Impact of tumor size  in predicting outcome in patients with ampullary cancer

Impact of tumor size in predicting outcome in patients with ampullary cancer | 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 Impact of tumor size in predicting outcome in patients with ampullary cancer Paromita Roy, Pritam Ray, Rohit Tapadia, Sudeep Banerjee, Indranil Mallick, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8014203/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Mar, 2026 Read the published version in Journal of Gastrointestinal Cancer → Version 1 posted 9 You are reading this latest preprint version Abstract Purpose : Periampullary, pancreatic ductal, distal bile duct and duodenal carcinomas have overlapping gross presentation and morphology. Exact site of origin is often difficult to establish conclusively, yet they have differing AJCC TNM staging systems. This makes grossing Whipple’s specimens daunting in centers with limited volume, increasing the chance of inaccurate staging. The aim of this study is to validate an alternative size-based staging system for ampullary cancers, using pancreatic ductal adenocarcinoma staging characteristics, which can simplify pathological assessment of Whipple’s specimens. Methods : Clinicopathologic data from all consecutive patients of ampullary adenocarcinoma were retrospectively reviewed. Prognostic correlation of this alternative size-based staging system (using cut-offs of 2 and 4cm) was done with disease free survival (DFS) and overall survival (OS). This alternative staging proposal was compared with the current AJCC8 tumour staging system and other histological prognostic parameters. Results : After applying exclusion criteria, 146 cases were analyzed in this study. The tumor size-based stage did not correlate significantly with DFS (p=0.4) or OS (p=0.3), but the AJCC8 T stage did (p=0.03). Multivariate analysis using both AJCC T stage and size-based categorization, also did not show any prognostic correlation with outcome, though positive surgical margins, perineural invasion and the pN2 nodal status were established as independent prognostic factors. Conclusions : Tumor size-based staging (using pancreatic ductal cancer criteria) is currently inferior to AJCC TNM stage for ampullary carcinoma and needs further evaluation in large multi-institutional studies. Ampulla Tumour size Survival Whipple AJCC TNM periampullary grossing Figures Figure 1 Figure 2 Introduction Whipple specimens can pose significant challenges and confusion, even to experienced pathologists. Anatomic variations and proximity of several important structures in this resection specimen raises challenges in grossing, including the identification of the tumor epicenter for accurate site classification and staging.[1] Most commonly the tumours in this small zone include pancreatic ductal adenocarcinomas (PDAC) and ampullary adenocarcinoma (AC). Though PDAC is more common in the Western population, in the Eastern population ACs are more common than PDAC.[2] Rarely, distal cholangiocarcinoma, and duodenal adenocarcinomas can also involve the periampullary region. Each of these sites have different staging systems and require documentation of different gross and microscopic parameters. ACs are specifically defined as tumors that arise from the distal-most portion of the common bile duct (CBD) or pancreatic duct (PD), as they get surrounded by the sphincter of Oddi.[1] The confluence of the CBD and PD may or may not occur at this level, and in case of the latter, they may open separately but adjacent to each other into the duodenal lumen through the major papilla.[3] AC accounts for only 0.2 to 0.5% of all gastrointestinal cancers.[4] A subset of ACs show pancreatobiliary histology, that is molecularly more similar to PDAC than cholangiocarcinoma.[5] Yet, these tumours have a better outcome than PDAC, primarily believed to be due to a smaller size at identification, causing early obstruction to bile drainage due to the location of the tumor epicenter.[6] The current American Joint Committee on Cancer (AJCC) staging system, 8th edition for AC is based on the depth of invasion progressively into the sphincter of Oddi, duodenal submucosa, muscularis, pancreatic parenchyma, peripancreatic tissue, duodenal serosa, and finally superior mesenteric artery/celiac axis/common hepatic artery involvement.[7] This was an improvement over AJCC 7, with better stratification of level of duodenal wall invasion (into stages 1a, 2, 3b and 4) and subclassification of pancreas invasion based on a cut off of 5mm (into stages 3a and b) for improved prognostic accuracy.[8] The recently updated Union for International Cancer Control (UICC) TNM 9th edition is similar to AJCC 8 with no further changes.[9] However, the staging system has not been extensively validated and various researchers have demonstrated shortcomings of the current staging system.[10–13] This calls for a need to re-look at the pTNM system for AC. For PDAC the current tumor staging is based on tumour size (using cut-offs of 0.5cm, 1cm, 2cm and 4cm).[7] At the time of grossing, it may often be unclear to the pathologist if the primary site of tumor origin is pancreas or ampulla. In the case of voluminous tumors, the site of origin may remain undetermined, as the landmark structures to determine ampullary origin are effaced by the tumor. Hence a size-based staging would make assessment easier and the grossing protocols uniform for the tumours in the periampullary region. In this study, we have proposed an alternative staging for ACs using the PDAC staging characteristics (based on tumour size). We aim to evaluate the prognostic significance of this alternative size-based staging system, and compare with the current AJCC staging for AC. Methodology Clinicopathologic data from all consecutive patients who underwent surgery with curative intent for AC between June 2012 and June 2022 were collected retrospectively from the electronic medical records. Palliative procedures, cases with neoadjuvant treatment, non-adenocarcinoma histology, those with undetermined tumor size even after re-review, and cases lost to follow-up were excluded. An institutional review board consent waiver was sought for this study (EC/WV/TMC/18/23). Histopathological prognostic parameters recorded included tumour subtype, tumour size, grade, perineural invasion (PNI), lymphovascular invasion (LVI), tumour budding (using International tumour budding consensus conference (ITBCC) scoring criteria with 20x hotspot field of 0.95mm sq), margin status, nodal yield, and existing tumour and nodal stage, which were noted from the pathology reports.[14] The tumor size recorded in the reports during macroscopic assessment of the specimen (and correlated with microscopy) were documented using the greatest dimension, and categorized as 0-0.5cm, >0.5-1.0cm, >1.0-2cm, >2 cm to 4cm and >4cm. Hematoxylin-eosin stained slides of cases older than 2018, were reviewed to re-stage them as per the AJCC 8th edition staging system for AC. As the stage definition of pT3a and b are based on the depth of invasion into pancreas (upto or >5mm), this sub-classification could not be clearly done for some cases even after re-reviewing the slides and these were grouped together as pT3. Follow-up was recorded from the electronic medical records (EMR) and the outcome was coded as the occurrence of local, regional, or distant failure until the last follow-up. Disease free (DFS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared by log rank (Mantel-Cox) test. A p-value of <0.05 was regarded as statistically significant. Patients who died within 30 days after surgery were excluded from survival analyses. The data was analyzed using SPSS v24.0 software. Results From 260 consecutive cases that underwent whipple resection (47 of them with pylorus preserving pancreaticoduodenectomy), 146 cases of AC were included for analysis in this study (after excluding cases of non-adenocarcinoma histology such as neuroendocrine tumours, non-invasive intra-ampullary adenomas etc, post neoadjuvant cases, palliative intent surgeries, and those who were lost to follow-up),. The details of clinicopathological parameters are recorded in Table 1 . Tumour and nodal stage done based on AJCC 8th edition were additionally regrouped as pT1 (including subgroups 1a, 1b and uncategorized pT1 cases), pT2 and pT3. There were no pT4 cases in our cohort. They were also categorized into 3 groups based on tumor size (0–2 cm, >2cm up to 4 cm, and > 4cm). The nodal yield ranged from 16–29 nodes, with