A simplified prediction model for early intrahepatic recurrence after hepatectomy for patients with unilobar hepatocellular carcinoma without macroscopic vascular invasion: An implication for adjuvant therapy and postoperative surveillance
An accurate prediction model of early recurrence of hepatocellular carcinoma (HCC) after hepatectomy is important to ascertain the postoperative adjuvant treatment and surveillance. This is a retrospective cohort study including 1125 patients with HCC underwent curative hepatic resection. They were...
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| Veröffentlicht in: | Surgical oncology 2019-09, Vol.30, p.6-12 |
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| creator | Ng, Kelvin K. Cheung, Tan-To Pang, Herbert H. Wong, Tiffany C. Dai, Jeff W. Ma, Ka-Wing She, Wong-Hoi Kotewall, C.Nicholas Lo, Chung-Mau |
| description | An accurate prediction model of early recurrence of hepatocellular carcinoma (HCC) after hepatectomy is important to ascertain the postoperative adjuvant treatment and surveillance.
This is a retrospective cohort study including 1125 patients with HCC underwent curative hepatic resection. They were randomly divided into training (n = 562) and validation (n = 563) sets. Early intrahepatic recurrence within 18 months from surgery is the primary outcome. In the training set, a prediction scoring model (Recurrent Liver Cancer Score RLCS) was developed, which was legitimised in the validation set.
RLCS was developed based on four clinicopathologic risk factors (serum alpha fetoprotein, tumor size, multiple tumors or satellite nodules, and microvascular invasion). Low-risk and high-risk groups had statistically significant differences in early recurrence rates (18% vs. 43.8%). The 5-year recurrence-free survival rates of low risk and high risk groups were 52.9% and 27.8%, respectively. This model showed good calibration and discriminatory ability in the validation set (c-index of 0.647).
RLCS is a user-friendly prediction scoring model which can accurately predict the occurrence of early intrahepatic recurrence of HCC. It establishes the basis of postoperative adjuvant treatment and surveillance in future studies.
•User-friendly prediction model (RLCS) of early recurrence of HCC.•4 risk factors (serum AFP, tumor size, multiplicity, and microvascular invasion).•Low-risk and high-risk groups had different recurrence and survival rates.•Good calibration and discriminatory ability of RLCS. |
| doi_str_mv | 10.1016/j.suronc.2019.05.017 |
| format | Article |
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This is a retrospective cohort study including 1125 patients with HCC underwent curative hepatic resection. They were randomly divided into training (n = 562) and validation (n = 563) sets. Early intrahepatic recurrence within 18 months from surgery is the primary outcome. In the training set, a prediction scoring model (Recurrent Liver Cancer Score RLCS) was developed, which was legitimised in the validation set.
RLCS was developed based on four clinicopathologic risk factors (serum alpha fetoprotein, tumor size, multiple tumors or satellite nodules, and microvascular invasion). Low-risk and high-risk groups had statistically significant differences in early recurrence rates (18% vs. 43.8%). The 5-year recurrence-free survival rates of low risk and high risk groups were 52.9% and 27.8%, respectively. This model showed good calibration and discriminatory ability in the validation set (c-index of 0.647).
RLCS is a user-friendly prediction scoring model which can accurately predict the occurrence of early intrahepatic recurrence of HCC. It establishes the basis of postoperative adjuvant treatment and surveillance in future studies.
