Title: Resting energy expenditure, body composition, and metabolic alterations in breast cancer
survivors vs. healthy controls: A cross-sectional study
Version: 0 Date: 30 Oct 2023
Reviewer's report:
The aim of this investigation was to characterize differences in resting energy expenditure (REE)
between breast cancer survivors (BCS) and healthy control subjects. The authors should be
commended on the inclusion of a matched control group and measurement of body composition
and cardiometabolic parameters with REE in a moderate sample size (considering the barriers in
conducting research in clinical populations). However, there are major concerns with collinearity
in the statistical models that affect the interpretation. The manuscript could be improved through
re-analysis of data, changing the presentation of some of the data to improve readability, and
providing more information about the methods and population characteristics, among other
suggestions described below.
Abstract
BCS do not have higher mREE, but rather higher FFM-adjusted REE according to this data.
Please revise the wording here and other conclusions based on the changes made in the
manuscript.
“We hypothesize that increased energy requirements are caused by metabolic stress related
to cancer/treatment.” Please remove or revise. This is not supported by the data because the
study did not measure “metabolic stress” and its more likely that the slightly (not statistically
significant) lower FFM in BCS. Statements such as this one would better suited in the discussion
to support a more nuanced interpretation of data.
Introduction
Use of people-first language is more appropriate (i.e., people with breast cancer vs. breast cancer
patients).
I suggest removing or drastically shortening the discussion on measured vs. predicted REE, as
it is not directly relevant.
To help readers in non-oncology settings, it would be helpful to define breast cancer survivors
versus patients.
The terms ‘metabolic state’ and ‘metabolic dysfunction’ are very confusing. I suggest using the
terms hyper/hypo metabolism or something similar instead of metabolic state.
Similarly, the term ‘relative REE’ is misleading (relative to what?). I suggest the authors simply
use REE/FFM or ‘adjusted REE’.
Methods
Please provide the dates of enrollment and study visits.
Pg 5: What was the rationale for age range?
Pg5: Please specify if post treatment was post “active” treatment (i.e., chemotherapy, radiation,
surgery), as adjuvant estrogen suppression is still considered treatment.
Pg5: Specify the inclusion for cancer stages; it seems like all stages of people with previous
IDC/stage 0 are included, but this is not explicitly stated.
Pg 5: Specify if people on any kind of medication that could alter REE (e.g., thyroid medication)
were excluded.
Pg5: Please provide specific criteria used for defining each metabolic criteria (e.g., total or LDL
cholesterol values for dyslipidemia, blood pressure, etc.)
Healthy controls: Please elaborate on the meaning of ‘no pharmaceuticals’.
The information on indirect calorimetry measurements are very confusing because the authors
state that the Omnical metabolic cart was used, followed by a statement that the measurements
were conducted in a respiratory room. If REE was measured with metabolic cart, please indicate
if gas exchange was collected using a ventilated hood or mask. If REE was measured in the
room, please add information on calibration, equipment, etc. (see the reporting checklist in Table
2 in PMID:  32841524).
Please remove ‘gold standard’ to describe the BodPod, as this is controversial.
Statistical analyses:
Indicate if any alterative tests were used if continuous variables were nonparametric or if all
variables were parametric.
Clarify the meaning of R2 change (I assume it is the incremental increase in R2 with each
additional variable).
Define exactly what is meant by ‘controlled for’ in the regression models. Similarly, a sub-
section of the results and Table 4 has ‘confounding variables’ in the title. However, it appears as
though all variables entered into the predictive models are predictive, not confounding. Please
revise the methods to clarify ‘confounding’ or use terms like ‘predictive variables’.
Results:
Please provide information on how many participants were screened or approached to
participate.
More information on BCS treatment modalities is needed (e.g., current estrogen suppression
regimen [AI? GnRH agonists?]).
Assessment of estrogen suppression status in the analyses is needed, considering changes
in body composition in BCS may be at least partially mediated by menopausal status and
estrogen suppression modality (e.g., PMID: 15681521,  21046232), and experimental hormone
suppression in healthy females impacts REE (PMID: 26338457, 15741268).
