The Influence of Muscle Morphology on Oncological Outcomes: A Review.

Introduction

Cancer is a prevalent disease with significant impact on a persons’ quality of life, perceived health, and life expectancy[ 1 - 3 ]. It is one of the main causes of death worldwide, with more than 10 million deaths in 2020[ 1 ]. The most prevalent cancer types are breast, lung, colorectal, prostate, skin and stomach. One of the consequences of cancer and cancer treatment is muscle wasting, a condition with reduced muscle mass that negatively impacts prognosis and quality of life[ 4 ].

Muscle health is gaining increasing interest not only in an oncological setting but also in other medical fields. While awaiting the currently ongoing global definition of sarcopenia, which is a work in progress by the Global Leadership Initiative on Sarcopenia (GLIS)[ 5 ], the most updated definition states that sarcopenia is a muscular disease with low strength as key feature, combined with low muscle quantity or quality[ 6 ]. This occurs mainly in older persons but can also appear earlier in life or even in children[ 6 ]. Sarcopenia can be primary and thus age-related, however certain disease states, such as cancer but also declines in nutritional intake and physical activity, can induce secondary sarcopenia[ 6 , 7 ]. Sarcopenia is closely linked with cachexia, which is defined as a multifactorial syndrome with severe loss of weight due to an underlying disease and is cytokine-mediated. Cachexia mainly involves loss of fat and muscle[ 7 , 8 ]. Both sarcopenia and cachexia are common in cancer patients: 15-50% has sarcopenia, and 25-80% suffers from cachexia[ 7 ]. These two entities often co-exist and can exacerbate each other[ 7 ].

Different imaging methods are available to evaluate muscle status. Dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA) measure muscle quantity. For these techniques cut-off values have been established. For computed tomography (CT) measurements cut-off values for sarcopenia have been more recently proposed[ 9 ]. However, multiple studies use different values. Magnetic resonance imaging (MRI) is often used in research and in oncological or surgical settings. Ultrasound (US) is a technique that is gaining more attention for the evaluation of muscle status since it is easily accessible, inexpensive, and non-invasive. The advantages of CT, MRI and US are that they can assess both muscle quantity and quality[ 6 , 10 , 11 ].

Muscle quantity can be assessed through muscle thickness (MT), cross-sectional area (CSA), skeletal muscle mass (SMM) and skeletal muscle index (SMI): skeletal muscle area divided by height. Muscle quality is possibly equally important, and covers assessments of histology, radiology, functionality or metabolism[ 5 ]. It is determined by a combination of metabolic features, number of type II fibres, insulin resistance, fat infiltration, fibrosis, disrupted aerobic capacity and neurological derangements[ 12 ]. The evaluation of muscle quality is more challenging however. Suggestions have been made to measure the pennation angle (PA), fascicle length (FL), echo intensity (EI), muscle elastography (ME), phase angle (PhA) and muscle density (MD)[ 6 ]. The latter is defined as the mean attenuation coefficient, expressed in Hounsfield Units (HU), measuring muscular fat infiltration[ 13 ]. Skeletal muscle gauge (SMG) is a less frequently computed muscle parameter that is calculated by multiplying the SMI and the MD[ 14 ].

Sarcopenia is prevalent, especially in older individuals, with prevalence varying from 10 to 27% in older persons, depending on the definition and cut-off values used. However, muscles of younger individuals aged <60 years can also be affected, with prevalence ranging from 8 to 36%[ 15 ]. Muscle status is an important parameter for general health. It is already known that sarcopenia confers higher mortality rates, more functional decline, higher risk of falling and an increased risk of hospitalization[ 16 ]. Sarcopenia and oncological problems often co-exist, and the combination is associated with higher prevalence of adverse outcomes. In oncological treatment, decisions are often made considering chronological age. However, sarcopenia is associated with poorer prognosis and more postoperative complications in oncology patients. This is due to a combination of primary and secondary sarcopenia. Sarcopenic patients with cancer suffer from more pulmonary complications, infections, higher readmission rates and increased length of hospitalization[ 17 ]. A higher treatment toxicity and a reduced quality of life are also seen[ 18 ].

