skeletal muscle mass and cancer patient quality of life: a meta-analysis
Loss of skeletal muscle mass (sarcopenia), is a widely prevalent problem among cancer patients with incidence ranging from 11 to 74%. Low skeletal muscle mass at baseline is predictive of poor cancer outcomes such as decreased overall survival, increased risk of recurrence, increased chemotherapy toxicity, and a decline in quality of life. It seems that, in adult cancer patients, low skeletal muscle mass may provide additional and relevant information as a clinical outcome predictor. For this reason, body composition analysis has become a major focus in cancer studies. Consequently, health-related quality of life (HRQOL) has become a critical endpoint in clinical trials for advanced cancer.
Health-related quality of life (HRQOL)
HRQOL addresses both specific symptoms and generic aspects (e.g., physical, role, emotional, social, cognitive, sexual, and spiritual) of day-to-day functioning in the context of having a disease or being treated for a medical condition. In cancer populations, specific HRQOL tools are considered for their role as independent predictors for therapy response and survival. Gotay et al showed that baseline HRQOL levels have prognostic value for survival. Another important benefit of HRQOL assessment is that it can provide information extending beyond the perspective of a patient, allowing clinicians to explore both biological and genetic underpinnings of cancer symptoms and side effects.
Several cross-sectional studies have already been conducted on clinical trials using HRQOL endpoints in patients with advanced NSCLC, lung, and gastrointestinal cancers. All of them reported a strong relationship between low skeletal muscle mass and poor overall HRQOL, and greater symptoms of depression.
This systematic review and meta-analysis investigated the correlation between skeletal muscle mass and HRQOL. In addition, the authors also evaluated the relationship between CT-derived skeletal muscle mass radiodensity and measures of HRQOL
Methods
Data sources and search strategy
The authors performed a comprehensive search for relevant articles published from January 1, 2007 through September 2, 2020 using five databases: Ovid MEDLINE, Embase via Ovid, CINAHL plus, Scopus, and PsycInfo. The search terms were “sarcopenia”, “skeletal muscle”, “quality of life”, and “cancer”.
Study selection
At the full-text screening, two reviewers assessed relevant literature independently. The studies were eligible for further qualitative and quantitative analysis only if they i) assessed the relationship between body composition using CT ii) had HRQOL assessed using a validated tool and iii) included patients aged > 18 years with any cancer at any stage of treatment. The authors excluded studies that were: i) non-English and ii) conference abstracts, narrative review articles, or letters to the editor.
Clinical outcome
The primary outcome of this review was the analysis of the association between CT-derived skeletal muscle index (SMI, cm2/m2) or cross-sectional skeletal muscle area (cm2), and global HRQOL scores at baseline. Domain HRQOL scores, longitudinal changes in skeletal muscle mass and/or HRQOL, and skeletal muscle radiodensity were the secondary outcomes.
Data extraction
Two reviewers extracted the data independently. The extracted items were: author-year, country, study design, patient characteristics (number of patients, their age and gender, cancer type and stage), body composition assessment data (the software used, tissues assessed, radiodensity, anatomical site of analysis, frequency of body composition measurements, and thresholds of determination of optimal vs, suboptimal values) and HRQOL assessment data (tools used, frequency of assessment, and HRQOL scores). Clinical outcome data were also extracted independently. The results were then reconciled and discrepancies were discussed until a consensus was reached.
Results synthesis and statistical analysis
Full-text studies classifying skeletal muscle mass as a dichotomous variable (low or normal) were combined in a meta-analysis to investigate the cross-sectional association with HRQOL. Due to study heterogeneity, the authors performed a meta-analysis using a random-effects model and investigated skeletal muscle index change. Standardized mean differences with 95% confidence intervals (CI) were calculated as the summary effect measure. To test for the heterogeneity of the studies, the authors calculated I2 statistics. If I2 values exceeded 50%, the authors concluded that there was substantial heterogeneity. Standardized mean differences (SMD) with 95% confidence intervals (CI) were calculated as the summary effect measure. SMD of 0.2, 0.5, and 0.8 were considered small, moderate, and large effects, respectively. Subsequently, exploratory subgroup analyses were also performed. Clinical outcome data not suitable for meta-analysis were synthesized qualitatively.
Quality assessment
Quality assessments were independent. For studies where CT-derived body composition was a primary outcome, the site of analysis, software used, and radiodensity reference ranges for identifying tissue types were listed and assessed.
Results
Study selection
After removing duplicates, a total of 6090 studies were screened on September 2, 2020. Of these, 5892 were excluded due to their irrelevance to the research question. 198 articles were deemed eligible for review, with 14 meeting inclusion criteria for qualitative analysis involving 2776 patients. The authors were sent letters requesting additional information or clarification of data from 13 studies.
Analysis of skeletal muscle
Ten studies (n = 1375) categorized patients according to baseline skeletal muscle mass (low or normal). Five different cut-points were used across these studies, with low muscle mass attributed to 58% of participants (n = 795). Six studies used continuous linear associations of correlation or linear regression to assess the relationship between skeletal muscle mass and quality of life. However, there was heterogeneity; thus these results were qualitatively synthesized.
