complicated anatomic position, and advanced stage at diagnosis [ 3 ]. Early tumors are often incidentally detected on radiological imaging or by cholecystectomy performed for another indication. It is challenging to accurately and preoperatively diagnose GBC because patients are often asymptomatic or present with nonspecific symptoms that mimic common benign diseases in radiological findings. Contrast-enhanced computed tomography (CT), magnetic resonance imaging (MRI), and fluorodeoxyglucose-positron emission tomography/CT (FDG-PET/CT) have been reported to be useful for GBC diagnosis, but their utility remains controversial [ 4 – 8 ]. Typical imaging features of localized GBC include asymmetric gallbladder wall thickening, polyps larger than 10 mm, and a solid mass replacing the gallbladder lumen [ 9 ]. Advanced tumors are often infiltrative and can be confused on CT, MRI, and FDG-PET/CT with xanthogranulomatous cholecystitis (XGC). It is clinically important to accurately diagnose GBC and distinguish it from benign gallbladder diseases, which would contribute to improving the prognostic outcome of this deadly disease and avoiding unnecessary surgical treatment for benign disease. In several malignant diseases, the practical use of nutritional and immunological status for predicting prognostic outcomes has been a research hotspot in recent years [ 10 – 16 ]. Furthermore, in GBC, a low geriatric nutritional risk index (GNRI) has been shown to be an independent poor prognostic factor after radical surgery [ 11 ]. However, the usefulness of nutritional and immunological indices in distinguishing GBC from benign disease is uncertain. Here, we investigated the clinical utility of nutritional and immunological indices in distinguishing GBC from benign disease. Patients and Methods Study population From April 2007 to December 2023, 113 patients underwent surgical excision or curative surgery for suspected GBC at Kumamoto University Hospital. All patients underwent transabdominal ultrasonography (TUS) or enhanced CT with findings suspicious for GBC, and further examinations such as an endoscopic ultrasonography (EUS) or FDG-PET/CT were performed. The inclusion criteria were as follows: 1) patients with suspicion of GBC by ultrasonography or CT such as a gallbladder mass, gallbladder wall thickening, or enlarged gallbladder polyps larger than 10 mm; 2) patients who received further diagnostic examinations such as MRI, EUS, transpapillary bile cytology, and FDG-PET/CT and were suspected of having GBC by radiologists and gastroenterological endoscopists; and 3) patients who had undergone surgical excision or curative surgery for suspected GBC based on the surgeons' mutual agreement. In accordance with the pathological diagnosis, the subjects were divided into 37 patients with benign disease and 76 patients with GBC, and their clinical characteristics are summarized in Table 1 . The benign group included cholecystitis (n = 14), XGC (n = 8), adenomyomatosis (ADM) (n = 7), gallbladder polyps (n = 5), hyperplasia (n = 2), and xanthoma (n = 1). In the benign group, inflammatory diseases such as cholecystitis and XGC accounted for more than half of the cases, followed by ADM and gallbladder polyps. In the malignant group, more than 75% of cases were T2 or less, and 23% had advanced GBC of T3 or T4 (Table 1 ). All patients provided written informed consent, and the Ethics Committee of Kumamoto University approved this study's protocol. Our institutional ethical review board approved this study (IRB No. 1801), and all procedures met the guidelines of the Declaration of Helsinki. Nutritional and immunological indices The GNRI, modified Glasgow prognostic score (mGPS), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and prognostic nutrition index (PNI) were obtained as nutritional and immunological indices. Statistical analysis Continuous variables are presented as the median and interquartile range, and categorical values are presented as absolute and relative frequencies. Variables were compared using the Mann–Whitney U test. Categorical data were subjected to the chi-square test or Fisher's exact test, as appropriate. Receiver operating characteristic (ROC) curves were constructed for the nutritional indices to compare the benign and malignant groups of gallbladder lesions, optimal cutoff values were determined, and the areas under the curve (AUCs) were calculated. The cutoff values were determined by ROC–AUC analysis and set for continuous variables in univariate and multivariate logistic regression analyses. All statistical analyses were performed using JMP Pro, version 16.0.0 (SAS Institute, Cary, NC, USA). A P-value < 0.05 was considered statistically significant. Results Comparison of clinical factors and conventional diagnostic examinations between the benign and GBC groups The GBC group had a significantly higher age and significantly lower preoperative albumin levels compared with those in the benign group (P=0.013 and P=0.028, respectively) ( Table 1 ). In addition, the results of preoperative diagnostic tools such as tumor markers, cytology, and radiological imaging between the benign and malignant groups of the entire cohort are summarized in Table 2 . There were no significant differences in the serum tumor markers carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) between the two groups. Although cases with preoperative biliary cytology examinations were limited in both groups at approximately 24%, the positive rate (cytology class IV and V) was significantly higher in the GBC group at 44.4% compared with that in the benign group (0%) (P=0.017), while the false-negative rate was 55.6% in the GBC group. The EUS examination rate was significantly higher in the benign group at 89.2% compared with 67.1% in the GBC group (P=0.016), and interestingly, 84.4% of the benign group received a suspected GBC result. The main finding on EUS was an irregular surface protuberance/mass in 82.3% of the GBC group and 50.0% of the benign group. FDG-PET/CT was performed in approximately 60% of patients in both groups, and there was no significant difference in the SUVmax values between the two groups. In the benign group with positive local uptake, the pathological diagnoses were mainly inflammatory diseases such as chronic cholecystitis (42.8%), XGC (31.3%), and ADM (12.5%) ( Table 2 ). Comparison of nutritional and immunological indices between the benign and GBC groups Five nutritional and immunological indices (GNRI, mGPS, NLR, PLR, and PNI) were compared between the benign and GBC groups. The AUC and cutoff values for the GNRI, NLR, PLR, and PNI were calculated using ROC–AUC analyses ( Figure 1 ). The AUC values of the GNRI, NLR, PLR, and PNI were 0.61, 0.57, 0.58, and 0.61, respectively, and the sensitivity and specificity were 0.62 and 0.70, 0.75 and 0.43, 0.89 and 0.27, and 0.30 and 0.89, respectively. The GBC group exhibited significantly higher values for the mGPS, NLR, and PLR indices, whereas the GNRI and PNI indices in the GBC group were significantly lower than those in the benign group ( Table 3 and Figure 2 ). Univariate and multivariate analyses of clinical factors associated with GBC Univariate and multivariate analyses were performed to elucidate the preoperative factors to discriminate GBC from benign disease ( Table 4 ). In the comparison between the benign and GBC groups, high age (≥75 years), low GNRI, high PLR, and low PNI were significantly associated with GBC in univariate analysis (odds ratios and P-values: 2.52 and 0.039, 3.62 and 0.0027, 3.15 and 0.029, and 3.36 and 0.039, respectively). In multivariate analyses (logistic regression analyses), high age (≥75 years), low GNRI, and high PLR were significantly associated with GBC (odds ratios and P-values: 3.27 and 0.014, 2.67 and 0.044, and 3.82 and 0.024, respectively). Comparison of nutritional and immunological indices between benign and early GBC (below T1) Excluding advanced GBC (≥T2), we further compared the nutritional and immunological indices between the benign group and those with early-stage GBC (Tis-T1), which may be more difficult to discriminate from benign disease by conventional diagnostic tools. In total, 37 benign cases and 18 early GBC (≤ T1) cases were compared for the nutritional and immunological indices ( Figure 3 ). The AUC values of the GNRI, NLR, PLR, and PNI were 0.70, 0.46, 0.55, and 0.67, respectively, and the sensitivity and specificity were 0.72 and 0.70, 1.0 and 0.13, 0.97 and 0.17, and 0.56 and 0.76, respectively. The GNRI in the early GBC group was significantly lower compared with that in the benign group (P=0.0049) ( Table 5 and Figure 4 ). The other indices (mGPS, NLR, PLR, and PNI) were not significantly different between the two groups. In logistic regression analyses, a low GNRI was the only significant predictive factor for early GBC (Tis-T1) (the odds ratio and P-value were 6.15 and 0.0044, respectively) ( Table 6 ). Comparison of surgical outcomes between the benign and GBC groups Comparisons of the surgical outcomes between the benign and GBC groups are shown in Table 7 . The GBC group had more highly invasive surgeries. The GBC group had significantly higher rates of laparotomy (P=0.0033), extrahepatic bile duct resection (P<0.0001), longer operative times (P<0.0001), greater blood loss (P<0.0001), higher rates of blood transfusion (P=0.041), higher postoperative hospital days (P<0.0001), and more postoperative complications (P=0.017) compared with those in the benign group. Discussion This study showed that aggravated nutritional and immunological status were detectable in GBC compared with benign disease. In particular, a low GNRI and high PLR were highly associated with GBC. Furthermore, a low GNRI was detectable even in early GBC (Tis-T1). These results suggested that nutritional and immunological indices could be simple diagnostic tools to predict GBC. To our knowledge, this is the first report showing that nutritional and immunological indices are useful in discriminating GBC from benign disease. Host–tumor interactions between cancer cells and host nutritional immunity are well known to have a significant impact on the malnutrition status and immune-suppression in cancer patients. Metabolic and nutritional disorders in cancer carriers can develop not only in advanced cancers but also in early-stage cancers [ 17 ]. The nutritional and immunological indices examined in this study have been reported to be prognostic and predictive factors in hepatobiliary cancers. The GNRI depends on body weight and the serum albumin level, both of which represent nutritional status. For example, in GBC, a low GNRI (< 98) and a high C-reactive protein/albumin ratio (≥ 0.07) have been reported as worse prognostic factors after surgery [ 10 , 11 ]. The present study first advocated the utility of the GNRI in discriminating GBC from benign gallbladder diseases, and the practical use was apparent even in early GBC (Tis-T1). The NLR and PLR are nutritional indices using blood cell components and are complementary to each other. The total lymphocyte count, a classic nutritional indicator [ 18 ], has shown usefulness as a marker of malnutrition, such as low BMI and weight loss, along with serum albumin levels [ 19 ]. In addition, lymphocytes are widely used as an indicator of immunocompetence, since they act in a tumor-suppressive manner and play a role in tumor immunity [ 20 ]. Platelets, like neutrophils, are blood cell components that play a role in inflammatory reactions, and thrombocytosis is often observed in solid tumor patients with chronic inflammation [ 21 ]. Since platelets themselves are deeply involved in cancer progression [ 22 ], the PLR, which is the ratio of platelet and lymphocyte counts, represents the inflammatory and immunological status. In the present study, a high PLR may reflect a platelet increase associated with the inflammatory response and immunosuppression in GBC. The PLR also has been reported to be a prognostic factor after papillary carcinoma surgery [ 14 ]. Conventional diagnostic tools, including tumor markers, radiological imaging, ultrasonography, and cytology, have been widely used to accurately and preoperatively diagnose GBC. CEA and CA19-9 have been used for GBC detection as tumor