Title: Construction and validation of a predictive model for hepatocellular carcinoma based on
serum markers
Version: 2 Date: 07 Jul 2022
Reviewer's report:
This article by Zheng et al. aimed to construct a predictive model based on baseline serum
markers to predict the early-stage onset and evaluate the prognosis in patients with HCC.
Although it is indeed an important and urgent matter to establish an effective model to diagnose
early-onset HCC and predict patient outcome. There are a few concerns that I need to raise
regarding the design of this investigation.
1. The baseline characteristics of this cohort are significantly different. Patients’ age, gender,
HBV and HCV status, ALP, ALB, GGT, TP, WBC, NEUT, AFP, AFP-L3, and PIVKAII
all show drastic difference. This indicates the two groups are imbalance and therefore not
comparable. I would suggest the authors perform propensity score matching (PSM) and repeat
the analysis to get a more convincing result;
2. One of the authors aim in this study was to construct a model that could predict early onset
of HCC, yet the patient cohort includes all stages of patients. It is therefore not possible to draw
conclusion that this model can predict early onset based on its current form. I would suggest the
authors separate patients of different stages and perform individual analysis;
3. Since this model is constructed by clinical parameters that is of easy access, the authors should
consider adding a validation group to examine the efficacy of this model;
4. Figure legends is missing from the manuscript, and the figures and tables should also be given
appropriate titles and annotations so that they could be understood as a single;
5. Language can be polished but is acceptable at its current form.
Title: Construction and validation of a predictive model for hepatocellular carcinoma based on
serum markers
Version: 2 Date: 07 Jul 2022
Reviewer's report:
This article by Zheng et al. aimed to construct a predictive model based on baseline serum
markers to predict the early-stage onset and evaluate the prognosis in patients with HCC.
Although it is indeed an important and urgent matter to establish an effective model to diagnose
early-onset HCC and predict patient outcome. There are a few concerns that I need to raise
regarding the design of this investigation.
1. The baseline characteristics of this cohort are significantly different. Patients’ age, gender,
HBV and HCV status, ALP, ALB, GGT, TP, WBC, NEUT, AFP, AFP-L3, and PIVKAII
all show drastic difference. This indicates the two groups are imbalance and therefore not
comparable. I would suggest the authors perform propensity score matching (PSM) and repeat
the analysis to get a more convincing result;
2. One of the authors aim in this study was to construct a model that could predict early onset
of HCC, yet the patient cohort includes all stages of patients. It is therefore not possible to draw
conclusion that this model can predict early onset based on its current form. I would suggest the
authors separate patients of different stages and perform individual analysis;
3. Since this model is constructed by clinical parameters that is of easy access, the authors should
consider adding a validation group to examine the efficacy of this model;
4. Figure legends is missing from the manuscript, and the figures and tables should also be given
appropriate titles and annotations so that they could be understood as a single;
5. Language can be polished but is acceptable at its current form.
Please review this paper.
user
Title: Construction and validation of a predictive model for hepatocellular carcinoma based on
serum markers
Version: 2 Date: 07 Jul 2022
Reviewer's report:
This article by Zheng et al. aimed to construct a predictive model based on baseline serum
markers to predict the early-stage onset and evaluate the prognosis in patients with HCC.
Although it is indeed an important and urgent matter to establish an effective model to diagnose
early-onset HCC and predict patient outcome. There are a few concerns that I need to raise
regarding the design of this investigation.
1. The baseline characteristics of this cohort are significantly different. Patients’ age, gender,
HBV and HCV status, ALP, ALB, GGT, TP, WBC, NEUT, AFP, AFP-L3, and PIVKAII
all show drastic difference. This indicates the two groups are imbalance and therefore not
comparable. I would suggest the authors perform propensity score matching (PSM) and repeat
the analysis to get a more convincing result;
2. One of the authors aim in this study was to construct a model that could predict early onset
of HCC, yet the patient cohort includes all stages of patients. It is therefore not possible to draw
conclusion that this model can predict early onset based on its current form. I would suggest the
authors separate patients of different stages and perform individual analysis;
3. Since this model is constructed by clinical parameters that is of easy access, the authors should
consider adding a validation group to examine the efficacy of this model;
4. Figure legends is missing from the manuscript, and the figures and tables should also be given
appropriate titles and annotations so that they could be understood as a single;
5. Language can be polished but is acceptable at its current form.
assistant