Background
Partial hepatectomy is an important treatment for elderly patients with hepatocellular
carcinoma. However, prediction of long-term outcomes of an individual elderly patient
after partial hepatectomy still is lacking. This study aimed to develop 2 nomograms
to pre- or postoperatively predict overall survival for these patients.
Methods
Of the 528 elderly patients (aged ≥65 years) who underwent partial hepatectomy for
hepatocellular carcinoma at the Eastern Hepatobiliary Surgery Hospital between 2008
and 2011, 425 patients served as a training cohort to develop pre- and postoperative
nomograms, and the remaining 103 patients comprised a validation cohort. The Cox proportional
hazards model was used for univariate and multivariable analyses of tumor recurrence
and overall survival. Discrimination and calibration of the models were measured using
the concordance index, calibration plots, and Kaplan-Meier curves.
Results
Based on preoperative data, the independent risk factors of overall survival were
age ≥75 years, Charlson score, α-fetoprotein ≥20 μg/L, hepatitis B virus-deoxyribonucleic
acid ≥104 IU/mL, and tumor diameter. Based on postoperative data, nonanatomic hepatectomy,
absence of tumor encapsulation, and presence of microvascular invasion were additional
independent risk factors. These independent predictors were incorporated into the
pre- and postoperative nomograms, respectively. The concordance indexes of the 2 nomograms
for overall survival prediction were 0.70 (95% confidence interval, 0.67–0.74) and
0.72 (0.69–0.78), respectively. Both nomograms accurately predicted 1-, 3-, and 5-year
overall survival probability, and their predictive performances were optimally validated.
Conclusion
The proposed 2 nomograms showed good individualized predictive performance in elderly
patients with hepatocellular carcinoma before and after partial hepatectomy.
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Article info
Publication history
Published online: October 21, 2017
Accepted:
July 28,
2017
Footnotes
Supported by the State Key Project on Infectious Diseases of China (2012ZX10002-016 to F.S.) and the Creative Research Groups of National Natural Science Foundation of China (30921006 to F.S.).
Identification
Copyright
© 2017 Elsevier Inc. All rights reserved.