Title: The distribution of reproductive risk factors disclosed the heterogeneity of receptor-
defined breast cancer subtypes among Tanzanian women
Version: 1 Date: 12 Jun 2021
Reviewer's report:
There is a breast cancer case series study in Tanzania. Molecular subtypes were assayed and
epidemiological risk factors were collected.
The main critiques of the paper are inaccurate data interpretation, and “over analysis” – the
amount of data do not support the complex analysis methods. The paper can be significantly
shortened. Table 3, Supplementary Table 1 & 2 can be deleted. See detailed comments below.
First, the study compared four subtypes of breast cancer but there is no healthy non-cancer group.
Therefore, the odds ratio or proportion comparison in risk factors between subtypes can only
be interpreted as one subtype is more/less likely to have a risk factor than another subtype or
there is risk factor heterogeneity across subtype, but the study cannot conclude whether a risk
factor is associated with a subtype. For example, “No significant association was found between
age at menarche and different BC molecular subtypes” in the current case-case study meant
that the study failed to find age at menarche is heterogeneous among breast cancer molecular
subtypes; it did not mean age at menarche is not associated with any of BC subtypes. Previous
literature showed that early age at menarche is positively associated with breast cancer regardless
of molecular subtypes.
Second, the numbers of luminal B, Her2, and TNBC are relatively small (<60), so multivariable
analysis using logistic regression should be performed with caution as overfitting of the model
is likely. E.g. <4~5 predictors per 50 events might be okay. When the sample size is too small in
subset of the analysis, odds ratios could be very large (like 13) and p values are not accurate at all.
Third, the author chose one-vs-rest binary logistic regression rather than multinomial logistic
regression, so the model assumes that all “no TNBC” subtypes are the same in the TNBC logistic
regression.
Fourth, the presentation in Table 2 is good and clear, but results in Table 3 are confusing. It
seems that different referent group of menopausal status were used for different subtypes.
Fifth, the results presented in Supplementary Table 1 & 2 are less meaningful. Age is related to
menopausal status, so within patients < 40 years, it is not meaningful to examine the association
between menopausal status and subtype. How many postmenopausal Luminal B patients were
younger than age 40? It is skeptical to report an odds ratio of 13.33.
Discussion: Line 278: “we observed that BC incidences were higher in urban residences than
rural residences.” This interpretation is not appropriate because the total number of urban and
rural residences have not been collected in this study so no denominator for incidence rates.
ILC is strongly associated with luminal subtypes in most previous studies conducted in Africa,
Europe and America as well as large population cancer registries. It is a surprise to observe ILC
is high in TNBC subtype in the current study. It is also surprised to see TNBC was diagnosed
at older age.
The study did not observe difference in family history of breast cancer among subtypes. This
just suggests no heterogeneity. Citing only one paper (PreFace study) consistent this finding but
ignoring other papers not consistent this finding is not appropriate.