Background Skeletal muscle depletion or sarcopenia is related to multiple adverse clinical outcome. However, frailty questionnaires are currently applied in the daily practice to identify patients who are potentially (un)suitable for treatment but are time consuming and straining for patients and the clinician. Screening for sarcopenia in patients with head and neck cancer (HNC) could be a promising fast biomarker for frailty. Our objective was to quantify sarcopenia with pre‐treatment low skeletal muscle mass from routinely obtained neck computed tomography scans at level of third cervical vertebra in patients diagnosed with HNC and evaluate its association with frailty. Methods A total of 112 HNC patients with Stages III and IV disease were included from a prospective databiobank. The amount of skeletal muscle mass was retrospectively defined using the skeletal muscle index (SMI). Correlation analysis between SMI and continuous frailty data and the observer agreement were analysed with Pearson's r correlation coefficients. Sarcopenia was present when SMI felt below previously published non‐gender specific thresholds (<43.2 cm2/m2). Frailty was evaluated by Geriatrics 8 (G8), Groningen Frailty Indicator, Timed Up and Go test, and Malnutrition Universal Screening Tool. A univariate and multivariate logistic regression analysis was performed for all patients and men separately to obtain odds ratios (ORs) and 95% confidence intervals (95% CIs). Results The cohort included 82 men (73%) and 30 women (27%), with a total mean age of 63 (±9) years. The observer agreement for cross‐sectional measurements was excellent for both intra‐observer variability (r = 0.99, P < 0.001) and inter‐observer variability (r = 0.98, P < 0.001). SMI correlated best with G8 frailty score (r = 0.38, P < 0.001) and did not differ per gender. Sarcopenia was present in 54 (48%) patients, whereof 25 (46%) men and 29 (54%) women. Prevalence of frailty was between 5% and 54% depending on the used screening tool. The multivariate regression analysis for all patients and men separately isolated the G8 questionnaire as the only independent variable associated with sarcopenia (OR 0.76, 95% CI 0.66–0.89, P < 0.001 and OR 0.76, 95% CI 0.66–0.88, P < 0.001, respectively). Conclusions This is the first study that demonstrates that sarcopenia is independently associated with frailty based on the G8 questionnaire in HNC patients. These results suggest that in the future, screening for sarcopenia on routinely obtained neck computed tomography scans may replace time consuming frailty questionnaires and help to select the (un)suitable patients for therapy, which is highly clinically relevant.

Objectives Cross-sectional area (CSA) measurements of the neck musculature at the level of third cervical vertebra (C3) on CT scans are used to diagnose radiological sarcopenia, which is related to multiple adverse outcomes in head and neck cancer (HNC) patients. Alternatively, these assessments are performed with neck MRI, which has not been validated so far. For that, the objective was to evaluate whether skeletal muscle mass and sarcopenia can be assessed on neck MRI scans. Methods HNC patients were included between November 2014 and November 2018 from a prospective data-biobank. CSAs of the neck musculature at the C3 level were measured on CT (n = 125) and MRI neck scans (n = 92 on 1.5-T, n = 33 on 3-T). Measurements were converted into skeletal muscle index (SMI), and sarcopenia was defined (SMI < 43.2 cm2/m2). Pearson correlation coefficients, Bland–Altman plots, McNemar test, Cohen’s kappa coefficients, and interclass correlation coefficients (ICCs) were estimated. Results CT and MRI correlated highly on CSA and SMI (r = 0.958–0.998, p < 0.001). The Bland–Altman plots showed a nihil mean ΔSMI (− 0.13–0.44 cm2/m2). There was no significant difference between CT and MRI in diagnosing sarcopenia (McNemar, p = 0.5–1.0). Agreement on sarcopenia diagnosis was good with κ = 0.956–0.978 and κ = 0.870–0.933, for 1.5-T and 3-T respectively. Observer ICCs in MRI were excellent. In general, T2-weighted images had the best correlation and agreement with CT. Conclusions Skeletal muscle mass and sarcopenia can interchangeably be assessed on CT and 1.5-T and 3-T MRI neck scans. This allows future clinical outcome assessment during treatment irrespective of used modality. Key Points • Screening for low amount of skeletal muscle mass is usually measured on neck CT scans and is highly clinical relevant as it is related to multiple adverse outcomes in head and neck cancer patients. • We found that skeletal muscle mass and sarcopenia determined on CT and 1.5-T and 3-T MRI neck scans at the C3 level can be used interchangeably. • When CT imaging of the neck is missing for skeletal muscle mass analysis, patients can be assessed with 1.5-T or 3-T neck MRIs.

A low skeletal muscle index (SMI), defined with cut-off values, is a promising predictor for adverse events (AEs) in head and neck squamous cell cancer (HNSCC) patients. The aim was to generate sex-specific SMI cut-off values based on AE to diagnose low SMI and to analyse the relationship between low SMI and AEs in HNSCC patients. In this present study, HNSCC patients were prospectively included in a large oncological data-biobank and SMI was retrospectively measured using baseline neck scans. In total, 193 patients were included and were stratified according to treatment modality: (chemo-)radiotherapy ((C)RT) (n = 135) and surgery (n = 61). AE endpoints were based on the occurrence of clinically relevant toxicities (Common Terminology Criteria for Adverse Events grade ≥ III) and postoperative complications (Clavien–Dindo Classification grade ≥ II). Sex-specific SMI cut-off values were generated with receiver operating characteristic curves, based on the AE endpoints. The relationship of the baseline characteristics and AEs was analysed with logistic regression analysis, with AEs as the endpoint. Multivariable logistic analysis showed that low SMI (OR 3.33, 95%CI 1.41–7.85) and tumour stage (OR 3.45, 95%CI 1.28–9.29) were significantly and independently associated to (C)RT toxicity. Low SMI was not related to postoperative complications. To conclude, sex-specific SMI cut-off values, were generated based on the occurrence of AEs. Low SMI and tumour stage were independently related to (C)RT toxicity in HNSCC patients.

The aim of this study was to evaluate whether radiologically defined sarcopenia, or a low skeletal muscle index (SMI), could be used as a practical biomarker for frailty and postoperative complications (POC) in patients with head and neck skin cancer (HNSC). This was a retrospective study on prospectively collected data. The L3 SMI (cm2/m2) was calculated with use of baseline CT or MRI neck scans and low SMIs were defined using sex-specific cut-off values. A geriatric assessment with a broad range of validated tools was performed at baseline. POC was graded with the Clavien–Dindo Classification (with a grade of > II as the cut-off). Univariate and multivariable regression analyses were performed with low SMIs and POC as the endpoints. The patients’ (n = 57) mean age was 77.0 ± 9 years, 68.4% were male, and 50.9% had stage III–IV cancer. Frailty was determined according to Geriatric 8 (G8) score (OR 7.68, 95% CI 1.19–49.66, p = 0.032) and the risk of malnutrition was determined according to the Malnutrition Universal Screening Tool (OR 9.55, 95% CI 1.19–76.94, p = 0.034), and these were independently related to low SMIs. Frailty based on G8 score (OR 5.42, 95% CI 1.25–23.49, p = 0.024) was the only variable related to POC. However, POC was more prevalent in patients with low SMIs (∆ 19%, OR 1.8, 95% CI 0.5–6.0, p = 0.356).To conclude, a low SMI is a practical biomarker for frailty and malnutrition in HNSC. Future research should be focused on interventions based on low SMI scores and assess the effect of the intervention on SMI, frailty, malnutrition, and POC.