markers [ 23 , 24 ]. Zhou et al. conducted a meta-analysis of the efficacy of serum CA19-9 in detecting GBC and reported a sensitivity of 0.69 (95% confidence interval: 0.61–0.77) and specificity of 0.91 (95% confidence interval: 0.87–0.95) when CA19-9 was used to differentiate between GBC and benign disease [ 24 ]. In this study, serum CAE and CA19-9 levels were not significant predictive factors for detecting GBC in multivariate analyses. CT is most often used to examine patients with suspected GBC. Min et al. showed that CT findings can be used to predict gallbladder cancer in cases with localized gallbladder wall thickening. The top four most accurate CT imaging features in predicting GBC were identified: heterogeneously enhancing single layer or strongly enhancing thick inner layer; gallbladder wall thickness > 6.5 mm; hyperenhancement on arterial phase; and the absence of intramural small cystic lesions (accuracies of 90.0%, 88.3%, 85.0%, and 85.0%, respectively). The combination of any three high-risk features exhibited the highest accuracy (94.2%) [ 4 ]. In contrast, several comparative studies have reported that MRI is superior to CT in detecting GBC. Kalage et al. reported that MRI was more useful in diagnosing thickened wall GBC compared with CT; although none of the CT findings were significantly associated with GBC, MRI showed that heterogeneous enhancement, an indistinct border with the liver, and diffusion restriction were substantially associated with malignancy, and intramural cysts were associated with benign lesions [ 6 ]. Other retrospective studies reported that MRI was significantly more sensitive (80.8%) than CT (50%) in differentiating ADM from GBC [ 25 ]; the sensitivity and specificity of MRI in differentiating XGC from GBC were 93.3% and 84.4%, respectively, compared with 88.4% and 65% for CT, respectively [ 26 ]. Because of the advantages of multiparameter imaging, MRI has the potential to more adequately evaluate gallbladder lesions because of its superior soft tissue contrast and could complement CT findings. CT, MRI, and TUS are commonly used to detect and differentiate gallbladder lesions, but EUS is considered superior to these in terms of gallbladder imaging because it shows the layered structure of the gallbladder and provides high-resolution images [ 27 – 29 ]. EUS is reported to be useful in diagnosing benign and malignant gallbladder lesions and in determining the depth of GBC [ 30 ]. In small (< 2 cm) polyp lesions of the gallbladder, EUS has proven useful, with a diagnostic accuracy for EUS (97%) that is higher than that of TUS (76%) [ 31 ]. However, several studies have reported limitations of EUS in differentiating non-neoplastic polyps < 1 cm from neoplastic polyps. EUS correctly identified 63.2% of neoplastic polyps, but its accuracy for polyps 1.0 cm (88.9%) [ 32 ]. Kim et al. evaluated the clinical utility of EUS in the differential diagnosis of gallbladder wall thickening and reported that wall thickening > 10 mm and internal hypoechogenicity are independent predictors of neoplastic gallbladder wall thickening [ 33 ]. However, in some cases, the diagnosis of GBC is very difficult to make on EUS findings. Furthermore, in this study, malignant suspicion based on EUS by a gastroenterological endoscopist was likely to be higher in the GBC group than in the benign group, although the difference was not significant. EUS-guided puncture aspiration cytology for gallbladder lesions provides pathologic confirmation but is rarely performed to obtain a histologic diagnosis because the technique is not easy to perform, must be performed by a skillful endoscopist, and carries the risk of bile leakage and needle scar seeding [ 30 , 34 ]. Bile cytology by endoscopic transpapillary gallbladder drainage is effective in the diagnosis of GBC, with reported diagnostic efficacy including a sensitivity of 59.1%, specificity of 100%, 93.2% accuracy, 100% positive predictive value and 92.5% negative predictive value [ 35 ], but in this study, the implementation status was limited to about 25% of cases and the false-negative rate was 55.6%, which did not show much efficacy. The role of FDG-PET/CT in the examination of GBC remains controversial [ 7 , 8 ], and European and US guidelines do not recommend routine FDG-PET/CT use for disease staging [ 36 , 37 ]. However, the British Association of Radiologists and the Japanese Guidelines for the management of biliary tract cancers recommend the use of FDG-PET/CT for staging suspected GBC when metastatic disease is difficult to determine on cross-sectional imaging [ 38 , 39 ]. A markedly higher positive predictive value (94% vs. 78%) was recorded for the detection of regional lymph node metastases with FDG-PET/CT in comparison with CT. It was also reported to be significantly more sensitive in detecting distant metastases compared with CT (95% vs. 63%) [ 40 ]. In contrast, Lee et al. reported no significant advantage of FDG-PET/CT over CT in GBC diagnosis. Thus, FDG-PET/CT has the ability to detect metastatic disease but may not be useful to predict primary pathology within the gallbladder as in this study. Considering all of these options, the definitive diagnostic examination to accurately and preoperatively diagnose GBC is still not determined. The nutritional and immunological indices (low GNRI and high PLR) in the present study are simple, noninvasive, and readily available for discriminating GBC from benign disease, and their application was useful in early GBC (Tis-T1). Artificial intelligence (AI) has developed rapidly in recent years, and there is currently an increasing amount of medical-related research focused on machine learning and deep learning technologies. Studies are underway to use AI technology to analyze medical images such as ultrasonography and CT to detect and classify gallbladder lesions, and AI could be a powerful tool to help improve the diagnostic efficiency of GBC [ 41 , 42 ]. There are several limitations to this study. First, there is a potential risk of selection bias because of the single-center, retrospective study design. A multicenter prospective study is needed to validate this study’s results. Second, differences in patient characteristics between the two groups were present. The preoperative age and albumin levels differed between the two groups and may have influenced the results. Conclusion In conclusion, patients with GBC have accompanying aggravated nutritional and immunological status compared with those of patients with benign disease. Specifically, a low GNRI and high PLR are highly associated with GBC, and a low GNRI was detectable even in early GBC (Tis-T1). The assessment of nutritional and immunological status combined with conventional diagnostic tools may be useful for accurately diagnosing GBC and distinguishing it from benign gallbladder diseases, which would contribute to improving the prognostic outcome of this deadly disease and to eliminating unnecessary surgical treatment for benign disease. Declarations Data availability Raw data were generated at Department of Gastroenterological Surgery, Graduate School of Medical Sciences, Kumamoto University. Derived data supporting the findings of this study are available from the corresponding author H.H on request. Author contributions: D.O. and H.H. determined the study plan, collected data, conducted formal analysis and drafted the manuscript. S.Y., R.I, Y.K., S.N., H.O. collaborated and advised on this study. M.I. provided critical review of clinical findings. All authors read and approved the final manuscript. Acknowledgments We thank Jenna MacArthur, PhD, from Edanz (https://jp.edanz.com/ac) for editing a draft of this manuscript. Conflict of interest statement: The authors declare that they have no competing financial interests or personal relationships that could have influenced this study. Ethics statement: This study was approved by the Institutional Review Board (IRB) of Kumamoto University Hospital (IRB No. 1801) and adhered to the principles outlined in the Declaration of Helsinki. This study has not been replicated using other resources. 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Clin Radiol 71(7):e171–e188Royal College Of Physicians Of Edinburgh; British Nuclear Medicine Society; Administration Of Radioactive Substances Advisory Committee Nagino M, Hirano S, Yoshitomi H et al (2021) Clinical practice guidelines for the management of biliary tract cancers 2019: The 3rd English edition. J Hepatobiliary Pancreat Sci 28(1):26–54 Lee SW, Kim HJ, Park JH et al (2010) Clinical usefulness of 18F-FDG PET-CT for patients with gallbladder cancer and cholangiocarcinoma. J Gastroenterol 45(5):560–566 Obaid AM, Turki A, Bellaaj H et al (2023) Detection of Gallbladder Disease Types Using Deep Learning: An Informative Medical Method. Diagnostics (Basel) 13(10):1744 Gupta P, Basu S, Rana P et al (2023) Deep-learning enabled ultrasound based detection of gallbladder cancer in northern India: a prospective diagnostic study. Lancet Reg Health Southeast Asia 24:100279 Tables Table 1. Baseline characteristics of the patients in the benign and GBC groups Benign (n = 37) GBC (n = 76) P-value Male, n (%) 17 (45.6) 29 (38.2) 0.43 Age, years # 68 [55–75] 74 [66–79] 0.013 BMI, kg/m 2 # 23.2 [20.9–25.5] 22.6 [20.1–25.6] 0.82 Comorbidity, n (%) Diabetes mellitus Hypertension Dyslipidemia 7 (18.9) 16 (43.2) 7 (18.9) 16 (21.1) 40 (52.6) 13 (17.1) 0.79 0.35 0.81 ASA-PS, n (%) 1 2 3 1 (2.7) 31 (83.8) 5 (13.5) 6 (7.9) 61 (80.3) 9 (11.8) 0.56 Alb, g/dl # 4.0 [3.7–4.3] 3.8 [3.5–4.2] 0.028 T-Bil, mg/dl # 0.7 [0.5–1.0] 0.7 [0.6–0.9] 0.59 CRP, mg/dl # 0.08 [0.05–0.22] 0.13 [0.05–0.62] 0.09 WBC, /μL # 5400 [4200–6350] 5700 [4525–7000] 0.15 Total peripheral neutrophils, /μL # 2789 [2369–4014] 3472 [2726–4563] 0.11 Total peripheral lymphocytes, /μL # 1452 [1206–1774] 1528 [1226–1909] 0.61 Platelets, ×10 4 /μL # 19.9 [17.2–24.4] 21.6 [18.0–28.6] 0.06 Hb, g/dL # 12.7 [11.9–14.3] 12.6 [11.1–13.5] 0.23 Pathological diagnosis, n (%) Cholecystitis 14 (37.8) XGC 8 (21.6) ADM 7 (18.9) Polyp 5 (13.5) Hyperplasia 2 (5.4) Xanthoma 1 (2.7) GBC 76 (100) － T stage, n (%) － Tis-T1 18 (23.7) T2 40 (52.6) T3 9 (11.8) T4 9 (11.8) － N stage, n (%) － N0 56 (73.7) N1 18 (23.7) N2 2 (2.6) － TNM stage, n (%) － 0-I 18 (23.7) II 28 (36.8) III-IV 30 (39.5) － Abbreviations : BMI, body mass Index; ASA-PS, American Society of Anesthesiologists-Physical Status; Alb, albumin; T-Bil, total bilirubin; CRP, C-reactive protein; WBC, white blood cell; Hb, hemoglobin; XGC, xanthogranulomatous cholecystitis; ADM, adenomyomatosis; GBC, gallbladder carcinoma # Median [interquartile range] Table 2. Preoperative diagnostic tools such as tumor markers, cytology, and radiological imaging Benign (n = 37) GBC (n = 76) P-value CEA, ng/ml # 2.5 [1.7–3.2] 2.1 [1.3–3.2] 0.37 CA19-9, U/ml # 10.8 [6.4–31.0] 13.7 [5.4–26.0] 0.73 Gallstones or biliary sludge † , n (%) 18 (48.7) 28 (36.8) 0.23 Preoperative EUS, n (%) 32 (86.5) 51 (67.1) 0.029 Main findings of EUS, n (%) Irregular surface protuberance/mass Wall thickening Enlarged polyp Unevaluable 16 (50.0) 11 (34.4) 2 (6.2) 3 (9.4) 42 (82.3) 6 (11.8) 1 (2.0) 2 (3.9) － Suspected malignancy on EUS by gastroenterological endoscopist, n (%) 27 (84.4) 49 (96.1) 0.062 Preoperative cytology, n (%) 9 (24.3) 18 (23.7) 0.94 Class I – III Class IV or V 9 (100) 0 (0) 10 (55.6) 8 (44.4) 0.017 FDG-PET/CT, n (%) Local uptake positive Local SUVmax value # Nodal uptake positive Nodal SUVmax value # 22 (59.5) 16 (72.7) 6.3 [3.7–10.7] 2 (9.1) 2.7 [1.8–6.7] 47 (61.8) 41 (87.2) 6.8 [4.2–12.4] 13 (27.7) 5.6 [3.3–12.5] 0.81 0.14 0.58 0.081 0.096 Pathological diagnosis with local uptake positive, n (%) Cholecystitis 7 (43.8) XGC 5 (31.3) ADM 2 (12.5) Hyperplasia 1 (6.2) Polyp 1 (6.2) GBC 76 (100) － Abbreviations : CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; EUS, endoscopic ultrasonography; FDG-PET, fluorodeoxyglucose-positron emission tomography; CT, computed tomography; XGC, xanthogranulomatous cholecystitis; ADM, adenomyomatosis; GBC, gallbladder carcinoma Reference range, CEA ≤ 5.0 ng/ml; CA19-9 ≤ 37.0 U/ml # Median [interquartile range]; † Gallstones or biliary sludge detected by any examination Table 3. Nutritional and immunological indices for the benign and GBC groups