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Predictors for Early Liver Cancer Survival After Ablation and Surgical Resection: A Surveillance, Epidemiology, and End Results Program-Medicare Study.
Charalel, Resmi A; Mushlin, Alvin I; Zheng, Xinyan; Mao, Jialin; Carlos, Ruth; Brown, Robert S; Fortune, Brett E; Talenfeld, Adam D; Madoff, David C; Ibrahim, Said; Johnson, Matthew S; Sedrakyan, Art.
Affiliation
  • Charalel RA; Division of Interventional Radiology, Department of Radiology, Weill Cornell Medicine, New York, New York; Department of Population Health Sciences, Weill Cornell Medicine; Member of American College of Radiology Interventional Radiology Expert Panel 2 and Economics Committee for Interventional Radi
  • Mushlin AI; Department of Population Health Sciences, Weill Cornell Medicine; Member of American College of Radiology Interventional Radiology Expert Panel 2 and Economics Committee for Interventional Radiology, New York, New York; Department of Medicine, Weill Cornell Medicine, New York, New York.
  • Zheng X; Department of Population Health Sciences, Weill Cornell Medicine; Member of American College of Radiology Interventional Radiology Expert Panel 2 and Economics Committee for Interventional Radiology, New York, New York.
  • Mao J; Department of Population Health Sciences, Weill Cornell Medicine; Member of American College of Radiology Interventional Radiology Expert Panel 2 and Economics Committee for Interventional Radiology, New York, New York.
  • Carlos R; Department of Radiology, Michigan Medicine; Editor in Chief, Journal of American College of Radiology, Ann Arbor, Michigan.
  • Brown RS; Department of Medicine, Weill Cornell Medicine, New York, New York.
  • Fortune BE; Department of Medicine, Montefiore Health, Bronx, New York.
  • Talenfeld AD; Division of Interventional Radiology, Department of Radiology, Weill Cornell Medicine, New York, New York.
  • Madoff DC; Department of Radiology, Yale School of Medicine, New Haven, Connecticut.
  • Ibrahim S; Department of Medicine, Northwell Health, Manhasset, New York.
  • Johnson MS; Department of Radiology, Indiana University School of Medicine, Indianapolis, Indiana.
  • Sedrakyan A; Department of Population Health Sciences, Weill Cornell Medicine; Member of American College of Radiology Interventional Radiology Expert Panel 2 and Economics Committee for Interventional Radiology, New York, New York.
J Am Coll Radiol ; 21(2): 295-308, 2024 Feb.
Article in En | MEDLINE | ID: mdl-37922972
ABSTRACT

OBJECTIVE:

To identify independent predictors of all-cause and cancer-specific mortality after ablation or surgical resection (SR) for small hepatocellular carcinomas (HCCs), after adjusting for key confounders.

METHODS:

Using Surveillance, Epidemiology, and End Results Program-Medicare, HCCs less than 5 cm treated with ablation or SR in 2009 to 2016 (n = 956) were identified. Univariate and multivariable Cox regression models for all-cause and cancer-specific mortality were performed including demographics, clinical factors (tumor size, medical comorbidities, and liver disease factors), social determinants of health, and treatment characteristics. We also determined the most influential predictors of survival using a random forest analysis.

RESULTS:

Larger tumor size (3-5 cm) is predictive of all-cause (hazard ratio [HR] 1.31, P = .002) and cancer-specific mortality (HR 1.59, P < .001). Furthermore, chronic kidney disease is predictive of all-cause mortality (HR 1.43, P = .013), though it is not predictive of cancer-specific death. Multiple liver disease factors are predictive of all-cause and cancer-specific mortality including portal hypertension and esophageal varices (HRs > 1, P < .05). Though Asian race is protective in univariate models, in fully adjusted, multivariable models, Asian race is not a significant protective factor. Likewise, other social determinants of health are not significantly predictive of all-cause or cancer-specific mortality. Finally, treatment with SR, in later procedure years or at high-volume centers, is protective for all-cause and cancer-specific mortality. In machine learning models, year procedure was performed, ascites, portal hypertension, and treatment choice were the most influential factors.

DISCUSSION:

Treatment characteristics, liver disease factors, and tumor size are more important predictors of all-cause and cancer-specific death than social determinants of health for small HCCs.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Carcinoma, Hepatocellular / Hypertension, Portal / Liver Neoplasms Limits: Aged / Humans Country/Region as subject: America do norte Language: En Journal: J Am Coll Radiol Journal subject: RADIOLOGIA Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Carcinoma, Hepatocellular / Hypertension, Portal / Liver Neoplasms Limits: Aged / Humans Country/Region as subject: America do norte Language: En Journal: J Am Coll Radiol Journal subject: RADIOLOGIA Year: 2024 Document type: Article