a median yield of 22 nodes. The median involved nodal count was 1 (ranging from 1–3 nodes); and median lymph node ratio was 0.03 (range 0.00 to 0.14). Tables 2 a and b show the correlation of TNM stage and tumour size with other prognostic parameters. While the AJCC T stage correlates with LVI, PNI, lymph node ratio and nodal stage; the tumour size correlates with LVI and N stage, but not with T stage. The median follow-up period of our cohort was 21 months (range 2-113 months). Recurrence was noted in 35 cases, of which 13 were local, 14 cases had retroperitoneal lymph node recurrence and 28 had distant metastasis (liver metastasis − 23 cases (16%); lung − 4 cases (2.7%); bone 1 case (0.7%)). The 3 year DFS was 62.6% while the 3 year OS was 86.7%. Univariate analysis based on tumor size groups showed a 2 year DFS of 69.1%, 66.8% and 71.1% for tumor sizes of up to 2 cm, > 2 cm − 4 cm and > 4 cm (p = 0.4) (Fig. 1 ). We additionally evaluated our cases using cut-offs of pancreatic tumour staging (up to 0.5cm, > 0.5- 1cm, > 1-2cm, > 2-4cm and > 4cm), but this grouping also showed no prognostic significance (p = 0.4) with 2 year DFS of 74.3%, 65%, 66.8% and 71% respectively. (Fig. 2 ) Based on T stage groups it was 79.5%, 69.9% and 61.3% for pT1, pT2 and pT3 tumors (p = 0.09). However, when all stage subgroups were compared, it showed statistically significant correlation with DFS (p = 0.03) There was no difference between intestinal and pancreaticobiliary histologies (68.6% vs. 61.1%, p = 0.9). On the other hand, positive margins (0% vs 70.2%, p < 0.001), presence of LVI (54.8% vs. 87.5%, p < 0.001), presence of PNI (48.5% vs. 83.5%, p < 0.001) and lymph node stage and ratio (p < 0.001), correlated significantly with DFS. On correlating with OS, tumour size groups showed a 2 year survival of 92.4%, 84.1% and 88.9% and 3 year survival of 90.1%, 84.1% and 66.7% for tumor sizes of 0.1-2 cm, 2.1-4 cm and > 4 cm (p = 0.3). Multivariable analysis of prognostic factors is shown in Table 3 . The only independent prognostic factors for DFS were positive surgical margins, perineural invasion and the pN2 nodal status. Discussion AC has traditionally been staged using a "sphere model" in which the ampulla is thought to be sequentially covered by the duodenum, pancreas, and finally peripancreatic soft tissues, with the stage increasing as the tumor invades more in that speculative order.[ 15 ] This approach is in contrast to the size-based staging of PDAC, which was introduced in the AJCC 8th edition. For accurate staging, careful assessment of the tumour site of origin is required. Whipple specimens are one of the most difficult for grossing, due to the complex anatomy and rarity. The bi-valving or axial sectioning methods are more suited for pancreatic head tumours, but small ampullary tumours can be completely missed by these methods.[ 16 , 17 ] In our experience, cutting along the bile duct to open the specimen, is an easy quick approach, which gives better visualization of ampullary tumours, for evaluation of invasion of adjacent structures A large study involving 1080 patients from the SEER (surveillance epidemiology and end result) database and using tumour size as a criteria, an alternate staging system was proposed by Wang et al for AC.[ 12 ] In contrast to our study and the size guideline for head of pancreas staging, they used cut-offs of 1cm (pT1), > 1 to 3cm (pT2) and > 3cm or peripancreatic involvement for pT3 and found this new staging system to be a better discriminator of prognosis than the AJCC 7th edition stage. Using similar cut-offs of 1 cm, our cohort did not show any prognostic significance (p = 0.184). The traditional AJCC 8th edition T stage when grouped as pT1, T2 and T3 also did not show any significant prognostic correlation, though when subgroups were compared, pT stage was a highly significant predictor of outcome in our cohort (p = 0.03). Kim and Imamura both showed that though there was clinically significant prognostic difference between some of the T subgroups, this was not the case for most of the stage subgroups. Kim showed significant difference between pT1a and 1b (p = 0.005), pT3a and 3b (p = 0.03), pN0 and N1 (p = 0.001), and N1 and N2 (p = 0.007); there was no significant difference between T1b (invading duodenal submucosa) and T2 (invading duodenal muscularis) (p = 0.20), T2 and T3a (p = 0.84), T3b and T4 (p = 0.17). Imamura showed similar observations between stage pT1b and T2 (p = 0.9319), T2 and T3a (p = 0.0732), and T3a and T3b (p = 0.2118).[ 6 , 11 ] Lymph node stage (N2) and lymph node ratio are significant predictors of outcome in our cohort, both in multivariate and univariate analysis respectively, as shown by other studies. The alternative lymph node ratio based staging and lymph node involvement based clinical staging showed better prognostic assessment than the current AJCC stage. [ 13 , 18 ] Conclusion Though a uniform size based staging criteria has the potential to simplify grossing approach for ampullary and pancreatic head tumours, it was not superior to the current 8th AJCC/UICC TNM staging system in predicting survival in our cohort. Larger multi-institutional studies are required to explore the potential of an alternative size based uniform staging system for AC and PDAC. Declarations Author Contribution Paromita Roy, DC and IM wrote the main manuscript textPR, PR, RT, SB, IM, DC (all authors) reviewed the manuscriptIM prepared the figures and did the statistical analysis References Abu Hilal M, Uijterwijk BA, Lemmers DHL, Janssen BV, Besselink MG, Bianchi D, Fariña A, Fukushima N, Gill AJ, Hong S-M, Krasinskas A, Luchini C, Melocchi L, Rossi G, Scarpa A, Basturk O, Chatterjee D, Chou A, Esposito I, Feakins R, Groot Koerkamp B, Hruban RH, La Rosa S, Shi C, Singhi A, Verheij J, Wang H, Alfieri S, Ausania F, Alseidi A, Bruno MJ, Boggi U, Bnà C, Dervenis C, Falconi M, Ghidini M, Kist JW, Marchegiani G, Milella M, Salvia R, Siriwardena A, Wilmink H, Zaniboni A, Al-Janabi S, Holm MB, Roos E, Sano N, Song IH, Tarcan Z, Balzano G, Frigerio I, Guglielmi A, Malleo G, Asbun H, Adsay V, Verbeke C (2025) The Brescia international multidisciplinary consensus guidelines on the optimal pathology assessment and multidisciplinary pathways of non-pancreatic neoplasms in and around the ampulla of Vater (PERIPAN). 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Histopathological characteristics of ampullary carcinoma Characteristic N = 146 1 Age 56 (49, 65) Gender Male 92 (63%) Female 54 (37%) Histologic type Adenocarcinoma, intestinal type 58 (39.7%) Adenocarcinoma, pancreatico-biliary type 69 (47.2%) Adenocarcinoma, mixed/unclassified 13 (8.9%) Colloid carcinoma (mucinous noncystic carcinoma) 1 (0.7%) Signet-ring cell carcinoma 2 (1.4%) Adenosquamous carcinoma 1 (0.7%) Intraductal papillary-mucinous neoplasm with an associated invasive carcinoma 1 (0.7%) Neuroendocrine carcinoma (poorly differentiated)# 0 (0%) Clear cell adenocarcinoma 1 (0.7%) Histologic grade G1: Well differentiated 23 (16%) G2: Moderately differentiated 97 (66%) G3: Poorly differentiated 26 (18%) Maximum tumour dimension (cm) 1.70 (1.30, 2.50) Size group 0.0-2.0 cm 0-0.5 cm >0.5-1.0 cm >1.0-2.0 cm 95 (65%) 5 (03%) 21 (14.3%) 69 (47.3%) 2.1-4.0 cm 42 (29%) > 4.0 cm 9 (6.2%) Margin main Uninvolved 142 (97%) Involved 4 (2.7%) Lymphovascular_invasion Not identified 70 (48%) Present 76 (52%) Perineural_invasion Not identified 90 (62%) Present 56 (38%) Total number of peri-pancreatic lymph nodes 22 (16, 29) Number of peri-pancreatic lymph nodes involved by tumour 1.00 (1.0, 3.00) Lymph Node ratio 0.03 (0.00, 0.14) pT stage (As per AJCC/UICC TNM 8th edition) pT1 3 (2.1%) pT1a 10 (6.8%) pT1b 25 (17%) pT1c 0 (0%) pT2 44 (30%) pT3 12 (8.2%) pT3a 15 (10%) pT3b 37 (25%) pT4 0 (0%) Grouped pT stage pT1 38 (26%) pT2 44 (30%) pT3 64 (44%) pN stage (According to AJCC/UICC TNM 8th edition) pN0 69 (47%) pN1 54 (37%) pN2 23 (16%) Bud count 6 (2, 12) Tumour budding group (ITBCC) Low (0-5) 69 (47%) Intermediate (6-11) 39 (27%) High (>=12) 38 (26%) 1 Median (Q1, Q3); n (%) Table 2a. Correlation of T stage with other histological factors in ampullary carcinoma Characteristic pT1 N = 38 1 pT2 N = 44 1 pT3 N = 64 1 pT4 N = 0 1 p-value 2 Size group 0.072 0.0-2.0 cm 30 (79%) 30 (68%) 35 (55%) 0 (NA%) 2.1-4.0 cm 8 (21%) 12 (27%) 22 (34%) 0 (NA%) > 4.0 cm 0 (0%) 2 (4.5%) 7 (11%) 0 (NA%) Margin main 0.12 Uninvolved 38 (100%) 44 (100%) 60 (94%) 0 (NA%) Involved 0 (0%) 0 (0%) 4 (6.3%) 0 (NA%) lymphovascular_invasion <0.001 Not identified 28 (74%) 24 (55%) 18 (28%) 0 (NA%) Present 10 (26%) 20 (45%) 46 (72%) 0 (NA%) perineural_invasion <0.001 Not identified 33 (87%) 33 (75%) 24 (38%) 0 (NA%) Present 5 (13%) 11 (25%) 40 (63%) 0 (NA%) Total number of peri-pancreatic lymph nodes 23 (18, 28) 22 (15, 28) 22 (16, 30) NA (NA, NA) 0.5 Number of peri-pancreatic lymph nodes involved by tumour 0.00 (0.00, 1.00) 0.00 (0.00, 2.00) 2.00 (0.00, 4.50) NA (NA, NA) <0.001 Lymph Node ratio 0.00 (0.00, 0.03) 0.00 (0.00, 0.09) 0.09 (0.00, 0.21) NA (NA, NA) <0.001 pN stage (According to AJCC/UICC TNM 8th edition) 0.003 pN0 26 (68%) 23 (52%) 20 (31%) 0 (NA%) pN1 10 (26%) 16 (36%) 28 (44%) 0 (NA%) pN2 2 (5.3%) 5 (11%) 16 (25%) 0 (NA%) 1 n (%); Median (Q1, Q3) 2 Fisher's exact test; Kruskal-Wallis rank sum test Table 2b. Correlation of tumour size with other histological factors in ampullary carcinoma Characteristic 0.0-2.0 cm N = 95 1 2.1-4.0 cm N = 42 1 > 4.0 cm N = 9 1 p-value 2 pT stage 0.072 pT1 30 (32%) 8 (19%) 0 (0%) pT2 30 (32%) 12 (29%) 2 (22%) pT3 35 (37%) 22 (52%) 7 (78%) pT4 0 (0%) 0 (0%) 0 (0%) Margin main 0.071 Uninvolved 94 (99%) 40 (95%) 8 (89%) Involved 1 (1.1%) 2 (4.8%) 1 (11%) lymphovascular_invasion 0.022 Not identified 53 (56%) 13 (31%) 4 (44%) Present 42 (44%) 29 (69%) 5 (56%) perineural_invasion 0.8 Not identified 60 (63%) 25 (60%) 5 (56%) Present 35 (37%) 17 (40%) 4 (44%) Total number of peri-pancreatic lymph nodes 21 (15, 27) 24 (16, 30) 21 (19, 29) 0.3 Number of peri-pancreatic lymph nodes involved by tumour 0.00 (0.00, 3.00) 2.00 (0.00, 4.00) 0.00 (0.00, 4.00) 0.2 Lymph Node ratio 0.00 (0.00, 0.12) 0.06 (0.00, 0.15) 0.00 (0.00, 0.19) 0.3 pN stage (According to AJCC/UICC TNM 8th edition) 0.009 pN0 47 (49%) 17 (40%) 5 (56%) pN1 40 (42%) 13 (31%) 1 (11%) pN2 8 (8.4%) 12 (29%) 3 (33%) 1 n (%); Median (Q1, Q3) 2 Fisher's exact test; Kruskal-Wallis rank sum test Table 3. Multivariate analysis of prognostic features Characteristic HR 95% CI p-value Margin main Uninvolved — — Involved 10.9 2.42, 48.9 0.002 lymphovascular_invasion Not identified — — Present 1.77 0.69, 4.56 0.2 perineural_invasion Not identified — — Present 2.71 1.28, 5.75 0.009 Size group 0.0-2.0 cm — — 2.1-4.0 cm 0.67 0.31, 1.44 0.3 > 4.0 cm 0.47 0.13, 1.74 0.3 pN stage (According to AJCC/UICC TNM 8th edition) pN0 — — pN1 0.97 0.38, 2.51 >0.9 pN2 2.81 1.05, 7.56 0.041 Abbreviations: CI = Confidence Interval, HR = Hazard Ratio Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 17 Mar, 2026 Read the published version in Journal of Gastrointestinal Cancer → Version 1 posted Editorial decision: Revision requested 07 Dec, 2025 Reviews received at journal 01 Dec, 2025 Reviews received at journal 18 Nov, 2025 Reviewers agreed at journal 18 Nov, 2025 Reviewers agreed at journal 10 Nov, 2025 Reviewers invited by journal 09 Nov, 2025 Editor assigned by journal 08 Nov, 2025 Submission checks completed at journal 04 Nov, 2025 First submitted to journal 02 Nov, 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8014203","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":547122879,"identity":"7672a9f4-e2a1-49ce-8090-9f55c5e73e09","order_by":0,"name":"Paromita 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Center","correspondingAuthor":false,"prefix":"","firstName":"Pritam","middleName":"","lastName":"Ray","suffix":""},{"id":547122881,"identity":"5b6d5983-0c02-46f7-bc5e-641b4136a146","order_by":2,"name":"Rohit Tapadia","email":"","orcid":"","institution":"Tata Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Rohit","middleName":"","lastName":"Tapadia","suffix":""},{"id":547122882,"identity":"e2313eaf-e7d6-4873-82eb-497c68886ef2","order_by":3,"name":"Sudeep Banerjee","email":"","orcid":"","institution":"Tata Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Sudeep","middleName":"","lastName":"Banerjee","suffix":""},{"id":547122883,"identity":"078574b2-b952-476c-b00e-b7baa9f5b94b","order_by":4,"name":"Indranil Mallick","email":"","orcid":"","institution":"Tata Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Indranil","middleName":"","lastName":"Mallick","suffix":""},{"id":547122884,"identity":"c72076e2-88b5-4233-a0f6-da2b79a311fc","order_by":5,"name":"Deyali Chatterjee","email":"","orcid":"","institution":"Vanderbilt University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Deyali","middleName":"","lastName":"Chatterjee","suffix":""}],"badges":[],"createdAt":"2025-11-03 03:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8014203/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8014203/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12029-026-01441-x","type":"published","date":"2026-03-17T15:59:23+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":96285039,"identity":"ba017edd-2d46-4285-bd71-e864b2d4bee9","added_by":"auto","created_at":"2025-11-19 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11:55:53","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":120593,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8014203/v1/c6409ef576d38e820486240c.html"},{"id":96285031,"identity":"9a4e88ab-770d-4e21-b12b-6022f2b27bcb","added_by":"auto","created_at":"2025-11-19 11:55:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":85683,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan Meier survival graph showing correlation of tumour size groups with disease free survival\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8014203/v1/eff5bdd15e42c07345e8e85e.png"},{"id":96285032,"identity":"0caf1e11-ffb3-4217-b067-9662fafa9a79","added_by":"auto","created_at":"2025-11-19 11:55:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":98563,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan Meier survival graph showing correlation of tumour size groups (based on pancreatic tumour staging criteria) with disease free survival\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8014203/v1/20db1759da252b3416428f93.png"},{"id":105224728,"identity":"43636e86-9582-459b-87e4-ad27260b4640","added_by":"auto","created_at":"2026-03-23 16:15:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2597732,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8014203/v1/3cc81639-fc52-4c16-8b11-9c73208752f9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of tumor size in predicting outcome in patients with ampullary cancer ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWhipple specimens can pose significant challenges and confusion, even to experienced pathologists. Anatomic variations and proximity of several important structures in this resection specimen raises challenges in grossing, including the identification of the tumor epicenter for accurate site classification and staging.[1] Most commonly the tumours in this small zone include pancreatic ductal adenocarcinomas (PDAC) and ampullary adenocarcinoma (AC). Though PDAC is more common in the Western population, in the Eastern population ACs are more common than PDAC.[2] Rarely, distal cholangiocarcinoma, and duodenal adenocarcinomas can also involve the periampullary region. Each of these sites have different staging systems and require documentation of different gross and microscopic parameters. \u003c/p\u003e\n\u003cp\u003eACs are specifically defined as tumors that arise from the distal-most portion of the common bile duct (CBD) or pancreatic duct (PD), as they get surrounded by the sphincter of Oddi.[1] The confluence of the CBD and PD may or may not occur at this level, and in case of the latter, they may open separately but adjacent to each other into the duodenal lumen through the major papilla.[3] AC accounts for only 0.2 to 0.5% of all gastrointestinal cancers.[4] A subset of ACs show pancreatobiliary histology, that is molecularly more similar to PDAC than cholangiocarcinoma.[5] Yet, these tumours have a better outcome than PDAC, primarily believed to be due to a smaller size at identification, causing early obstruction to bile drainage due to the location of the tumor epicenter.[6] \u003c/p\u003e\n\u003cp\u003eThe current American Joint Committee on Cancer (AJCC) staging system, 8th edition for AC is based on the depth of invasion progressively into the sphincter of Oddi, duodenal submucosa, muscularis, pancreatic parenchyma, peripancreatic tissue, duodenal serosa, and finally superior mesenteric artery/celiac axis/common hepatic artery involvement.[7] This was an improvement over AJCC 7, with better stratification of level of duodenal wall invasion (into stages 1a, 2, 3b and 4) and subclassification of pancreas invasion based on a cut off of 5mm (into stages 3a and b) for improved prognostic accuracy.[8] The recently updated Union for International Cancer Control (UICC) TNM 9th edition is similar to AJCC 8 with no further changes.