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: 
0 
Date: 
19 Apr 2021
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?
Yes - experiments and analyses were performed appropriately
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: 
The authors present a thoughtful nomogram paper to predict survival outcomes
among those with rectal adenocarcinoma. The authors generally used standard of
care approaches to building nomograms, but the methods could be improved
with respect to the competing risk nature of the algorithm. The authors do not
use some methods that have been in common use with competing risk
nomograms for 10+ years. Some more comments follow.
REQUESTED REVISIONS: 
Major Comment 1) Something appears incorrect with Table 3. The coefficients
are much too large. For example, one of the coefficients for age is 186.948, but
the hazard ratio of 1.467 which is not equal to exp(186.948). 
Comment 2) The concordance indices used were not designed for competing risk
regressions but for Cox regressions. The methods of Ruan and Gray can be used
to calculate concordance statistics for the competing risk regression (Ruan PK,
Gray RJ. Analyses of cumulative incidence functions via non
‐
parametric
multiple imputation. Stat Med. 2008; 27: 5709
‐
5724.) Others have used the
method for competing risk nomograms.
Comment 3) Including race in a nomogram may be inadvisable, as the authors
could not control for characteristics that could confound the relationship of race
with outcomes, such as socio-economic status, access to insurance, and other
factors. Marital status is similarly fraught. While there might be scientific
reasons to investigate the impact of race and marital status on outcomes, the
authors have not necessarily motivated how the use of race and marital status via
the nomogram would improve clinical decision making without exacerbating
health disparities. The authors attribute the marital effect to "mental health and
well-being" without citations. Often the marital effect is seen as a proxy for
social support which affects the ability to travel to medical appointments and
hence seek appropriate care.
Comment 4) The chemotherapy effect may be due to those who do not receive
chemotherapy being poor candidates for chemotherapy (i.e. selection bias based
on health characteristics not available in SEER), rather than a true effect of
chemotherapy. 
Comment 5) Chemotherapy and radiation are not well collected by SEER, so
there is substantial misclassification. Comparing outcomes between those who
did and did not receive such therapy in SEER is generally not recommended.
The authors could cite the following web page so that others know the
limitations: https://seer.cancer.gov/data-
software/documentation/seerstat/nov2020/treatment-limitations-nov2020.html as
accessed on April 15, 2021.
Comment 6) The initial drop in sample size from 108,017 to 34,700 (Figure 1)
could be better documented in Figure 1. If this is due to many being diagnosed
prior to 2004, such a large decrease could be viewed as acceptable. However, if
the reason is due to missing data that is not well collected by SEER, missing data
could bias the results. 
Minor comment: Discussion: The authors state: "Recently, a parameter termed as
'cumulative incidence', calculated by the competing-risk model, has been
recommended to conquer the defects of traditional survival analysis [16-17]."
The authors describe their methods as novel, but actually competing risk
nomograms and cumulative incidence curves have been in common use for over
20 years. Michael W. Kattan published many competing risk nomograms in high
impact journals in the early 2000s, and is widely considered the modern founder
for the method. Perhaps his work should be cited.
Minor comment: The term multivariate might be more appropriately termed
multivariable. The authors did not use true multivariate methods (e.g., principal
component analysis).
ADDITIONAL REQUESTS/SUGGESTIONS: 
No further concerns beyond those already stated.
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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?
No
Are the methods sufficiently described to allow the study to be repeated?
Yes
Is the use of statistics and treatment of uncertainties appropriate?
No
Is the presentation of the work clear?
Yes
Are the images in this manuscript (including electrophoretic gels and blots) free
from apparent manipulation?
Yes