The aim of this study was twofolded. First, to review which muscle parameters were associated to certain clinical outcomes in oncology, such as: overall survival, progression-free survival, cancer-specific survival, chemotoxicity, surgical outcomes, response to oncologic treatment, length of stay and rehospitalisation, and quality of life. Second, we wanted to give an insight in the current literature about muscle status and oncological outcomes, so that an impetus can be given for a more routine geriatric assessment and follow-up when considering oncologic treatments.

Methods

This systematic review is part of a series of systematic reviews considering clinical health outcomes and muscle parameters which will be published separately, and are part of Sarcopenia through Ultrasound (SARCUS), a larger European non-funded academic project initiated in 2016, which involves researchers in different institutions in different countries, and has been gathered under the auspices of the European Union Geriatric Medicine Society (EuGMS) and the University of Antwerp, Belgium. This manuscript presents the efforts of the SARCUS project in gathering knowledge about the different outcomes in Oncology.

The combined systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines (19). The protocol was registered in the Prospective Register of Systematic Reviews Database (PROSPERO) under the registration number CRD42020179671. In this protocol, numerous clinical outcomes were investigated in association with macroscopic muscle parameters (such as oncological, surgical, medical, survival, length of stay, mobility, frailty, nutritional, bone health, respiratory, masticulatory, functionality, dysphagia, …). Later, these results were divided into different articles with focus on one specific outcome parameter.

Inclusion and exclusion criteria

The following keywords and their related MESH terms were used for the search (see Table 1 for the complete search terms): Ultrasound, Computed Tomography, Magnetic Resonance Imaging, Pennation angle, Muscle thickness, Echo-intensity, Muscle density, Cross-sectional area, Fascicle length. In the first article selection, all possible clinical outcomes were included. Exclusion criteria were studies involving children, animals or cadaver studies, review studies and case reports. Only articles in English were included in the study according to existing literature[ 20 , 21 ].

Search strategy and article selection

An initial search was performed on April 14 th 2020. Because numerous new articles were published in the time of data extraction and analysis, follow-up searches were conducted on September 29 th 2021 and April 11 th 2023 to check for the latest published research to improve the quality of the paper. Systematic searches were performed using SCOPUS, AMED and EBM Reviews - ACP Journal Club. Duplicates were removed and titles and abstracts were selected for eligibility by two investigators (SB and SP) using Rayyan software. In case of disagreement about in- or exclusion, the article was included. Then, the full text articles were sought through different libraries or through contacting the authors via Researchgate. Subsequently, the articles were subdivided among the authors for further selection and data extraction. Each full text article was checked on suitability for the study by SB and one other reviewer out of 18 different researchers, and data extraction was performed by both reviewers.

Data extraction and analysis

Data were extracted by 18 different researchers, and checked personally by SB. Disagreement was solved through intensive discussion. The extracted data included author, year of publication and country of investigation, population of interest (with gender and mean age), examined muscle or muscle group, imaging technique, muscle parameter, the investigated outcome measure, and the findings.

Results of the analysis on oncological outcomes were subdivided into six categories: survival, chemotoxicity, postoperative outcomes, response to treatment, duration of hospitalization and quality of life. Since survival can be defined in different ways, the differentiation was made between overall survival, progression-free survival, and cancer-specific survival.

Results

Study selection

A total of 6693 articles were identified after the last search for the combined health outcomes. After eliminating duplicates, the study yielded 4948 unique articles. After title and abstract selection, 988 studies remained. Full text articles were found in 978 cases for the total health study for article selection and quality assessment. 10 articles could not be found, either because no full text was available in the English language, or because they could not be retrieved on the different libraries or through Researchgate. Of these, 566 articles were eventually considered suitable for data extraction of all outcome parameters. For the review focused on oncological outcomes, 117 of 566 articles were included. The overview of study selection can be found in Figure 1 . Table 2 shows the general study characteristics of the included articles. Table 3 indicates the different investigated primary tumor locations. An overview of the included articles is shown in Tables 4-9.