Primary outcome: Association of muscle mass with global HRQOL scores at baseline
The results of seven studies that used HRQOL assessment tools showed that low muscle mass was associated with poorer global HRQOL scores [n = 985, standardized mean difference – 0.27, 95% CI – 0.40, – 0.14, P < 0.0001]. Also, there was low statistical heterogeneity within these data (I2 = 2%). The inclusion or exclusion of van Roekelet al. (follow-up HRQOL = 2 – 10 years post-CT analysis) did not affect the findings of the meta-analysis. Sheeanet al. assessed the relationship between skeletal muscle as a categorical variable and global HRQOL scores in their study but was not included in the meta-analysis as data were presented as median. Five studies assessed the relationship between skeletal muscle scores as a continuous variable and global HRQL scores at baseline. Four studies found statistically insignificant associations. Bye et al. in their study on advanced lung cancer patients (n = 734), reported a significant association between SMI and global HRQOL in male patients.
Secondary outcome: Association of skeletal muscle mass and domain HRQOL score at baseline
The overall summary effect measure of five studies indicated that patients who had low skeletal muscle mass at baseline also had poorer physical functioning domain HRQOL scores (n= 507, standardized mean difference – 0.40, 95% CI – 0.74 to 0.05, P= 0.02). However, there were no significant associations for social, role, emotional, or cognitive functioning domain scores (all P> 0.05). Mitsui et al assessed the relationship between low (n =91) or normal (n = 210) skeletal muscle mass with domains of HRQOL specific to prostate cancer treatment. This study found no significant differences in urinary, bowel, sexual and hormonal domains (all P > 0.05). Five included studies evaluated the cross-sectional relationship between HRQOL at baseline and skeletal muscle mass as a continuous variable but there was little evidence of an association.
Secondary outcome: Association between changes in skeletal muscle and HRQOL over time
Derksen et al showed a clinically relevant increase in global HRQOL scores with the group experiencing stable muscle mass (β9.9, 95% CI 2.4, 17.5, P < 0.05) and the group experiencing gain in muscle mass (β14.7, 95% CI 8.0, 21.4, P < 0.05). There was clinically significant association with increased role functioning scores in patients with stable muscle mass (β12.0, 95% CI 2.2, 21.7, P < 0.05) or gain in muscle mass (β17.9, 95% CI 9.4, 26.5, P < 0.05). Wang et al reported correlation between the loss in total psoas muscle CSA from pre-treatment to three month follow-up with decline in domain scores for activity (r – 0.399, P = 0.019), recreation/entertainment (r – 0.438, P = 0.0096), and swallowing (r – 0.401, P = 0.019).
Secondary outcome: Association between skeletal muscle radiodensity and base-line HRQOL
Among the four studies that investigated the relationship between skeletal muscle radiodensity and HRQOL, two found no association. Conversely, a study of participants found a negative association between skeletal muscle radiodensity and physical functioning in females. Another study (n = 428) reported lower skeletal muscle radiodensity with worse physical functioning on both uni and multivariate analysis after controlling for weight loss, ECOG performance status, and low SMI.
Discussion
Sarcopenia has been recognized as an important issue in oncology for over a decade now. However, it is only recently that studies have focused on comparing pre and post-treatment outcomes. This systematic review and meta-analysis contributed to the understanding of the relationship between CT-derived assessment of skeletal muscle mass and HRQOL in adult cancer patients. The study showed that adults with low skeletal muscle mass have lower HRQOL scores compared to the ones with normal skeletal muscle mass. A subset of included studies evaluated the correlation between skeletal muscle mass across the continuum of values and HRQOL scores. However, there was little evidence unless non-linear analysis was used. The findings of this meta-analysis also showed a multifactorial and bidirectional relationship between SMI and quality of life. Bye et al. and Daly et al. reported the association between reduced skeletal muscle radiodensity and low HRQOL scores. Four studies included in this review reported measures of muscle strength and one included a measure of muscle function as one of the outcomes. The authors noticed that none of the studies included reported the participant’s treatment status at the time of the CT scan. And in studies that reported treatment status, there was significant variation. Considering the insufficient description of treatment status, further studies involving multivariate analysis should be needed. The primary outcome of this meta-analysis used five different cut points across seven studies. The results indicated that the choice of cut point could have influenced the findings in relation to HRQOL.
This meta-analysis has some limitations that should be acknowledged. The inability to determine the cause of muscle mass loss complicated the interpretation of the results. Seven HRQOL assessment tools were utilized across the 14 included studies, resulting in the incompatibility of some HRQOL data for inclusion in a meta-analysis. The usage of seven HRQOL assessment tools created some incompatible data that the authors could not include in the meta-analysis. There was also heterogeneity in measuring skeletal muscle mass from CT. The variable difference (religion, age, disease stage and performance status, the number of comorbidities, education, and proportion of individuals receiving chemotherapy treatment) in the final cohort may have varying impacts on the outcomes.
In summary, the findings derived from 14 studies revealed that low skeletal muscle mass may be associated with lower global and physical functioning HRQOL scores in adult cancer patients. Additional prospective and longitudinal studies are needed to more accurately determine the interplay between HRQOL and skeletal muscle mass in the context of cancer treatment.
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