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Slicer score appears to be useful tool after HCC resection

The Singapore Liver Cancer Recurrence Score was accurate in predicting outcomes for Singaporean patients who underwent resection for hepatocellular carcinoma, according to published findings.

“We have constructed a new postoperative nomogram, the Singapore Liver Cancer Recurrence score, to predict the probability of freedom from recurrence in patients who have undergone curative surgical resection for HCC,” the researchers wrote. “We also demonstrate that it performs better than several major HCC staging systems in use today in predicting probability of freedom from recurrence.”

Researchers analyzed medical records of 544 Singaporean patients who underwent primary curative resection surgery for HCC between 1992 and 2007 at Singapore General Hospital. Of these patients, 405 patients were included in the final analysis. The researchers used an “outcome-blinded” modeling strategy including clustering, data reduction and transformation, to compare the Singapore Liver Cancer Recurrence score (SLICER) technique in estimating freedom from relapse, the primary outcome. The SLICER score was then compared with other HCC prognostic models using concordance-indices and likelihood analysis, according to the study.

The researchers’ nomogram predicted freedom from relapse and combined non-neoplastic liver cirrhosis, multifocality, preoperative alpha-fetoprotein level, Child-Pugh score, vascular invasion, tumor size, surgical margin and symptoms at presentation, according to the researchers.

The nomogram was able to perform better than any other HCC prognostic models for predicting freedom from relapse through log-likelihood ratio statistics (HR = 1.05; 95% CI, 1.04–1.06). Good calibration was observed at 3 and 5 years post-resection, as was a concordance index of 0.69 for predicting relapse.

A decision curve analysis concluded that SLICER had a superior net benefit between 0 and 40% threshold probability compared with the other models, but did improve performance over the 40% threshold.

“This represents superior estimation of decision outcomes at higher threshold probability levels,” the researchers wrote.

The researchers concluded: “We have developed a model to predict individualized probabilities of relapse following complete resection of localized hepatocellular carcinoma, in a large, near-national consecutive series of patients, which demonstrates excellent calibration and performance. This provides a foundation for individualized patient counseling and management, biomarker development, and trial design for adjuvant trials in HCC.” – by Melinda Stevens

Disclosures: The researchers report no relevant financial disclosures.