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Abstract

Background

Immunotherapy has shown promise in treating various subtypes of metastatic cancers, but many patients are frail and may have compromised immune systems, which can influence treatment outcomes. Sarcopenia, a condition characterized by loss of muscle mass and systemic inflammation, is a potential factor that may negatively impact the response to immunotherapy. However, more data must be collected on the extent of its influence. Therefore, this study aims to investigate the effects of sarcopenia, systemic inflammation, and Eastern Cooperative Oncology Group Performance Status (ECOG PS) on the response to immunotherapy.

Methods

We enrolled 100 patients treated with immune checkpoint inhibitors between 2015 and 2021 who underwent computed tomography of the abdomen before the first immunotherapy dose. This study was conducted retrospectively. Gender-specific thresholds were used for the diagnosis of sarcopenia. C-reactive protein (CRP), erythrocyte sedimentation rate, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), albumin, and lactate dehydrogenase (LDH) were used as markers of systemic inflammation. Systemic inflammatory markers and sarcopenia were assessed using univariable and multivariable analyses for overall survival (OS) and progression-free survival (PFS).

Results

Sarcopenia was found to be a significant prognostic factor associated with poor PFS (HR, 2.33; 95% confidence interval [CI], 1.45-3.74; P < 0.001). In addition, hypoalbuminemia was identified as a significant prognostic factor for predicting OS (HR, 2.10; 95% CI, 1.21-3.66; P = 0.008).

Conclusions

Closer monitoring and prevention of sarcopenia may enhance both OS and PFS. Additionally, our composite model may assist oncologists in predicting responses to immunotherapy more accurately. However, further prospective studies are needed to validate these findings.

Plain Language Summary

Background This study examines how muscle loss (sarcopenia), body inflammation, and overall health status affect patients’ responses to cancer treatment with immunotherapy. Methods We studied 100 patients who received immunotherapy between 2015 and 2021. Before starting treatment, these patients had an abdominal scan to check for muscle loss. We also measured several inflammatory markers in their blood, such as CRP and NLR. We analyzed how muscle loss and these inflammatory markers affected the patients’ survival and how long they remained without cancer worsening. Results We found that patients with muscle loss were more likely to have their cancer progress sooner. Low protein levels, called albumin, which indicate poor nutrition and inflammation, were linked to shorter overall survival. Conclusion Monitoring and preventing muscle loss may help improve how long patients live and how well they respond to immunotherapy.

Keywords

ECOG PS hypoalbuminemia sarcopenia immunotherapy overall survival inflammation

Introduction

Immune checkpoint inhibitors (ICIs) have begun a new era in cancer treatment.¹ These inhibitors target the programmed cell death (PD-1) receptor or its ligand, programmed cell death-ligand 1 (PD-L1), and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4). Thanks to these inhibitors, an efficient anti-tumor T cell response can be restored.² ICIs are used in various types of cancer, including melanoma, non-small cell lung cancer (NSCLC), colon cancer, head and neck squamous cell carcinoma, and more.^3-6 Although immunotherapy has become essential for cancer treatment, predictive tools for determining responses have not been identified among advanced cancer patients. Several biomarkers have been discovered in recent years, encompassing tumor mutation burden (TMB), microsatellite instability, PD-L1 expression level, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR).^7-9 Previous studies show that a high TMB correlates with a favorable response to ICIs, particularly in melanoma and NSCLC cases characterized by high mutation burdens resulting from ultraviolet light and tobacco smoke.¹⁰ PD-L1 amplification has primarily functioned as a positive predictive marker for targeting the PD-1/PD-L1 axis across various cancers, including NSCLC, melanoma, and bladder cancer.¹¹ Moreover, a higher NLR and PLR may cause a reduction in the response to ICIs.⁹ Nevertheless, while these biomarkers pertain to immunotherapy responsiveness, their predictive values still need improvement to address this challenge thoroughly.

Sarcopenia is characterized by diminished muscle quality, quantity, and impaired functionality.^12,13 Computed tomography (CT) and magnetic resonance imaging (MRI) studies have been used to assess reductions in muscle mass, supported by evidence for estimating muscle mass.¹² Additionally, CT and MRI are commonly used in oncology to assess tumor response to immunotherapy and can also be utilized to evaluate muscle mass. While the precise connection between sarcopenia and cancer remains incompletely elucidated, a correlation exists between cancer and inflammation. Cytokines and chemokines that arise from chronic inflammation and cancer, such as tumor necrosis factor, interleukins-1 and -6, and macrophage-derived chemokines, can impact tissue remodeling, stromal development and induce angiogenic factors that foster tumor growth and dissemination.¹⁴ These cytokines and chemokines initiate molecular pathways leading to skeletal muscle wastage, instigating an imbalance between protein synthesis and catabolism.¹⁵ These pathways consequently contribute to the onset of sarcopenia, establishing an indirect link between sarcopenia and cancer.¹⁶ Furthermore, myosteatosis is a promising new prognostic biomarker for survival outcomes in patients with advanced cancer. Myosteatosis is distinct from sarcopenia, which involves excessive fat infiltration in skeletal muscle, leading to a decline in muscle function. Similar to sarcopenia, myosteatosis has been associated with a poor prognosis in several cancers. In most patients, sarcopenia and myosteatosis are found together and negatively affect patients’ prognosis.^17,18

