Skeletal muscle measurements predict surgical wound complications but not overall survival in patients with soft tissue sarcoma

Sarcopenia is a negative prognostic factor in localized extremities/trunk wall soft tissue sarcomas

OBJECTIVE

Sarcopenia is an emerging determinant of oncologic patients' prognosis, but few data are available in extremities and trunk wall soft tissue sarcomas (ESTS). The aim was to evaluate sarcopenia impact on outcomes of patients affected by ESTS.

METHODS

Through SliceOMatic software we selected cross-sectional skeletal muscle area (SMA), subcutaneous fat area (SFA) and visceral fat area (VFA) on a basal CT-slice at level of the third lumbar vertebra. Muscle density (MD) was computed in Hounsfield units (HU). Skeletal mass index (SMI, cm2/m2) was computed by normalizing SMA for the square of patient's height. Cut-offs for SMI were 52 and 39 cm2/m2 for men and women, respectively, while we used median values for MD, SFA and VFA. We explored the correlation of the different parameters with post-surgical complications and survival outcomes (Kaplan-Meier method).

RESULTS

268 patients were included. Median SMAs, SMIs and MD were 155.7 cm2, 51.2 cm2/m2, and 33.8 HU for men, 91.4 cm2, 39.2 cm2/m2, and 30.4 HU for women. Sarcopenia rate was not significantly higher in patients ≥65 years nor according to baseline prognostic factors (Sarculator app). Overall survival (OS) was significantly worse for sarcopenic patients: median OS 111.7 months (95%CI 72.8-150.6) vs not reached (NR; HR = 1.55, 95%CI:1.00-2.41, p = 0.049) for low-vs high-SMI; median OS 79.6 months (38.6-120.6) vs NR (HR 2.11, 1.34-3.34, p = 0.001) for low-vs high-MD, respectively. Sarcopenic patients showed increased post-surgical complications (30.5 % vs 17.0 %, p = 0.073).

CONCLUSION

Although retrospective, our study suggests to further explore sarcopenia as a negative prognostic factor in ESTS patients.

Development and validation of a nomogram to predict surgical site infection after soft-tissue sarcoma resection

Aims

Surgical site infection (SSI) after soft-tissue sarcoma (STS) resection is a serious complication. The purpose of this retrospective study was to investigate the risk factors for SSI after STS resection, and to develop a nomogram that allows patient-specific risk assessment.

Methods

A total of 547 patients with STS who underwent tumour resection between 2005 and 2021 were divided into a development cohort and a validation cohort. In the development cohort of 402 patients, the least absolute shrinkage and selection operator (LASSO) regression model was used to screen possible risk factors of SSI. To select risk factors and construct the prediction nomogram, multivariate logistic regression was used. The predictive power of the nomogram was evaluated by receiver operating curve (ROC) analysis in the validation cohort of 145 patients.

Results

LASSO regression analysis selected possible risk factors for SSI, including age, diabetes, operating time, skin graft or flap, resected tumour size, smoking, and radiation therapy. Multivariate analysis revealed that age, diabetes, smoking during the previous year, operating time, and radiation therapy were independent risk factors for SSI. A nomogram was developed based on the results of multivariate logistic regression analysis. In the development cohort, the incidence of SSI was 4.5% in the low-risk group (risk score < 6.89) and 26.6% in the high-risk group (risk score ≥ 6.89; p < 0.001). In the validation cohort, the incidence of SSI was 2.0% in the low-risk group and 15.9% in the high-risk group (p = 0.004).

Conclusion

Our nomogram will enable surgeons to assess the risk of SSI in patients with STS. In patients with high risk of SSI, frequent monitoring and aggressive interventions should be considered to prevent this.

Diagnostic Value of Sarcopenia Computed Tomography Metrics for Older Patients with or without Cancers with Gastrointestinal Disorders

OBJECTIVES

The diagnostic utility of poor body composition measures in sarcopenia remains unclear. We hypothesize that the skeletal muscle gauge [combination of skeletal muscle index (SMI) and skeletal muscle density (SMD); SMG = SMI × SMD] would have significant diagnostic and predictive value in certain muscle regions and populations.

DESIGN

Prospective cross-sectional study.

SETTING AND PARTICIPANTS

We examined inpatients age ≥60 years with or without cancer and with gastrointestinal disorders.

METHODS

We used computed tomography (CT) image metrics in the 12th thoracic (T12), third lumbar (L3), erector spinae muscle (ESM), and psoas muscle (PM) regions to establish correlations with the 2019 Asian Working Group for Sarcopenia Consensus and used receiver operating characteristic area under the curve (AUC) to compare differences between metrics. Associations between CT metrics and mortality were reported as relative risk after adjustments.