General study characteristics

All of the included articles were original studies. Ninety-eight had a retrospective set-up and 19 were prospective. Ninety-six had data on survival. Twenty articles contained information on chemotoxicity and 33 on outcomes after oncological surgery. Twelve articles involved the response to the oncologic treatment. The duration of hospitalization and the rate of readmission was described in 20 articles. Finally, three articles highlighted the association of muscle parameters with the quality of life in patients suffering from cancer.

Most included studies measured muscle parameters by CT (102 articles). The remainder of the studies used MRI (14 studies), US (3 studies), BIA (3 studies) or DXA (1 study). Four articles included more than one measurement method. Most studies described the effect of skeletal muscle index (SMI, a quantitative measure) and muscle density (MD, a qualitative measure) on oncologic outcomes. In the great majority of these studies, SMI was calculated by CT as the CSA or all muscle tissue at the level of L3, divided by the square of height (cm 2 /m 2 ). However, few studies used the CSA of all muscles at L4 or T12 divided by the square of height, or used DEXA or BIA to define SMI (by appendicular skeletal muscle mass divided by the square of height). Most, but not all studies used the cut-off values for SMI as stated by Martin et al. CSA, MT, and SMG are other muscle parameters used in the included studies. All results with positive, negative or no effect are summarized in Figure 2 .

Oncology and survival

Ninety-six articles studied the effect of radiographic muscle parameters on survival. An overview of all the included articles can be found in Table 4 [ 22 - 115 ].

Overall survival

Overall survival (OS) was the most commonly used parameter used in survival analysis. It is defined as the time from randomization in the study until death. Ninety studies investigated the effect of muscle parameters on OS.

Sixty-two studies investigated the impact of skeletal muscle index (SMI) as measured by CT. An association between higher SMI and improved overall survival was seen in 36/62 (58%), with hazard ratios (HR) reported in 31 of these ranging from 1.22 to 4.9 (median 2.1). In 25/62 (40%) no significant association of SMI on overall survival was seen. One article revealed conflicting results favouring low SMI, with HR of 0.19. The authors attributed this to the high number of women in their population.

Forty articles described the association of muscle density by CT with OS. Higher MD was associated with better survival in 21/40 (52%), with HR for low MD ranging from 1.11 to 4.02 (median 2.01). In 19/40 (48%), no significant impact of MD could be found.

Although SMG is calculated from SMI and MD, the four articles that investigated SMG did not significantly show an effect on OS. MT showed a beneficial association between greater MT and OS in 10/13 (77%) studies, with HR ranging from 1.23 to 10.79 (median 2.13). The studies on MT mostly used MRI, but one article described the use of US. CSA was measured by CT in 13 articles, and by MRI in two. In 8/15 (53%) of the studies higher CSAs were significantly associated with better OS, with HR ranging from 1.09 to 2.16 (median 2.36) in the six articles that mentioned HR. Concerning the CT-based psoas muscle index (PMI), 3/6 (50%) showed a significant beneficial association of higher PMI on OS (median HR 2.33). Only one study used EI, but no significant effect on survival was shown.

Progression-free survival

Progression-free survival (PFS) is measured as the time from randomisation until either disease progression or death and was discussed in 39 original studies. Of the 31 studies on CT-based SMI and SMI-defined sarcopenia, 45% showed a significant impact, with HR ranging from 1.16 to 4.40 (median 1.82). Twenty-seven articles measured the effect of MD on PFS. In 16 studies (59%), significant results were seen. Of these, 13 favoured high MD with HR for low density ranging from 1.50 to 2.42 (median 1.99). Three however found higher PFS in low MD, with HR ranging from 0.49 to 0.68. Seven studies used CSA, but only two had significant results (28%), with a mean HR of 3.38. PMI was described in three articles, with significant benefit of higher PMI in two. One out of three articles showed a positive effect of SMG with HR of 1.10, but no significant correlations were found in two out of three articles. Only one article described effect of MT, with a HR of 4.57.

