The effectiveness of skeletal muscle evaluation at the third cervical vertebral level for computed tomography‐defined sarcopenia assessment in patients with head and neck cancer

Vangelov, Belinda; Bauer, Judith; Moses, Daniel; Smee, Robert

doi:10.1002/hed.27000

Cited by 17 publications

(15 citation statements)

References 45 publications

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“…This study aimed to investigate the use of the vertebral landmark of C3 for muscle mass assessment in this population when L3 is not available in diagnostic CT scans. Although a prediction model has been previously suggested by Swartz et al [ 15 ], our group has shown that equation to not have good agreement with gold standard measures at L3 in our population [ 26 ]. The present study is the first to our knowledge to explore the applicability of C3-CSA in prediction modelling for L3-CSA in a majority overweight or obese population.…”

Section: Discussionmentioning

confidence: 67%

“…That model, however, was developed from a relatively small ( n = 52), heterogeneous cohort of patients with HNC and cross-validation was not conducted. As previously mentioned, evaluation of the application of the model on an Australian population of mostly overweight or obese patients found that it had weak agreement with measures taken at L3 to an acceptable clinical level [ 26 ]. A mean percentage difference in SMI measures of 5.6% was found (range − 34 to 33.1%, r = 0.548, p < 0.001), which translated clinically to a 5% misclassification of sarcopenia.…”

Section: Discussionmentioning

confidence: 99%

“…Our group has demonstrated previously that there may be issues in the translatability and accuracy of sarcopenia diagnosis, specifically with the application of the Swartz et al [ 15 ] model, in differing populations, especially in those with a higher proportion of overweight or obese patients. We found weak agreement between measures in our predominantly overweight population [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

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A prediction model for skeletal muscle evaluation and computed tomography-defined sarcopenia diagnosis in a predominantly overweight cohort of patients with head and neck cancer

Vangelov

Bauer

Moses

et al. 2022

Eur Arch Otorhinolaryngol

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Purpose This study investigates the feasibility of computed tomography (CT)-defined sarcopenia assessment using a prediction model for estimating the cross-sectional area (CSA) of skeletal muscle (SM) in CT scans at the third lumbar vertebra (L3), using measures at the third cervical level (C3) in a predominantly overweight population with head and neck cancer (HNC). Methods Analysis was conducted on adult patients with newly diagnosed HNC who had a diagnostic positron emission tomography–CT scan. CSA of SM in CT images was measured at L3 and C3 in each patient, and a predictive formula developed using fivefold cross-validation and linear regression modelling. Correlation and agreement between measured CSA at L3 and predicted values were evaluated using intraclass correlation coefficients (ICC) and Bland–Altman plot. The model’s ability to identify sarcopenia was investigated using Cohen’s Kappa (k). Results A total of 109 patient scans were analysed, with 64% of the cohort being overweight or obese. The prediction model demonstrated high level of correlation between measured and predicted CSA measures (ICC 0.954, r = 0.916, p < 0.001), and skeletal muscle index (SMI) (ICC 0.939, r = 0.883, p < 0.001). Bland–Altman plot showed good agreement in SMI, with mean difference (bias) = 0.22% (SD 8.65, 95% CI − 3.35 to 3.79%), limits of agreement (− 16.74 to 17.17%). The model had a sensitivity of 80.0% and specificity of 85.0%, with moderate agreement on sarcopenia diagnosis (k = 0.565, p = 0.004). Conclusion This model is effective in predicting lumbar SM CSA using measures at C3, and in identifying low SM in a predominately overweight group of patients with HNC.

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Section: Discussionmentioning

confidence: 67%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A prediction model for skeletal muscle evaluation and computed tomography-defined sarcopenia diagnosis in a predominantly overweight cohort of patients with head and neck cancer

Vangelov

Bauer

Moses

et al. 2022

Eur Arch Otorhinolaryngol

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“…This prediction rule was used in the present study. A recent study by Vangelov et al questioned the use of C3MA as an evaluation tool of skeletal muscle mass in HNSCC patients [ 38 ]. Although the authors found a good correlation of measured L3MA and calculated L3MA from C3MA, systemic biases were reported with underestimation of L3MA for low values of C3MA and overestimation for high C3MA values and therefore hampering classification of individual patients into sarcopenic and non-sarcopenic.…”

Section: Discussionmentioning

confidence: 99%

Sarcopenia as a Prognostic Marker in Elderly Head and Neck Squamous Cell Carcinoma Patients Undergoing (Chemo-)Radiation