•User-friendly prediction model (RLCS) of early recurrence of HCC.•4 risk factors (serum AFP, tumor size, multiplicity, and microvascular invasion).•Low-risk and high-risk groups had different recurrence and survival rates.•Good calibration and discriminatory ability of RLCS.</description><identifier>ISSN: 0960-7404</identifier><identifier>EISSN: 1879-3320</identifier><identifier>DOI: 10.1016/j.suronc.2019.05.017</identifier><identifier>PMID: 31500787</identifier><language>eng</language><publisher>Netherlands: Elsevier Ltd</publisher><subject>Adjuvant therapy ; Adolescent ; Adult ; Aged ; Aged, 80 and over ; Blood transfusions ; Calibration ; Carcinoma, Hepatocellular - pathology ; Carcinoma, Hepatocellular - surgery ; Child ; Child, Preschool ; Female ; Follow-Up Studies ; Hepatectomy ; Hepatectomy - methods ; Hepatitis ; Hepatocellular carcinoma ; Histology ; Humans ; Liver cancer ; Liver Neoplasms - pathology ; Liver Neoplasms - surgery ; Male ; Medical imaging ; Medical prognosis ; Metastasis ; Microvasculature ; Middle Aged ; Models, Statistical ; Neoadjuvant Therapy ; Neoplasm Recurrence, Local - pathology ; Neoplasm Recurrence, Local - surgery ; Nodules ; Nomograms ; Patient Selection ; Patients ; Postoperative Period ; Prediction models ; Prognosis ; Prospective Studies ; Retrospective Studies ; Risk analysis ; Risk factors ; Risk groups ; Scoring models ; Statistical analysis ; Surgery ; Surveillance ; Survival Rate ; Training ; Transplants & implants ; Tumors ; Veins & arteries ; Viral infections ; Young Adult</subject><ispartof>Surgical oncology, 2019-09, Vol.30, p.6-12</ispartof><rights>2019 Elsevier Ltd</rights><rights>Copyright © 2019 Elsevier Ltd. All rights reserved.</rights><rights>2019. Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c390t-8c9a8c55b1728f275c14aaf4b366d03ae11ce2a750cdda47677ead0e261073f23</citedby><cites>FETCH-LOGICAL-c390t-8c9a8c55b1728f275c14aaf4b366d03ae11ce2a750cdda47677ead0e261073f23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.suronc.2019.05.017$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31500787$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ng, Kelvin K.</creatorcontrib><creatorcontrib>Cheung, Tan-To</creatorcontrib><creatorcontrib>Pang, Herbert H.</creatorcontrib><creatorcontrib>Wong, Tiffany C.</creatorcontrib><creatorcontrib>Dai, Jeff W.</creatorcontrib><creatorcontrib>Ma, Ka-Wing</creatorcontrib><creatorcontrib>She, Wong-Hoi</creatorcontrib><creatorcontrib>Kotewall, C.Nicholas</creatorcontrib><creatorcontrib>Lo, Chung-Mau</creatorcontrib><title>A simplified prediction model for early intrahepatic recurrence after hepatectomy for patients with unilobar hepatocellular carcinoma without macroscopic vascular invasion: An implication for adjuvant therapy and postoperative surveillance</title><title>Surgical oncology</title><addtitle>Surg Oncol</addtitle><description>An accurate prediction model of early recurrence of hepatocellular carcinoma (HCC) after hepatectomy is important to ascertain the postoperative adjuvant treatment and surveillance.
This is a retrospective cohort study including 1125 patients with HCC underwent curative hepatic resection. They were randomly divided into training (n = 562) and validation (n = 563) sets. Early intrahepatic recurrence within 18 months from surgery is the primary outcome. In the training set, a prediction scoring model (Recurrent Liver Cancer Score RLCS) was developed, which was legitimised in the validation set.
RLCS was developed based on four clinicopathologic risk factors (serum alpha fetoprotein, tumor size, multiple tumors or satellite nodules, and microvascular invasion). Low-risk and high-risk groups had statistically significant differences in early recurrence rates (18% vs. 43.8%). The 5-year recurrence-free survival rates of low risk and high risk groups were 52.9% and 27.8%, respectively. This model showed good calibration and discriminatory ability in the validation set (c-index of 0.647).
RLCS is a user-friendly prediction scoring model which can accurately predict the occurrence of early intrahepatic recurrence of HCC. It establishes the basis of postoperative adjuvant treatment and surveillance in future studies.