Table 1: please report body composition parameters.
I understand the rationale for not comparing the proportion of participants on/off therapy or
with/without metabolic dysfunction between groups, but a Chi-square test could test “metabolic
state” (hypo/hyper metabolism).
Table 2: The formatting of data for BCS with/without metabolic dysfunction is very difficult to
interpret. Please change each of these to a single row and report only one number for controls.
P-values can be placed in their own column/row as well.
“Higher FM(kg,%) and lower FFM(kg,%) were found in BCs compared to the controls, although
differences were not significant”. The beginning of this sentence is misleading, as results were
not significant or trending towards significance. Please re-state.
I am not convinced that FFM should be used as an independent variable in the model predicting
REE/FFM due to multicollinearity issues. i.e., it is difficult to determine the unique contribution
of FFM to the model. Please provide rationale and an alternate approach to show there are not
collinearity concerns (e.g., interaction terms, regularization regression techniques, or principle
component analyses) or remove this model
According to Table 3, the order in which variables were added were different; hence, that is very
likely why body weight was predictive in controls but not BCS.
I am not convinced that “The metabolic state (hyper-/hypo-/normometabolism) had a main effect
on both absolute and relative mREE” as stated in the discussion because the method used to
calculate metabolic state (mREE as a percent of pREE) used the outcome (mREE or relative
REE). See the comment about collinearity above.
It would be clinically helpful to know if metabolic dysfunction is related to ‘metabolic
state’ (hypo/normal/hypermetabolism).
Discussion:
It is possible that the between-group differences in REE/FFM are due to trends in lower (albeit
not statistically significant) FFM in the BCS group. Normally, mREE should not be expressed
by dividing by FFM given the differences in heterogeneity/proportion of organs and tissues
differs according to body size (PMIDs: 11739093, 22205519). However, some of these issues are
negated when comparing to a well-matched group. A short discussion on mathematical reasons
why there are differences in REE/FFM is warranted.
The last 3 sentences in first paragraph state very similar concepts; please revise.
“The causal relationship between the increase in metabolic stress and metabolic derangements
was first hypothesized by Lipscombe et al.(2013) who conducted longitudinal research on
24,976 BCs, and found an increased risk (HR 1.24) for developing type 2 diabetes >2y post
chemotherapy(27).”  This statement is too strong, as the cited study did not directly measure
“metabolic stress”. Please remove or revise.
“After adjusting to FFM however, relative mREE no longer determined increased energy
requirements”. Please revise, as increased REE does not directly equate to increased energy
requirements (which is the sum of determined by REE, physical activity, and TEF, with
consideration of individual’s body weight goals).
“From our study, we cannot determine the relationship between FM and metabolic dysfunctions,
and an increase in absolute or relative mREE.” It is not clear as to why these relationships could
not be determined, as all of the data are there.
The last sentence before ‘Limitations’ is not clear. Please revise.
The rationale and calculations supporting that statistical power was 60% should be presented
in the statistical methods section.
Not taking hormonal fluctuations or status into account should not be a limitation because the
data are available.
The conclusion that accurate measurement of body composition is needed is not supported by
the data because controls and BCS had similar pREE and mREE and predictors of mREE were
similar between groups. Similarly the statement that “since the individual contribution of the
metabolic derangements to REE remains unknown and can lead to an altered metabolic state”
is not supported by the data presented.
Minor:
Pg3: patients with stage II-IV breast cancer (missing word)
Pg3: remove ‘is seen to be’
Pg3: The last sentence in paragraph 2 seems like it ends abruptly (dietary support could help
prevent adverse body composition changes?)
Pg4: Purpose 2 wording is confusing
Pg6: ‘demographic characteristics’ title should be something like ‘demographic and
anthropometric’ variables because body height and body weight are not demographics.
Pg6: The following demographic data (missing word)
Throughout: Please consider reporting kcal without decimals, as ICs are not accurate to the 0.1
level and to improve readability.
Pg13: spelling error in determinants