Haehl

Alvino

Rühle

et al. 2022

Cancers

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Sarcopenia is associated with reduced survival and increased toxicity in malignant diseases. The prevalence of sarcopenia increases with age and is an important cause of functional decline. We analyzed sarcopenia and sarcopenia dynamics in elderly head-and-neck squamous cell carcinoma (HNSCC) patients undergoing (chemo)radiation. Skeletal muscle mass of 280 elderly HNSCC-patients (>65 yrs) receiving curative (chemo)radiation was manually outlined and quantified on CT scans at the level of the C3 (C3MA). Cross-sectional muscle area at L3 (L3MA) was calculated and normalized to height (L3MI). Frequency distributions of clinical parameters as well as overall survival (OS), progression-free survival (PFS) and locoregional control (LRC) were calculated regarding sarcopenia. Calculated L3MA correlated with pretherapeutic hemoglobin-levels (ρ = 0.280) bodyweight (ρ = 0.702) and inversely with patient-age (ρ = −0.290). Sarcopenic patients featured larger tumors (T3/4 69.0% vs. 52.8%, p < 0.001), a higher burden of comorbidity (age-adjusted Charlson Comorbidity Index 4.8 vs. 4.2, p = 0.015) and more severe chronic toxicities (CTCAE grade 3/4 24.0% vs. 11.8%, p = 0.022). OS was significantly deteriorated in sarcopenic patients with a median of 23 vs. 91 months (logrank p = 0.002) (HR 1.79, CI 1.22–2.60, p = 0.003) and sarcopenia remained an independent prognostic factor for reduced OS in the multivariate analysis (HR 1.64, CI 1.07–2.52, p = 0.023). After therapy, 33% of previously non-sarcopenic patients developed sarcopenia, while 97% of pre-treatment sarcopenic remained sarcopenic. Median bodyweight decreased by 6.8%, whereas median calculated L3MA decreased by 2.4%. In contrast to pretherapeutic, post-therapeutic sarcopenia is no prognosticator for reduced OS. Pretherapeutic sarcopenia is a significant prognostic factor in elderly HNSCC patients undergoing (chemo-)radiation and should be considered in pretherapeutic decision-making. Its role as a predictive marker for tailored supportive interventions merits further prospective evaluation.

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“…Skeletal muscle mass (SMM) was defined as the total cross-sectional skeletal muscle area (TMA in cm 2 ). SMI was calculated by dividing the total cross-sectional skeletal muscle area (TMA-cm 2 ) at the level of lumbar vertebra L3 by height squared (m 2 ), which could proportionally reflect whole-body muscles of patients ( 32 , 33 ). And measurements of muscle on sectional CT is considered as the gold standard method at present ( 34 , 35 ).…”

Section: Methodsmentioning

confidence: 99%

Sarcopenia Was a Poor Prognostic Predictor for Patients With Advanced Lung Cancer Treated With Immune Checkpoint Inhibitors

Liu

Ren

et al. 2022

Front. Nutr.

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BackgroundIt remains not well known whether skeletal muscle mass (SMM) loss has any impact on the effectiveness of immune checkpoint inhibitors (ICIs) in patients with advanced lung cancer. We aimed to evaluate the association between SMM and clinical outcome of patients with advanced lung cancer receiving ICIs as first line or second line.Materials and MethodsFrom March 1st, 2019 to March 31st, 2021 at our hospital, 34 patients with advanced lung cancer treated with first-line or second-line ICIs were enrolled retrospectively. The estimation of skeletal muscle index (SMI) for sarcopenia was assessed at the level of the third lumbar vertebra (L3) on computed tomography (CT) images obtained within 4 weeks before initiation of ICIs treatment. The impact of sarcopenia (low SMI) on progression free survival (PFS) was analyzed using Kaplan-Meier method and log-rank tests. The effect of various variables on PFS was evaluated using Cox proportional hazards regression model with univariate and multivariate analysis. The impact on treatment response including objective response rate (ORR) and disease control rate (DCR) and immunotherapy related adverse events (irAEs) between patients with and without sarcopenia was compared by the chi-squared test. The comparison of SMI value between patients with objective response (OR), disease control (DC) and those without OR and DC was used student t-test or Mann-Whitney U test.ResultsBoth in univariate and multivariate analysis, sarcopenia and treatment lines were the predictive factors for PFS (p < 0.05). Patients with sarcopenia had significantly shorter PFS than that of non-sarcopenic ones [6.57 vs. 16.2 months, hazard ratios (HR) = 2.947 and 3.542, and 95% confidence interval (CI): 1.123–13.183 and 1.11–11.308, p = 0.022 and 0.033]. No significant difference in ORR and irAEs was found. Patients with sarcopenia had lower DCR than those without sarcopenia. The mean SMI value of DCR group and non-DCR group was 32.94 ± 5.49 and 44.77 ± 9.06 cm2/m2, respectively (p = 0.008).ConclusionSarcopenia before immunotherapy might be a significant predictor for poor prognosis including shorter PFS and lower DCR in patients with advanced lung cancer treated with ICIs as first line or second line.

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The effectiveness of skeletal muscle evaluation at the third cervical vertebral level for computed tomography‐defined sarcopenia assessment in patients with head and neck cancer

Cited by 17 publications

References 45 publications

A prediction model for skeletal muscle evaluation and computed tomography-defined sarcopenia diagnosis in a predominantly overweight cohort of patients with head and neck cancer

A prediction model for skeletal muscle evaluation and computed tomography-defined sarcopenia diagnosis in a predominantly overweight cohort of patients with head and neck cancer

Sarcopenia as a Prognostic Marker in Elderly Head and Neck Squamous Cell Carcinoma Patients Undergoing (Chemo-)Radiation

Sarcopenia Was a Poor Prognostic Predictor for Patients With Advanced Lung Cancer Treated With Immune Checkpoint Inhibitors

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