Predictive model for acute abdominal pain after transarterial chemoembolization for liver cancer
©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved..
BACKGROUND: Transarterial chemoembolization (TACE) is the first-line treatment for patients with unresectable liver cancer; however, TACE is associated with postembolization pain.
AIM: To analyze the risk factors for acute abdominal pain after TACE and establish a predictive model for postembolization pain.
METHODS: From January 2018 to September 2018, all patients with liver cancer who underwent TACE at our hospital were included. General characteristics; clinical, imaging, and procedural data; and postembolization pain were analyzed. Postembolization pain was defined as acute moderate-to-severe abdominal pain within 24 h after TACE. Logistic regression and a classification and regression tree were used to develop a predictive model. Receiver operating characteristic curve analysis was used to examine the efficacy of the predictive model.
RESULTS: We analyzed 522 patients who underwent a total of 582 TACE procedures. Ninety-seven (16.70%) episodes of severe pain occurred. A predictive model built based on the dataset from classification and regression tree analysis identified known invasion of blood vessels as the strongest predictor of subsequent performance, followed by history of TACE, method of TACE, and history of abdominal pain after TACE. The area under the receiver operating characteristic curve was 0.736 [95% confidence interval (CI): 0.682-0.789], the sensitivity was 73.2%, the specificity was 65.6%, and the negative predictive value was 92.4%. Logistic regression produced similar results by identifying age [odds ratio (OR) = 0.971; 95%CI: 0.951-0.992; P = 0.007), history of TACE (OR = 0.378; 95%CI: 0.189-0.757; P = 0.007), history of abdominal pain after TACE (OR = 6.288; 95%CI: 2.963-13.342; P < 0.001), tumor size (OR = 1.978; 95%CI: 1.175-3.330; P = 0.01), multiple tumors (OR = 2.164; 95%CI: 1.243-3.769; P = 0.006), invasion of blood vessels (OR = 1.756; 95%CI: 1.045-2.950; P = 0.034), and TACE with drug-eluting beads (DEB-TACE) (OR = 2.05; 95%CI: 1.260-3.334; P = 0.004) as independent predictive factors for postembolization pain.
CONCLUSION: Blood vessel invasion, TACE history, TACE with drug-eluting beads, and history of abdominal pain after TACE are predictors of acute moderate-to-severe pain. The predictive model may help medical staff to manage pain.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:26 |
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| Enthalten in: |
World journal of gastroenterology - 26(2020), 30 vom: 14. Aug., Seite 4442-4452 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Bian, Li-Fang [VerfasserIn] |
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| Links: |
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| Themen: |
Journal Article |
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| Anmerkungen: |
Date Completed 14.05.2021 Date Revised 14.05.2021 published: Print Citation Status MEDLINE |
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| doi: |
10.3748/wjg.v26.i30.4442 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM314470379 |
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| 100 | 1 | |a Bian, Li-Fang |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Predictive model for acute abdominal pain after transarterial chemoembolization for liver cancer |
| 264 | 1 | |c 2020 | |
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| 500 | |a Date Completed 14.05.2021 | ||
| 500 | |a Date Revised 14.05.2021 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved. | ||
| 520 | |a BACKGROUND: Transarterial chemoembolization (TACE) is the first-line treatment for patients with unresectable liver cancer; however, TACE is associated with postembolization pain | ||
| 520 | |a AIM: To analyze the risk factors for acute abdominal pain after TACE and establish a predictive model for postembolization pain | ||
| 520 | |a METHODS: From January 2018 to September 2018, all patients with liver cancer who underwent TACE at our hospital were included. General characteristics; clinical, imaging, and procedural data; and postembolization pain were analyzed. Postembolization pain was defined as acute moderate-to-severe abdominal pain within 24 h after TACE. Logistic regression and a classification and regression tree were used to develop a predictive model. Receiver operating characteristic curve analysis was used to examine the efficacy of the predictive model | ||
| 520 | |a RESULTS: We analyzed 522 patients who underwent a total of 582 TACE procedures. Ninety-seven (16.70%) episodes of severe pain occurred. A predictive model built based on the dataset from classification and regression tree analysis identified known invasion of blood vessels as the strongest predictor of subsequent performance, followed by history of TACE, method of TACE, and history of abdominal pain after TACE. The area under the receiver operating characteristic curve was 0.736 [95% confidence interval (CI): 0.682-0.789], the sensitivity was 73.2%, the specificity was 65.6%, and the negative predictive value was 92.4%. Logistic regression produced similar results by identifying age [odds ratio (OR) = 0.971; 95%CI: 0.951-0.992; P = 0.007), history of TACE (OR = 0.378; 95%CI: 0.189-0.757; P = 0.007), history of abdominal pain after TACE (OR = 6.288; 95%CI: 2.963-13.342; P < 0.001), tumor size (OR = 1.978; 95%CI: 1.175-3.330; P = 0.01), multiple tumors (OR = 2.164; 95%CI: 1.243-3.769; P = 0.006), invasion of blood vessels (OR = 1.756; 95%CI: 1.045-2.950; P = 0.034), and TACE with drug-eluting beads (DEB-TACE) (OR = 2.05; 95%CI: 1.260-3.334; P = 0.004) as independent predictive factors for postembolization pain | ||
| 520 | |a CONCLUSION: Blood vessel invasion, TACE history, TACE with drug-eluting beads, and history of abdominal pain after TACE are predictors of acute moderate-to-severe pain. The predictive model may help medical staff to manage pain | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Liver cancer | |
| 650 | 4 | |a Pain | |
| 650 | 4 | |a Postembolization syndrome | |
| 650 | 4 | |a Predictive model | |
| 650 | 4 | |a Transarterial chemoembolization | |
| 700 | 1 | |a Zhao, Xue-Hong |e verfasserin |4 aut | |
| 700 | 1 | |a Gao, Bei-Lei |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Sheng |e verfasserin |4 aut | |
| 700 | 1 | |a Ge, Guo-Mei |e verfasserin |4 aut | |
| 700 | 1 | |a Zhan, Dong-Di |e verfasserin |4 aut | |
| 700 | 1 | |a Ye, Ting-Ting |e verfasserin |4 aut | |
| 700 | 1 | |a Zheng, Yan |e verfasserin |4 aut | |
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