[9] However, the staging system has not been extensively validated and various researchers have demonstrated shortcomings of the current staging system.[10–13] This calls for a need to re-look at the pTNM system for AC. For PDAC the current tumor staging is based on tumour size (using cut-offs of 0.5cm, 1cm, 2cm and 4cm).[7] At the time of grossing, it may often be unclear to the pathologist if the primary site of tumor origin is pancreas or ampulla. In the case of voluminous tumors, the site of origin may remain undetermined, as the landmark structures to determine ampullary origin are effaced by the tumor. Hence a size-based staging would make assessment easier and the grossing protocols uniform for the tumours in the periampullary region. \u003c/p\u003e\n\u003cp\u003eIn this study, we have proposed an alternative staging for ACs using the PDAC staging characteristics (based on tumour size). We aim to evaluate the prognostic significance of this alternative size-based staging system, and compare with the current AJCC staging for AC.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eClinicopathologic data from all consecutive patients who underwent surgery with curative intent for AC between June 2012 and June 2022 were collected retrospectively from the electronic medical records. Palliative procedures, cases with neoadjuvant treatment, non-adenocarcinoma histology, those with undetermined tumor size even after re-review, and cases lost to follow-up were excluded. An institutional review board consent waiver was sought for this study (EC/WV/TMC/18/23). \u003c/p\u003e\n\u003cp\u003eHistopathological prognostic parameters recorded included tumour subtype, tumour size, grade, perineural invasion (PNI), lymphovascular invasion (LVI), tumour budding (using International tumour budding consensus conference (ITBCC) scoring criteria with 20x hotspot field of 0.95mm sq), margin status, nodal yield, and existing tumour and nodal stage, which were noted from the pathology reports.[14] The tumor size recorded in the reports during macroscopic assessment of the specimen (and correlated with microscopy) were documented using the greatest dimension, and categorized as 0-0.5cm, \u0026gt;0.5-1.0cm, \u0026gt;1.0-2cm, \u0026gt;2 cm to 4cm and \u0026gt;4cm. Hematoxylin-eosin stained slides of cases older than 2018, were reviewed to re-stage them as per the AJCC 8th edition staging system for AC. As the stage definition of pT3a and b are based on the depth of invasion into pancreas (upto or \u0026gt;5mm), this sub-classification could not be clearly done for some cases even after re-reviewing the slides and these were grouped together as pT3. \u003c/p\u003e\n\u003cp\u003eFollow-up was recorded from the electronic medical records (EMR) and the outcome was coded as the occurrence of local, regional, or distant failure until the last follow-up. Disease free (DFS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared by log rank (Mantel-Cox) test. A p-value of \u0026lt;0.05 was regarded as statistically significant. Patients who died within 30 days after surgery were excluded from survival analyses. The data was analyzed using SPSS v24.0 software.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFrom 260 consecutive cases that underwent whipple resection (47 of them with pylorus preserving pancreaticoduodenectomy), 146 cases of AC were included for analysis in this study (after excluding cases of non-adenocarcinoma histology such as neuroendocrine tumours, non-invasive intra-ampullary adenomas etc, post neoadjuvant cases, palliative intent surgeries, and those who were lost to follow-up),.\u003c/p\u003e\u003cp\u003eThe details of clinicopathological parameters are recorded in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eTumour and nodal stage done based on AJCC 8th edition were additionally regrouped as pT1 (including subgroups 1a, 1b and uncategorized pT1 cases), pT2 and pT3. There were no pT4 cases in our cohort. They were also categorized into 3 groups based on tumor size (0\u0026ndash;2 cm, \u0026gt;2cm up to 4 cm, and \u0026gt;\u0026thinsp;4cm). The nodal yield ranged from 16\u0026ndash;29 nodes, with a median yield of 22 nodes. The median involved nodal count was 1 (ranging from 1\u0026ndash;3 nodes); and median lymph node ratio was 0.03 (range 0.00 to 0.14). Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003ea and b show the correlation of TNM stage and tumour size with other prognostic parameters. While the AJCC T stage correlates with LVI, PNI, lymph node ratio and nodal stage; the tumour size correlates with LVI and N stage, but not with T stage.\u003c/p\u003e\u003cp\u003eThe median follow-up period of our cohort was 21 months (range 2-113 months). Recurrence was noted in 35 cases, of which 13 were local, 14 cases had retroperitoneal lymph node recurrence and 28 had distant metastasis (liver metastasis \u0026minus;\u0026thinsp;23 cases (16%); lung \u0026minus;\u0026thinsp;4 cases (2.7%); bone 1 case (0.7%)). The 3 year DFS was 62.6% while the 3 year OS was 86.7%.\u003c/p\u003e\u003cp\u003eUnivariate analysis based on tumor size groups showed a 2 year DFS of 69.1%, 66.8% and 71.1% for tumor sizes of up to 2 cm, \u0026gt;\u0026thinsp;2 cm \u0026minus;\u0026thinsp;4 cm and \u0026gt;\u0026thinsp;4 cm (p\u0026thinsp;=\u0026thinsp;0.4) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We additionally evaluated our cases using cut-offs of pancreatic tumour staging (up to 0.5cm, \u0026gt;\u0026thinsp;0.5- 1cm, \u0026gt;\u0026thinsp;1-2cm, \u0026gt;\u0026thinsp;2-4cm and \u0026gt;\u0026thinsp;4cm), but this grouping also showed no prognostic significance (p\u0026thinsp;=\u0026thinsp;0.4) with 2 year DFS of 74.3%, 65%, 66.8% and 71% respectively. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eBased on T stage groups it was 79.5%, 69.9% and 61.3% for pT1, pT2 and pT3 tumors (p\u0026thinsp;=\u0026thinsp;0.09). However, when all stage subgroups were compared, it showed statistically significant correlation with DFS (p\u0026thinsp;=\u0026thinsp;0.03) There was no difference between intestinal and pancreaticobiliary histologies (68.6% vs. 61.1%, p\u0026thinsp;=\u0026thinsp;0.9). On the other hand, positive margins (0% vs 70.2%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), presence of LVI (54.8% vs. 87.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), presence of PNI (48.5% vs. 83.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and lymph node stage and ratio (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), correlated significantly with DFS.\u003c/p\u003e\u003cp\u003eOn correlating with OS, tumour size groups showed a 2 year survival of 92.4%, 84.1% and 88.9% and 3 year survival of 90.1%, 84.1% and 66.7% for tumor sizes of 0.1-2 cm, 2.1-4 cm and \u0026gt;\u0026thinsp;4 cm (p\u0026thinsp;=\u0026thinsp;0.3).\u003c/p\u003e\u003cp\u003eMultivariable analysis of prognostic factors is shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The only independent prognostic factors for DFS were positive surgical margins, perineural invasion and the pN2 nodal status.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAC has traditionally been staged using a \"sphere model\" in which the ampulla is thought to be sequentially covered by the duodenum, pancreas, and finally peripancreatic soft tissues, with the stage increasing as the tumor invades more in that speculative order.[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] This approach is in contrast to the size-based staging of PDAC, which was introduced in the AJCC 8th edition. For accurate staging, careful assessment of the tumour site of origin is required. Whipple specimens are one of the most difficult for grossing, due to the complex anatomy and rarity. The bi-valving or axial sectioning methods are more suited for pancreatic head tumours, but small ampullary tumours can be completely missed by these methods.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] In our experience, cutting along the bile duct to open the specimen, is an easy quick approach, which gives better visualization of ampullary tumours, for evaluation of invasion of adjacent structures\u003c/p\u003e\u003cp\u003eA large study involving 1080 patients from the SEER (surveillance epidemiology and end result) database and using tumour size as a criteria, an alternate staging system was proposed by Wang et al for AC.