•User-friendly prediction model (RLCS) of early recurrence of HCC.•4 risk factors (serum AFP, tumor size, multiplicity, and microvascular invasion).•Low-risk and high-risk groups had different recurrence and survival rates.•Good calibration and discriminatory ability of RLCS.</description><subject>Adjuvant therapy</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Blood transfusions</subject><subject>Calibration</subject><subject>Carcinoma, Hepatocellular - pathology</subject><subject>Carcinoma, Hepatocellular - surgery</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Female</subject><subject>Follow-Up Studies</subject><subject>Hepatectomy</subject><subject>Hepatectomy - methods</subject><subject>Hepatitis</subject><subject>Hepatocellular carcinoma</subject><subject>Histology</subject><subject>Humans</subject><subject>Liver cancer</subject><subject>Liver Neoplasms - pathology</subject><subject>Liver Neoplasms - surgery</subject><subject>Male</subject><subject>Medical imaging</subject><subject>Medical prognosis</subject><subject>Metastasis</subject><subject>Microvasculature</subject><subject>Middle Aged</subject><subject>Models, Statistical</subject><subject>Neoadjuvant Therapy</subject><subject>Neoplasm Recurrence, Local - pathology</subject><subject>Neoplasm Recurrence, Local - surgery</subject><subject>Nodules</subject><subject>Nomograms</subject><subject>Patient Selection</subject><subject>Patients</subject><subject>Postoperative Period</subject><subject>Prediction models</subject><subject>Prognosis</subject><subject>Prospective Studies</subject><subject>Retrospective Studies</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>Risk groups</subject><subject>Scoring models</subject><subject>Statistical analysis</subject><subject>Surgery</subject><subject>Surveillance</subject><subject>Survival Rate</subject><subject>Training</subject><subject>Transplants & implants</subject><subject>Tumors</subject><subject>Veins & arteries</subject><subject>Viral infections</subject><subject>Young Adult</subject><issn>0960-7404</issn><issn>1879-3320</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9ks-O0zAQxiMEYsvCGyBkiQuXlrHzxykHpGoFC9JKXOBsTe2J6iqxg-0U9al5BZy0cNgDJ9vyb2a-mfmK4jWHDQfevD9u4hS80xsBfLuBegNcPilWvJXbdVkKeFqsYNvAWlZQ3RQvYjwCQCMFf17clLwGkK1cFb93LNph7G1nybAxkLE6We_Y4A31rPOBEYb-zKxLAQ80YrKaBdJTCOQ0MewSBbZ8kE5-OC8xM0YuRfbLpgObnO39Hq-Y19T3U5-fGoO2zg-4YH5KbEAdfNR-zEVOGPWCWZevWdMHtnNsEatx0ThXQnOcTugSSwcKOJ4ZutyHj8mP-Z3siVie04ls32PW-7J41mEf6dX1vC1-fP70_e7L-uHb_de73cNal1tI61ZvsdV1vedStJ2QteYVYlfty6YxUCJxrkmgrEEbg5VspCQ0QKLhIMtOlLfFu0veMfifE8WkBhvnxtGRn6ISom2BV61oMvr2EXr0U3BZ3UzVTVVD3WaqulDzgGKgTo3BDhjOioOaDaGO6mIINRtCQa2yIXLYm2vyaT-Q-Rf01wEZ-HgBKE_jZCmoqO28WWPzlpMy3v6_wh-K8NH8</recordid><startdate>201909</startdate><enddate>201909</enddate><creator>Ng, Kelvin K.</creator><creator>Cheung, Tan-To</creator><creator>Pang, Herbert H.</creator><creator>Wong, Tiffany C.</creator><creator>Dai, Jeff W.</creator><creator>Ma, Ka-Wing</creator><creator>She, Wong-Hoi</creator><creator>Kotewall, C.Nicholas</creator><creator>Lo, Chung-Mau</creator><general>Elsevier Ltd</general><general>Elsevier Limited</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>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>201909</creationdate><title>A simplified prediction model for early intrahepatic recurrence after hepatectomy for patients with unilobar hepatocellular carcinoma without macroscopic vascular invasion: An implication for adjuvant therapy and postoperative surveillance</title><author>Ng, Kelvin K. ; Cheung, Tan-To ; Pang, Herbert H. ; Wong, Tiffany C. ; Dai, Jeff W. ; Ma, Ka-Wing ; She, Wong-Hoi ; Kotewall, C.Nicholas ; Lo, Chung-Mau</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c390t-8c9a8c55b1728f275c14aaf4b366d03ae11ce2a750cdda47677ead0e261073f23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Adjuvant therapy</topic><topic>Adolescent</topic><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Blood transfusions</topic><topic>Calibration</topic><topic>Carcinoma, Hepatocellular - pathology</topic><topic>Carcinoma, Hepatocellular - surgery</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Female</topic><topic>Follow-Up Studies</topic><topic>Hepatectomy</topic><topic>Hepatectomy - methods</topic><topic>Hepatitis</topic><topic>Hepatocellular carcinoma</topic><topic>Histology</topic><topic>Humans</topic><topic>Liver cancer</topic><topic>Liver Neoplasms - pathology</topic><topic>Liver Neoplasms - surgery</topic><topic>Male</topic><topic>Medical imaging</topic><topic>Medical prognosis</topic><topic>Metastasis</topic><topic>Microvasculature</topic><topic>Middle Aged</topic><topic>Models, Statistical</topic><topic>Neoadjuvant Therapy</topic><topic>Neoplasm Recurrence, Local - pathology</topic><topic>Neoplasm Recurrence, Local - surgery</topic><topic>Nodules</topic><topic>Nomograms</topic><topic>Patient Selection</topic><topic>Patients</topic><topic>Postoperative Period</topic><topic>Prediction models</topic><topic>Prognosis</topic><topic>Prospective Studies</topic><topic>Retrospective Studies</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>Risk groups</topic><topic>Scoring models</topic><topic>Statistical analysis</topic><topic>Surgery</topic><topic>Surveillance</topic><topic>Survival Rate</topic><topic>Training</topic><topic>Transplants & implants</topic><topic>Tumors</topic><topic>Veins & arteries</topic><topic>Viral infections</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ng, Kelvin K.