Reliable Performance of mALBI Grade-Based Risk Models for Predicting the Prognosis of Patients With Hepatocellular
Takeshi Hatanaka1, Satoru Kakizaki2,3, Atsushi Hiraoka4
1Department of Gastroenterology, Gunma Saiseikai Maebashi Hospital, Maebashi, Japan.
Aim:
This study aimed to compare the prognostic performance of the risk models for patients with hepatocellular carcinoma (HCC) receiving atezolizumab and bevacizumab (Atez/Bev) as first-line treatment.
Methods:
Among 449 patients included in this retrospective multicenter study, we compared the prognostic performance of 13 risk models for the 12-month and 18-month survival status using area under the curve (AUC), net reclassification improvement (NRI), and relative integrated discrimination improvement (IDI) analysis. We also constructed a calibration plot to assess the fitness of each model.
Results:
Regarding the analysis of the 12-month survival status, none of the risk models demonstrated AUC values higher than the modified albumin-bilirubin (mALBI) grade. In the NRI analysis, only the IMmunotherapy with AFP, BCLC staging, mALBI, and DCP evaluation (IMABALI-De score) exhibited a statistically significant improvement compared with the mALBI grade (p = 0.009). While the modified albumin-bilirubin grade (mALF) score and prognostic nutritional index (PNI) did not exhibit significant differences compared to the mALBI grade (p = 0.3 and 0.2, respectively), the remaining risk models were inferior to the mALBI grade. In the relative IDI analysis, none of the risk models showed a significant improvement compared with the mALBI grade. The calibration plot of the PNI was unsatisfactory. The results for the 18-month survival status were consistent with those for the 12-month survival status. A time-dependent ROC analysis demonstrated that both the mALBI grade and the mALBI-based model showed consistent performance over time.
Conclusions:
The mALBI grade, as well as the IMABALI-De and mALF scores (both of which are risk models based on mALBI grade), exhibited reliable performance in predicting the prognosis of patients with HCC.