Benign (n = 37) GBC (n = 76) P-value GNRI, n (%) ≥ 101.7 < 101.7 26 (70.3) 11 (29.7) 30 (39.5) 46 (60.5) 0.0021 mGPS, n (%) 0 1 2 13 (35.1) 24 (64.9) 0 17 (22.4) 45 (59.2) 14 (18.4) 0.015 NLR, n (%) ≥ 1.76 < 1.76 21 (56.8) 16 (43.2) 57 (75.0) 19 (25.0) 0.049 PLR, n (%) ≥ 98.9 < 98.9 27 (73.0) 10 (27.0) 68 (89.5) 8 (10.5) 0.025 PNI, n (%) ≥ 42.3 < 42.3 33 (89.2) 4 (10.8) 54 (71.1) 22 (28.9) 0.032 Abbreviations : GNRI, geriatric nutritional risk index; mGPS, modified Glasgow prognostic score; NLR, neutrophil/lymphocyte ratio; PLR, platelet/lymphocyte ratio; PNI, prognostic nutritional index Table 4. Univariate and multivariate analyses of clinical factors associated with GBC Clinicopathological factor Univariate Multivariate OR (95% CI) P-value OR (95% CI) P-value Male sex 0.73 (0.33–1.61) 0.43 Age ≥ 75 2.52 (1.05–6.05) 0.039 3.27 (1.27–9.46) 0.014 BMI 5.0 ng/mL 1.55 (0.39–6.09) 0.53 CA19-9 > 37 U/mL 1.11 (0.40–3.08) 0.84 Gallstones or bile mud † 0.62 (0.28–1.36) 0.23 Suspected malignancy on EUS by gastroenterological endoscopist 4.54 (0.82–25.0) 0.082 FDG-PET/CT local uptake 2.56 (0.72–9.13) 0.15 GNRI < 101.7 3.62 (1.56–8.41) 0.0027 2.67 (1.03–7.34) 0.044 mGPS ≥ 1 1.88 (0.79–4.46) 0.15 NLR ≥ 1.76 2.29 (0.99–5.25) 0.052 PLR ≥ 98.9 3.15 (1.13–9.08) 0.029 3.82 (1.20–13.2) 0.024 PNI < 42.3 3.36 (1.06–10.62) 0.039 1.83 (0.51–7.61) 0.36 Abbreviations : BMI, body mass index; CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; FDG-PET, fluorodeoxyglucose-positron emission tomography; CT, computed tomography; GNRI, geriatric nutritional risk index; mGPS, modified Glasgow prognostic score; NLR, neutrophil/lymphocyte ratio; PLR, platelet/lymphocyte ratio; PNI, prognostic nutritional index; OR, odds ratio; CI, confidence interval † Gallstones or bile mud detected by any examination Table 5. Nutritional and immunological indices for the benign and early GBC (≤ T1) groups Benign (n = 37) GBC ≤ T1 (n = 18) P-value GNRI, n (%) ≥ 101.6 < 101.6 27 (73.0) 10 (27.0) 6 (33.3) 12 (66.7) 0.0049 mGPS, n (%) 0 1 2 13 (35.1) 24 (64.9) 0 5 (27.8) 11 (61.1) 2 (11.1) 0.11 NLR, n (%) ≥ 3.42 < 3.42 5 (13.5) 32 (86.5) 0 (0) 18 (100.0) 0.10 PLR, n (%) ≥ 298.1 < 298.1 1 (2.7) 36 (97.3) 3 (16.7) 15 (83.3) 0.061 PNI, n (%) ≥ 43.9 < 43.9 28 (75.7) 9 (24.3) 9 (50.0) 9 (50.0) 0.057 Abbreviations : GNRI, geriatric nutritional risk index; mGPS, modified Glasgow prognostic score; NLR, neutrophil/lymphocyte ratio; PLR, platelet/lymphocyte ratio; PNI, prognostic nutritional index. Table 6. Logistic regression analysis of clinical factors associated with early GBC (≤ T1) Clinicopathological factor Univariate OR (95% CI) P-value Male sex 1.18 (0.38–3.68) 0.78 Age ≥ 75 2.49 (0.75–8.40) 0.13 BMI 5.0 ng/mL 1.41 (0.16–29.8) 0.77 CA19-9 > 37 U/mL 3.73 (0.59–72.96) 0.18 Gallstones or bile mud † 0.67 (0.21–2.09) 0.49 Suspected malignancy on EUS by gastroenterological endoscopist 2.22 (0.23–21.13) 0.49 FDG-PET/CT local uptake 1.69 (0.31–13.19) 0.56 GNRI < 101.6 6.15 (1.85–23.27) 0.0044 mGPS ≥ 1 1.41 (0.42–5.18) 0.59 NLR ≥ 3.42 n.s. 0.99 PLR ≥ 298.1 7.2 (0.85–152.13) 0.10 PNI < 43.9 3.11 (0.95–10.55) 0.062 Abbreviations : BMI, body mass Index; CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; FDG-PET, fluorodeoxyglucose-positron emission tomography; CT, computed tomography; GNRI, geriatric nutritional risk index; mGPS, modified Glasgow prognostic score; NLR, neutrophil/lymphocyte ratio; PLR, platelet/lymphocyte ratio; PNI, prognostic nutritional index; OR, odds ratio; CI, confidence interval † Gallstones or bile mud detected by any examination Table 7. Surgical outcomes in the benign and malignant groups Benign (n = 37) GBC (n = 76) P-value Surgical procedure, n (%) Cholecystectomy Gallbladder bed resection S4a+5 resection Extended right hepatectomy SSPPD HPD 18 (48.7) 15 (40.5) 4 (10.8) 0 0 0 15 (19.8) 29 (38.2) 26 (34.2) 2 (2.6) 2 (2.6) 2 (2.6) 0.0095 Laparoscopic and robotic surgery, n (%) 13 (35.1) 9 (11.8) 0.0033 Extrahepatic bile duct resection, n (%) 7 (18.9) 55 (72.4) <0.0001 Operation time, min # 213 [141–278] 399 [273–489] <0.0001 Blood loss, ml # 140 [18–300] 493 [208–879] <0.0001 Intraoperative transfusion, n (%) 1 (2.7) 12 (15.8) 0.041 Postoperative in-hospital stay, days # 7 [6–11] 14 [10–25] <0.0001 Postoperative complication (CD † ≥ IIIA), n (%) 2 (5.4) 18 (23.7) 0.017 90-day mortality, n (%) 0 2 (2.6) 0.32 Abbreviations : S4a+5, segment 4a and 5; SSPPD, subtotal stomach-preserving pancreaticoduodenectomy; HPD, hepatopancreato-duodenectomy; CD, Clavien–Dindo classification # Median [interquartile range] Cite Share Download PDF Status: Published Journal Publication published 07 May, 2025 Read the published version in International Journal of Clinical Oncology → Version 1 posted Editorial decision: Major revisions 26 Jan, 2025 Reviewers agreed at journal 09 Jan, 2025 Reviewers invited by journal 09 Jan, 2025 Editor assigned by journal 09 Jan, 2025 First submitted to journal 07 Jan, 2025 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. 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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-5786974","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":400172176,"identity":"9ba0b0d6-3e80-4da2-83eb-80812522e95d","order_by":0,"name":"Daisuke Ogawa","email":"","orcid":"","institution":"Kumamoto University: Kumamoto Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Daisuke","middleName":"","lastName":"Ogawa","suffix":""},{"id":400172177,"identity":"45ee7288-76b2-48d7-910a-80e7422a2c8f","order_by":1,"name":"Hiromitsu Hayashi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYBACAwkwJSEngSbBRlCLMVSLAdFaGBJnoGnBDcylm59J/PhjkT5zRnbipxsVf+QYJBIYP/xg4MvDpcVyzjEzyd42idzZErmbpXPOGBgDtTBL9jCwFeN02I0EMwneBonceRK5G6Rz2wwS999IYJAG+iWxAaeW9G+Sf/5IpMsBbfkN0tIAtOU3fi05ZtI8bBIJ0hK526ShWtgI2JJTbC3bJmE4s+ftNuucM8bGDDwP2yx7DPD5JX3jzTd/6uQljuduvp1TISfHwJ58+MaPimM4QwwIWNAjnhHoJINjCXi0MH/AJlqDT8soGAWjYBSMLAAAbBlQwLHC1TAAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-1832-4287","institution":"Kumamoto University: Kumamoto Daigaku","correspondingAuthor":true,"prefix":"","firstName":"Hiromitsu","middleName":"","lastName":"Hayashi","suffix":""},{"id":400172178,"identity":"be46055d-c340-47e3-a9b6-a7f0b57c949d","order_by":2,"name":"Shinsei Yumoto","email":"","orcid":"","institution":"Kumamoto University: Kumamoto Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Shinsei","middleName":"","lastName":"Yumoto","suffix":""},{"id":400172179,"identity":"a9c81e47-ba87-4a14-a621-8fe9022c6c7c","order_by":3,"name":"Rumi Itoyama","email":"","orcid":"","institution":"Kumamoto University: Kumamoto Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Rumi","middleName":"","lastName":"Itoyama","suffix":""},{"id":400172180,"identity":"5d855dd3-9ca9-4140-8ef4-3ca69afe65f2","order_by":4,"name":"Yuki Kitano","email":"","orcid":"","institution":"Kumamoto University: Kumamoto Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Yuki","middleName":"","lastName":"Kitano","suffix":""},{"id":400172181,"identity":"3da76e26-fae9-46be-8dfe-1957a3c51f51","order_by":5,"name":"Shigeki Nakagawa","email":"","orcid":"","institution":"Kumamoto University: Kumamoto Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Shigeki","middleName":"","lastName":"Nakagawa","suffix":""},{"id":400172182,"identity":"a1b9c857-686d-4bba-8a55-c911e4112d71","order_by":6,"name":"Hirohisa Okabe","email":"","orcid":"","institution":"Kumamoto University: Kumamoto Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Hirohisa","middleName":"","lastName":"Okabe","suffix":""},{"id":400172183,"identity":"3efe89f7-fdd4-4898-b62e-ba4f7cb5ca03","order_by":7,"name":"Masaaki Iwatsuki","email":"","orcid":"","institution":"Kumamoto University: Kumamoto Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Masaaki","middleName":"","lastName":"Iwatsuki","suffix":""}],"badges":[],"createdAt":"2025-01-08 08:10:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5786974/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5786974/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10147-025-02764-8","type":"published","date":"2025-05-07T15:57:48+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":73786202,"identity":"dae4f4ad-b02f-4589-972c-a770af9610bc","added_by":"auto","created_at":"2025-01-14 16:20:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51329,"visible":true,"origin":"","legend":"\u003cp\u003eROC–AUC curves for nutritional and immunological indices in the benign and GBC groups. The AUC and cutoff values for the (A) GNRI, (B) NLR, (C) PLR, and (D) PNI were 0.61 and 101.7, 0.57 and 1.76, 0.58 and 98.9, and 0.61 and 42.3, respectively.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5786974/v1/c989ad6be3f3ef6d8b3f7b92.png"},{"id":73786203,"identity":"e70f2c58-cea3-4185-9bbb-9a20085b9e1a","added_by":"auto","created_at":"2025-01-14 16:20:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":41181,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of patients in the cutoff levels of the nutritional and immunological indices in the benign and GBC groups. (A) GNRI high (≥101.7) and GNRI low (\u0026lt;101.7); GNRI low was significantly higher in the GBC group. (B) mGPS was significantly higher in the GBC group. (C) NLR high (≥1.76) and NLR low (\u0026lt;1.76); NLR high was significantly higher in the GBC group. (D) PLR high (≥98.9) and PLR low (\u0026lt;98.9); PLR high was significantly higher in the GBC group. (E) PNI high (≥42.3) and PNI low (\u0026lt;42.3); PNI low was significantly higher in the GBC group.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5786974/v1/c52e946533c2d6618a88675a.png"},{"id":73784868,"identity":"370df3a3-04f8-4dfc-b063-0dbec9fe8753","added_by":"auto","created_at":"2025-01-14 16:04:29","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":50759,"visible":true,"origin":"","legend":"\u003cp\u003eROC–AUC curves for nutritional and immunological indices in the benign and early GBC (≤ T1) groups. The AUC and cutoff values for the (A) GNRI, (B) NLR, (C) PLR, and (D) PNI were 0.70 and 101.6, 0.46 and 3.42, 0.55 and 298.1, and 0.67 and 43.9, respectively.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5786974/v1/a8d4c2ddd245552cc1f51494.png"},{"id":73784863,"identity":"4da17c24-8112-497e-bb7f-6d7c773b3774","added_by":"auto","created_at":"2025-01-14 16:04:29","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":44379,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of patients in the cutoff levels of the nutritional and immunological indices in the benign and early GBC (≤ T1) groups. (A) GNRI high (≥101.6) and GNRI low (\u0026lt;101.6); GNRI low was significantly higher in the early GBC group. There were no significant differences between the benign and early GBC groups regarding (B) mGPS, (C) NLR high (≥1.76) and NLR low (\u0026lt;1.76), (D) PLR high (≥98.9) and PLR low (\u0026lt;98.9), and (E) PNI high (≥42.3) and PNI low (\u0026lt;42.3).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5786974/v1/da1c9ec582ae7fc86eef03c9.png"},{"id":82537656,"identity":"f6e3454f-0385-42b0-bfac-8a5db35be299","added_by":"auto","created_at":"2025-05-12 16:09:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1537475,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5786974/v1/dcf247ff-b6c4-4fe3-860b-b489515b8272.pdf"}],"financialInterests":"","formattedTitle":"Clinical usefulness of nutritional and immunological indices to distinguish gallbladder carcinoma from benign disease","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGallbladder carcinoma (GBC) is one of the common hepatobiliary malignancies, predominantly occurring in certain regions including Eastern Europe, East Asia, Southeast Asia, and Latin America [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The prognosis of GBC is very poor, with 5-year survival rates of 5\u0026ndash;20% even after surgery because of the aggressive tumor biology, complicated anatomic position, and advanced stage at diagnosis [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Early tumors are often incidentally detected on radiological imaging or by cholecystectomy performed for another indication. It is challenging to accurately and preoperatively diagnose GBC because patients are often asymptomatic or present with nonspecific symptoms that mimic common benign diseases in radiological findings. Contrast-enhanced computed tomography (CT), magnetic resonance imaging (MRI), and fluorodeoxyglucose-positron emission tomography/CT (FDG-PET/CT) have been reported to be useful for GBC diagnosis, but their utility remains controversial [\u003cspan additionalcitationids=\"CR5 CR6 CR7\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Typical imaging features of localized GBC include asymmetric gallbladder wall thickening, polyps larger than 10 mm, and a solid mass replacing the gallbladder lumen [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Advanced tumors are often infiltrative and can be confused on CT, MRI, and FDG-PET/CT with xanthogranulomatous cholecystitis (XGC). It is clinically important to accurately diagnose GBC and distinguish it from benign gallbladder diseases, which would contribute to improving the prognostic outcome of this deadly disease and avoiding unnecessary surgical treatment for benign disease.