</creatorcontrib><creatorcontrib>Cheung, Tan-To</creatorcontrib><creatorcontrib>Pang, Herbert H.</creatorcontrib><creatorcontrib>Wong, Tiffany C.</creatorcontrib><creatorcontrib>Dai, Jeff W.</creatorcontrib><creatorcontrib>Ma, Ka-Wing</creatorcontrib><creatorcontrib>She, Wong-Hoi</creatorcontrib><creatorcontrib>Kotewall, C.Nicholas</creatorcontrib><creatorcontrib>Lo, Chung-Mau</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Surgical oncology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ng, Kelvin K.</au><au>Cheung, Tan-To</au><au>Pang, Herbert H.</au><au>Wong, Tiffany C.</au><au>Dai, Jeff W.</au><au>Ma, Ka-Wing</au><au>She, Wong-Hoi</au><au>Kotewall, C.Nicholas</au><au>Lo, Chung-Mau</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A simplified prediction model for early intrahepatic recurrence after hepatectomy for patients with unilobar hepatocellular carcinoma without macroscopic vascular invasion: An implication for adjuvant therapy and postoperative surveillance</atitle><jtitle>Surgical oncology</jtitle><addtitle>Surg Oncol</addtitle><date>2019-09</date><risdate>2019</risdate><volume>30</volume><spage>6</spage><epage>12</epage><pages>6-12</pages><issn>0960-7404</issn><eissn>1879-3320</eissn><abstract>An accurate prediction model of early recurrence of hepatocellular carcinoma (HCC) after hepatectomy is important to ascertain the postoperative adjuvant treatment and surveillance.
This is a retrospective cohort study including 1125 patients with HCC underwent curative hepatic resection. They were randomly divided into training (n = 562) and validation (n = 563) sets. Early intrahepatic recurrence within 18 months from surgery is the primary outcome. In the training set, a prediction scoring model (Recurrent Liver Cancer Score RLCS) was developed, which was legitimised in the validation set.
RLCS was developed based on four clinicopathologic risk factors (serum alpha fetoprotein, tumor size, multiple tumors or satellite nodules, and microvascular invasion). Low-risk and high-risk groups had statistically significant differences in early recurrence rates (18% vs. 43.8%). The 5-year recurrence-free survival rates of low risk and high risk groups were 52.9% and 27.8%, respectively. This model showed good calibration and discriminatory ability in the validation set (c-index of 0.647).
RLCS is a user-friendly prediction scoring model which can accurately predict the occurrence of early intrahepatic recurrence of HCC. It establishes the basis of postoperative adjuvant treatment and surveillance in future studies.
•User-friendly prediction model (RLCS) of early recurrence of HCC.•4 risk factors (serum AFP, tumor size, multiplicity, and microvascular invasion).•Low-risk and high-risk groups had different recurrence and survival rates.•Good calibration and discriminatory ability of RLCS.</abstract><cop>Netherlands</cop><pub>Elsevier Ltd</pub><pmid>31500787</pmid><doi>10.1016/j.suronc.2019.05.017</doi><tpages>7</tpages></addata></record> |
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| subjects | Adjuvant therapy Adolescent Adult Aged Aged, 80 and over Blood transfusions Calibration Carcinoma, Hepatocellular - pathology Carcinoma, Hepatocellular - surgery Child Child, Preschool Female Follow-Up Studies Hepatectomy Hepatectomy - methods Hepatitis Hepatocellular carcinoma Histology Humans Liver cancer Liver Neoplasms - pathology Liver Neoplasms - surgery Male Medical imaging Medical prognosis Metastasis Microvasculature Middle Aged Models, Statistical Neoadjuvant Therapy Neoplasm Recurrence, Local - pathology Neoplasm Recurrence, Local - surgery Nodules Nomograms Patient Selection Patients Postoperative Period Prediction models Prognosis Prospective Studies Retrospective Studies Risk analysis Risk factors Risk groups Scoring models Statistical analysis Surgery Surveillance Survival Rate Training Transplants & implants Tumors Veins & arteries Viral infections Young Adult |
| title | A simplified prediction model for early intrahepatic recurrence after hepatectomy for patients with unilobar hepatocellular carcinoma without macroscopic vascular invasion: An implication for adjuvant therapy and postoperative surveillance |
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