Title: Integrating traditional biomarkers and emerging predictors to assess neoadjuvant
chemotherapy efficacy in breast cancer: a multifactorial analysis of Ki-67, CDK4, EGFR, TILs
and ctDNA
Version: 0 Date: 18 Sep 2024
Reviewer:  Yuquan Chen
Reviewer's report:
This manuscript provides valuable insights into the integration of traditional clinicopathological
factors and emerging biomarkers, such as EGFR, Ki-67, CDK4, TILs, and ctDNA, in predicting
neoadjuvant chemotherapy (NACT) efficacy and long-term survival in breast cancer patients.
While the study's findings are promising and demonstrate the potential for more personalized
treatment strategies, there are several areas that require significant improvement. The study
design lacks a clear rationale for the chosen sample size, and there is no discussion on whether
the study is adequately powered to draw meaningful conclusions. A power analysis should
be conducted, and the limitations of using a retrospective dataset need to be addressed more
comprehensively. Furthermore, the methodology section is insufficiently detailed, particularly
regarding the propensity score matching process. The manuscript does not clearly explain
how confounders were identified or how the authors ensured that residual confounding was
minimized. Additionally, while the biomarkers analyzed are of interest, the manuscript fails to
provide an adequate background on why these particular biomarkers were selected, and their
biological significance in the context of breast cancer needs to be better articulated. The survival
analysis presented in Figure 2, though important, is not adequately explained in the text. There
is no discussion on how censored data were handled, and the potential biases introduced by
patient censoring are not considered. A more detailed presentation of hazard ratios and survival
statistics would strengthen the analysis. Moreover, the subgroup analysis related to breast cancer
subtypes is not sufficiently explored. While the manuscript mentions differing pCR rates among
subtypes, the biological rationale for these differences is lacking. A deeper examination of
how these subtypes respond to NACT and the potential implications for treatment strategies
is necessary. The significant correlation between TIL levels and pCR rates is a key finding,
but its potential impact on immunotherapy is underdeveloped. Given the increasing relevance
of immunotherapy in breast cancer treatment, the discussion should be expanded to explore
the role of TILs in enhancing NACT outcomes and improving immunotherapeutic approaches.
Additionally, while pCR is heavily emphasized as a measure of NACT efficacy, the limitations
of using pCR as a primary endpoint should be acknowledged, particularly since it may not always
predict long-term survival outcomes across all breast cancer subtypes. Lastly, the statistical
analysis section requires more depth, particularly in terms of how missing data were handled
and whether sensitivity analyses were performed. The inclusion of confidence intervals and a
more transparent presentation of the statistical methods would enhance the rigor of the findings.
In conclusion, while this study presents important contributions to the understanding of NACT
response in breast cancer, significant revisions are necessary, particularly in terms of study
design, methodology clarity, and the depth of analysis, to make it suitable for publication.