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] In contrast to our study and the size guideline for head of pancreas staging, they used cut-offs of 1cm (pT1), \u0026gt;\u0026thinsp;1 to 3cm (pT2) and \u0026gt;\u0026thinsp;3cm or peripancreatic involvement for pT3 and found this new staging system to be a better discriminator of prognosis than the AJCC 7th edition stage. Using similar cut-offs of 1 cm, our cohort did not show any prognostic significance (p\u0026thinsp;=\u0026thinsp;0.184).\u003c/p\u003e\u003cp\u003eThe traditional AJCC 8th edition T stage when grouped as pT1, T2 and T3 also did not show any significant prognostic correlation, though when subgroups were compared, pT stage was a highly significant predictor of outcome in our cohort (p\u0026thinsp;=\u0026thinsp;0.03). Kim and Imamura both showed that though there was clinically significant prognostic difference between some of the T subgroups, this was not the case for most of the stage subgroups. Kim showed significant difference between pT1a and 1b (p\u0026thinsp;=\u0026thinsp;0.005), pT3a and 3b (p\u0026thinsp;=\u0026thinsp;0.03), pN0 and N1 (p\u0026thinsp;=\u0026thinsp;0.001), and N1 and N2 (p\u0026thinsp;=\u0026thinsp;0.007); there was no significant difference between T1b (invading duodenal submucosa) and T2 (invading duodenal muscularis) (p\u0026thinsp;=\u0026thinsp;0.20), T2 and T3a (p\u0026thinsp;=\u0026thinsp;0.84), T3b and T4 (p\u0026thinsp;=\u0026thinsp;0.17). Imamura showed similar observations between stage pT1b and T2 (p\u0026thinsp;=\u0026thinsp;0.9319), T2 and T3a (p\u0026thinsp;=\u0026thinsp;0.0732), and T3a and T3b (p\u0026thinsp;=\u0026thinsp;0.2118).[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eLymph node stage (N2) and lymph node ratio are significant predictors of outcome in our cohort, both in multivariate and univariate analysis respectively, as shown by other studies. The alternative lymph node ratio based staging and lymph node involvement based clinical staging showed better prognostic assessment than the current AJCC stage. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThough a uniform size based staging criteria has the potential to simplify grossing approach for ampullary and pancreatic head tumours, it was not superior to the current 8th AJCC/UICC TNM staging system in predicting survival in our cohort. Larger multi-institutional studies are required to explore the potential of an alternative size based uniform staging system for AC and PDAC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eParomita Roy, DC and IM wrote the main manuscript textPR, PR, RT, SB, IM, DC (all authors) reviewed the manuscriptIM prepared the figures and did the statistical analysis\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbu Hilal M, Uijterwijk BA, Lemmers DHL, Janssen BV, Besselink MG, Bianchi D, Fari\u0026ntilde;a A, Fukushima N, Gill AJ, Hong S-M, Krasinskas A, Luchini C, Melocchi L, Rossi G, Scarpa A, Basturk O, Chatterjee D, Chou A, Esposito I, Feakins R, Groot Koerkamp B, Hruban RH, La Rosa S, Shi C, Singhi A, Verheij J, Wang H, Alfieri S, Ausania F, Alseidi A, Bruno MJ, Boggi U, Bn\u0026agrave; C, Dervenis C, Falconi M, Ghidini M, Kist JW, Marchegiani G, Milella M, Salvia R, Siriwardena A, Wilmink H, Zaniboni A, Al-Janabi S, Holm MB, Roos E, Sano N, Song IH, Tarcan Z, Balzano G, Frigerio I, Guglielmi A, Malleo G, Asbun H, Adsay V, Verbeke C (2025) The Brescia international multidisciplinary consensus guidelines on the optimal pathology assessment and multidisciplinary pathways of non-pancreatic neoplasms in and around the ampulla of Vater (PERIPAN). United European Gastroenterol J. https://doi.org/10.1002/ueg2.70074\u003c/li\u003e\n\u003cli\u003eGaidhani RH, Balasubramaniam G (2021) An epidemiological review of pancreatic cancer with special reference to India. Indian J Med Sci 73:99\u0026ndash;109. https://doi.org/10.25259/ijms_92_2020\u003c/li\u003e\n\u003cli\u003eAvisse C, Flament J-B, Delattre J-F (2000) Ampulla of Vater. Surg Clin North Am 80:201\u0026ndash;212. https://doi.org/10.1016/s0039-6109(05)70402-3\u003c/li\u003e\n\u003cli\u003eJemal A, Siegel R, Ward E, Hao Y, Xu J, Murray T, Thun MJ (2008) Cancer statistics, 2008. CA Cancer J Clin 58:71\u0026ndash;96. https://doi.org/10.3322/CA.2007.0010\u003c/li\u003e\n\u003cli\u003eCheng J, Mao Y, Hong W, Hu W, Shu P, Huang K, Yu J, Jiang M, Li L, Wang W, Ni D, Li S (2022) Multimodal data analysis reveals that pancreatobiliary-type ampullary adenocarcinoma resembles pancreatic adenocarcinoma and differs from cholangiocarcinoma. J Transl Med 20:272. https://doi.org/10.1186/s12967-022-03473-w\u003c/li\u003e\n\u003cli\u003eKim K, Chie EK, Jang J-Y, Kim SW, Oh D-Y, Im S-A, Kim T-Y, Bang Y-J, Ha SW (2009) Role of adjuvant chemoradiotherapy for ampulla of Vater cancer. Int J Radiat Oncol Biol Phys 75:436\u0026ndash;441. https://doi.org/10.1016/j.ijrobp.2008.11.067\u003c/li\u003e\n\u003cli\u003eAmin MB, Greene FL, Edge SB, Compton CC, Gershenwald JE, Brookland RK, Meyer L, Gress DM, Byrd DR, Winchester DP (2017) The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more \u0026ldquo;personalized\u0026rdquo; approach to cancer staging. CA Cancer J Clin 67:93\u0026ndash;99. https://doi.org/10.3322/caac.21388\u003c/li\u003e\n\u003cli\u003eLemmers DH, Nappo G, Robinson S, Bonds M, Mortimer M, Mavroeidis VK, Burdio F, Bolm L, Pessaux P, Wellner U, Ielpo B, Soonawalla Z, Al-Sarireh B, Armstrong T, Alseidi A, White S, Zerbi A, Besselink MG, Hilal MA (2022) Validation of the eighth edition of the American joint committee on cancer (AJCC) TNM staging system in patients with resected ampullary adenocarcinoma. HPB (Oxford) 24:S303. https://doi.org/10.1016/j.hpb.2022.05.640\u003c/li\u003e\n\u003cli\u003eBrierley JD, Giuliani M, O\u0026rsquo;Sullivan B, Rous B, Van Eycken E (2025) TNM classification of malignant tumours, 9th ed. John Wiley \u0026amp; Sons, Nashville, TN\u003c/li\u003e\n\u003cli\u003eKim SJ, An S, Kang HJ, Kim JY, Jang MA, Lee JH, Song K-B, Hwang DW, Cho H, Kim SC, Yu E, Hong S-M (2018) Validation of the eighth edition of the American Joint Committee on Cancer staging system for ampulla of Vater cancer. Surgery 163:1071\u0026ndash;1079. https://doi.org/10.1016/j.surg.2017.12.018\u003c/li\u003e\n\u003cli\u003eImamura T, Yamamoto Y, Sugiura T, Okamura Y, Ito T, Ashida R, Ohgi K, Uesaka K (2019) The Prognostic Relevance of the New 8th Edition of the Union for International Cancer Control Classification of TNM Staging for Ampulla of Vater Carcinoma. Ann Surg Oncol 26:1639\u0026ndash;1648. https://doi.org/10.1245/s10434-019-07238-6\u003c/li\u003e\n\u003cli\u003eWang S-J, Li Y-F, Liao S, Wei Y-Z, Zhou Y-M (2021) Proposal of a new T-stage classification system for ampullary carcinoma based on Surveillance, Epidemiology and End Result (SEER) database. Hepatobiliary Pancreat Dis Int 20:568\u0026ndash;573. https://doi.org/10.1016/j.hbpd.2021.07.009\u003c/li\u003e\n\u003cli\u003eHe J, Kim JR, Lee SY, Oh J, Park T, Kang MJ, Kwon W, Kim H, Kim S-W, Cameron JL, Wolfgang CL, Jang J-Y (2017) Proposed new staging system for ampulla of Vater cancer with greater discriminatory ability: multinational study from eastern and western centers. J Hepatobiliary Pancreat Sci 24:475\u0026ndash;484. https://doi.org/10.1002/jhbp.486\u003c/li\u003e\n\u003cli\u003eZlobec I, Berger MD, Lugli A (2020) Tumour budding and its clinical implications in gastrointestinal cancers. Br J Cancer 123:700\u0026ndash;708. https://doi.org/10.1038/s41416-020-0954-z\u003c/li\u003e\n\u003cli\u003eCloyd JM (2019) Staging for Ampullary Carcinoma: Is Less Actually More? Ann Surg Oncol 26:1598\u0026ndash;1600. https://doi.org/10.1245/s10434-019-07241-x\u003c/li\u003e\n\u003cli\u003eAdsay NV, Basturk O, Saka B, Bagci P, Ozdemir D, Balci S, Sarmiento JM, Kooby DA, Staley C, Maithel SK, Everett R, Cheng JD, Thirabanjasak D, Weaver DW (2014) Whipple made simple for surgical pathologists: orientation, dissection, and sampling of pancreaticoduodenectomy specimens for a more practical and accurate evaluation of pancreatic, distal common bile duct, and ampullary tumors. Am J Surg Pathol 38:480\u0026ndash;493. https://doi.org/10.1097/PAS.0000000000000165\u003c/li\u003e\n\u003cli\u003eVerbeke CS (2017) Operative specimen handling and evaluation of resection margins. In: Pancreatic Cancer. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 67\u0026ndash;87\u003c/li\u003e\n\u003cli\u003eZhang X, Sun C, Li Z, Wang T, Zhao L, Niu P, Guo C, Chen Y, Che X, Zhao D (2021) Development and validation of a new lymph node ratio-based staging system for ampullary carcinoma after curative pancreaticoduodenectomy. Front Oncol 11:811595. https://doi.org/10.3389/fonc.2021.811595\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Histopathological characteristics of ampullary carcinoma\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"600\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN = 146\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e56 (49, 65)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Male\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e92 (63%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Female\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e54 (37%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistologic type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Adenocarcinoma, intestinal type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e58 (39.7%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Adenocarcinoma, pancreatico-biliary type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e69 (47.2%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Adenocarcinoma, \u0026nbsp;mixed/unclassified\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13 (8.9%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Colloid carcinoma (mucinous noncystic carcinoma)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1 (0.7%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Signet-ring cell carcinoma\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2 (1.4%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Adenosquamous carcinoma\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1 (0.7%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Intraductal papillary-mucinous neoplasm with an associated invasive carcinoma\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1 (0.7%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Neuroendocrine carcinoma (poorly differentiated)#\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (0%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Clear cell adenocarcinoma\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1 (0.7%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistologic grade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; G1: Well differentiated\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e23 (16%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; G2: Moderately differentiated\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e97 (66%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; G3: Poorly differentiated\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e26 (18%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaximum tumour dimension (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.70 (1.30, 2.50)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSize group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; 0.0-2.0 cm\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0-0.5 cm\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026gt;0.5-1.0 cm\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026gt;1.0-2.0 cm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95 (65%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e5 (03%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e21 (14.3%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e69 (47.3%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; 2.1-4.0 cm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e42 (29%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026gt; 4.0 cm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9 (6.2%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMargin main\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Uninvolved\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e142 (97%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Involved\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4 (2.7%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLymphovascular_invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Not identified\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e70 (48%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Present\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e76 (52%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePerineural_invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Not identified\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e90 (62%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Present\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e56 (38%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal number of peri-pancreatic lymph nodes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22 (16, 29)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of peri-pancreatic lymph nodes involved by tumour\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.00 (1.0, 3.00)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLymph Node ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03 (0.00, 0.14)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epT stage (As per AJCC/UICC TNM 8th edition)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3 (2.1%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT1a\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10 (6.8%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT1b\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25 (17%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT1c\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (0%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e44 (30%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12 (8.2%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT3a\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15 (10%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT3b\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e37 (25%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (0%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrouped pT stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e38 (26%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e44 (30%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e64 (44%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epN stage (According to AJCC/UICC TNM 8th edition)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pN0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e69 (47%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pN1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e54 (37%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pN2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e23 (16%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBud count\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6 (2, 12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumour budding group (ITBCC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Low (0-5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e69 (47%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Intermediate (6-11)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e39 (27%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 493px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; High (\u0026gt;=12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e38 (26%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 600px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eMedian (Q1, Q3); n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2a. Correlation of T stage with other histological factors in ampullary carcinoma\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"607\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epT1 N = 38\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epT2 N = 44\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epT3 N = 64\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epT4 N = 0\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSize group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.072\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; 0.0-2.0 cm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30 (79%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30 (68%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e35 (55%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (NA%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; 2.1-4.0 cm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8 (21%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12 (27%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22 (34%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (NA%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026gt; 4.0 cm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (0%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2 (4.5%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7 (11%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (NA%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMargin main\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Uninvolved\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e38 (100%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e44 (100%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e60 (94%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (NA%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Involved\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (0%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (0%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4 (6.3%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (NA%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003elymphovascular_invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Not identified\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28 (74%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e24 (55%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18 (28%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (NA%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Present\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10 (26%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20 (45%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e46 (72%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (NA%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eperineural_invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Not identified\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e33 (87%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e33 (75%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e24 (38%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (NA%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Present\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (13%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11 (25%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e40 (63%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (NA%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal number of peri-pancreatic lymph nodes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e23 (18, 28)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22 (15, 28)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22 (16, 30)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNA (NA, NA)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of peri-pancreatic lymph nodes involved by tumour\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.00 (0.00, 1.00)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.00 (0.00, 2.00)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.00 (0.00, 4.50)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNA (NA, NA)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLymph Node ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.00 (0.00, 0.03)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.00 (0.00, 0.09)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.09 (0.00, 0.21)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNA (NA, NA)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epN stage (According to AJCC/UICC TNM 8th edition)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pN0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e26 (68%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e23 (52%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20 (31%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (NA%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pN1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10 (26%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16 (36%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28 (44%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (NA%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pN2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2 (5.3%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (11%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16 (25%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (NA%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 607px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003en (%); Median (Q1, Q3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 607px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eFisher\u0026apos;s exact test; Kruskal-Wallis rank sum test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2b. Correlation of tumour size with other histological factors in ampullary carcinoma\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"610\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0-2.0 cm N = 95\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.1-4.0 cm N = 42\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt; 4.0 cm N = 9\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epT stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.072\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30 (32%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8 (19%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (0%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30 (32%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12 (29%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2 (22%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e35 (37%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22 (52%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7 (78%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pT4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (0%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (0%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0 (0%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMargin main\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.071\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Uninvolved\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e94 (99%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e40 (95%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8 (89%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Involved\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1 (1.1%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2 (4.8%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1 (11%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003elymphovascular_invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Not identified\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e53 (56%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13 (31%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4 (44%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Present\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e42 (44%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e29 (69%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (56%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eperineural_invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Not identified\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e60 (63%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25 (60%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (56%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Present\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e35 (37%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17 (40%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4 (44%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal number of peri-pancreatic lymph nodes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21 (15, 27)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e24 (16, 30)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21 (19, 29)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of peri-pancreatic lymph nodes involved by tumour\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.00 (0.00, 3.00)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.00 (0.00, 4.00)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.00 (0.00, 4.00)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLymph Node ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.00 (0.00, 0.12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.06 (0.00, 0.15)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.00 (0.00, 0.19)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epN stage (According to AJCC/UICC TNM 8th edition)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pN0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e47 (49%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17 (40%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (56%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pN1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e40 (42%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13 (31%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1 (11%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pN2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8 (8.4%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12 (29%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3 (33%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 610px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003en (%); Median (Q1, Q3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 610px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eFisher\u0026apos;s exact test; Kruskal-Wallis rank sum test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Multivariate analysis of prognostic features\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"479\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\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 valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMargin main\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Uninvolved\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026mdash;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026mdash;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Involved\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.42, 48.9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003elymphovascular_invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Not identified\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026mdash;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026mdash;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Present\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.77\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.69, 4.56\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eperineural_invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Not identified\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026mdash;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026mdash;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Present\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.71\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.28, 5.75\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSize group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; 0.0-2.0 cm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026mdash;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026mdash;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; 2.1-4.0 cm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.67\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.31, 1.44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026gt; 4.0 cm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.47\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.13, 1.74\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epN stage (According to AJCC/UICC TNM 8th edition)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pN0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026mdash;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026mdash;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pN1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.97\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.38, 2.51\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;0.9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; pN2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.81\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.05, 7.56\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.041\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 479px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations: CI = Confidence Interval, HR = Hazard Ratio\u003c/strong\u003e\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":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-gastrointestinal-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijgc","sideBox":"Learn more about [Journal of Gastrointestinal Cancer](https://www.springer.com/journal/12029)","snPcode":"12029","submissionUrl":"https://submission.nature.com/new-submission/12029/3","title":"Journal of Gastrointestinal Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Ampulla, Tumour size, Survival, Whipple, AJCC, TNM, periampullary, grossing ","lastPublishedDoi":"10.21203/rs.3.rs-8014203/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8014203/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e: Periampullary, pancreatic ductal, distal bile duct and duodenal carcinomas have overlapping gross presentation and morphology. Exact site of origin is often difficult to establish conclusively, yet they have differing AJCC TNM staging systems. This makes grossing Whipple’s specimens daunting in centers with limited volume, increasing the chance of inaccurate staging. The aim of this study is to validate an alternative size-based staging system for ampullary cancers, using pancreatic ductal adenocarcinoma staging characteristics, which can simplify pathological assessment of Whipple’s specimens.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Clinicopathologic data from all consecutive patients of ampullary adenocarcinoma were retrospectively reviewed. Prognostic correlation of this alternative size-based staging system (using cut-offs of 2 and 4cm) was done with disease free survival (DFS) and overall survival (OS). This alternative staging proposal was compared with the current AJCC8 tumour staging system and other histological prognostic parameters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: After applying exclusion criteria, 146 cases were analyzed in this study. The tumor size-based stage did not correlate significantly with DFS (p=0.4) or OS (p=0.3), but the AJCC8 T stage did (p=0.03). Multivariate analysis using both AJCC T stage and size-based categorization, also did not show any prognostic correlation with outcome, though positive surgical margins, perineural invasion and the pN2 nodal status were established as independent prognostic factors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Tumor size-based staging (using pancreatic ductal cancer criteria) is currently inferior to AJCC TNM stage for ampullary carcinoma and needs further evaluation in large multi-institutional studies.\u003c/p\u003e","manuscriptTitle":"Impact of tumor size in predicting outcome in patients with ampullary cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-19 11:55:48","doi":"10.21203/rs.3.rs-8014203/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-07T21:56:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-01T09:48:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-18T19:01:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"304103414714148814653765765693974622305","date":"2025-11-18T17:57:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"2358875661987797255459311661369101697","date":"2025-11-10T20:24:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-10T00:06:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-09T00:39:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-04T08:45:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Gastrointestinal Cancer","date":"2025-11-03T03:04:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-gastrointestinal-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijgc","sideBox":"Learn more about [Journal of Gastrointestinal Cancer](https://www.springer.com/journal/12029)","snPcode":"12029","submissionUrl":"https://submission.nature.com/new-submission/12029/3","title":"Journal of Gastrointestinal Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6996afb5-27f4-486c-b29b-563ea3dd20b6","owner":[],"postedDate":"November 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-23T16:12:16+00:00","versionOfRecord":{"articleIdentity":"rs-8014203","link":"https://doi.org/10.1007/s12029-026-01441-x","journal":{"identity":"journal-of-gastrointestinal-cancer","isVorOnly":false,"title":"Journal of Gastrointestinal Cancer"},"publishedOn":"2026-03-17 15:59:23","publishedOnDateReadable":"March 17th, 2026"},"versionCreatedAt":"2025-11-19 11:55:48","video":"","vorDoi":"10.1007/s12029-026-01441-x","vorDoiUrl":"https://doi.org/10.1007/s12029-026-01441-x","workflowStages":[]},"version":"v1","identity":"rs-8014203","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8014203","identity":"rs-8014203","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}