Skip to main content

Main menu

  • Home
  • About
    • About CBM
    • Editorial Board
  • Articles
    • Ahead of print
    • Current Issue
    • Archive
    • Collections
    • Cover Story
  • For Authors
    • Instructions for Authors
    • Resources
    • Submit a Manuscript
  • For Reviewers
    • Become a Reviewer
    • Instructions for Reviewers
    • Resources
    • Outstanding Reviewer
  • Subscription
  • Alerts
    • Email Alerts
    • RSS Feeds
    • Table of Contents
  • Contact us
  • Other Publications
    • cbm

User menu

  • My alerts

Search

  • Advanced search
Cancer Biology & Medicine
  • Other Publications
    • cbm
  • My alerts
Cancer Biology & Medicine

Advanced Search

 

  • Home
  • About
    • About CBM
    • Editorial Board
  • Articles
    • Ahead of print
    • Current Issue
    • Archive
    • Collections
    • Cover Story
  • For Authors
    • Instructions for Authors
    • Resources
    • Submit a Manuscript
  • For Reviewers
    • Become a Reviewer
    • Instructions for Reviewers
    • Resources
    • Outstanding Reviewer
  • Subscription
  • Alerts
    • Email Alerts
    • RSS Feeds
    • Table of Contents
  • Contact us
  • Follow cbm on Twitter
  • Visit cbm on Facebook
Research ArticleOriginal Article

Preoperative ultrasound combined with routine blood tests in predicting the malignant risk of pancreatic cystic neoplasms

Xiuchao Wang, Junjin Wang, Xi Wei, Lihui Zhao, Bo Ni, Zekun Li, Chuntao Gao, Song Gao, Tiansuo Zhao, Jian Wang, Weidong Ma, Xiao Hu and Jihui Hao
Cancer Biology & Medicine October 2022, 19 (10) 1503-1516; DOI: https://doi.org/10.20892/j.issn.2095-3941.2022.0258
Xiuchao Wang
1Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Junjin Wang
1Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xi Wei
2Department of Diagnostic and Therapeutic Ultrasonography, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lihui Zhao
2Department of Diagnostic and Therapeutic Ultrasonography, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Bo Ni
1Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Zekun Li
1Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Chuntao Gao
1Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Song Gao
1Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tiansuo Zhao
1Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jian Wang
1Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Weidong Ma
1Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xiao Hu
3Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266000, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Xiao Hu
  • For correspondence: [email protected] [email protected]
Jihui Hao
1Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jihui Hao
  • For correspondence: [email protected] [email protected]
  • Article
  • Figures & Data
  • References
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Supplementary Materials
  • Figure 1
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 1

    Screening of model variables. Variables were screened with Best Subsets Regression (BSR) (A, B; AIC = 151.3), Lasso regression (C, D; AIC = 152.27), and univariate regression and multiple logistic regression (AIC = 144.02).

  • Figure 2
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 2

    (A) Multivariate analysis revealing that increased CA19-9, increased CEA, increased NLR, increased MCHC, non-O blood group, age > 55 years, cysts located in the head or neck of the pancreas, and an unclear cyst imaging border were independent predictors of PCN malignancy. (B) Nomogram for estimating the risk of malignancy in PCN. The nomogram is used to find the position of each variable on the corresponding axis, a vertical line is drawn to the points axis to obtain the value of the corresponding variable, the points are added for all variables, and then a line is drawn from the total points axis to determine the probability of a malignant tumor at the lower part of the nomogram.

  • Figure 3
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 3

    ROC analysis of the malignancy prediction ability of the sum of scores. (A) Internal validation of the nomogram. (B) External validation of the nomogram. (C, D) Nomogram calibration in the model group (C) and the validation group (D). The horizontal axis indicates the risk of malignant PCN predicted by the nomogram, and the vertical axis is the probability of malignant PCN for a random sample of 1000 actual observations. The line from the lower left to the upper right corner of the plot region represents the reference line of the ideal prediction.

  • Figure 4
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 4

    DCA curves for assessing the net benefit of model application in the model development cohort and validation cohort.