\u003c/p\u003e \u003cp\u003eIn several malignant diseases, the practical use of nutritional and immunological status for predicting prognostic outcomes has been a research hotspot in recent years [\u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14 CR15\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Furthermore, in GBC, a low geriatric nutritional risk index (GNRI) has been shown to be an independent poor prognostic factor after radical surgery [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, the usefulness of nutritional and immunological indices in distinguishing GBC from benign disease is uncertain. Here, we investigated the clinical utility of nutritional and immunological indices in distinguishing GBC from benign disease.\u003c/p\u003e"},{"header":"Patients and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy population\u003c/h2\u003e\n \u003cp\u003eFrom April 2007 to December 2023, 113 patients underwent surgical excision or curative surgery for suspected GBC at Kumamoto University Hospital. All patients underwent transabdominal ultrasonography (TUS) or enhanced CT with findings suspicious for GBC, and further examinations such as an endoscopic ultrasonography (EUS) or FDG-PET/CT were performed. The inclusion criteria were as follows: 1) patients with suspicion of GBC by ultrasonography or CT such as a gallbladder mass, gallbladder wall thickening, or enlarged gallbladder polyps larger than 10 mm; 2) patients who received further diagnostic examinations such as MRI, EUS, transpapillary bile cytology, and FDG-PET/CT and were suspected of having GBC by radiologists and gastroenterological endoscopists; and 3) patients who had undergone surgical excision or curative surgery for suspected GBC based on the surgeons\u0026apos; mutual agreement.\u003c/p\u003e\n \u003cp\u003eIn accordance with the pathological diagnosis, the subjects were divided into 37 patients with benign disease and 76 patients with GBC, and their clinical characteristics are summarized in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The benign group included cholecystitis (n\u0026thinsp;=\u0026thinsp;14), XGC (n\u0026thinsp;=\u0026thinsp;8), adenomyomatosis (ADM) (n\u0026thinsp;=\u0026thinsp;7), gallbladder polyps (n\u0026thinsp;=\u0026thinsp;5), hyperplasia (n\u0026thinsp;=\u0026thinsp;2), and xanthoma (n\u0026thinsp;=\u0026thinsp;1). In the benign group, inflammatory diseases such as cholecystitis and XGC accounted for more than half of the cases, followed by ADM and gallbladder polyps. In the malignant group, more than 75% of cases were T2 or less, and 23% had advanced GBC of T3 or T4 (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll patients provided written informed consent, and the Ethics Committee of Kumamoto University approved this study\u0026apos;s protocol. Our institutional ethical review board approved this study (IRB No. 1801), and all procedures met the guidelines of the Declaration of Helsinki.\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eNutritional and immunological indices\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe GNRI, modified Glasgow prognostic score (mGPS), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and prognostic nutrition index (PNI) were obtained as nutritional and immunological indices.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eContinuous variables are presented as the median and interquartile range, and categorical values are presented as absolute and relative frequencies. Variables were compared using the Mann\u0026ndash;Whitney U test. Categorical data were subjected to the chi-square test or Fisher\u0026apos;s exact test, as appropriate. Receiver operating characteristic (ROC) curves were constructed for the nutritional indices to compare the benign and malignant groups of gallbladder lesions, optimal cutoff values were determined, and the areas under the curve (AUCs) were calculated. The cutoff values were determined by ROC\u0026ndash;AUC analysis and set for continuous variables in univariate and multivariate logistic regression analyses. All statistical analyses were performed using JMP Pro, version 16.0.0 (SAS Institute, Cary, NC, USA). A P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eComparison of\u0026nbsp;clinical factors and conventional diagnostic examinations between the benign and GBC groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe GBC group had a significantly higher age and significantly lower preoperative albumin levels compared with those in the benign group (P=0.013 and P=0.028, respectively) (\u003cstrong\u003eTable 1\u003c/strong\u003e). In addition, the results of preoperative diagnostic tools such as tumor markers, cytology, and radiological imaging between the benign and malignant groups of the entire cohort are summarized in \u003cstrong\u003eTable 2\u003c/strong\u003e. There were no significant differences in the serum tumor markers carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) between the two groups. Although cases with preoperative biliary cytology examinations were limited in both groups at approximately 24%, the positive rate (cytology class IV and V) was significantly higher in the GBC group at 44.4% compared with that in the benign group (0%) (P=0.017), while the false-negative rate was 55.6% in the GBC group. The EUS examination rate was significantly higher in the benign group at 89.2% compared with 67.1% in the GBC group (P=0.016), and interestingly, 84.4% of the benign group received a suspected GBC result. The main finding on EUS was an irregular surface protuberance/mass in 82.3% of the GBC group and 50.0% of the benign group. FDG-PET/CT was performed in approximately 60% of patients in both groups, and there was no significant difference in the SUVmax values between the two groups. In the benign group with positive local uptake, the pathological diagnoses were mainly inflammatory diseases such as chronic cholecystitis (42.8%), XGC (31.3%), and ADM (12.5%) (\u003cstrong\u003eTable 2\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of\u0026nbsp;nutritional and immunological indices between the benign and GBC groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFive nutritional and immunological indices (GNRI, mGPS, NLR, PLR, and PNI) were compared between the benign and GBC groups. The AUC and cutoff values for the GNRI, NLR, PLR, and PNI were calculated using ROC–AUC analyses (\u003cstrong\u003eFigure 1\u003c/strong\u003e). The AUC values of the GNRI, NLR, PLR, and PNI were 0.61, 0.57, 0.58, and 0.61, respectively, and the sensitivity and specificity were 0.62 and 0.70, 0.75 and 0.43, 0.89 and 0.27, and 0.30 and 0.89, respectively. The GBC group exhibited significantly higher values for the mGPS, NLR, and PLR indices, whereas the GNRI and PNI indices in the GBC group were significantly lower than those in the benign group (\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eand\u003cstrong\u003e\u0026nbsp;Figure 2\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUnivariate and multivariate analyses of clinical factors associated with GBC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnivariate and multivariate analyses were performed to elucidate the preoperative factors to discriminate GBC from benign disease (\u003cstrong\u003eTable 4\u003c/strong\u003e). In the comparison between the benign and GBC groups, high age (≥75 years), low GNRI, high PLR, and low PNI were significantly associated with GBC in univariate analysis (odds ratios and P-values: 2.52 and 0.039, 3.62 and 0.0027, 3.15 and 0.029, and 3.36 and 0.039, respectively). In multivariate analyses (logistic regression analyses), high age (≥75 years), low GNRI, and high PLR were significantly associated with GBC (odds ratios and P-values: 3.27 and 0.014, 2.67 and 0.044, and 3.82 and 0.024, respectively).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of nutritional and immunological indices between benign and early GBC (below T1)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExcluding advanced GBC (≥T2), we further compared the nutritional and immunological indices between the benign group and those with early-stage GBC (Tis-T1), which may be more difficult to discriminate from benign disease by conventional diagnostic tools. In total, 37 benign cases and 18 early GBC (≤ T1) cases were compared for the nutritional and immunological indices (\u003cstrong\u003eFigure 3\u003c/strong\u003e). The AUC values of the GNRI, NLR, PLR, and PNI were 0.70, 0.46, 0.55, and 0.67, respectively, and the sensitivity and specificity were 0.72 and 0.70, 1.0 and 0.13, 0.97 and 0.17, and 0.56 and 0.76, respectively. The GNRI in the early GBC group was significantly lower compared with that in the benign group (P=0.0049) (\u003cstrong\u003eTable 5\u0026nbsp;\u003c/strong\u003eand\u003cstrong\u003e\u0026nbsp;Figure 4\u003c/strong\u003e). The other indices (mGPS, NLR, PLR, and PNI) were not significantly different between the two groups. In logistic regression analyses, a low GNRI was the only significant predictive factor for early GBC (Tis-T1) (the odds ratio and P-value were 6.15 and 0.0044, respectively) (\u003cstrong\u003eTable 6\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of surgical outcomes between the benign and GBC groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eComparisons of the surgical outcomes between the benign and GBC groups are shown in \u003cstrong\u003eTable 7\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eThe GBC group had more highly invasive surgeries. The GBC group had significantly higher rates of laparotomy (P=0.0033), extrahepatic bile duct resection (P\u0026lt;0.0001), longer operative times (P\u0026lt;0.0001), greater blood loss (P\u0026lt;0.0001), higher rates of blood transfusion (P=0.041), higher postoperative hospital days (P\u0026lt;0.0001), and more postoperative complications (P=0.017) compared with those in the benign group.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study showed that aggravated nutritional and immunological status were detectable in GBC compared with benign disease. In particular, a low GNRI and high PLR were highly associated with GBC. Furthermore, a low GNRI was detectable even in early GBC (Tis-T1). These results suggested that nutritional and immunological indices could be simple diagnostic tools to predict GBC. To our knowledge, this is the first report showing that nutritional and immunological indices are useful in discriminating GBC from benign disease.\u003c/p\u003e \u003cp\u003eHost\u0026ndash;tumor interactions between cancer cells and host nutritional immunity are well known to have a significant impact on the malnutrition status and immune-suppression in cancer patients. Metabolic and nutritional disorders in cancer carriers can develop not only in advanced cancers but also in early-stage cancers [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The nutritional and immunological indices examined in this study have been reported to be prognostic and predictive factors in hepatobiliary cancers. The GNRI depends on body weight and the serum albumin level, both of which represent nutritional status. For example, in GBC, a low GNRI (\u0026lt;\u0026thinsp;98) and a high C-reactive protein/albumin ratio (\u0026ge;\u0026thinsp;0.07) have been reported as worse prognostic factors after surgery [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The present study first advocated the utility of the GNRI in discriminating GBC from benign gallbladder diseases, and the practical use was apparent even in early GBC (Tis-T1).