Cancer-specific survival

Cancer-specific survival (CSS) is the time from randomization until death caused by the index cancer. Only three articles searched for the effect on CSS. All three investigated SMI, with significant results in two of them (HR 1.74 and 2.07). One article did not find a significant correlation with MD, PMI nor MT.

Chemotoxicity

Twenty articles were included in the chemotoxicity search, 18 of them were retrospective. Seventeen investigated SMI, 13 MD, three SMG and four CSA. Of the 17 articles investigating SMI, 10 showed a significant relation with chemotoxicity (59%), with lower SMI appearing to be associated with dose-limiting toxicity or showing less chance of chemotherapy completion. Other studies showed more grade three or higher chemotoxicity, more leukopenia or more neuropathy. One study found only an effect on acute toxicities and not on chronic toxicity. Of those reporting MD, 7 out of 13 (54%) reported an association with chemotoxicity rates: 6/7 demonstrated a higher rate of adverse events, grade 3 or higher chemotoxicity and less chemotherapy completion in the presence of low MD or myosteatosis. Conversely, one article showed higher immune-related adverse events in high MD, probably because of better immune response. Lower SMG showed more adverse events and toxicity in 2/3 articles. All four articles showed that lower CSA gave rise to earlier drug-lowering toxicity, more grade three or higher toxicity and more acute and chronic toxicity. All results are shown in Table 5 25,30,38,40,41,43,46,48,55,63,65,70,86,114-120 .

Surgical outcomes in oncology

Results of surgical outcomes can be found in Table 6 25,27,29,34,39,49-51,57,58,63,83,84,92,94,102-104,107,121-133 . Thirty-two articles on surgical outcomes were included, of which 10 are prospective (31%). Eighteen described SMI. Seven (39%) saw a beneficial effect of a higher SMI, with lower risk of overall complications, respiratory failure, and infectious complications. Fourteen out of 17 MD studies (82%) noted that low MD gave rise to more postoperative complications, and more infectious, haemorrhagic, and cardiovascular problems. Half of the 8 articles on CSA showed that a lower CSA was related to more complications and respiratory failure. Low SMM showed more ileus and infectious and cardiac problems in 2 studies.

Response to oncologic treatment

Results generally favoured improved response with higher muscle parameters. Twelve articles described muscle parameters in relation to the chance of response to oncologic treatment (11 retrospective). Nine described the effect of SMI, of which only 1 found a significant effect on local progression (HR 0.89). Out of 8 studies, 3 found relevant correlations between MD and treatment response, with higher MD rendering a higher chance of IL2- response, higher treatment response and higher pathological response. SMG could predict time to treatment failure in 1 out of 2 articles. For CSA, 1 out of 2 articles found a higher pathological response in patients with greater CSA (OR 1.50). The one article on MT could not show a significant effect. These results are summarized in Table 7 [ 25 , 27 , 30 , 36 , 48 , 55 , 74 , 86 , 115 , 134 - 136 ].

Length of stay and rehospitalization.

On this topic, 20 articles were retained (15 retrospective), which can be found in Table 8 [ 25 , 27 , 29 ], [ 39 , 57 , 58 , 63 , 86 , 92 , 94 , 102 , 104 , 107 , 114 , 123 , 125 - 127 , 130 , 133 ]. For SMI, 7 investigated the effect on length of stay, of which only 1 found longer hospitalization duration in lower SMI. In 1 out of 2 articles, a higher rate of rehospitalization was found in those with low SMI. Half of the articles (56%) which looked at MD in relation to length of stay found that those with lower MD had a longer length of stay. One in 6 saw more rehospitalization in low MD patients. People with more hospitalizations had lower SMG. Patients with lower psoas or pectoralis muscle index had an increased risk of longer hospital stay in 4 out of 5 articles. Similar results were found for CSA in 1 out of 2 articles. One article described that patients with lower SMM had to stay longer in the hospital. Two studies looked at discharge destination in relation to muscle parameters in oncological patients, one of which found higher discharge rates to a care facility seen in those with lower MD or total psoas index.