Tables

  • Figures
  • Supplementary Materials
    • View popup
    Table 1

    Univariate logistic regression analysis based on preoperative data in the model cohort

    Variable (%)LevelOverall (%)Benign (%)Malignant (%)OR (95% CI)P
    n–20412183––
    Age (years)≤ 5587 (42.6)69 (57.0)18 (21.7)1.42 (1.25–1.61)< 0.001*
    > 55117 (57.4)52 (43.0)65 (78.3)––
    GenderFemale122 (59.8)84 (69.4)38 (45.8)1.27 (1.11–1.45)0.001*
    Male82 (40.2)37 (30.6)45 (54.2)––
    LocationBody/tail111 (54.4)84 (69.4)27 (32.5)1.43 (1.26–1.63)< 0.001*
    Head/neck93 (45.6)37 (30.6)56 (67.5)––
    Size (cm)≤ 2.75158 (77.5)97 (80.2)61 (73.5)1.1 (0.93–1.29)0.265
    > 2.7546 (22.5)24 (19.8)22 (26.5)––
    SolidNo79 (38.7)62 (51.2)17 (20.5)1.37 (1.2–1.56)< 0.001*
    Yes125 (61.3)59 (48.8)66 (79.5)––
    BoundaryClear100 (49.0)83 (68.6)17 (20.5)1.59 (1.41–1.79)< 0.001*
    Blurred104 (51.0)38 (31.4)66 (79.5)––
    JaundiceNo187 (91.7)120 (99.2)67 (80.7)1.79 (1.42–2.26)< 0.001*
    Yes17 (8.3)1 (0.8)16 (19.3)––
    StomachacheNo109 (53.4)75 (62.0)34 (41.0)1.23 (1.07–1.4)0.003*
    Yes95 (46.6)46 (38.0)49 (59.0)––
    Blood typeType-O51 (25.0)35 (28.9)16 (19.3)1.13 (0.97–1.32)0.119
    Non-O153 (75.0)86 (71.1)67 (80.7)––
    CRP (mg/L)≤ 1.2945 (22.1)11 (13.3)34 (28.1)1.23 (1.05–1.45)0.012*
    > 1.29159 (77.9)72 (86.7)87 (71.9)––
    RBC (×1012/L)≤ 4.371 (34.8)37 (30.6)34 (41.0)0.9 (0.78–1.03)0.127
    > 4.3133 (65.2)84 (69.4)49 (59.0)––
    HGB (g/L)≤ 137.5109 (53.4)69 (57.0)40 (48.2)1.09 (0.95–1.25)0.216
    > 137.595 (46.6)52 (43.0)43 (51.8)––
    HCT (%)≤ 36.5532 (15.7)14 (11.6)18 (21.7)0.83 (0.69–1.00)0.051
    > 36.55172 (84.3)107 (88.4)65 (78.3)––
    MCV (fl)≤ 90.6593 (45.6)60 (49.6)33 (39.8)1.1 (0.96–1.26)0.168
    > 90.65111 (54.4)61 (50.4)50 (60.2)––
    MCH (pg)≤ 30.75124 (60.8)79 (65.3)45 (54.2)1.12 (0.97–1.28)0.113
    > 30.7580 (39.2)42 (34.7)38 (45.8)––
    MCHC (g/L)≤ 341.5174 (85.3)109 (90.1)65 (78.3)1.25 (1.04–1.51)0.020*
    > 341.530 (14.7)12 (9.9)18 (21.7)––
    RDW.CV (%)≤ 13.4164 (80.4)107 (88.4)57 (68.7)1.35 (1.15–1.6)< 0.001*
    > 13.440 (19.6)14 (11.6)26 (31.3)––
    HR≤ 2.87543 (21.1)16 (13.2)27 (32.5)0.76 (0.64–0.89)0.001*
    > 2.875161 (78.9)105 (86.8)56 (67.5)––
    RETR (%)≤ 0.98524 (11.8)11 (9.1)13 (15.7)0.86 (0.7–1.06)0.154
    > 0.985180 (88.2)110 (90.9)70 (84.3)––
    RET (×109/L)≤ 82.4158 (77.5)90 (74.4)68 (81.9)0.90 (0.77–1.06)0.207
    > 82.446 (22.5)31 (25.6)15 (18.1)––
    WBC (×109/L)≤ 6.16124 (60.8)81 (66.9)43 (51.8)1.17 (1.02–1.34)0.030*
    > 6.1680 (39.2)40 (33.1)40 (48.2)––
    NEUT (×109/L)≤ 2.683 (40.7)58 (47.9)25 (30.1)1.19 (1.04–1.37)0.011*
    > 2.6121 (59.3)63 (52.1)58 (69.9)––
    LYMPH (×109/L)≤ 1.905132 (64.7)71 (58.7)61 (73.5)0.86 (0.74–0.98)0.030*
    > 1.90572 (35.3)50 (41.3)22 (26.5)––
    MONO (×109/L)≤ 0.535119 (58.3)79 (65.3)40 (48.2)1.19 (1.03–1.36)0.015*
    > 0.53585 (41.7)42 (34.7)43 (51.8)––
    PLT (×109/L)≤ 207.568 (33.3)34 (28.1)34 (41.0)0.87 (0.75–1.00)0.056
    > 207.5136 (66.7)87 (71.9)49 (59.0)––
    MPV (fl)≤ 11.25150 (73.5)99 (81.8)51 (61.4)1.29 (1.11–1.5)0.001*
    > 11.2554 (26.5)22 (18.2)32 (38.6)––
    P-LCR (%)≤ 37.85164 (80.4)107 (88.4)57 (68.7)1.35 (1.15–1.6)< 0.001*
    > 37.8540 (19.6)14 (11.6)26 (31.3)––
    PLR≤ 196.4723 (11.3)10 (8.3)13 (15.7)0.84 (0.68–1.03)0.102
    > 196.47181 (88.7)111 (91.7)70 (84.3)––
    NLR≤ 1.7992 (45.1)67 (55.4)25 (30.1)1.28 (1.12–1.46)< 0.001*
    > 1.79112 (54.9)54 (44.6)58 (69.9)––
    LMR≤ 3.6461 (29.9)22 (18.2)39 (47.0)0.72 (0.62–0.83)< 0.001*
    > 3.64143 (70.1)99 (81.8)44 (53.0)––
    CA19-9 (U/mL)−146 (71.6)109 (90.1)37 (44.6)1.72 (1.51–1.95)< 0.001*
    +58 (28.4)12 (9.9)46 (55.4)––
    CA242 (U/mL)−170 (83.3)117 (96.7)53 (63.9)1.77 (1.5–2.08)< 0.001*
    +34 (16.7)4 (3.3)30 (36.1)––
    CEA (μg/L)−184 (90.2)120 (99.2)64 (77.1)1.83 (1.48–2.26)< 0.001*
    +20 (9.8)1 (0.8)19 (22.9)––

