Lead Investigator: Linbin Lu, The 900th Hospital of PLA
Title of Proposal Research: Trajectories of alpha-fetoprotein and liver cancer outcomes after atezolizumab treatment
Vivli Data Request: 7822
Funding Source: None
Potential Conflicts of Interest: None
Summary of the Proposed Research:
The project background:
Hepatocellular carcinoma (HCC), the most common type of primary liver cancer, ranks the third leading cause of cancer-related death worldwide, with chronic hepatitis B virus (HBV) infection for key determinants in China. The level of α-fetoprotein (AFP) in the blood is most commonly used for detecting and clinical follow-up of patients with HCC. To further explore the new utility of this old marker, the level of AFP in the blood (over 20% decrease after therapy) is employed to predict treatment response and survival among the HCC patients undergoing chemotherapy and receiving sorafenib, cabozantinib, ramucirumab, which are all drugs that are approved to treat different types of cancer, and PD-L1 (programmed death ligand-1) inhibitors, which are a group of anticancer drugs that block the activity of Programmed death-1 (PD-1)proteins which are present on the surface of cells and can prevent the body’s immune system from attacking cancer cells.
Necessity of the research:
The role of AFP change, including change over time, is still unclear and poorly defined, with an urgent need to identify the change over time of AFP for HCC. Our previous work found a novel AFP serological response curve for intermediate-stage HCC after transarterial chemoembolization (TACE).TACE is a 2-part treatment for liver cancer where high doses of chemotherapy are given to the tumor to destroy cancer cells, and the blood supply to the tumor is blocked so that it is starved of oxygen and the nutrients it needs to grow.
However, whether AFP serological response curve is an optimal biomarker for advanced HCC treated with PD-1 inhibitors is still unknown.
How the research will add to medical science or patient care:
In our previous study, three distinct trajectories of AFP levels in the blood were identified high-rising, low-stable, and sharp-falling. Of note, we found that about 10- fold difference in death risk existed between AFP high-rising and sharp-falling group. Because there is still no ideal biomarker for HCC treated with PD-1 inhibitors, to validate AFP serological response in advanced HCC is an urgent need.
How the research will be conducted:
In this longitudinal, multicenter, randomized controlled trial, we aim to characterize trajectories of AFP and examine its impact on clinical outcomes for HCC patients treated with PD-1 inhibitors.
Statistical Analysis Plan:
Unsupervised cluster analysis was performed to explore the trajectories of serum AFP level using a latent class growth mixed model (LCGMM). Log transformation was applied for serum AFP levels because of its left skewness. The R package lcmm (version 1.9.2) in R 3.6.3 was used to perform LCGMM, setting the log AFP as a function of time with a class number ranging from 2 to 5 with the same starting values calculated from the 1-group model.
When the LCGMM model was fitted, I assessed the polynomial function of linear, quadratic, and cubic and tried the grouping number from 1 to 6 in each function form. To avoid convergence towards local maxima, LCGMM models with 2 to 6 classes were performed several times with different sets of random starting values based on the 1-class model. The criteria for the choice of a best-fit model together with the study-specific requirements were as followed: (1) significant improvement of the model in Bayesian information criterion (at least 10 points reduction); (2) a posterior probability > 0.7 for all latent classes; and (3) ≥ 5% participants in any single trajectory class. Finally, cubic trajectories of the three groups were the optimal fit model based on the above criteria.
Characteristics across different groups were compared using Student’s t-test or Kruskal–Wallis tests for continuous variables and χ² statistics or Fisher’s exact test for categorical variables. We used multiple imputation to deal with the missing data. Kaplan-Meier method was firstly used to estimate the OS and PFS for each trajectory group, with the differences compared by the log-rank test. Cox proportional hazard models were used to explore the association between AFP trajectories and clinical outcome, which was adjusted of gender, major tumor size (≤5, >5), intrahepatic lesions number(≤3, >3), and AFP (<25, ≥25). To address the non-linearity of confounding factors, we set up a final model adjusted for logAFP (smooth) through restricted cubic spline and other baseline confounders. The relative importance of each parameter to survival risk was assessed using the χ² from Harrell’s rms R package. Sensitivity Analysis Finally, I applied three approaches to evaluate the risk estimates’ robustness in a sensitivity analysis. To eliminate the unmeasured confounding factors, inverse-probability-of-treatment weighted analysis (IPTW) was performed through marginal structural models. In this model, the predicted probabilities, which were calculated by gender, largest tumor size (≤5, >5), intrahepatic lesions number (≤3, >3), and logAFP(Smooth), were used to evaluate the stabilized inverse-probability-of-treatment weight. To search for potential heterogeneity sources, subgroup analyses were performed by participating cohort, age, sex, baseline Child-Pugh class, major tumor size, and intrahepatic tumor number, with tests for interaction by the Cox regression model. To account for potential biases of the various following-up times, sequential landmark analyses evaluating survival with distinct AFP trajectories were performed for patients with overall survival of fewer than 3 years, 4 years, and 5 years.
Additional analysis includes the development and validation of a risk score using complete blood count to predict the OS of patients receiving PD-1 inhibitor.
Requested Studies:
A Phase III, Open-Label, Randomized Study of Atezolizumab in Combination With Bevacizumab Compared With Sorafenib in Patients With Untreated Locally Advanced or Metastatic Hepatocellular Carcinoma
Data Contributor: Roche
Study ID: NCT03434379
Sponsor ID: YO40245
Public Disclosures:
Lu, L., Zheng, P., Pan, Y., Huang, S., Shao, E., Huang, Y., Wang, X., Chen, Y., Cuo, G., Yang, H. and Guo, W., 2023. Trajectories of α-fetoprotein and unresectable hepatocellular carcinoma outcomes receiving atezolizumab plus bevacizumab: a secondary analysis of IMbrave150 study. British Journal of Cancer, 129(4), pp.620-625. Doi: 10.1038/s41416-023-02334-7