Quality of life in oncology

Finally, quality of life was assessed in 3 articles ( Table 9 )[ 40 , 137 , 138 ]. Lower SMI was associated with lower ECOG-PS in 2 articles. MD was associated with lower ECOG-PS and lower total and physical quality of life scores.

Discussion

This study aimed to provide a high-quality, updated overview on the current knowledge on association of muscle parameters and certain clinical outcomes in oncology. Second, we wanted to give insight in the current literature regarding muscle parameters assessable in radiology and oncological outcomes.

In this systematic review, 117 articles were included and divided into six outcome categories: survival, chemotoxicity, surgical outcomes, treatment response, length of stay, and health-associated quality of life. Although the search included CT, MRI, US, BIA and DXA, most studies used CT to measure muscle parameters. This is because most patients with cancer have already undergone CT scans for staging. US and MRI are sometimes used in head and neck oncology because often MRI is superior to CT to distinguish different structures. Quantitative measurements included were mostly SMI, but also MT or CSA. MD was used as a qualitative parameter.

Six different cancer outcomes were described, of which survival is the most frequently investigated. In older studies, OS was mainly used. However, since this endpoint is more expensive and time-consuming, a shift towards PFS and CSS was seen in studies concerning pharmacologic treatment in oncology research. Quantitative muscle parameters were clearly associated with survival, as were qualitative parameters in a substantial number of studies. Although SMG can be seen as a good combination of quantitative and qualitative characteristics, it could not show a significant impact in most survival studies. These findings are in concordance with previous systematic reviews and meta-analyses on oncology survival. Ge et al. found significant associations between low SMI and low MD and lower long-term OS in ovarian cancer patients. However, they could not find an association with PFS[ 139 ]. In solid tumors, low SMI was associated with worse survival according to a study by Shachar[ 140 ]. Aleixo et al. found shorter OS in patients with myosteatosis in different cancer types[ 141 ]. A study by Yang et al. measured lower OS and PFS with lower temporal MT in patients with brain tumor[ 142 ]. To our knowledge, this is the first systematic review including multiple muscle parameters in different types of cancer.

Chemotoxicity could be predicted by muscle parameters. Low MD, but also low SMI increased the risk of chemotoxicity, with concomitant morbidity and early treatment discontinuation. Until now, dosage of chemotherapy is most frequently guided by body surface area (BSA) since this has been shown to correlate with blood volume, cardiac output, and renal function. However, patients with similar BSA can have very different distributions of muscle and adipose tissue. This often leads to over- or underdosing of chemotherapy, with reduced survival and increased complications[ 143 ]. Therefore, the American Society of Clinical Oncology (ASCO) guidelines suggest using muscle parameters and measures of body composition in drug dosage determination[ 144 ]. Using a combination of SMI and MD can therefore be helpful to guide clinicians in their treatment regimen decisions.

Sarcopenia and unfavourable muscle parameters negatively impact outcomes and increase adverse effects in cardiac and abdominal surgery[ 145 , 146 ]. This review found a clear impact of SMI, CSA, and MD in most of the included studies, with lower muscle quantity or quality related to higher postoperative complications. In oncology, a negative influence of sarcopenia on surgical complications and survival is also described[ 147 - 150 ]. Assessing the patients’ muscle status could help determining who is suitable for surgical treatment or deciding whether a patient needs more rigorous follow-up for complications after surgery. It can even be helpful to optimize muscle health through preoperative rehabilitation and nutritional interventions to potentially enhance the chances of positive postoperative outcomes and reduce complications.