In recent years, sarcopenia and inflammation have gained importance in predicting immunotherapy response.^10-12 Prior investigations have demonstrated that individuals with sarcopenia exhibit lower overall survival (OS) rates and reduced progression-free survival (PFS).^19-21 Our study aimed to assess the impact of sarcopenia, systemic inflammation, and the Eastern Cooperative Oncology Group Performance Status (ECOG PS) on the overall survival and progression-free survival of advanced cancer patients undergoing treatment with immune checkpoint inhibitors (ICIs).

Methods

We conducted a retrospective assessment of patients with metastatic cancer who underwent treatment with immune checkpoint inhibitors (ICIs) at Hacettepe University Cancer Institute between January 2015 and February 2021. One hundred fifty patients were initially reviewed, and 100 patients who met the eligibility criteria were included in the study. The study incorporated the following eligibility criteria: age older than 18 years, presence of recurrent or metastatic disease, availability of comprehensive clinical and demographic data, availability of a baseline abdomen CT scan taken within the last 6 months before the initial immunotherapy dose, availability of imaging to facilitate radiological response evaluation, and presence of systemic inflammatory markers measured within 3 days before the first immunotherapy dose. All patients meeting these specified criteria were included in the study. The reporting of this study conforms to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines²², and the study was approved by our institution’s Ethics Review Board (approval number: GO 21/335). The research adhered to the 1964 Declaration of Helsinki principles and its subsequent amendments. The requirement for informed consent was waived by our Institutional Review Board because of the retrospective nature of the study. We gathered demographic information, clinical data, date of diagnosis, sites of metastasis before commencing immunotherapy, previous treatments, date of disease progression, and the date of death, as well as the most recent follow-up from patient files and computer records.

Additionally, baseline laboratory parameters were recorded, including neutrophil count, lymphocyte count, platelet count, erythrocyte sedimentation rate, C-reactive protein (CRP), and lactate dehydrogenase (LDH). Furthermore, we calculated NLR and PLR. NLR and PLR values higher than the median were categorized as high.

The skeletal muscle index value was derived by dividing the cumulative muscle volumes of sections intersecting the L3 vertebra level by the square of the height. Gender-specific threshold values were employed to diagnose sarcopenia, with measurements under 45.4 cm²/m² for males and 34.4 cm²/m² for females. The thresholds from Derstine et al.’s research were applied in our study to ensure accurate and population-specific diagnostic criteria.²³

Statistics

Continuous variables were compared using Student's t-test or Mann-Whitney U test. In contrast, categorical variables were compared using Chi-squared test or Fisher’s exact test as appropriate for the data distribution. Based on sarcopenic status, the primary and secondary endpoints comprised PFS and OS, respectively. OS was calculated from the initial immunotherapy dose until the date of death. On the other hand, PFS was computed from the first dose to the date of clinical or radiographic progression or death. A four-tier risk grouping was formulated, considering ECOG PS and sarcopenic status. Survival probabilities for PFS and OS were computed using the Kaplan-Meier method, and differences in survival probabilities were compared using the log-rank test. Cox proportional hazards regression analyses were conducted to identify predictors of PFS and OS within a cohort of 100 patients without missing data points in the variables.

Results

Fifty-seven patients were aged 60 years or older, while 69 were male. Sarcopenia was observed in 41 patients. The baseline characteristics of patients and disease attributes are delineated based on their sarcopenia status in Table 1. Among the sarcopenic group, the median BMI was 23.6 kg/m² for males and 24.5 kg/m² for females. Conversely, the non-sarcopenic group exhibited a median BMI of 28.0 kg/m² for males and 26.8 kg/m² for females.

Table 1.

Baseline Characteristics of Patients Stratified by Sarcopenia Status.

