Review for 10.1186/s12876-022-02479-4 (2022)

Title: Effect of skeletal muscle loss during neoadjuvant imatinib therapy on clinical outcomes
in patients with locally advanced GIST
Version: 1 Date: 14 Jun 2022
Reviewer:  Jan Peter Marquardt
Reviewer's report:
The authors analysed the effect of CT-derived skeletal muscle in 57 patients with locally
advanced GIST treated with neoadjuvant Imatinib. Rates of sarcopenia increased over the
course of treatment and skeletal muscle loss was associated with worse overall survival and
postoperative complications. Neither pre- nor posttreatment sarcopenia alone was associated
with survival or complications.
Major points:
- Materials and Methods, section Measurement and Definition of Body Composition, second
paragraph: Please elaborate on the methodology of acquiring segmentations. What software
was used? What part of the segmentation was automated and what part was manual? Was
the attenuation threshold applied during segmentation or on subsequent calculation of cross-
sectional area? How was the level of the third lumbar vertebra determined?
- Materials and Methods, section Measurement and Definition of Body Composition, second
paragraph: The choice of skeletal muscle index (SMI) as the primary metric for skeletal muscle
is solid and well established in body composition research. However, more recent research has
started to highlight the importance of skeletal muscle attenuation. The combination of SMI with
attenuation called skeletal muscle gauge (SMG) has been demonstrated to be a better predictor
of clinical and patient-reported outcomes than either of its two components alone. The authors
are invited to consider sticking to SMI as their primary metric but also investigate attenuation
and SMG as part of a sensitivity analysis. This could add support to the authors' hypothesis on
a conceptual level without needing to increase sample size or acquire new data
- Materials and Methods, section Statistical analysis, first paragraph: In the absence of previously
established cutoff values for clinically significant skeletal muscle loss, the authors chose to
define their own cutoff. For this, they split an already small cohort into even smaller subcohorts
based on sex. They then used an even smaller number of events to determine an "optimal cutoff"
for skeletal muscle loss rather than having pre-defined a clinically meaningful cutoff. This makes
the resulting cutoff values to be extremely prone to overfitting to the used data set. The cutoff
is then validated in the same setting it was generated in which makes misrepresentation of its
accuracy highly likely. It is strongly suggested that the authors use skeletal muscle loss as a
continuous variable. A clinically meaningful, pre-determined cutoff can be used for illustrative
purposes.
- Materials and Methods, section Statistical analysis, first paragraph: The small number of events
severely limits the use of multivariable models. For a Cox regression, at least 10 events per
variable are recommended to avois overfitting
- Table 3: Do the authors have a specific reason to dichotomise BMI as underweight versus
non-underweight? How many patients in the cohort were underweight? The effect size seems
very extreme and could be a result of having generated a very small subgroup through
dichotomisation. The authors are encouraged to look at BMI as a continuous variable, at least as
part of a sensitivity analysis. Moreover, operations such as dichotomisations should be included
in the methods section
Minor points:
- Introduction, third paragraph: CT-derived measurements allow distinction of different tissues
and therefore allow accounting for inter-sex differences better than other methods, not vice versa
- Introduction, third paragraph: Importantly, "opportunistic" skeletal muscle on images acquired
for other reasons does not lead to any potential harm or inconvenience for the patient, most
inmportantly radiation exposure. This is mentioned in the discussion but is worth mentioning
here as well
- Materials and Methods, section Measurement and Definition of Body Composition, first
paragraph: The correlation of L3 measurements with whole body measurements is probably
better placed in the introduction
- Materials and Methods, section Measurement and Definition of Body Composition, second
paragraph: Please elaborate on the image acquisition parameters, including tube potential, -
current, and reconstruction kernel. Was the imaging protocol identical for all scans of all
patients? What devices were used to obtain the images? Was intravenous contrast administered,
and if so, what phase were the images acquired in? If there are differences between patients, a
table would be very helpful
- Figure 1: The nomenclature ”Pre-SMI” and “Post-SMI” has the potential to confuse readers. If
a more explicit alternative such as "pretreatment SMI" is possible without cluttering the figure
too much, this could help add clarity
- Materials and Methods, section Outcome measures, fourth paragraph: Please distinguish three
year survival from overall survival
- Materials and Methods, section Statistical analysis, first paragraph: What determined whether
data was expressed using median + IQR versus mean + SD? What determined the test used for
comparison?
- Materials and Methods, section Statistical analysis, first paragraph: As adverse events are not
inherently dichotomous, is there a reason the authors chose to dichotomise them? Please consider
a test using ordinal outcomes such as an ordinal logistic regression, at least as part of a sensitivity
analysis
- Materials and Methods, section Statistical analysis, first paragraph: The mentioned "Uden
index" is neither widely known nor referenced in the manuscript
- Materials and Methods, section Statistical analysis, first paragraph: What determined the choice
of logrank tests versus Cox regression with a single, dichotomous predictor?
- Results, section Changes in sarcopenia during neoadjuvant therapy, first paragraph: How are
the p-values for the area under the ROC curves calculated and what do they represent?
- Results, section Changes in sarcopenia during neoadjuvant therapy, first paragraph: For the
female subgroup, if the test is for the area under the ROC curve is better than chance, the
confidence interval and the p-value do not match
- Figure 4: The numbers do not match the graphical representation, e.g. in the SML group the
32% of low effect has a bigger section of the bar than the 44% of moderate effect. Further,
the authors can consider scaling the figure for relative size only to help interpret inter-group
differences
- Results, section The relationship between sarcopenia and long-term prognosis after surgery,
first paragraph: Does "Kaplan-Meier analysis" refer to a logrank test?