Early Diagnosis of Anastomotic Leakage After Gastric Cancer Surgery Via Analysis of Inflammatory Factors in Abdominal Drainage
Background Anastomotic leakage (AL) is the most serious postoperative complication for patients with gastric cancer. We aim to develop clinically tools to detect AL in the early phase by analysis of the inflammatory factors (IFs) in abdominal drainage. Methods We prospectively included 326 patients...
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| Veröffentlicht in: | Annals of surgical oncology 2022-02, Vol.29 (2), p.1230-1241 |
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| creator | Shi, Jinyao Wu, Zhouqiao Wu, Xiaolong Shan, Fei Zhang, Yan Ying, Xiangji Li, Ziyu Ji, Jiafu |
| description | Background
Anastomotic leakage (AL) is the most serious postoperative complication for patients with gastric cancer. We aim to develop clinically tools to detect AL in the early phase by analysis of the inflammatory factors (IFs) in abdominal drainage.
Methods
We prospectively included 326 patients to establish two independent cohorts, and the concentration of IFs within abdominal drainage was detected. In the primary cohort, an IF-based AL prediction model was constructed using the least absolute shrinkage and selection operator (LASSO) regression. The predictive value of the model was later validated via the validation cohort.
Results
Analyzing the IFs with LASSO regression, we developed an Anastomotic Score system on postoperative Day 3 (AScore-POD3), which yielded high diagnostic efficacy in the primary cohort (the area under the curve (AUC) = 0.87). The predictive value of AScore-POD3 was validated in the validation cohort, and its AUC was 0.83. We further built an AScore-POD3 based nomogram by combining the AScore-POD3 system with other clinical risk factors of AL. The C-index of the nomogram was 0.93 in the primary cohort and 0.82 in the validation cohort.
Conclusions
Our study suggests that AL can be early diagnosed after gastric cancer surgery by measuring drainage IFs. |
| doi_str_mv | 10.1245/s10434-021-10763-y |
| format | Article |
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Anastomotic leakage (AL) is the most serious postoperative complication for patients with gastric cancer. We aim to develop clinically tools to detect AL in the early phase by analysis of the inflammatory factors (IFs) in abdominal drainage.
Methods
We prospectively included 326 patients to establish two independent cohorts, and the concentration of IFs within abdominal drainage was detected. In the primary cohort, an IF-based AL prediction model was constructed using the least absolute shrinkage and selection operator (LASSO) regression. The predictive value of the model was later validated via the validation cohort.
Results
Analyzing the IFs with LASSO regression, we developed an Anastomotic Score system on postoperative Day 3 (AScore-POD3), which yielded high diagnostic efficacy in the primary cohort (the area under the curve (AUC) = 0.87). The predictive value of AScore-POD3 was validated in the validation cohort, and its AUC was 0.83. We further built an AScore-POD3 based nomogram by combining the AScore-POD3 system with other clinical risk factors of AL. The C-index of the nomogram was 0.93 in the primary cohort and 0.82 in the validation cohort.
Conclusions
Our study suggests that AL can be early diagnosed after gastric cancer surgery by measuring drainage IFs.</description><identifier>ISSN: 1068-9265</identifier><identifier>EISSN: 1534-4681</identifier><identifier>DOI: 10.1245/s10434-021-10763-y</identifier><identifier>PMID: 34550478</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Abdomen ; Anastomotic leak ; Anastomotic Leak - diagnosis ; Anastomotic Leak - etiology ; Cancer surgery ; Complications ; Drainage ; Early Detection of Cancer ; Gastric cancer ; Gastrointestinal Oncology ; Humans ; Inflammation ; Medicine ; Medicine & Public Health ; Nomograms ; Oncology ; Patients ; Postoperative ; Prediction models ; Retrospective Studies ; Risk factors ; Stomach Neoplasms - surgery ; Surgery ; Surgical drains ; Surgical Oncology ; Wound drainage</subject><ispartof>Annals of surgical oncology, 2022-02, Vol.29 (2), p.1230-1241</ispartof><rights>Society of Surgical Oncology 2021</rights><rights>2021. Society of Surgical Oncology.</rights><rights>Society of Surgical Oncology 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-1e947d0a19ffef145e2c354c1feaf0c8da9ac3bd2a5cb57b4d1b5b83ada9bffa3</citedby><cites>FETCH-LOGICAL-c375t-1e947d0a19ffef145e2c354c1feaf0c8da9ac3bd2a5cb57b4d1b5b83ada9bffa3</cites><orcidid>0000-0001-5580-4979 ; 0000-0001-6878-5543</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1245/s10434-021-10763-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1245/s10434-021-10763-y$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,778,782,27911,27912,41475,42544,51306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34550478$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Shi, Jinyao</creatorcontrib><creatorcontrib>Wu, Zhouqiao</creatorcontrib><creatorcontrib>Wu, Xiaolong</creatorcontrib><creatorcontrib>Shan, Fei</creatorcontrib><creatorcontrib>Zhang, Yan</creatorcontrib><creatorcontrib>Ying, Xiangji</creatorcontrib><creatorcontrib>Li, Ziyu</creatorcontrib><creatorcontrib>Ji, Jiafu</creatorcontrib><title>Early Diagnosis of Anastomotic Leakage After Gastric Cancer Surgery Via Analysis of Inflammatory Factors in Abdominal Drainage</title><title>Annals of surgical oncology</title><addtitle>Ann Surg Oncol</addtitle><addtitle>Ann Surg Oncol</addtitle><description>Background
Anastomotic leakage (AL) is the most serious postoperative complication for patients with gastric cancer. We aim to develop clinically tools to detect AL in the early phase by analysis of the inflammatory factors (IFs) in abdominal drainage.