RESULTS

We evaluated 385 patients (median age, 69.0 years; 60.8% men) and found consistent trends in cancer (49.6%) and noncancer (50.4%) cohorts. SMG had a stronger correlation with muscle mass than SMD [mean rho: 0.68 (range, 0.59‒0.73) vs 0.39 (range, 0.28‒0.48); all P < .01] in T12, L3, and PM regions and a stronger correlation with muscle function than SMI [mean rho: 0.60 (range, 0.50‒0.77) vs 0.36 (range, 0.22‒0.58); all P < .05] in T12, ESM, and L3 regions. SMG outperformed SMI in diagnostic accuracy in all regions, particularly for L3 (AUC: 0.87‒0.88 vs 0.80‒0.82; both P < .05). PMG (PM gauge) and L3SMG did not differ, whereas EMG (ESM gauge) or T12SMG and L3SMG did (AUC: 0.80‒0.82 vs 0.87‒0.88; all P < .05). L3SMI, L3SMD, T12SMG, EMG, and PMG showed no association with 1-year cancer-related mortality after adjusting for confounders; however, L3SMG [relative risk = 0.92 (0.85‒0.99); P = .023) was.

CONCLUSIONS AND IMPLICATIONS

L3SMG covers all features of sarcopenia with more diagnostic value than other metrics, allowing a complete sarcopenia assessment with CT alone and not just in populations with cancer.

Prevalence of Low Muscle Mass in the Computed Tomography at the Third Lumbar Vertebra Level Depends on Chosen Cut-Off in 200 Hospitalised Patients-A Prospective Observational Trial

Measuring skeletal muscle area (SMA) at the third lumbar vertebra level (L3) using computed tomography (CT) is increasingly popular for diagnosing low muscle mass. The aim was to describe the effect of the CT L3 cut-off choice on the prevalence of low muscle mass in medical and surgical patients. Two hundred inpatients, who underwent an abdominal CT scan for any reason, were included. Skeletal muscle area (SMA) was measured according to Hounsfield units on a single CT scan at the L3 level. First, we calculated sex-specific cut-offs, adjusted for height or BMI and set at mean or mean-2 SD in our population. Second, we applied published cut-offs, which differed in statistical calculation and adjustment for body stature and age. Statistical calculation of the cut-off led to a prevalence of approximately 50 vs. 1% when cut-offs were set at mean vs. mean-2 SD in our population. Prevalence varied between 5 and 86% when published cut-offs were applied (p < 0.001). The adjustment of the cut-off for the same body stature variable led to similar prevalence distribution patterns across age and BMI classes. The cut-off choice highly influenced prevalence of low muscle mass and prevalence distribution across age and BMI classes.

Impact of Skeletal Muscle Measurements by Chest Computed Tomography on Survival and Postoperative Complications in Patients with Soft Tissue Sarcoma

This study aims to evaluate whether sarcopenia, measured by chest computed tomography (CT), affects survival outcomes and postoperative complications in soft tissue sarcoma (STS) patients undergoing surgery. In this retrospective study, CT scans of 79 patients were reviewed to measure pectoralis and T12 vertebra muscle area. Both were then adjusted for height (cm²/m²) as pectoralis muscle index (PMI) and T12 vertebra muscle index (TMI). Analyses were performed by dichotomizing muscle indices at gender-specific 50th percentile; PMI and TMI < 50th percentile were defined as low, and ≥50th percentile as high. Overall postsurgical complication rate (PCR) was 16%. Median length of hospital stay (LOHS) was 10 days (3-90). PMI and TMI were significantly lower in women (p = 0.02, p = 0.04). Median body mass index was significantly higher in high PMI and TMI groups (p = 0.01 for both). PCR and LOHS were similar between low and high PMI and TMI groups. Median follow-up was 29 months, 37 patients had recurrence and 23 died. No significant difference was noted between low and high PMI and TMI groups, in terms of disease-free or overall survival. PMI and TMI as measured by chest CT had no impact on survival outcomes or postoperative complications in localized STS.

Skeletal muscle gauge as a prognostic factor in patients with colorectal cancer

Background

Although skeletal muscle index (SMI) and radiodensity (SMD) are well‐known prognostic factors, the clinical impact of the integrated measure, known as skeletal muscle gauge (SMG), has been limited in patients with colorectal cancer (CRC).

Patients and Methods

A total of 727 and 268 patients with CRC at two tertiary centers were included and allocated into the training and test sets, respectively. Preoperative slice computed tomography images of the third lumbar area were evaluated for SMI and SMD. SMG was calculated as SMI × SMD and expressed as an arbitrary unit (AU). The optimal cutoff SMG value was determined to maximize the overall survival (OS) difference between the groups with respect to sex in the training set. The multivariate Cox proportional hazard model evaluated the association of its clinical significance.

Results

With regard to SMG, 1640 and 1523 AU were identified as cutoff values for males and females, respectively. The patients with low SMG values showed significantly worse 5‐year OS than those with high SMG values in the two datasets (both p < 0.001). In the multivariate analysis, low SMG was identified as an independent poor prognostic factor of OS in the training set (hazard ratio 2.18, 95% confidence interval 1.43–3.32, p < 0.001) and test set (hazard ratio 1.79, 95% confidence interval 1.07–3.00, p = 0.025), whereas SMI and SMD were not.

Conclusion

SMG acts synergistically to improve its prognostic predictive accuracy as compared with SMI or SMD alone in patients with CRC. Additional research is warranted to define its significance in different ethnic groups.