TY - JOUR
T1 - The Singapore Liver Cancer Recurrence (SLICER) Score for relapse prediction in patients with surgically resected hepatocellular carcinoma
AU - Ang, Soo Fan
AU - Ng, Elizabeth Shu Hui
AU - Li, Huihua
AU - Ong, Yu Han
AU - Choo, Su Pin
AU - Ngeow, Joanne
AU - Toh, Han Chong
AU - Lim, Kiat Hon
AU - Yap, Hao Yun
AU - Tan, Chee Kiat
AU - Ooi, London Lucien Peng Jin
AU - Chung, Alexander Yaw Fui
AU - Chow, Pierce Kah Hoe
AU - Foo, Kian Fong
AU - Tan, Min Han
AU - Cheow, Peng Chung
N1 - Publisher Copyright:
© 2015 Ang et al.
PY - 2015/4/1
Y1 - 2015/4/1
N2 - Background and Aims: Surgery is the primary curative option in patients with hepatocellular carcinoma (HCC). Current prognostic models for HCC are developed on datasets of primarily patients with advanced cancer, and may be less relevant to resectable HCC. We developed a postoperative nomogram, the Singapore Liver Cancer Recurrence (SLICER) Score, to predict outcomes of HCC patients who have undergone surgical resection. Methods: Records for 544 consecutive patients undergoing first-line curative surgery for HCC in one institution from 1992-2007 were reviewed, with 405 local patients selected for analysis. Freedom from relapse (FFR) was the primary outcome measure. An outcome-blinded modeling strategy including clustering, data reduction and transformation was used. We compared the performance of SLICER in estimating FFR with other HCC prognostic models using concordance-indices and likelihood analysis. Results: A nomogram predicting FFR was developed, incorporating non-neoplastic liver cirrhosis, multifocality, preoperative alpha-fetoprotein level, Child-Pugh score, vascular invasion, tumor size, surgical margin and symptoms at presentation. Our nomogram outperformed other HCC prognostic models in predicting FFR by means of log-likelihood ratio statistics with good calibration demonstrated at 3 and 5 years post-resection and a concordance index of 0.69. Using decision curve analysis, SLICER also demonstrated superior net benefit at higher threshold probabilities. Conclusion: The SLICER score enables well-calibrated individualized predictions of relapse following curative HCC resection, and may represent a novel tool for biomarker research and individual counseling.
AB - Background and Aims: Surgery is the primary curative option in patients with hepatocellular carcinoma (HCC). Current prognostic models for HCC are developed on datasets of primarily patients with advanced cancer, and may be less relevant to resectable HCC. We developed a postoperative nomogram, the Singapore Liver Cancer Recurrence (SLICER) Score, to predict outcomes of HCC patients who have undergone surgical resection. Methods: Records for 544 consecutive patients undergoing first-line curative surgery for HCC in one institution from 1992-2007 were reviewed, with 405 local patients selected for analysis. Freedom from relapse (FFR) was the primary outcome measure. An outcome-blinded modeling strategy including clustering, data reduction and transformation was used. We compared the performance of SLICER in estimating FFR with other HCC prognostic models using concordance-indices and likelihood analysis. Results: A nomogram predicting FFR was developed, incorporating non-neoplastic liver cirrhosis, multifocality, preoperative alpha-fetoprotein level, Child-Pugh score, vascular invasion, tumor size, surgical margin and symptoms at presentation. Our nomogram outperformed other HCC prognostic models in predicting FFR by means of log-likelihood ratio statistics with good calibration demonstrated at 3 and 5 years post-resection and a concordance index of 0.69. Using decision curve analysis, SLICER also demonstrated superior net benefit at higher threshold probabilities. Conclusion: The SLICER score enables well-calibrated individualized predictions of relapse following curative HCC resection, and may represent a novel tool for biomarker research and individual counseling.
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U2 - 10.1371/journal.pone.0118658
DO - 10.1371/journal.pone.0118658
M3 - Article
C2 - 25830231
AN - SCOPUS:84926609869
SN - 1932-6203
VL - 10
JO - PLoS One
JF - PLoS One
IS - 4
M1 - e0118658
ER -