    *P < 0.05 was considered statistically significant. CRP, C-reactive protein; RBC, red blood cell; HGB, hemoglobin; HCT, red blood cell specific volume; MCV, mean corpuscular volume; MCH, mean corpuscular hemoglobin; MCHC, mean corpuscular hemoglobin concentration; RDW.CV, red blood cell volume distribution width; HR, hemoglobin-red blood cell distribution width ratio; RETR, reticulocyte ratio; RET, reticulocyte; WBC, peripheral white blood cells; NEUT, neutrophils; LYMPH, lymphocyte; MONO, monocyte; PLT, platelet; MPV, mean platelet volume; P-LCR, platelet-larger cell ratio; PLR, lymphocyte-monocyte ratio; NLR, neutrophil-lymphocyte ratio; LMR, lymphocyte-monocyte ratio; CA19-9, carbohydrate antigen 19-9; CA242, carbohydrate chain antigen 242; CEA, carcinoembryonic antigen; OR, odds ratio; CI, confidence interval; +, CA199 > 37 U/ml, CA242 > 20 U/ml, CEA > 5 μg/L.

      • View popup
      Table 2

      Differences between the development cohort and validation cohort

      VariableLevelOverall (%)Development cohortValidation cohortP
      No. patients29020486
      Age (years)≤ 55117 (40.3)87300.218
      > 55173 (59.7)11756
      LocationBody/tail164 (56.6)111530.258
      Head/neck126 (43.4)9333
      BoundaryClear144 (49.7)100440.739
      Blurred146 (50.3)10442
      Blood typeType-O79 (27.2)51280.187
      Non-O211 (72.8)15358
      MCHC (g/L)≤ 341.5241 (83.1)174670.125
      > 341.549 (16.9)3019
      NLR≤ 1.79132 (45.5)92400.825
      > 1.79158 (54.5)11246
      CA19-9 (U/mL)≤ 37209 (72.1)146630.770
      > 3781 (27.9)5823
      CEA (μg/L)≤ 5256 (88.3)184720.117
      > 534 (11.7)2014
      • View popup
      Table 3

      Risk stratification and restratification

      Imaging and tumor marker modelNomogram risk modelTotalReclassified as higher risk (%)Reclassified as lower risk (%)
      Risk< 0.5≥ 0.5
      < 0.5
      No. of patients1173315033 (22%)NA
      No. of benign10571127 (6.25%)NA
      No. of malignant12263826 (68.4%)NA
      ≥ 0.5
      No. of patients45054NA4 (7.4%)
      No. of benign369NA3 (33.3%)
      No. of malignant14445NA1 (2.2%)
      Total
      No. of patients1218320433 (22%)4 (7.4%)
      No. of benign108131217 (6.25%)3 (33.3%)
      No. of malignant13708326 (68.4%)1 (2.2%)

      NRI = 26.8%; P < 0.001.