\u003c/p\u003e \u003cp\u003eThe NLR and PLR are nutritional indices using blood cell components and are complementary to each other. The total lymphocyte count, a classic nutritional indicator [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], has shown usefulness as a marker of malnutrition, such as low BMI and weight loss, along with serum albumin levels [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In addition, lymphocytes are widely used as an indicator of immunocompetence, since they act in a tumor-suppressive manner and play a role in tumor immunity [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Platelets, like neutrophils, are blood cell components that play a role in inflammatory reactions, and thrombocytosis is often observed in solid tumor patients with chronic inflammation [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Since platelets themselves are deeply involved in cancer progression [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], the PLR, which is the ratio of platelet and lymphocyte counts, represents the inflammatory and immunological status. In the present study, a high PLR may reflect a platelet increase associated with the inflammatory response and immunosuppression in GBC. The PLR also has been reported to be a prognostic factor after papillary carcinoma surgery [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConventional diagnostic tools, including tumor markers, radiological imaging, ultrasonography, and cytology, have been widely used to accurately and preoperatively diagnose GBC. CEA and CA19-9 have been used for GBC detection as tumor markers [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Zhou et al. conducted a meta-analysis of the efficacy of serum CA19-9 in detecting GBC and reported a sensitivity of 0.69 (95% confidence interval: 0.61\u0026ndash;0.77) and specificity of 0.91 (95% confidence interval: 0.87\u0026ndash;0.95) when CA19-9 was used to differentiate between GBC and benign disease [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In this study, serum CAE and CA19-9 levels were not significant predictive factors for detecting GBC in multivariate analyses.\u003c/p\u003e \u003cp\u003eCT is most often used to examine patients with suspected GBC. Min et al. showed that CT findings can be used to predict gallbladder cancer in cases with localized gallbladder wall thickening. The top four most accurate CT imaging features in predicting GBC were identified: heterogeneously enhancing single layer or strongly enhancing thick inner layer; gallbladder wall thickness\u0026thinsp;\u0026gt;\u0026thinsp;6.5 mm; hyperenhancement on arterial phase; and the absence of intramural small cystic lesions (accuracies of 90.0%, 88.3%, 85.0%, and 85.0%, respectively). The combination of any three high-risk features exhibited the highest accuracy (94.2%) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In contrast, several comparative studies have reported that MRI is superior to CT in detecting GBC. Kalage et al. reported that MRI was more useful in diagnosing thickened wall GBC compared with CT; although none of the CT findings were significantly associated with GBC, MRI showed that heterogeneous enhancement, an indistinct border with the liver, and diffusion restriction were substantially associated with malignancy, and intramural cysts were associated with benign lesions [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Other retrospective studies reported that MRI was significantly more sensitive (80.8%) than CT (50%) in differentiating ADM from GBC [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]; the sensitivity and specificity of MRI in differentiating XGC from GBC were 93.3% and 84.4%, respectively, compared with 88.4% and 65% for CT, respectively [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Because of the advantages of multiparameter imaging, MRI has the potential to more adequately evaluate gallbladder lesions because of its superior soft tissue contrast and could complement CT findings.\u003c/p\u003e \u003cp\u003eCT, MRI, and TUS are commonly used to detect and differentiate gallbladder lesions, but EUS is considered superior to these in terms of gallbladder imaging because it shows the layered structure of the gallbladder and provides high-resolution images [\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. EUS is reported to be useful in diagnosing benign and malignant gallbladder lesions and in determining the depth of GBC [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In small (\u0026lt;\u0026thinsp;2 cm) polyp lesions of the gallbladder, EUS has proven useful, with a diagnostic accuracy for EUS (97%) that is higher than that of TUS (76%) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, several studies have reported limitations of EUS in differentiating non-neoplastic polyps\u0026thinsp;\u0026lt;\u0026thinsp;1 cm from neoplastic polyps. EUS correctly identified 63.2% of neoplastic polyps, but its accuracy for polyps\u0026thinsp;\u0026lt;\u0026thinsp;1.0 cm was lower (40%) than that for polyps\u0026thinsp;\u0026gt;\u0026thinsp;1.0 cm (88.9%) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Kim et al. evaluated the clinical utility of EUS in the differential diagnosis of gallbladder wall thickening and reported that wall thickening\u0026thinsp;\u0026gt;\u0026thinsp;10 mm and internal hypoechogenicity are independent predictors of neoplastic gallbladder wall thickening [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, in some cases, the diagnosis of GBC is very difficult to make on EUS findings. Furthermore, in this study, malignant suspicion based on EUS by a gastroenterological endoscopist was likely to be higher in the GBC group than in the benign group, although the difference was not significant.\u003c/p\u003e \u003cp\u003eEUS-guided puncture aspiration cytology for gallbladder lesions provides pathologic confirmation but is rarely performed to obtain a histologic diagnosis because the technique is not easy to perform, must be performed by a skillful endoscopist, and carries the risk of bile leakage and needle scar seeding [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Bile cytology by endoscopic transpapillary gallbladder drainage is effective in the diagnosis of GBC, with reported diagnostic efficacy including a sensitivity of 59.1%, specificity of 100%, 93.2% accuracy, 100% positive predictive value and 92.5% negative predictive value [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], but in this study, the implementation status was limited to about 25% of cases and the false-negative rate was 55.6%, which did not show much efficacy.\u003c/p\u003e \u003cp\u003eThe role of FDG-PET/CT in the examination of GBC remains controversial [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and European and US guidelines do not recommend routine FDG-PET/CT use for disease staging [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, the British Association of Radiologists and the Japanese Guidelines for the management of biliary tract cancers recommend the use of FDG-PET/CT for staging suspected GBC when metastatic disease is difficult to determine on cross-sectional imaging [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. A markedly higher positive predictive value (94% vs. 78%) was recorded for the detection of regional lymph node metastases with FDG-PET/CT in comparison with CT. It was also reported to be significantly more sensitive in detecting distant metastases compared with CT (95% vs. 63%) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In contrast, Lee et al. reported no significant advantage of FDG-PET/CT over CT in GBC diagnosis. Thus, FDG-PET/CT has the ability to detect metastatic disease but may not be useful to predict primary pathology within the gallbladder as in this study.\u003c/p\u003e \u003cp\u003eConsidering all of these options, the definitive diagnostic examination to accurately and preoperatively diagnose GBC is still not determined. The nutritional and immunological indices (low GNRI and high PLR) in the present study are simple, noninvasive, and readily available for discriminating GBC from benign disease, and their application was useful in early GBC (Tis-T1).\u003c/p\u003e \u003cp\u003eArtificial intelligence (AI) has developed rapidly in recent years, and there is currently an increasing amount of medical-related research focused on machine learning and deep learning technologies. Studies are underway to use AI technology to analyze medical images such as ultrasonography and CT to detect and classify gallbladder lesions, and AI could be a powerful tool to help improve the diagnostic efficiency of GBC [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are several limitations to this study. First, there is a potential risk of selection bias because of the single-center, retrospective study design. A multicenter prospective study is needed to validate this study\u0026rsquo;s results. Second, differences in patient characteristics between the two groups were present. The preoperative age and albumin levels differed between the two groups and may have influenced the results.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, patients with GBC have accompanying aggravated nutritional and immunological status compared with those of patients with benign disease. Specifically, a low GNRI and high PLR are highly associated with GBC, and a low GNRI was detectable even in early GBC (Tis-T1). The assessment of nutritional and immunological status combined with conventional diagnostic tools may be useful for accurately diagnosing GBC and distinguishing it from benign gallbladder diseases, which would contribute to improving the prognostic outcome of this deadly disease and to eliminating unnecessary surgical treatment for benign disease.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw data were generated at\u0026nbsp;Department of Gastroenterological Surgery, Graduate School of Medical Sciences, Kumamoto University. Derived data supporting the findings of this study are available from the corresponding author H.H on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eD.O. and H.H.\u0026nbsp;determined the study plan, collected data, conducted formal analysis and drafted the manuscript. S.Y., R.I, Y.K., S.N., H.O. collaborated and advised on this study. M.I. provided critical review of clinical findings. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Jenna MacArthur, PhD, from Edanz (https://jp.edanz.com/ac) for editing a draft of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest statement:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing financial interests or personal relationships that could have influenced this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board (IRB) of Kumamoto University Hospital (IRB No. 1801) and adhered to the principles outlined in the Declaration of Helsinki. This study has not been replicated using other resources.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRawla P, Sunkara T, Thandra KC et al (2019) Epidemiology of gallbladder cancer. Clin Exp Hepatol 5(2):93\u0026ndash;102\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTorre LA, Siegel RL, Islami F et al (2018) Worldwide Burden of and Trends in Mortality From Gallbladder and Other Biliary Tract Cancers. Clin Gastroenterol Hepatol 16(3):427\u0026ndash;437\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIshihara S, Horiguchi A, Miyakawa S et al (2016) Biliary tract cancer registry in Japan from 2008 to 2013. J Hepatobiliary Pancreat Sci 23(3):149\u0026ndash;157\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMin JH, Choi SY, Kim SH et al (2024) Should we suspect gallbladder cancer if which CT finding is observed in patients with localized gallbladder wall thickening? 