Methods
We prospectively included 326 patients to establish two independent cohorts, and the concentration of IFs within abdominal drainage was detected. In the primary cohort, an IF-based AL prediction model was constructed using the least absolute shrinkage and selection operator (LASSO) regression. The predictive value of the model was later validated via the validation cohort.
Results
Analyzing the IFs with LASSO regression, we developed an Anastomotic Score system on postoperative Day 3 (AScore-POD3), which yielded high diagnostic efficacy in the primary cohort (the area under the curve (AUC) = 0.87). The predictive value of AScore-POD3 was validated in the validation cohort, and its AUC was 0.83. We further built an AScore-POD3 based nomogram by combining the AScore-POD3 system with other clinical risk factors of AL. The C-index of the nomogram was 0.93 in the primary cohort and 0.82 in the validation cohort.
Conclusions
Our study suggests that AL can be early diagnosed after gastric cancer surgery by measuring drainage IFs.</description><subject>Abdomen</subject><subject>Anastomotic leak</subject><subject>Anastomotic Leak - diagnosis</subject><subject>Anastomotic Leak - etiology</subject><subject>Cancer surgery</subject><subject>Complications</subject><subject>Drainage</subject><subject>Early Detection of Cancer</subject><subject>Gastric cancer</subject><subject>Gastrointestinal Oncology</subject><subject>Humans</subject><subject>Inflammation</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Nomograms</subject><subject>Oncology</subject><subject>Patients</subject><subject>Postoperative</subject><subject>Prediction models</subject><subject>Retrospective Studies</subject><subject>Risk factors</subject><subject>Stomach Neoplasms - surgery</subject><subject>Surgery</subject><subject>Surgical drains</subject><subject>Surgical Oncology</subject><subject>Wound drainage</subject><issn>1068-9265</issn><issn>1534-4681</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNp9kD1v2zAQhokiQZO4_QMdAgKZ1fJEUh-j4dhuAAMdmmQlThRpyLHElJQHLfntPdduunU68t4PEg9jX0B8hVzpbwmEkioTOWQgykJm0wd2DZpWqqjggs6iqLI6L_QVu0lpJwSUUuiP7EoqrYUqq2v2tsS4n_h9h9shpC7x4Pl8wDSGPoyd5RuHL7h1fO5HF_mahEjbBQ6Wrj8PcevixJ87PIb207ngYfB77HscA4krtDQT7wY-b9rQd2Tk9xFpbt0ndulxn9zn85yxp9XycfE92_xYPyzmm8zKUo8ZuFqVrUCovXcelHa5lVpZ8A69sFWLNVrZtDlq2-iyUS00uqkkktB4j3LG7k69rzH8Org0ml04RPpJMnkBBciyhppc-cllY0gpOm9eY9djnAwIc0RuTsgNITd_kJuJQrfn6kPTu_Y98pcxGeTJkEgaCNi_t_9T-xuOwI99</recordid><startdate>20220201</startdate><enddate>20220201</enddate><creator>Shi, Jinyao</creator><creator>Wu, Zhouqiao</creator><creator>Wu, Xiaolong</creator><creator>Shan, Fei</creator><creator>Zhang, Yan</creator><creator>Ying, Xiangji</creator><creator>Li, Ziyu</creator><creator>Ji, Jiafu</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TO</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0001-5580-4979</orcidid><orcidid>https://orcid.org/0000-0001-6878-5543</orcidid></search><sort><creationdate>20220201</creationdate><title>Early Diagnosis of Anastomotic Leakage After Gastric Cancer Surgery Via Analysis of Inflammatory Factors in Abdominal Drainage</title><author>Shi, Jinyao ; Wu, Zhouqiao ; Wu, Xiaolong ; Shan, Fei ; Zhang, Yan ; Ying, Xiangji ; Li, Ziyu ; Ji, Jiafu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-1e947d0a19ffef145e2c354c1feaf0c8da9ac3bd2a5cb57b4d1b5b83ada9bffa3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Abdomen</topic><topic>Anastomotic leak</topic><topic>Anastomotic Leak - diagnosis</topic><topic>Anastomotic Leak - etiology</topic><topic>Cancer surgery</topic><topic>Complications</topic><topic>Drainage</topic><topic>Early Detection of Cancer</topic><topic>Gastric cancer</topic><topic>Gastrointestinal Oncology</topic><topic>Humans</topic><topic>Inflammation</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Nomograms</topic><topic>Oncology</topic><topic>Patients</topic><topic>Postoperative</topic><topic>Prediction