      IDI = 0.2708; P < 0.001.

      Supplementary Materials

      • Figures
      • Tables
      • [cbm-19-1503-s001.pdf]
      PreviousNext
      Back to top

      In this issue

      Cancer Biology & Medicine: 19 (10)
      Cancer Biology & Medicine
      Vol. 19, Issue 10
      15 Oct 2022
      • Table of Contents
      • Index by author
      Print
      Download PDF
      Email Article

      Thank you for your interest in spreading the word on Cancer Biology & Medicine.

      NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

      Enter multiple addresses on separate lines or separate them with commas.
      Preoperative ultrasound combined with routine blood tests in predicting the malignant risk of pancreatic cystic neoplasms
      (Your Name) has sent you a message from Cancer Biology & Medicine
      (Your Name) thought you would like to see the Cancer Biology & Medicine web site.
      Citation Tools
      Preoperative ultrasound combined with routine blood tests in predicting the malignant risk of pancreatic cystic neoplasms
      Xiuchao Wang, Junjin Wang, Xi Wei, Lihui Zhao, Bo Ni, Zekun Li, Chuntao Gao, Song Gao, Tiansuo Zhao, Jian Wang, Weidong Ma, Xiao Hu, Jihui Hao
      Cancer Biology & Medicine Oct 2022, 19 (10) 1503-1516; DOI: 10.20892/j.issn.2095-3941.2022.0258

      Citation Manager Formats

      • BibTeX
      • Bookends
      • EasyBib
      • EndNote (tagged)
      • EndNote 8 (xml)
      • Medlars
      • Mendeley
      • Papers
      • RefWorks Tagged
      • Ref Manager
      • RIS
      • Zotero
      Share
      Preoperative ultrasound combined with routine blood tests in predicting the malignant risk of pancreatic cystic neoplasms
      Xiuchao Wang, Junjin Wang, Xi Wei, Lihui Zhao, Bo Ni, Zekun Li, Chuntao Gao, Song Gao, Tiansuo Zhao, Jian Wang, Weidong Ma, Xiao Hu, Jihui Hao
      Cancer Biology & Medicine Oct 2022, 19 (10) 1503-1516; DOI: 10.20892/j.issn.2095-3941.2022.0258
      Reddit logo Twitter logo Facebook logo Mendeley logo
      • Tweet Widget
      • Facebook Like
      • Google Plus One

      Jump to section

      • Article
        • Abstract
        • Introduction
        • Materials and methods
        • Results
        • Discussion
        • Conclusions
        • Supporting Information
        • Grant support
        • Conflict of interest statement
        • Author contributions
        • Footnotes
        • References
      • Figures & Data
      • Info & Metrics
      • References
      • PDF

      Related Articles

      • No related articles found.
      • Google Scholar

      Cited By...

      • No citing articles found.
      • Google Scholar

      More in this TOC Section

      • Identification of the E2F1-RAD51AP1 axis as a key factor in MGMT-methylated GBM TMZ resistance
      • Neutrophils as key regulators of tumor immunity that restrict immune checkpoint blockade in liver cancer
      • Genetic polymorphisms in genes regulating cell death and prognosis of patients with rectal cancer receiving postoperative chemoradiotherapy
      Show more Original Article

      Similar Articles

      Keywords

      • Pancreatic cystic neoplasms
      • malignancy prediction
      • nomogram
      • ultrasound
      • blood routine

      Navigate

      • Home
      • Current Issue

      More Information

      • About CBM
      • About CACA
      • About TMUCIH
      • Editorial Board
      • Subscription

      For Authors

      • Instructions for authors
      • Journal Policies
      • Submit a Manuscript

      Journal Services

      • Email Alerts
      • Facebook
      • RSS Feeds
      • Twitter

       

      © 2023 Cancer Biology & Medicine

      Powered by HighWire