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J Gastrointest Surg 19(12):2171\u0026ndash;2177\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang W, Liu W, Zhang N et al (2018) Preoperative platelet-lymphocyte ratio is an independent prognostic factor in ampullary carcinoma following pancreaticoduodenectomy. Oncol Lett 16(4):4879\u0026ndash;4888\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanda M, Fujii T, Kodera Y et al (2011) Nutritional predictors of postoperative outcome in pancreatic cancer. Br J Surg 98(2):268\u0026ndash;274\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eToiyama Y, Miki C, Inoue Y et al (2011) Evaluation of an inflammation-based prognostic score for the identification of patients requiring postoperative adjuvant chemotherapy for stage II colorectal cancer. Exp Ther Med 2(1):95\u0026ndash;101\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGullett N, Rossi P, Kucuk O et al (2009) Cancer-induced cachexia: a guide for the oncologist. J Soc Integr Oncol. Fall;7(4):155\u0026thinsp;\u0026ndash;\u0026thinsp;69\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller CL (1978) Immunological assays as measurements of nutritional status: a review. JPEN J Parenter Enter Nutr 2(4):554\u0026ndash;566\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGonz\u0026aacute;lez Madro\u0026ntilde;o A, Mancha A, Rodr\u0026iacute;guez FJ et al (2011) d. The use of biochemical and immunological parameters in nutritional screening and assessment. Nutr Hosp. May-Jun;26(3):594\u0026ndash;601\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrivennikov SI, Greten FR, Karin M (2010) Immunity, inflammation, and cancer. Cell 140(6):883\u0026ndash;899\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStone RL, Nick AM, McNeish IA et al (2012) Paraneoplastic thrombocytosis in ovarian cancer. N Engl J Med 366(7):610\u0026ndash;618\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJain S, Harris J, Ware J (2010) Platelets: linking hemostasis and cancer. Arterioscler Thromb Vasc Biol 30(12):2362\u0026ndash;2367\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou X (2022) Meta-analysis of the diagnostic performance of serum carbohydrate antigen 19\u0026thinsp;\u0026ndash;\u0026thinsp;9 for the detection of gallbladder cancer. Int J Biol Markers 37(1):81\u0026ndash;89\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSinha SR, Prakash P, Singh RK et al (2022) Assessment of tumor markers CA 19\u0026thinsp;\u0026ndash;\u0026thinsp;9, CEA, CA 125, and CA 242 for the early diagnosis and prognosis prediction of gallbladder cancer. World J Gastrointest Surg 14(11):1272\u0026ndash;1284\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBang SH, Lee JY, Woo H et al (2014 Mar-Apr) Differentiating between adenomyomatosis and gallbladder cancer: revisiting a comparative study of high-resolution ultrasound, multidetector CT, and MR imaging. Korean J Radiol 15(2):226\u0026ndash;234\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao F, Lu PX, Yan SX et al (2013) CT and MR features of xanthogranulomatous cholecystitis: an analysis of consecutive 49 cases. Eur J Radiol 82(9):1391\u0026ndash;1397\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzuma T, Yoshikawa T, Araida T et al (2001) Differential diagnosis of polypoid lesions of the gallbladder by endoscopic ultrasonography. Am J Surg 181(1):65\u0026ndash;70\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChoi WB, Lee SK, Kim MH et al (2000) A new strategy to predict the neoplastic polyps of the gallbladder based on a scoring system using EUS. Gastrointest Endosc 52(3):372\u0026ndash;379\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSadamoto Y, Oda S, Tanaka M et al (2002) A useful approach to the differential diagnosis of small polypoid lesions of the gallbladder, utilizing an endoscopic ultrasound scoring system. Endoscopy 34(12):959\u0026ndash;965\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTamura T, Ashida R, Kitano M (2022 Aug) The usefulness of endoscopic ultrasound in the diagnosis of gallbladder lesions. Front Med (Lausanne) 29:9:957557\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSugiyama M, Atomi Y, Yamato T (2000) Endoscopic ultrasonography for differential diagnosis of polypoid gall bladder lesions: analysis in surgical and follow up series. Gut 46(2):250\u0026ndash;254\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheon YK, Cho WY, Lee TH et al (2009) Endoscopic ultrasonography does not differentiate neoplastic from non-neoplastic small gallbladder polyps. World J Gastroenterol 15(19):2361\u0026ndash;2366\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim HJ, Park JH, Park DI et al (2012) Clinical usefulness of endoscopic ultrasonography in the differential diagnosis of gallbladder wall thickening. Dig Dis Sci 57(2):508\u0026ndash;515\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIto H, Hann LE, D'Angelica M et al (2009) Polypoid lesions of the gallbladder: diagnosis and followup. J Am Coll Surg 208(4):570\u0026ndash;575\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eItsuki H, Serikawa M, Sasaki T et al (2018) Indication and Usefulness of Bile Juice Cytology for Diagnosis of Gallbladder Cancer. Gastroenterol Res Pract 2018:5410349\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenson AB, D'Angelica MI, Abbott DE et al (2019) Guidelines Insights: Hepatobiliary Cancers, Version 2.2019. J Natl Compr Canc Netw 17(4):302\u0026ndash;310\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValle JW, Borbath I, Khan SA, ESMO Guidelines Committee et al (2016) Biliary cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol 27(suppl 5):v28\u0026ndash;v37\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThe Royal College Of Radiologists; Royal College Of Physicians Of London; Royal College Of Physicians And Surgeons Of Glasgow (2016) Evidence-based indications for the use of PET-CT in the United Kingdom 2016. Clin Radiol 71(7):e171\u0026ndash;e188Royal College Of Physicians Of Edinburgh; British Nuclear Medicine Society; Administration Of Radioactive Substances Advisory Committee\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNagino M, Hirano S, Yoshitomi H et al (2021) Clinical practice guidelines for the management of biliary tract cancers 2019: The 3rd English edition. J Hepatobiliary Pancreat Sci 28(1):26\u0026ndash;54\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee SW, Kim HJ, Park JH et al (2010) Clinical usefulness of 18F-FDG PET-CT for patients with gallbladder cancer and cholangiocarcinoma. J Gastroenterol 45(5):560\u0026ndash;566\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eObaid AM, Turki A, Bellaaj H et al (2023) Detection of Gallbladder Disease Types Using Deep Learning: An Informative Medical Method. Diagnostics (Basel) 13(10):1744\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGupta P, Basu S, Rana P et al (2023) Deep-learning enabled ultrasound based detection of gallbladder cancer in northern India: a prospective diagnostic study. Lancet Reg Health Southeast Asia 24:100279\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 643px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1. Baseline characteristics of the patients in the benign and GBC groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBenign\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 37)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGBC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 76)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eMale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e17 (45.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e29 (38.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eAge, years \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e68 [55\u0026ndash;75]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e74 [66\u0026ndash;79]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e23.2 [20.9\u0026ndash;25.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e22.6 [20.1\u0026ndash;25.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eComorbidity, n (%)\u003c/p\u003e\n \u003cp\u003eDiabetes mellitus\u003c/p\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003cp\u003eDyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7 (18.9)\u003c/p\u003e\n \u003cp\u003e16 (43.2)\u003c/p\u003e\n \u003cp\u003e7 (18.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16 (21.1)\u003c/p\u003e\n \u003cp\u003e40 (52.6)\u003c/p\u003e\n \u003cp\u003e13 (17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eASA-PS, n (%)\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1 (2.7)\u003c/p\u003e\n \u003cp\u003e31 (83.8)\u003c/p\u003e\n \u003cp\u003e5 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6 (7.9)\u003c/p\u003e\n \u003cp\u003e61 (80.3)\u003c/p\u003e\n \u003cp\u003e9 (11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eAlb, g/dl \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e4.0 [3.7\u0026ndash;4.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e3.8 [3.5\u0026ndash;4.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eT-Bil, mg/dl \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e0.7 [0.5\u0026ndash;1.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e0.7 [0.6\u0026ndash;0.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eCRP, mg/dl \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e0.08 [0.05\u0026ndash;0.22]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e0.13 [0.05\u0026ndash;0.62]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eWBC, /\u0026mu;L \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e5400 [4200\u0026ndash;6350]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e5700 [4525\u0026ndash;7000]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eTotal peripheral neutrophils, /\u0026mu;L \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e2789 [2369\u0026ndash;4014]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e3472 [2726\u0026ndash;4563]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eTotal peripheral lymphocytes, /\u0026mu;L \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e1452 [1206\u0026ndash;1774]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e1528 [1226\u0026ndash;1909]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003ePlatelets, \u0026times;10\u003csup\u003e4\u0026nbsp;\u003c/sup\u003e/\u0026mu;L \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e19.9 [17.2\u0026ndash;24.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e21.6 [18.0\u0026ndash;28.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eHb, g/dL \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e12.7 [11.9\u0026ndash;14.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e12.6 [11.1\u0026ndash;13.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003ePathological diagnosis, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eCholecystitis 14 (37.8) \u0026nbsp;\u003c/p\u003e\n \u003cp\u003eXGC \u0026nbsp;8 (21.6) \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eADM \u0026nbsp;7 (18.9) \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePolyp \u0026nbsp;5 (13.5) \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eHyperplasia \u0026nbsp;2 (5.4) \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eXanthoma \u0026nbsp;1 (2.7) \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eGBC \u0026nbsp;76 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eT stage, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp;Tis-T1 \u0026nbsp;18 (23.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;T2 \u0026nbsp; \u0026nbsp;40 (52.6)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; T3 \u0026nbsp; \u0026nbsp;9 (11.8)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; T4 \u0026nbsp; \u0026nbsp;9 (11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eN stage, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp;N0 \u0026nbsp;56 (73.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;N1 \u0026nbsp;18 (23.7)\u003c/p\u003e\n \u003cp\u003eN2 \u0026nbsp; 2 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eTNM stage, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp;0-I \u0026nbsp; 18 (23.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; II \u0026nbsp; 28 (36.8)\u003c/p\u003e\n \u003cp\u003eIII-IV \u0026nbsp;30 (39.