Title: A Cross-Sectional Analysis of Factors Associated with Cervical Cancer Screening in a
Large Midwest Primary Care Setting
Version: 2 Date: 02 Feb 2025
Reviewer's report:
This paper is an excellent use of EHR data to examine predictors of up-to-date cervical cancer
screening. The biggest challenge of the paper is that it presents a lot of comparisons without
clearly prioritizing or synthesizing them - I think it makes it hard to have strong take-aways,
as is clear from the fact that the conclusions in the current abstract do not make any specific
recommendations but broadly note -some- differences exist and -some- populations could
benefit from interventions. I would encourage the authors to revisit the data and more clearly
identify a few new pieces of information or actionable next steps from this work.
A few smaller notes:
-I don't love the term "racial minorities" which is somewhat meaningless - I would consider "of a
minoritized race" to indicate that we care because of the social process of minoritization (rather
than caring just because a group is a statistical minority) or if you want to be broader, just say
"non-White" which is a straightforward descriptor.
-I think the introduction could be shortened some to make room for additional nuance in the
results. Paragraphs 2 and 3 could be combined and paragraph 4 could be shortened (although
I like the set-up on income measures). Paragraph 4/5 could be combined.  (None of these are
strictly needed - feel free to ignore, but a suggestion if more space is needed for my requests
of the results section)
-In the methods I would say the HOUSES index is used to *estimate* SES rather than "determine
SES".
-The results are very short. Authors present an exhaustive list of ORs for demographic factors
but then only broadly summarize all other variables. I would consider a paragraph each for
demographic, healthcare, and SES variables and I would note broadly the direction for all with
some specific ORs where the differences are of a notable magnitude. In particular, the impact of
healthcare utilization is huge and relatively undiscussed. The SES data is by far the most novel
contribution yet it is barely discussed - expanding on the specific data that is reported in the
figure through an example data point or two would be valuable to a reader.
-In the discussion, I would use the first paragraph to summarize the key findings of your study
and not compare other studies until you've explained to the reader the main contributions of
your paper. Start with a few big take-aways and then progress (as you do here) to the specific
comparisons to other studies.
-I'd expand more on the benefits or comparisons of the HOUSES index - it seems generally
to agree with census tract measures - do you feel that it is adding something new compared to
prior measures?
-It could be nice to discuss benefits of self-collection more in the discussion - it comes out of left
field in your conclusion. I think it's a good point that it may help mitigate some of these barriers
- sharing any data that exists on acceptability in your most underserved populations would be a
good way to build a case in the discussion that you can echo in the conclusion.
-In the conclusion you refer to women "identifying as lower SES" but they didn't self-identify
right? They were estimated to be of lower SES?
-Finally, I'd love a stronger take-away - of course we need to understand barriers and implement
community based screening programs, but is there anything you didn't know at the start of the
study that you do know now to help guide that process? Should we focus more on neighborhood,
language, specific groups?