Review for 10.1186/s12876-022-02131-1 (2022)

Reviewer’s report
Title: 
Nomogram to predict cause-specific mortality of patients with rectal
adenocarcinoma undergoing surgery: a competing risk analysis.
Version: 
1 
Date: 
14 Jul 2021
Reviewer's report:
PEER REVIEWER ASSESSMENTS: 
OBJECTIVE - Full research articles: is there a clear objective that addresses one
or several testable research questions? (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 sufficient
technical rigor to allow confidence in the results?
Yes - experiments and analyses were performed appropriately
STATISTICS - Is the use of statistics in the manuscript appropriate?
Yes - appropriate statistical analyses have been used in the study
INTERPRETATION - Is the current interpretation/discussion of the results
reasonable and not overstated?
Yes - the author's interpretation is reasonable
OVERALL MANUSCRIPT POTENTIAL - Has the author addressed your
concerns sufficiently for you to now recommend the work as a technically sound
contribution? If not, can further revisions be made to make the work technically
sound?
Probably - with minor revisions
PEER REVIEWER COMMENTS: 
GENERAL COMMENTS: The authors have been moderately responsive to my
concerns, either addressing them, or justifying their approach. I still have
concerns about the way that race is used in the model given that confounding
factors such as income, insurance status, neighborhood socioeconomic status,
genetic biomarkers, and comorbidities are not included in the model. I am
worried that use of the model could potentially further health disparities in a
U.S. population since the investigators use U.S. data.
REQUESTED REVISIONS: 
Comment: I still have concerns about the casual use of race as a predictor
variable in a model. It is true that in the past people used race as a predictor in
models. However, in the past year due to the Black Lives Matter movement,
there has been greater scrutiny as to when race should and should not be used in
predictive models derived from U.S. data. Nomograms are prediction models
used to help patients, caregivers, and clinicians assess outcomes and make
treatment decisions. The authors have found that being black/African American
is associated with worse outcomes. However, at the patient level, this could be
due to confounding by income, insurance status, neighborhood socioeconomic
status, genetic biomarkers, and comorbidities. It saddens me to think that
patients and their families might use the authors' model to make care decisions,
and that race as used in the model, without control for confounding, could affect
those decisions. The papers cited about racial differences within the paper
(citations 22-25) examine race in a more nuanced way, including looking at
confounding variables. The papers listed in the response letter to justify race as a
predictor do not seem to address issues of confounding, and do not seem to
address contemporary 2021 concerns. Figure 2a seems appropriate as it would
not be intended for clinical decision making. However, including race in Figure
4, which is a tool for clinical decision making of U.S. cancer cases, seems
inappropriate without more attention to confounders in this U.S. population.
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Declaration of competing interests
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Have you received reimbursements, fees, funding, or salary from an
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Is the study design appropriate to answer the research question (including the use
of appropriate controls), and are the conclusions supported by the evidence
presented?
Yes
Are the methods sufficiently described to allow the study to be repeated?
Yes
Is the use of statistics and treatment of uncertainties appropriate?
Yes
Is the presentation of the work clear?
Yes
Are the images in this manuscript (including electrophoretic gels and blots) free
from apparent manipulation?
Yes