Review for 10.1186/s12876-023-02729-z (2023)

Reviewer’s report
Title: 
A novel predictive model of microvascular invasion in hepatocellular
carcinoma based on differential protein expression
Version: 
0 
Date: 
21 Oct 2022
Reviewer's report:
The authors constructed and verified a nomogram model for microvascular
invasion (MVI) based on hepatocellular carcinoma (HCC) tumor characteristics
and differential protein expressions with the model' sensitivity, specificity, and
AUC value of 0.81, 0.85, and 0.934 in training cohort, and AUC value of 0.917
in validation cohort. The diagnostic accuracy MVI of this model is higher than
previously reported. The text is well arranged, and the method is reliably applied.
But the paper needs some improvement before acceptance for publication. My
detailed comments are as followed: 
1.Accurate prediction of MVI before surgery can help clinicians make more
reasonable treatment decisions to truly achieve individualized treatment based on
tumor biological behavior. But the significant risk factors of GPC3, P53, RRM1,
BRCA1, and ARG, as well as MVI in this article, are all examined
postoperatively, which can hardly handled to predict MVI before surgery. Of
course, this model can apply to patients who has punctured of the liver before
surgery to make a individualized treatment decision. In fact, postoperative
pathological examination often used for prediction of the prognosis rather than
MVI prediction. It would be better if the authors add prognostic data.
2.The methods in abstract have no data that support the results.
3.The authors should show how the training and validation cohorts were
assigned in the corresponding text.
4. To make it easier to read, a numerical value containing a decimal point like
"7.887e-09", "0.9718" …… can round a decimal number to two or three decimal
places
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Is the study design appropriate to answer the research question (including the use
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