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 643px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e BMI, body mass Index; ASA-PS, American Society of Anesthesiologists-Physical Status; Alb, albumin; T-Bil, total bilirubin; CRP, C-reactive protein; WBC, white blood cell; Hb, hemoglobin; XGC, xanthogranulomatous cholecystitis; ADM, adenomyomatosis; GBC, gallbladder carcinoma\u003c/p\u003e\n \u003cp\u003e# Median [interquartile range]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 671px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2. Preoperative diagnostic tools such as tumor markers, cytology, and radiological imaging\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 265px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBenign\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 37)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGBC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 76)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCEA, ng/ml \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e2.5 [1.7\u0026ndash;3.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e2.1 [1.3\u0026ndash;3.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCA19-9, U/ml \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e10.8 [6.4\u0026ndash;31.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e13.7 [5.4\u0026ndash;26.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eGallstones or biliary sludge \u003csup\u003e\u0026dagger;\u003c/sup\u003e, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e18 (48.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e28 (36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003ePreoperative EUS, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e32 (86.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e51 (67.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eMain findings of EUS, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eIrregular surface protuberance/mass\u003c/p\u003e\n \u003cp\u003eWall thickening\u003c/p\u003e\n \u003cp\u003eEnlarged polyp\u003c/p\u003e\n \u003cp\u003eUnevaluable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e16 (50.0)\u003c/p\u003e\n \u003cp\u003e11 (34.4)\u003c/p\u003e\n \u003cp\u003e2 (6.2)\u003c/p\u003e\n \u003cp\u003e3 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e42 (82.3)\u003c/p\u003e\n \u003cp\u003e6 (11.8)\u003c/p\u003e\n \u003cp\u003e1 (2.0)\u003c/p\u003e\n \u003cp\u003e2 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eSuspected malignancy on EUS\u003c/p\u003e\n \u003cp\u003eby gastroenterological endoscopist, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e27 (84.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e49 (96.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003ePreoperative cytology, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e9 (24.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e18 (23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eClass I \u0026ndash; III\u003c/p\u003e\n \u003cp\u003eClass IV or V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e9 (100)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e10 (55.6)\u003c/p\u003e\n \u003cp\u003e8 (44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eFDG-PET/CT, n (%)\u003c/p\u003e\n \u003cp\u003eLocal uptake positive\u003c/p\u003e\n \u003cp\u003eLocal SUVmax value \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eNodal uptake positive\u003c/p\u003e\n \u003cp\u003eNodal SUVmax value \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e22 (59.5)\u003c/p\u003e\n \u003cp\u003e16 (72.7)\u003c/p\u003e\n \u003cp\u003e6.3 [3.7\u0026ndash;10.7]\u003c/p\u003e\n \u003cp\u003e2 (9.1)\u003c/p\u003e\n \u003cp\u003e2.7 [1.8\u0026ndash;6.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e47 (61.8)\u003c/p\u003e\n \u003cp\u003e41 (87.2)\u003c/p\u003e\n \u003cp\u003e6.8 [4.2\u0026ndash;12.4]\u003c/p\u003e\n \u003cp\u003e13 (27.7)\u003c/p\u003e\n \u003cp\u003e5.6 [3.3\u0026ndash;12.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003ePathological diagnosis with local uptake positive, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003eCholecystitis 7 (43.8)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eXGC 5 (31.3)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eADM 2 (12.5)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eHyperplasia 1 (6.2) \u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePolyp 1 (6.2) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003eGBC 76 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 671px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; EUS, endoscopic ultrasonography; FDG-PET, fluorodeoxyglucose-positron emission tomography; CT, computed tomography; XGC, xanthogranulomatous cholecystitis; ADM, adenomyomatosis; GBC, gallbladder carcinoma\u003c/p\u003e\n \u003cp\u003eReference range, CEA \u0026le; 5.0 ng/ml; CA19-9 \u0026le; 37.0 U/ml\u003c/p\u003e\n \u003cp\u003e# Median [interquartile range];\u0026nbsp;\u0026dagger;\u0026nbsp;Gallstones or biliary sludge detected by any examination\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 605px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3. Nutritional and immunological indices for the benign and GBC groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBenign\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 37)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGBC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 76)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003eGNRI, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026ge; 101.7\u003c/p\u003e\n \u003cp\u003e\u0026lt; 101.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e26 (70.3)\u003c/p\u003e\n \u003cp\u003e11 (29.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e30 (39.5)\u003c/p\u003e\n \u003cp\u003e46 (60.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.0021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003emGPS, n (%)\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13 (35.1)\u003c/p\u003e\n \u003cp\u003e24 (64.9)\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17 (22.4)\u003c/p\u003e\n \u003cp\u003e45 (59.2)\u003c/p\u003e\n \u003cp\u003e14 (18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003eNLR, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026ge; 1.76\u003c/p\u003e\n \u003cp\u003e\u0026lt; 1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e21 (56.8)\u003c/p\u003e\n \u003cp\u003e16 (43.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e57 (75.0)\u003c/p\u003e\n \u003cp\u003e19 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003ePLR, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026ge; 98.9\u003c/p\u003e\n \u003cp\u003e\u0026lt; 98.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e27 (73.0)\u003c/p\u003e\n \u003cp\u003e10 (27.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e68 (89.5)\u003c/p\u003e\n \u003cp\u003e8 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003ePNI, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026ge; 42.3\u003c/p\u003e\n \u003cp\u003e\u0026lt; 42.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e33 (89.2)\u003c/p\u003e\n \u003cp\u003e4 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e54 (71.1)\u003c/p\u003e\n \u003cp\u003e22 (28.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 605px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e GNRI, geriatric nutritional risk index; mGPS, modified Glasgow prognostic score; NLR, neutrophil/lymphocyte ratio; PLR, platelet/lymphocyte ratio; PNI, prognostic nutritional index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"bottom\" style=\"width: 58.8026%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4. Univariate and multivariate analyses of clinical factors associated with GBC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 22.2721%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinicopathological factor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 19.0458%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 19.0458%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.2721%;\"\u003e\n \u003cp\u003eMale sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e0.73 (0.33\u0026ndash;1.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.2721%;\"\u003e\n \u003cp\u003eAge \u0026ge; 75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e2.52 (1.05\u0026ndash;6.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\n \u003cp\u003e3.27 (1.27\u0026ndash;9.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.2721%;\"\u003e\n \u003cp\u003eBMI \u0026lt; 22 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e1.07 (0.48\u0026ndash;2.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.2721%;\"\u003e\n \u003cp\u003eCEA \u0026gt; 5.0 ng/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e1.55 (0.39\u0026ndash;6.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.2721%;\"\u003e\n \u003cp\u003eCA19-9 \u0026gt; 37 U/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e1.11 (0.40\u0026ndash;3.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.2721%;\"\u003e\n \u003cp\u003eGallstones or bile mud \u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e0.62 (0.28\u0026ndash;1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.2721%;\"\u003e\n \u003cp\u003eSuspected malignancy on EUS\u003c/p\u003e\n \u003cp\u003eby gastroenterological endoscopist\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e4.54 (0.82\u0026ndash;25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.2721%;\"\u003e\n \u003cp\u003eFDG-PET/CT local uptake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e2.56 (0.72\u0026ndash;9.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.2721%;\"\u003e\n \u003cp\u003eGNRI \u0026lt; 101.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e3.62 (1.56\u0026ndash;8.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e0.0027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\n \u003cp\u003e2.67 (1.03\u0026ndash;7.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.2721%;\"\u003e\n \u003cp\u003emGPS \u0026ge; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e1.88 (0.79\u0026ndash;4.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.2721%;\"\u003e\n \u003cp\u003eNLR \u0026ge; 1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e2.29 (0.99\u0026ndash;5.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.2721%;\"\u003e\n \u003cp\u003ePLR \u0026ge; 98.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e3.15 (1.13\u0026ndash;9.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\n \u003cp\u003e3.82 (1.20\u0026ndash;13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.2721%;\"\u003e\n \u003cp\u003ePNI \u0026lt; 42.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.385%;\"\u003e\n \u003cp\u003e3.36 (1.06\u0026ndash;10.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.6608%;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.489%;\"\u003e\n \u003cp\u003e1.83 (0.51\u0026ndash;7.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.5567%;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 60.3637%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e BMI, body mass index; CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; FDG-PET, fluorodeoxyglucose-positron emission tomography; CT, computed tomography; GNRI, geriatric nutritional risk index; mGPS, modified Glasgow prognostic score; NLR, neutrophil/lymphocyte ratio; PLR, platelet/lymphocyte ratio; PNI, prognostic nutritional index; OR, odds ratio; CI, confidence interval\u003c/p\u003e\n \u003cp\u003e\u0026dagger; Gallstones or bile mud detected by any examination\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 605px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 5. Nutritional\u003c/strong\u003e \u003cstrong\u003eand immunological indices for the benign and early GBC (\u0026le; T1) groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBenign\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 37)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGBC \u0026le; T1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 18)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003eGNRI, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026ge; 101.6\u003c/p\u003e\n \u003cp\u003e\u0026lt; 101.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e27 (73.0)\u003c/p\u003e\n \u003cp\u003e10 (27.