	Sarcopenic (n = 41)	Non-sarcopenic (n = 59)	P value
Groups of age, n (%)			0.057
≤60	13(31,7%)	30(50,8%)
>60	28(68,3%)	29(49,2%)
Gender, n (%)			0,234
Male	31(75,6%)	38(64,4%)
Female	10(24,4%)	21(35,6%)
ECOG PS, n (%)			0,152
0-1	22(53,7%)	40(67,8%)
>1	19(46,3%)	19(32,2%)
Types of cancer, n (%)			0,318
MM	7(17,1%)	18(30,5%)
RCC	10(24,4%)	12(20,3%)
NSCLC	10(24,4%)	8(13,6%)
The others	14(34,1%)	21(35,6%)
Types of ICIs			0,476
Nivolumab	29(70,7%)	41(69,5%)
Atezolizumab	7(17,1%)	7(11,9%)
Pembrolizumab	3(7,3%)	3(5,1%)
İpilimumab	2(4,9%)	8(13,6%)
Lung metastasis before ICI	24(58,5%)	33(55,9%)	0,796
Liver metastasis before ICI	14(34,1%)	21(35,6%)	0,881
Number of prior therapies			0,796
≤1	24(58,5%)	33(55,9%)
>1	17(41,5%)	26,0(44,1%)

Abbreviations: ECOG PS: Eastern Cooperative Oncology Group Performance Status, MM: Malignant Melanoma, RCC: Renal Cell Carcinoma, NSCLC: Non-Small Cell Lung Cancer, ICIs: Immune Checkpoint Inhibitors.

Efficacy

Patients diagnosed with sarcopenia exhibited significantly lower progression-free survival (PFS) than those without sarcopenia (2.7 vs 6.7 months, respectively; P < 0.001) (Figure 1). In the univariable Cox regression analysis, gender (female), sarcopenia, Eastern Cooperative Oncology Group Performance Status (ECOG PS) ≥ 2, and elevated lactate dehydrogenase (LDH) levels emerged as significant prognostic factors for predicting poor PFS (Table 2). In the multivariable analysis, sarcopenia (HR, 2.33; 95% CI, 1.45-3.74; P < 0.001), ECOG PS ≥2 (HR, 3.50; 95% CI, 2.13-5.74; P < 0.001), and elevated LDH (HR, 1.68; 95% CI, 1.08-2.62; P = 0.021) were found to be independent factors associated with reduced PFS (Table 2).

Figure 1.

Progression-Free Survival Curve for Sarcopenic vs Non-Sarcopenic Patients (Kaplan-Meier).

Table 2.

Cox Regression Analysis Results for Progression-free Survival.

Variable (Reference)	Univariable		Multivariable
Variable (Reference)	HR (%95 CI)	P	HR (%95 CI)	P
Age (>60 years)	1.44 (0.85-2.42)	0.165	1.50 (0.93-2.36)	0.09
Gender (female)	1.90 (1.10-3.28)	0.020	1.64 (1- 2.70)	0.05
Sarcopenia (no sarcopenia)	2.75 (1.59-4.77)	<0.001	2.33 (1.45-3.74)	<0.001
ECOG PS ≥2 (0-1)	3.60 (2.18-5.93)	<0.001	3.50 (2.13- 5.74)	<0.001
NLR >3.57 (≤3.57)	1.10 (0.68-1.79)	0.675
PLR >190.8 (≤190.8)	1.43 (0.87-2.37)	0.155	1.35 (0.85-2.15)	0.194
Albumin<3.5 (≥3.5 g/dl)	1.10 (0.63-1.93)	0.731
LDH (higher than normal)	1.73 (1.07-2.78)	0.024	1.68 (1.08-2.62)	0.021
CRP (higher than normal)	1.42 (0.80-2.54)	0.228
Sedimentation (higher than normal)	1.13 (0.61-2.10)	0.687
BMI >25 (≤25)	1.10 (0.67-1.81)	0.686
Number of prior therapy>1 (≤1)	1.01 (0.64-1.60)	0.952	1.05 (0.68-1.62)	0.801

Abbreviations: HR: Hazard Ratio, CI: Confidence Interval, NLR: Neutrophil-To-Lymphocyte Ratio, PLR: Platelet-To-Lymphocyte Ratio, LDH: Lactate Dehydrogenase, CRP: C-Reactive Protein, BMI: Body Mass Index.

Patients with sarcopenia exhibited significantly poorer overall survival (OS) compared to those without sarcopenia (6.3 vs 12.1 months, respectively; P = 0.032) (Figure 2). In the Cox regression analysis, factors including age (>60 years), Eastern Cooperative Oncology Group Performance Status (ECOG PS) ≥ 2, albumin levels below 3.5 g/dl, and elevated sedimentation rates emerged as significant prognostic indicators for OS (Table 3). In the multivariable analysis, ECOG PS ≥2 (HR, 8.13; 95% CI, 4.35-15.2; P < 0.001) and albumin levels <3.5 (HR, 2.1; 95% CI, 1.21-3.66; P = 0.008) were found to be independent factors associated with reduced OS. However, sarcopenia did not emerge as a significant prognostic factor for OS, with an adjusted HR of 1.24 (95% CI, 0.71-2.16; P = 0.432) (Table 3).

