Title: Chlamydia Infection, PID, and Infertility: Further Evidence from a Case-control Study
in China
Version: 5 Date: 24 Feb 2022
Reviewer's report:
I would like to thank the authors for the thorough response on the comments. The manuscript
has improved significantly. I still do have concerns about the validity of the chlamydia history
variable. Furthermore a few comments based on either the manuscript or author responses.
1. As for my first comment in the first peerreview round (please see the previous comment in
brackets)
“1. Is the chlamydia history variable a valid variable for this analyses with the current definition-
prevalence/numbers? In the study it was concluded that only a marginal association between
chlamydia infection history and infertility was found. Authors support this finding by possible
conflicting literature on the role of chlamydia and infertility, however the systematic review
which is used as a reference showed a high risk for infertility following infection. I think the
results which has been found in this study needs more elaboration. The prevalence of chlamydia
history in this study was very low (2.4%, 0.4% and 0.4%) especially when this is compared to
current chlamydia (NAAT, during pregnancy or fertility work up) which was 5.9%, 7.3% and
7.1%. This would suggest (and the authors mention this briefly in the limitation section) that
chlamydia history in the study does not reflect the true chlamydia history. The result of this is
that many women were classified as chlamydia history negative, which might/probably resulted
in misclassifications. This might dilute the possible effect between chlamydia and infertility
significantly. Furthermore the numbers of previous chlamydia infection are extremely low (n =
6, 2, 2) How were proper analyses including adjustment for confounding done regarding these
low numbers? Please reflect on the validity of the chlamydia history variable (as well as the
current infection variable) and what impact that might have on the authors conclusion. The future
Pgp3 analyses will probably help addressing these issues.”
I’m not convinced about the validity of the chlamydia history variable. Why do the authors want
to report the chlamydia and infertility results in this manuscript knowing that the chlamydia
history infection status is most probably not representative and has very low numbers? The fact
that a statistical program is able to generate results does not directly imply that the results are
valid. Case-control studies are not suitable for rare exposures because of the bias that might
be introduced. Furthermore, the very interesting Pgp3 analysis shows really high chlamydia
antibody positivity(36-42%) versus the used chlamydia history prevalence (0.4-2.4%). I can’t
see how valid results or conclusions can be made.
My suggestion would be to just report descriptive statistics about  the chlamydia variable and
not to report the analyses due to the inevitable bias.
2. The way results and tables are presented is much improved. Few questions/remarks:
- In table 2: A cOR of 5.22 (0.54-50.37) was presented by NAAT chlamydia infection and
infertility. I don’t know what the ‘c’ in cOR means (please clarify in the table legend), but if
this is the unadjusted OR, than an OR of 5.22 doesn’t sound plausible given the percentages of
positive infections and infertility. Is this OR correct?
- The authors show the Stata output for the conditional logistic regression (clogit group yiyuanti,
group (Pair)). The number of observations in the analyses = 76, is that correct?
- In table 2 below the cOR the 96% CI was reported, this must be 95%CI I suppose?
- In table 2 the numbers and percentages for chlamydia NAAT infection and previous PID
diagnosis for the non-pregnant and pregnant controls are equal but in table 1 this is different
(and also given the reported ORs). For chlamydia infection history, the numbers are equal as
expected, but the percentages are different.
- In table 2 for clarification please report the outcome (infertility, as the authors did in table 3)
- Please check for all tables if the outcome is clear.