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e6 (33.3)\u003c/p\u003e\n \u003cp\u003e12 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.0049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003emGPS, n (%)\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13 (35.1)\u003c/p\u003e\n \u003cp\u003e24 (64.9)\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5 (27.8)\u003c/p\u003e\n \u003cp\u003e11 (61.1)\u003c/p\u003e\n \u003cp\u003e2 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003eNLR, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026ge; 3.42\u003c/p\u003e\n \u003cp\u003e\u0026lt; 3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e5 (13.5)\u003c/p\u003e\n \u003cp\u003e32 (86.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e18 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003ePLR, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026ge; 298.1\u003c/p\u003e\n \u003cp\u003e\u0026lt; 298.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e1 (2.7)\u003c/p\u003e\n \u003cp\u003e36 (97.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e3 (16.7)\u003c/p\u003e\n \u003cp\u003e15 (83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003ePNI, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026ge; 43.9\u003c/p\u003e\n \u003cp\u003e\u0026lt; 43.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e28 (75.7)\u003c/p\u003e\n \u003cp\u003e9 (24.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003cp\u003e9 (50.0)\u003c/p\u003e\n \u003cp\u003e9 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 605px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e GNRI, geriatric nutritional risk index; mGPS, modified Glasgow prognostic score; NLR, neutrophil/lymphocyte ratio; PLR, platelet/lymphocyte ratio; PNI, prognostic nutritional index.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"529\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 529px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 6. Logistic regression analysis of clinical factors associated with early GBC (\u0026le; T1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 285px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinicopathological factor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003eMale sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e1.18 (0.38\u0026ndash;3.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003eAge \u0026ge; 75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e2.49 (0.75\u0026ndash;8.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003eBMI \u0026lt; 22 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e0.93 (0.29\u0026ndash;2.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003eCEA \u0026gt; 5.0 ng/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e1.41 (0.16\u0026ndash;29.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003eCA19-9 \u0026gt; 37 U/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e3.73 (0.59\u0026ndash;72.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003eGallstones or bile mud \u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e0.67 (0.21\u0026ndash;2.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003eSuspected malignancy on EUS\u003c/p\u003e\n \u003cp\u003eby gastroenterological endoscopist\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e2.22 (0.23\u0026ndash;21.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003eFDG-PET/CT local uptake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e1.69 (0.31\u0026ndash;13.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003eGNRI \u0026lt; 101.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e6.15 (1.85\u0026ndash;23.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003emGPS \u0026ge; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e1.41 (0.42\u0026ndash;5.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003eNLR \u0026ge; 3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003en.s.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003ePLR \u0026ge; 298.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e7.2 (0.85\u0026ndash;152.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003ePNI \u0026lt; 43.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e3.11 (0.95\u0026ndash;10.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 529px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e BMI, body mass Index; CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; FDG-PET, fluorodeoxyglucose-positron emission tomography; CT, computed tomography; GNRI, geriatric nutritional risk index; mGPS, modified Glasgow prognostic score; NLR, neutrophil/lymphocyte ratio; PLR, platelet/lymphocyte ratio; PNI, prognostic nutritional index; OR, odds ratio; CI, confidence interval\u003c/p\u003e\n \u003cp\u003e\u0026dagger;\u0026nbsp;Gallstones or bile mud detected by any examination\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 605px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 7. Surgical outcomes in the benign and malignant groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBenign\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 37)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGBC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 76)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eSurgical procedure, n (%)\u003c/p\u003e\n \u003cp\u003eCholecystectomy\u003c/p\u003e\n \u003cp\u003eGallbladder bed resection\u003c/p\u003e\n \u003cp\u003eS4a+5 resection\u003c/p\u003e\n \u003cp\u003eExtended right hepatectomy\u003c/p\u003e\n \u003cp\u003eSSPPD\u003c/p\u003e\n \u003cp\u003eHPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18 (48.7)\u003c/p\u003e\n \u003cp\u003e15 (40.5)\u003c/p\u003e\n \u003cp\u003e4 (10.8)\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15 (19.8)\u003c/p\u003e\n \u003cp\u003e29 (38.2)\u003c/p\u003e\n \u003cp\u003e26 (34.2)\u003c/p\u003e\n \u003cp\u003e2 (2.6)\u003c/p\u003e\n \u003cp\u003e2 (2.6)\u003c/p\u003e\n \u003cp\u003e2 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.0095\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eLaparoscopic and robotic surgery, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e13 (35.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e9 (11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.0033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eExtrahepatic bile duct resection, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e7 (18.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e55 (72.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eOperation time, min \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e213 [141\u0026ndash;278]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e399 [273\u0026ndash;489]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eBlood loss, ml \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e140 [18\u0026ndash;300]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e493 [208\u0026ndash;879]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eIntraoperative transfusion, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e1 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e12 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003ePostoperative in-hospital stay, days \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e7 [6\u0026ndash;11]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e14 [10\u0026ndash;25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003ePostoperative complication\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(CD\u003csup\u003e\u0026dagger;\u003c/sup\u003e \u0026ge; IIIA), n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e2 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e18 (23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e90-day mortality, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e2 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 605px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e S4a+5, segment 4a and 5; SSPPD, subtotal stomach-preserving pancreaticoduodenectomy; HPD, hepatopancreato-duodenectomy; CD, Clavien\u0026ndash;Dindo classification\u003c/p\u003e\n \u003cp\u003e# Median [interquartile range]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\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":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-clinical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijco","sideBox":"Learn more about [International Journal of Clinical Oncology](http://link.springer.com/journal/10147)","snPcode":"10147","submissionUrl":"https://www.editorialmanager.com/ijco/default2.aspx","title":"International Journal of Clinical Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Gallbladder Neoplasm, Gallbladder Diseases, Nutrition Assessment","lastPublishedDoi":"10.21203/rs.3.rs-5786974/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5786974/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIt is challenging to accurately and preoperatively diagnose gallbladder carcinoma (GBC) because patients are often asymptomatic or present with nonspecific symptoms that mimic common benign diseases in radiological findings. In this study, we evaluated the clinical usefulness of nutritional and immunological indices to distinguish GBC from benign disease.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study included 113 patients who underwent surgical resection for suspected GBC (37 benign and 76 GBC cases by pathological diagnosis). As the nutritional and immunological indices, the geriatric nutritional risk index (GNRI), modified Glasgow prognostic score (mGPS), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and prognostic nutrition index (PNI) were examined, and their usefulness in distinguishing GBC from benign disease was determined using logistic regression analyses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eGBC cases displayed significantly worse nutritional and immunological status in the GNRI, mGPS, NLR, PLR, and PNI compared with those of the benign cases. As the predictive factors to distinguish GBC from benign disease, age\u0026thinsp;\u0026gt;\u0026thinsp;75 years, GNRI\u0026thinsp;\u0026lt;\u0026thinsp;101.7, and PLR\u0026thinsp;\u0026ge;\u0026thinsp;1.76 were identified by multivariate logistic regression analyses.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePatients with GBC showed poor nutritional or immunological status compared with patients with benign disease, and a low GNRI and high PLR may be noninvasive predictors of GBC.\u003c/p\u003e","manuscriptTitle":"Clinical usefulness of nutritional and immunological indices to distinguish gallbladder carcinoma from benign disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-14 16:04:24","doi":"10.21203/rs.3.rs-5786974/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2025-01-26T23:29:38+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-01-09T22:53:19+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-01-09T21:57:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-09T13:02:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Clinical Oncology","date":"2025-01-08T03:09:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-clinical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijco","sideBox":"Learn more about [International Journal of Clinical Oncology](http://link.springer.com/journal/10147)","snPcode":"10147","submissionUrl":"https://www.editorialmanager.com/ijco/default2.aspx","title":"International Journal of Clinical Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5bddcb05-1587-4bbc-9802-9f955c757e30","owner":[],"postedDate":"January 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-12T16:06:32+00:00","versionOfRecord":{"articleIdentity":"rs-5786974","link":"https://doi.org/10.1007/s10147-025-02764-8","journal":{"identity":"international-journal-of-clinical-oncology","isVorOnly":false,"title":"International Journal of Clinical Oncology"},"publishedOn":"2025-05-07 15:57:48","publishedOnDateReadable":"May 7th, 2025"},"versionCreatedAt":"2025-01-14 16:04:24","video":"","vorDoi":"10.1007/s10147-025-02764-8","vorDoiUrl":"https://doi.org/10.1007/s10147-025-02764-8","workflowStages":[]},"version":"v1","identity":"rs-5786974","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5786974","identity":"rs-5786974","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}