Development and Assessment of Nomogram Based on AFP Response for Patients with Unresectable Hepatocellular Carcinoma Treated with Immune Checkpoint Inhibitors
Round 1
Reviewer 1 Report
In the manuscript „Development and Assessment of Nomogram based on AFP response for Patients with Unresectable Hepatocellular Carcinoma Treated with Immune Checkpoint Inhibitors” the authors investigate factors affecting the efficacy of immune checkpoint inhibitor (ICI) treatment and develop a prognostic nomogram for patients with unresectable hepatocellular cancer (HCC) receiving ICI therapy. A total of 120 patients were enrolled in the study. Patients were randomly divided into a training set and a validation set. Serum α-fetoprotein protein (AFP) response was defined as a decline of ≥20% in AFP levels within the initial eight weeks of treatment. The results of the study revealed that AFP response, extrahepatic metastasis, and WBC count were independent predictors of PFS in patients with unresectable HCC receiving ICI.
The paper is generally well written. The authors should answer to the following points:
1. Could you better explain the different courses of the curves for training and validation groups in Fig.4!
2. What is the cut-off for low risk und high risk in Fig.5 (how many points)?
3. How many patients are in the low-risk group and in the high-risk group of Fig. 5?
4. The data of Fig.5 seems to be censored. Please show the percentage of censored data in the different groups!
5. Could you please discuss why the number of leukocytes seems to be a better prognostic marker than the number of neutrophils (Table 3)?
6. Would you please discuss your results with respect to the already published meta-analyses of ICI therapy in HCC, such as PMID 37520554!
Author Response
Please see the attachment
Author Response File: 
Author Response.pdf
Reviewer 2 Report
This paper described development of a nomogram for response for patients with hepatocellular carcinoma treated with immune checkpoint inhibitors. Overall, the paper presented results clearly. I only have relatively minor issues with the presentation.
In Figure 5, the KM curves should be step functions, and the curves drawn are not step functions. The confidence bounds should also be step functions.
How were the ROC curves in Figure 3 constructed? They seem smooth for such a small dataset.
Author Response
Please see the attachment
Author Response File: Author Response.pdf
Reviewer 3 Report
This is a well-organized paper that the authors collected 120 HCC patients who have received ICI treatment. The authors developed a nomogram model to predict the progression-free survival and proved that the model shows high AUC and well split the patients in terms of survival rate.
Here are some major concerns.
1. The cohort with 120 patients were split into the training and validation set. Are there any additional cohorts to serve as external validation set?
2. What’s the PFS for the training and validation set? It couldn’t be better to show the survival distribution of both sets in the supplementary figures and indicate that there is no distribution difference between the two sets.
3. For the PFS prediction, did the authors predict the exact survival time (continuous value) or did the authors binarize the survival?
4. It’s unclear how the nomogram prediction model was built. Which factors were used, how to normalize multiple variable, and how to integrate them into one predictor? Please provide more details for the model construction, given this is the major innovation for this project.
5. Can you authors show the ROC curves for single-variable model, please? For example, if only using AFP, what’s the ROC and the corresponding AUC. This will serve as baseline to compare how multi-variables overperform single-factor.
6. Detailed figure legend should be provided to illustrate each figure.
Good english presentation
Author Response
Please see the attachment
Author Response File: Author Response.pdf
Round 2
Reviewer 3 Report
The authors have addressed most of my concerns
