Assessment of Prognostic Value of Aspartate Aminotransferase-to-Platelet Ratio Index in Patients With Hepatocellular Carcinoma: Meta-Analysis of 28 Cohort Studies - Zhang, XinYue; Svn, Zhen; Liv, MengSi; Liu, MengNan; Zhang, YiHan; Sun, Qin (Frontiers in Medicine, 2021)
Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors globally; it is valuable to predict its prognosis after treatment. Aspartate aminotransferase-to-platelet index (APRI), a noninvasive diagnostic indicator, consists of two routine test parameters easily available in all patients. Our study aimed to investigate whether APRI can serve as an independent prognostic marker in patients with HCC. Methods: We extensively searched PubMed, Embase, and Web of Science databases on June 20, 2021 to determine all relevant literature. Studies that explored the association between APRI levels and prognosis of patients with HCC and reported risk estimate data were included. The Newcastle-Ottawa Scale was used to assess the quality of included studies. Results: A total of 1097 articles were initially identified, of which 28 studies involving 11041 patients met the eligibility criteria for meta-analysis. The pooled HRs for overall survival and disease-free survival were 1.77 (95% CI: 1.53–2.05, P<0.001) and (HR=1.59, 95%CI: 1.47–1.71, P<0.001), respectively, suggesting a significant correlation between elevated APRI levels and poor prognosis in patients with HCC. In subgroup analyses, statistical significance of the correlation disappeared in the Korean and Japanese population and in patients undergoing transarterial chemoembolization. Of note, the current results may be overestimated due to publication bias, but the conclusion remained unchanged when the bias was adjusted. Conclusion: In most cases, preoperative APRI can be used as an independent prognostic factor for patients with HCC, but it is necessary to incorporate other predictive prognostic systems to ensure accuracy before determining the specific beneficiary population and the optimal cutoff value.