models</topic><topic>Retrospective Studies</topic><topic>Risk factors</topic><topic>Stomach Neoplasms - surgery</topic><topic>Surgery</topic><topic>Surgical drains</topic><topic>Surgical Oncology</topic><topic>Wound drainage</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shi, Jinyao</creatorcontrib><creatorcontrib>Wu, Zhouqiao</creatorcontrib><creatorcontrib>Wu, Xiaolong</creatorcontrib><creatorcontrib>Shan, Fei</creatorcontrib><creatorcontrib>Zhang, Yan</creatorcontrib><creatorcontrib>Ying, Xiangji</creatorcontrib><creatorcontrib>Li, Ziyu</creatorcontrib><creatorcontrib>Ji, Jiafu</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Annals of surgical oncology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shi, Jinyao</au><au>Wu, Zhouqiao</au><au>Wu, Xiaolong</au><au>Shan, Fei</au><au>Zhang, Yan</au><au>Ying, Xiangji</au><au>Li, Ziyu</au><au>Ji, Jiafu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Early Diagnosis of Anastomotic Leakage After Gastric Cancer Surgery Via Analysis of Inflammatory Factors in Abdominal Drainage</atitle><jtitle>Annals of surgical oncology</jtitle><stitle>Ann Surg Oncol</stitle><addtitle>Ann Surg Oncol</addtitle><date>2022-02-01</date><risdate>2022</risdate><volume>29</volume><issue>2</issue><spage>1230</spage><epage>1241</epage><pages>1230-1241</pages><issn>1068-9265</issn><eissn>1534-4681</eissn><abstract>Background
Anastomotic leakage (AL) is the most serious postoperative complication for patients with gastric cancer. We aim to develop clinically tools to detect AL in the early phase by analysis of the inflammatory factors (IFs) in abdominal drainage.
Methods
We prospectively included 326 patients to establish two independent cohorts, and the concentration of IFs within abdominal drainage was detected. In the primary cohort, an IF-based AL prediction model was constructed using the least absolute shrinkage and selection operator (LASSO) regression. The predictive value of the model was later validated via the validation cohort.
Results
Analyzing the IFs with LASSO regression, we developed an Anastomotic Score system on postoperative Day 3 (AScore-POD3), which yielded high diagnostic efficacy in the primary cohort (the area under the curve (AUC) = 0.87). The predictive value of AScore-POD3 was validated in the validation cohort, and its AUC was 0.83. We further built an AScore-POD3 based nomogram by combining the AScore-POD3 system with other clinical risk factors of AL. The C-index of the nomogram was 0.93 in the primary cohort and 0.82 in the validation cohort.
Conclusions
Our study suggests that AL can be early diagnosed after gastric cancer surgery by measuring drainage IFs.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>34550478</pmid><doi>10.1245/s10434-021-10763-y</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-5580-4979</orcidid><orcidid>https://orcid.org/0000-0001-6878-5543</orcidid></addata></record> |
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| ispartof | Annals of surgical oncology, 2022-02, Vol.29 (2), p.1230-1241 |
| issn | 1068-9265 1534-4681 |
| language | eng |
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| source | MEDLINE; Springer Nature - Complete Springer Journals |
| subjects | Abdomen Anastomotic leak Anastomotic Leak - diagnosis Anastomotic Leak - etiology Cancer surgery Complications Drainage Early Detection of Cancer Gastric cancer Gastrointestinal Oncology Humans Inflammation Medicine Medicine & Public Health Nomograms Oncology Patients Postoperative Prediction models Retrospective Studies Risk factors Stomach Neoplasms - surgery Surgery Surgical drains Surgical Oncology Wound drainage |
| title | Early Diagnosis of Anastomotic Leakage After Gastric Cancer Surgery Via Analysis of Inflammatory Factors in Abdominal Drainage |
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