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Reply to comment on ‘Sarcopenic obesity in patients with head and neck cancer is predictive of critical weight loss during radiotherapy’ (BJN-2-2024-1107)

Published online by Cambridge University Press:  20 December 2024

Belinda Vangelov*
Affiliation:
Department of Radiation Oncology, Nelune Comprehensive Cancer Centre, Prince of Wales Hospital and Community Health Services, Randwick, NSW 2031, Australia
Robert I. Smee
Affiliation:
Department of Radiation Oncology, Nelune Comprehensive Cancer Centre, Prince of Wales Hospital and Community Health Services, Randwick, NSW 2031, Australia School of Clinical Medicine (Randwick Campus), Faculty of Medicine and Health, University of New South Wales, Randwick, NSW 2031, Australia Department of Radiation Oncology, Tamworth Base Hospital, Tamworth, NSW 2340, Australia
Judith Bauer
Affiliation:
Department of Nutrition, Dietetics and Food, School of Clinical Sciences, Monash University, Clayton, VIC 3168, Australia
*
Corresponding author: Belinda Vangelov; email [email protected]
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Abstract

Type
Letter to the Editor
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of The Nutrition Society

Dear Editor,

The authors would like to thank Topkan et al. for their interest in our recently published manuscript titled ‘Sarcopenic obesity in patients with head and neck cancer is predictive of critical weight loss during radiotherapy’(Reference Vangelov, Smee and Bauer1). We would like to address their comments on our statistical methodology and terminology.

Our study aimed to:

1. Investigate the prevalence of sarcopenic obesity (SO) in patients with head and neck cancer (HNC) who had completed curative radiotherapy (± chemotherapy) and its impact on survival

2. Identify any predictors of critical weight loss (CWL).

We found CWL in 58 % of the cohort (n 239) and sarcopenia (CT-defined) in 43 % (n 177). Topkan et al. call into question statistical methodology used; however, there appears to be misinterpretation on their part with the cohorts used in the analyses. Patients with sarcopenia (n 177) were dichotomised by CWL category (yes/no) and compared. Among these, eighty-nine patients with sarcopenia were then dichotomised by obesity status (SO yes/no) and again compared. As reported in the Results section, paragraph 3 – ‘In patients with sarcopenia, half experienced weight loss ≥ 5 % (n 89), and significantly more patients with SO had CWL (n 70 v. 19, P < 0·001)’. This statement refers to χ 2 analysis conducted within the subset of patients with sarcopenia and CWL, not 70/116 and 19/297 as Topkan et al. suggest, rather 70/89 v. 19/89. In this instance, the comparison is of patients within the same group, the onus being on ‘patients with sarcopenia’, and this specific statistical finding relates to this subgroup of patients, not as percentages of the whole cohort. This is a comparison of categorical unpaired data, and the methodology used is appropriate as per Nayak and Hazra(Reference Nayak and Hazra2).

Our multivariable binary logistic regression model examined predictors of CWL in the entire population, with SO as a dichotomous (yes/no) predictor variable (input into the backwards stepwise model, as detailed in the Methodology section).

It is important to distinguish that the two results brought into question – elevated incidence of CWL and predictors of CWL, involved analysis of different population groups/subgroups, and this is clearly stated in our manuscript.

Regarding Table 1, again, there appears to be misinterpretation. There are not two groups in this table, rather, the second column is the subset of patients with SO (n 116) (these patients are present in the first column as part of the whole cohort n 413). This table illustrates SO group characteristics and P-value comparisons would only be accurate if comparing two distinct groups (SO v. non-SO), which is not the case here. An additional table including this comparison may have been informative; however, this was not deemed necessary as part of the rigorous peer review process prior to the publication of our paper.

No survival difference was found between SO and non-SO patients in the whole cohort (Figures 2a and 2b), and a significant difference was observed when comparing sarcopenia status (regardless of BMI) as shown in Fig. 3. The comparison of overall survival between those with SO and those without, shown in Fig. 4, was conducted on the subset of patients with sarcopenia and demonstrated better survival in those with SO, as discussed in our manuscript.

Topkan et al. suggest our use of the term ‘sarcopenia’ is “erroneous terminology”. We disagree. The issues around defining and diagnosing sarcopenia is addressed in our Introduction, specifically mentioning radiologically defined sarcopenia as a measure of muscle depletion associated with morbidity and mortality in HNC(Reference Wong, Zhu and Kraus3Reference Surov and Wienke5). While myopenia refers to clinically relevant muscle loss due to illness and at any age, the use of the terms ‘sarcopenia’ and ‘sarcopenic obesity’ is appropriate in the context of our study. Suggesting that The European Working Group on Sarcopenia in Older People’s definition (EWGSOP2)(Reference Cruz-Jentoft, Bahat and Bauer6) of sarcopenia should be definitive, and that the use of the term be restricted in its application is unwarranted, given its extensive use in the oncology setting. Kubrak et al. conclude that the appropriate use of the term ‘sarcopenia’ should be determined through peer review by the scientific community(Reference Kubrak, Martin and Grossberg7).

Acknowledgements

No financial support provided.

B. V. - writing - original draft, writing - review and editing. R. S. - writing - review and editing. J. B. - writing - review and editing. All authors have viewed and agreed to the submission.

None to declare.

References

Vangelov, B, Smee, RI & Bauer, J (2024) Sarcopenic obesity in patients with head and neck cancer is predictive of critical weight loss during radiotherapy. Br J Nutr 132, 599606.CrossRefGoogle ScholarPubMed
Nayak, BK & Hazra, A (2011) How to choose the right statistical test? Indian J Ophthal 59, 8586.CrossRefGoogle Scholar
Wong, A, Zhu, D, Kraus, D, et al. (2021) Radiologically defined sarcopenia affects survival in head and neck cancer: a meta-analysis. Laryngoscope 131, 333341.CrossRefGoogle ScholarPubMed
Findlay, M, White, K, Stapleton, N, et al. (2021) Is sarcopenia a predictor of prognosis for patients undergoing radiotherapy for head and neck cancer? A meta-analysis. Clin Nutr 40, 17111718.CrossRefGoogle ScholarPubMed
Surov, A & Wienke, A (2021) Low skeletal muscle mass predicts relevant clinical outcomes in head and neck squamous cell carcinoma. A meta analysis. Ther Adv Med Oncol 13, 17588359211008844.CrossRefGoogle ScholarPubMed
Cruz-Jentoft, AJ, Bahat, G, Bauer, J, et al. (2019) Writing Group for the European Working Group on Sarcopenia in Older People 2 (EWGSOP2), and the Extended group for EWGSOP2. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 48, 1631.CrossRefGoogle Scholar
Kubrak, C, Martin, L, Grossberg, AJ, et al. (2024) Sarcopenia etymology: Sarcos (flesh) penia (poverty) i.e. absence, lack or deficiency of a body constituent. Clin Nutr 43, 17381739.CrossRefGoogle ScholarPubMed