Title: Development of Prognostic Models for HER2-positive Metastatic Breast Cancer in
Females: A Retrospective Population-Based Study
Version: 0 Date: 20 Nov 2024
Reviewer's report:
PEER REVIEWER ASSESSMENTS:
OBJECTIVE - Full research articles: is there a clear objective that addresses a testable research
question(s) (brief or other article types: is there a clear objective)?
Yes - there is a clear objective
DESIGN - Is the current approach (including controls and analysis protocols) appropriate for
the objective?
Yes - the approach is appropriate
EXECUTION - Are the experiments and analyses performed with technical rigor to allow
confidence in the results?
No - there are minor issues
STATISTICS - Is the use of statistics in the manuscript appropriate?
No - there are issues with the statistics in the study
INTERPRETATION - Is the current interpretation/discussion of the results reasonable and not
overstated?
No - there are minor issues
OVERALL MANUSCRIPT POTENTIAL - Is the current version of this work technically
sound? If not, can revisions be made to make the work technically sound?
Probably - with minor revisions
PEER REVIEWER COMMENTS:
GENERAL COMMENTS: Overall, the manuscript is a well-written, clear, and impressive piece
of work. The authors have evaluated a retrospective dataset of HER2+ breast cancer from SEER
repository for 2151 patients and evaluated the Breast Cancer Specific Survival and Overall
Survival. The models perform reasonably well in the dataset, with fair conclusions.
REQUESTED REVISIONS:
The manuscript has a clear objective and study design. I see a few issues with execution
and interpretation that I request authors to clarify. 1) A retrospective dataset has been used
from 2010-2015. The database is contributed from how many clinical sites and what level of
heterogeneity it captures needs to be elaborated in the methods section, which will help readers
for better clarity and a standalone document. 2) Breast cancer, diagnosis, its screening, and role
of new drugs, including NACT have changed significantly in the last 2 decades. Thus, taking
a dataset from 2010–15 for model training might be obsolete? How do authors justify their
model's applicability in the current state-of-the-art process of breast cancer treatment regime,
where new therapies and drugs are now available, impacting the outcome for patients? 3) Why
was no testing dataset used for model evaluation and cross-validation? 4) Table 1 seems not
right; the testing and validation numbers seem wrong; the numbers appeared switched among
the two groups. Please check all the tables and figures again thoroughly. 5) Similarly, as Figure
1 mentioned, training group n = 1505 and validation group n = 1505; this appears not to be right.
6) Currently, the discussion sections present a review report. It would be interesting to rewrite
the discussion with comparative analysis with other models and survival analysis published. 7)
Breast cancer is a widely explored area; it would be encouraging if authors could use third-party
open-source data or data from other published studies and run the analysis with their model,
evaluating for comparison with respect to literature. 8) Also, it is highly desirable to include
a literature comparison on similar models in a tabular format in the methods section: what are
the survival models already available, their n values, outcome prediction accuracy, and overall
acceptance by the clinical community. 9) The authors have already made the two developed
models, BCSS and OS, live. When were these made live? Has any group tested these models
independently, as they are already live; What is the feedback from clinical community; Have
authors made these models live for use in their own hospitals If so, what's the prediction outcome
in the prospective cohort (it could be a small number but still helpful).
ADDITIONAL REQUESTS/SUGGESTIONS:
Consider revision of the discussion section with comparative analysis. Breast cancer is a widely
studied area with much literature on survival and models; it would be encouraged to have a
comparison with respect to published studies, any differences or similarities, or action plans.
The authors must also present the limitation section more elaborately, as they have used a
retrospective dataset from 2010–15; in the last 10 years, a lot of new drugs, chemotherapy
options, screening methods, etc. have evolved, impacting the patient outcome and survival. How
do authors justify the proposed model's relevance in the current situation of the highly evolving
scientific world of breast cancer?