Predictive value of LDH kinetics in bevacizumab treatment and survival of patients with advanced NSCLC

Abstract

Butuo Li,1,2,* Cheng Li,3,* Meiying Guo,2,4 Shuheng Shang,2,4 Xiaogang Li,5 Peng Xie,2 Xindong Sun,2 Jinming Yu,1,2 Linlin Wang2 1Department of Radiation Oncology and Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University, Tianjin, People’s Republic of China; 2Department of Radiation Oncology, Shandong Cancer Hospital Affiliated to Shandong University, Shandong Academy of Medical Science, Jinan, People’s Republic of China; 3Department of Dean’s Office, Shandong Cancer Hospital Affiliated to Shandong University, Shandong Academy of Medical Science, Jinan, People’s Republic of China; 4Department of Radiation Oncology, School of Medicine, Shandong University, Jinan, People’s Republic of China; 5Department of Radiation Oncology, School of Medicine and Life Sciences, University of Jinan-Shandong Academy of Medical Sciences, Jinan, People’s Republic of China *These authors contributed equally to this work Background: The combination of bevacizumab and chemotherapy is still one of the standard treatments for advanced non-small-cell lung cancer (NSCLC) patients in the new era of targeted therapy. Although a high level of baseline lactate dehydrogenase (LDH) was found to predict survival benefit from bevacizumab in patients with metastatic colorectal cancer, the predictive value of serum level of LDH in NSCLC patients treated with bevacizumab has not been investigated yet. Moreover, dynamic evaluation of serum level of LDH changes may be more informative and promising in predicting patients’ prognosis. We thus sought to analyze LDH kinetics and evaluate its predictive role in the response and survival of advanced NSCLC patients treated with bevacizumab. Method: We retrospectively collected and analyzed a total of 161 advanced NSCLC patients who had undergone treatment with bevacizumab. Univariate and multivariate logistic regression analyses of serum level of LDH were used for response analyses, and Cox models for both overall survival (OS) and progression-free survival analyses (PFS). Longitudinal analysis of LDH was performed using a mixed-effect regression model. Results: On multivariate Cox models, increase of serum level of LDH after 4 cycles with bevacizumab (INC4) treatment was shown to be the independent risk factor for OS (hazard ratio =2.17, 95% CI: 1.21–3.90, P=0.009), and the serum level of LDH after 2 cycles (LDH2) and the increase of LDH after 6 cycles with bevacizumab (INC6) treatment were the predictive factors for PFS (hazard ratio =2.33, 95% CI: 1.38–3.93, P=0.001; hazard ratio =1.96, 95% CI: 1.27–3.03, P=0.002, respectively). Patients with increase of serum level of LDH after 2 cycles of treatment with bevacizumab (INC2) (odds ratio =3.75, 95% CI: 1.83–7.68, P<0.001) were more likely to attain stable disease/progressive disease on multivariate logistic regression analyses, while patients with complete response (CR)/partial response (PR) experienced a reduction of serum level of LDH every 2 cycles (Coef =-0.076, std error =0.017, P<0.001) over time. Conclusion: Dynamic changes of LDH were superior to baseline LDH in predicting prognosis of NSCLC patients treated with bevacizumab. Serum level of LDH reducing over time was a potential biomarker for patients to achieve good clinical response (CR/PR) to bevacizumab. Keywords: lactate dehydrogenase, bevacizumab, non-small-cell lung cancer, mixed-effect model, predictive factor

Keywords

• lactate dehydrogenase
• bevacizumab
• non-small-cell lung cancer
• mixed effect model
• predictive factor