Introduction
Lymphocytes inhibit the progression of hepatocellular carcinoma (HCC) through immune surveillance within an immunosuppressive microenvironment. Reduced lymphocyte counts, often associated with systemic inflammation, have been implicated in facilitating tumor progression. In contrast, elevated monocyte counts have been reported to be associated with microvascular invasion and poor prognosis in patients with HCC. Therefore, a high lymphocyte-to-monocyte ratio (LMR), calculated by dividing the lymphocyte count by the monocyte count, is considered a favorable prognostic indicator and is associated with improved clinical outcomes in patients with HCC.
Aims & Methods
We assessed the utility of the LMR in predicting the prognosis of patients with unresectable hepatocellular carcinoma who were treated with atezolizumab plus bevacizumab (Atezo/Bev). The study involved 941 patients who received Atezo/Bev treatment between September 2020 and February 2025. The median age was 74.0 years, and 754 were male. Performance status (PS) was distributed as follows: 741 patients with PS 0, 169 with PS 1, and 31 with PS ≥2. The liver background conditions were as follows: 149 patients with hepatitis B, 282 with hepatitis C, and 449 with non-hepatitis B or C (NBNC). Child-Pugh scores were distributed as follows: 522 patients with a score of 5, 254 with a score of 6, 67 with a score of 7, and 37 with a score of ≥8. The Barcelona Clinic Liver Cancer (BCLC) stages were as follows: 77 patients with stage ≤A, 317 with stage B, and 547 with stage ≥C. The median values of key biomarkers were as follows: LMR: 3.33, NLR: 2.63, AFP: 34.1 ng/mL. The median observation period was 14.3 months. NLR was included in Model 1, and LMR was incorporated in Model 2 of the multivariate analysis.
Results
The progression-free survival (PFS) was 6.8 months, and the overall survival (OS) was 23.6 months. The optimal cutoff for LMR, determined via time-dependent receiver operating characteristic (ROC) analysis based on median OS, was 3.6. The objective response rate (ORR) and disease control rate (DCR) were 27.3% and 76.5%, respectively. In the multivariate analysis of PFS, Model 1 identified the following factors as significant: BMI (HR: 0.98), Child-Pugh score ≥7 (HR: 1.34), BCLC stage C or higher (HR: 1.23), Log AFP (HR: 1.16), second or later treatment line (HR: 1.19). In Model 2, LMR was included as a significant factor (HR: 0.94). For OS, the following factors were identified as significant: age (HR: 1.01), Child-Pugh score ≥7 (HR: 2.09), BCLC stage C or higher (HR: 1.24), Log AFP (HR: 1.28), second or later treatment line (HR: 1.24), and NLR (HR: 1.03). The integrated discrimination improvement (IDI) for NLR and LMR at PFS (at 3 and 6 months) was 0.012 (95% CI: 0.012). The net reclassification improvement (NRI) was 0.016 (95% CI: 0.006-0.030, p<0.001) at 3 months, 0.023 (95% CI: 0.006-0.030, p<0.001) at 6 months, and 0.023 (95% CI: 0.004-0.024, p<0.001) at 12 months. The IDI for NLR and LMR at OS (12 and 24 months) was 0.027 (95% CI: 0.011-0.049, p=0.002) and 0.034 (95% CI: 0.012-0.064, p<0.001), with LMR demonstrating superior performance. The NRI for OS at 12 and 24 months was 0.036 (95% CI: 0.016-0.062, p<0.001) and 0.053 (95% CI: 0.020-0.091, p<0.001), respectively, both favoring LMR. In the time-dependent ROC analysis, the area under the curve (AUROC) was higher for LMR compared to NLR throughout the study period, with the exception of PFS at 3 months and OS at 18 months.
Conclusion
The LMR serves as a valuable biomarker for predicting prognosis in patients receiving Atezo/Bev.
Disclosure
Toshifumi Tada: lecture fees from AbbVie, AstraZeneca, Eisai, and Chugai
Atsushi Hiraoka: lecture fees from Eisai, Bayer, Eli Lilly, and Otsuka
Hidenori Toyoda: lecture fees from AbbVie, Eisai, Gilead, Terumo, and Bayer