Evaluation of Treatment Outcomes Using DNLR and GNRI in Combination Therapy for Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, particularly in Asia. Due to its lack of early symptoms, many patients are diagnosed at an advanced stage, making surgical resection unfeasible. In recent years, combination therapy with immune checkpoint inhibitors (ICIs) and anti-angiogenic drugs, such as Atezolizumab and Bevacizumab, has shown significant survival benefits in patients with unresectable HCC. However, accurately predicting treatment response and prognosis remains a challenge.

Traditional prognostic markers like the neutrophil-to-lymphocyte ratio (NLR) have been proven valuable in HCC patients. However, calculating NLR requires lymphocyte count data, which is sometimes unavailable in clinical practice. To address this, researchers have proposed the derived neutrophil-to-lymphocyte ratio (DNLR), which can be calculated using only neutrophil and white blood cell counts, providing an alternative for databases lacking lymphocyte data. Additionally, the Geriatric Nutritional Risk Index (GNRI), which reflects a patient’s nutritional status, has also been linked to cancer prognosis.

This study aims to evaluate the clinical value of DNLR and GNRI in predicting the prognosis of patients with unresectable HCC undergoing combination therapy with Atezolizumab and Bevacizumab, and to explore the predictive efficacy of combining GNRI with DNLR or NLR.

Source of the Paper

This paper was co-authored by Atsushi Naganuma and colleagues from multiple hospitals and research institutions in Japan, including NHO Takasaki General Medical Center, Gunma University Graduate School of Medicine, and Ehime Prefectural Central Hospital. Published in 2025 in the journal Cancer Medicine, the paper is titled Evaluation of Treatment Outcomes Using DNLR and GNRI in Combination Therapy with Atezolizumab and Bevacizumab for Hepatocellular Carcinoma.

Research Process and Results

1. Study Design and Patient Selection

This retrospective multicenter study included 975 HCC patients treated with Atezolizumab and Bevacizumab between September 2020 and January 2023 at multiple hospitals in Japan. After screening, 310 patients were included in the analysis. Inclusion criteria included: first-line treatment with Atezolizumab and Bevacizumab, complete white blood cell, neutrophil, and GNRI data. Exclusion criteria included: lack of white blood cell or lymphocyte data, inability to evaluate treatment response, or receiving second-line treatment.

2. Data Collection and Indicator Calculation

Researchers reviewed medical records to collect clinical characteristics, including age, gender, body mass index, liver function (Child-Pugh classification and modified albumin-bilirubin grade, mALBI), and tumor stage (Barcelona Clinic Liver Cancer staging, BCLC). DNLR was calculated as: DNLR = Neutrophil Count / (White Blood Cell Count - Neutrophil Count). GNRI was calculated as: GNRI = (14.89 × Serum Albumin [g/dL]) + (41.7 × [Current Weight/Ideal Weight]). Cutoff values for NLR and DNLR were set at 3.0 and 1.6, respectively.

3. Treatment Response and Survival Analysis

Patients received Atezolizumab and Bevacizumab combination therapy until disease progression or intolerable adverse events. Treatment response was assessed using the Response Evaluation Criteria in Solid Tumors (RECIST 1.1), categorized as complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD). Progression-free survival (PFS) and overall survival (OS) were calculated from the start of treatment to disease progression or death.

4. Key Results

• PFS and OS: Median PFS was 7.2 months (95% CI: 5.9–8.5), and median OS was 24.9 months (95% CI: 19.6–30.2).
• Prognostic Value of DNLR and NLR: The median OS in the high DNLR group was significantly lower than in the low DNLR group (9.5 months vs. 25.0 months, p < 0.001). Similarly, the median OS in the high NLR group was significantly lower than in the low NLR group (16.0 months vs. 25.0 months, p = 0.008). DNLR and NLR were significantly correlated (Pearson correlation coefficient = 0.523, p < 0.0001).
• Prognostic Value of GNRI: The median PFS and OS in the high GNRI group were significantly better than in the low GNRI group (PFS: 7.9 months vs. 6.3 months, p = 0.04; OS: 30.6 months vs. 18.9 months, p = 0.017).
• Combined GNRI-DNLR and GNRI-NLR Scores: The high GNRI-DNLR score group had significantly lower PFS and OS compared to the low score group (PFS: 2.4 months vs. 7.7 months, p = 0.001; OS: 8.1 months vs. 24.9 months, p < 0.001). The GNRI-NLR score showed a similar trend.

5. Multivariate Analysis

Multivariate analysis showed that non-viral etiology, AFP ≥ 400 ng/mL, and treatment response of CR or PR were independent predictors of PFS and OS. High GNRI-DNLR and GNRI-NLR scores were significantly associated with worse PFS and OS.

Conclusions and Significance

This study demonstrates that DNLR can serve as a substitute for NLR in predicting the prognosis of patients with unresectable HCC undergoing combination therapy with Atezolizumab and Bevacizumab. The combined GNRI-DNLR or GNRI-NLR scores provide better patient stratification, especially in cases where lymphocyte count data is unavailable. These findings offer clinicians a more comprehensive prognostic assessment tool, aiding in the optimization of personalized treatment strategies.

Highlights of the Study

1. Substitute Value of DNLR: DNLR effectively replaces NLR for prognostic assessment in the absence of lymphocyte count data.
2. Combined Use of GNRI and Immune Markers: The combined GNRI-DNLR or GNRI-NLR scores significantly improve the accuracy of prognostic stratification.
3. Multicenter Retrospective Study: The study included 310 patients from multiple hospitals, providing strong clinical representativeness.

Additional Valuable Information

This study also emphasizes the importance of liver function (Child-Pugh classification and mALBI) in the prognosis of HCC patients and highlights the need to consider liver function, tumor characteristics, and treatment history when formulating treatment strategies. Future research could further validate the applicability of the GNRI-DNLR score in other cancer types and treatment regimens.