Objective response rate (ORR), disease control rate (DCR) and local progression (LP) are less well described in current literature. Muscle quality seems to have a better prognostic impact on response than quantitative measurements. However, in a previous study, sarcopenia was associated with lower ORR and DCR in patients treated with Immune Checkpoint Inhibitors[ 151 ]. It is probable that body composition often predicts treatment response, since treatment dosages are generally determined by BSA, which does not always reflect differences in body composition. Therefore, people with similar BSA but distinct muscle parameters can suffer from over-or undertreatment, and, thus, a worse therapeutic response[ 143 ].

Length of stay and rehospitalization rate can be predicted by lower qualitative or quantitative muscle parameters in half of the investigated articles. Patients with lower muscle quality or quantity often suffer from more surgical complications and toxicity of treatment, which can reduce quality of life and cause an increase in healthcare expenses. Selecting the most suitable therapy for the individual can therefore be a cost-reducing tool for public healthcare systems that can simultaneously – and, more importantly - improve the patients’ wellbeing.

Adding to this, prolonging survival should not be the only goal in cancer treatment. Adding quantity of life years is important, but even more so is expanding qualitative time. Unfortunately, very few articles discuss the effect of muscle parameters on the patient’s perspective of treatment and life quality. A tendency towards lower quality of life (QOL) in oncological patients with lower muscle quantity and quality is seen, as is previously ascertained in sarcopenia in a general population[ 152 ]. Since the patients’ perspective and say in their treatment are very important, future studies should be not only focusing on hard end points, but also on the perception of a certain therapy.

The use of muscle parameters in determining the proper treatment dosage and maximising outcomes of oncologic therapy seems promising. Currently, SMI and MD as measured by CT at the level of L3 are the most studied parameters and can be utilized in a large proportion of oncology patients since the majority undergo abdominal CT in oncological staging. In other cancer types that don’t include abdominal CT in routine work-up, other muscle parameters can be used. Ultrasound is a promising technique since it is cheap, easy to use and can evaluate both quantitative and qualitative muscle characteristics. More research on this assessment technique is needed to confirm its usability.

Considering that muscle parameters influence survival and other outcomes in cancer patients, it could be helpful to improve the muscle status as early as possible after diagnosis. A systematic review by Rostoft et al. demonstrated that a geriatric assessment can be very helpful in oncological patients, can improve patient-centred outcomes and treatment completion, and can decrease toxicity and other complications[ 153 ]. Survival could potentially be improved with relatively simple interventions such as a protein-rich diet and resistance training, in accordance with their effect on mobility, as is proven in the SPRINTT trial[ 154 ]. If muscle status can be improved by treating sarcopenia in advance of starting chemotherapy, immune therapy, or surgery, the complications could be reduced, with less treatment dropouts and thus more success of the oncological treatment.

Another point of consideration and for further research can be follow-up of muscle parameters throughout the oncologic treatment trajectory. Oncology treatments have an unfavourable impact on muscle status through both sarcopenia and cachexia. Chemotherapy often leads to anaemia due to its myelotoxic trait, which impairs oxygen transport to the muscles. In addition, therapies such as anthracyclines can lead to myocardial damage and decrease cardiac output or lung damage. Immunosuppressants can cause loss of muscle mass. Chemotherapy-induced nausea and anorexia diminish protein intake. Cancer treatment is often accompanied by inactivity which can lead to secondary sarcopenia[ 155 , 156 ]. Treatment-independent cancer cachexia occurs as well in 80% of patients undergoing cancer treatment and is responsible for 22-30% of cancer-related deaths[ 157 ]. This is due to a systemic inflammatory response mediated by cytokines, chemokines and inflammatory mediators released by cancer cells[ 157 ]. This decline in muscle quantity and quality can further impair prognosis and necessitate adaptation of treatment. Additional research is desirable to study the pattern of muscle decline in oncology and in the different treatment options, and to determine how this should influence treatment dosages during therapy. Frequent follow-up of muscle status can then be performed regularly using easily accessible tools such as US.

Cut-off values or ranges for the different muscle parameters still need to be established. The EWGSOP2 did not suggest specific values for sarcopenia by measurement via CT, MRI, or US. For SMI, multiple cut-off values have been proposed, but without standard values it remains difficult to assess studies and guide practitioners to adapt therapy. The next policy-changing step in oncology would be to detect which (combination of) muscle parameters can be used to determine the individualized dose of chemotherapy or immune therapy instead of BSA. With gender-and age-specific cut-offs, an algorithm for treatment could be made. Frail patients often suffer more from the proposed therapy than from the cancer itself. The ideal range of the muscle parameters could then be an additional parameter to be considered in treatment decision, in order to prevent a potentially harmful therapeutic persistence.

Several strengths of this systematic review should be highlighted. First, this is the first systematic review investigating all muscle parameters measurable by CT, MRI, DXA, and US. It is not limited to a specific cancer type. The review did not only search for evidence about survival, but also other clinically meaningful outcome measures in an oncological setting, showing the advantages of measuring muscle mass and its parameters. This review can certainly help the field of oncology stepping away from the outdated BSA-based regimens and going towards more personalized, patient-tailored treatment plans, and can endorse the use of geriatric assessment and pretreatment interventions to improve muscle. Certain limitations can be mentioned. The extent of the study, including a heterogeneous group of cancer types, treatment options and macroscopic muscle measurements could influence outcomes. As there is a clear tendency towards worse outcomes with lower muscle status, all patients should be screened for this underlying condition, regardless of the cancer type. Another point of consideration is that different studies use different cut-off values for SMI to establish the presence of low muscle mass. Finally, the review aimed to be as inclusive and comprehensive as possible and included several definitions of sarcopenia in the studies retrieved. Some of these studies were not recent and did not follow the most updated standard definitions (EWGSOP2, AWGSOP, NIH, etc.), but previous or unstandardized definitions, which considered the use of muscle mass alone for the term sarcopenia[ 158 ]. Due to this, it is possible that some of the studies included were not actually measuring sarcopenia, but low quality or quantity of muscle mass instead. Therefore, they were actually measuring alternative muscle diseases or nutrition-related disorders which are also characterized and involve muscle issues, such as malnutrition, frailty, or importantly within this population, cachexia[ 159 ]. Although this could have repercussions on the comparability of the studies, this was not the set-up of this review.

Conclusion

Both qualitative and quantitative muscle parameters can be predictive for cancer survival, surgery outcomes, chemotoxicity, treatment response, length of stay and quality of life. It is strongly advised to start including muscle measurements in oncological treatment plans. This can help to determine who is suitable for a certain treatment and help identify patients who need more rigorous follow-up during their treatment. Furthermore, people could receive personalized pre-treatment plans including rehabilitation and nutritional support in order to enhance their outcomes and minimize the risk of complications. Further research is needed to clarify at which cut-off points better outcomes could be reached.

Authors’ contributions

Sophie Bastijns wrote the manuscript. Charlotte Beaudart performed the article search and provided statistical support. Sophie Bastijns, Blanca Alabadi, Thiago Gonzalez Barbosa-Silva, Kristoffer Brockhattingen, Scott Lamers, Karolina Piotrowicz, Carly Welch, and Stany Perkisas participated in the article selection and assessment. Blanca Alabadi, Thiago Gonzalez Barbosa-Silva, Kristoffer Brockhattingen, Scott Lamers, Karolina Piotrowicz, Carly Welch, Anne-Marie De Cock, and Stany Perkisas reviewed the manuscript. All authors read and approved the final version of the manuscript .

Acknowledgements

We wish to thank the following individuals for their contribution in data collection and article review: Femke Ariën, David Beckwée, Florence Benoit, Justin Chew, Olgun Deniz, Katleen Jegers, Meltem Halil, Suzy Hope, Nina Lefeber, Magdalena Malek, Dolores Sanchez-Rodriguez, Aldo Scafoglieri, Kate Taylor, Jona Van den Broeck, Daisy Wilson, Tilo Wünsch

Footnotes

Edited by: Yannis Dionyssiotis

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