Figure 2.

Overall Survival Curve for Sarcopenic vs Non-Sarcopenic Patients (Kaplan-Meier).

Table 3.

Cox Regression Analysis Results for Overall Survival.

Variable (Reference)	Univariable		Multivariable
Variable (Reference)	HR (%95 GA)	P	HR (%95 GA)	P
Age (>60 years)	2.87 (1.52-5.42)	0.001	2.74 (1.58-4.74)	<0.001
Gender (female)	1.22 (0.60-2.46)	0.571	1.22 (0.64-2.32)	0.545
Sarcopenia (no sarcopenia)	1.17 (0.63-2.15)	0.614	1.24 (0.71-2.16)	0.432
ECOG PS ≥2 (0-1)	7.9 (4-15.6)	<0.001	8.13 (4.35-15.20)	<0.001
NLR >3.57 (≤3.57)	1.11 (0.62- 1.98)	0.707
PLR >190.8 (≤190.8)	1.46 (0.78-2.73)	0.111	1.22 (0.72-2.06)	0.442
Albumin<3.5 (≥3.5 g/dl)	2.25 (1.17-4.35)	0.015	2.10 (1.21-3.66)	0.008
LDH (higher than normal)	1.45 (0.81-2.61)	0.21
CRP (higher than normal)	1.5 (0.74-3.07)	0.261
Sedimentation (higher than normal)	2.21 (1.07-4.86)	0.048	1.65 (0.87-3.10)	0.120
BMI >25 (≤25)	1.02 (0.55-1.89)	0.947
Number of prior therapy>1 (≤1)	1.13 (0.66-1.94)	0.640	1.11 (0.65-2.90)	0.679

Abbreviations: HR: Hazard Ratio, CI: Confidence Interval, ECOG PS: Eastern Cooperative Oncology Group Performance Status, NLR: Neutrophil-To-Lymphocyte Ratio, PLR: Platelet-To-Lymphocyte Ratio, LDH: Lactate Dehydrogenase, CRP: C-Reactive Protein, BMI: Body Mass Index.

We established a composite model integrating the Eastern Cooperative Oncology Group Performance Status (ECOG PS) and sarcopenia status (Table 4).

Table 4.

Cox Regression Analysis Results for Progression-free Survival (PFS) Stratified by ECOG PS and Sarcopenia Status.

Variable (Ref.)	Univariable		Multivariable
Variable (Ref.)	HR (%95 CI)	P	HR (%95 CI)	P
Age (>60 years)	1.13 (0.72-1.78)	0.583	1.13 (0.72-1.79)	0.580
Gender (female)	1.31 (0.82-2.20)	0.229	1.30 (0.81-2.08)	0.269
ECOG 0-1 non-sarcopenic (group 1 ref.)
ECOG 0-1-sarcopenic (group 2)	2.18 (1.71-5.65)	0.023	2.14 (1.11-4.13)	0.022
ECOG ≥2 nonsarcopenic (group 3)	3.11 (1.71-5.65)	<0.001	3.31 (1.84-5.96)	<0.001
ECOG ≥2 sarcopenic (group 4)	7.56 (3.92-14.55)	<0.001	7.8 (4.12-14.84)	<0.001
Number of prior therapy>1 (≤1)	1.03 (0.67-1.59)	0.879	1.03 (0.67-1.59)	0.879

Abbreviations: HR: Hazard Ratio, CI: Confidence Interval, ECOG PS: Eastern Cooperative Oncology Group Performance Status.

In the multivariable analysis (MVA), Group 4 demonstrated a significantly shorter progression-free survival (PFS) (HR, 7.56; 95% CI, 3.92-14.55; P < 0.001) compared to Group 1. Similarly, both Group 2 and Group 3 exhibited shorter PFS as well (Group 2 HR, 2.14; CI, 1.11-4.13; P = 0.023; Group 3 HR, 3.31; CI, 1.84-5.96; P < 0.001) relative to Group 1. The Kaplan-Meier estimation indicated that the median PFS was longer for Group 1 (11.1 months) compared to Group 2 (3.9 months), Group 3 (3.9 months), and Group 4 (2.3 months) (P < 0.001).

Discussion

Our analysis unveiled that baseline sarcopenia independently predicted poor PFS. Conversely, although sarcopenic patients tended to have worse OS (log-rank test, P = 0.032), baseline sarcopenia did not demonstrate a statistically significant association with OS in multivariable analysis. Other factors included in the multivariable analysis may have influenced the OS results. Neither NLR nor PLR emerged as predictive factors for OS or PFS. Furthermore, albumin exhibited a significant association with OS prediction, while LDH emerged as an important prognostic indicator for PFS. Remarkably, our study, encompassing systemic inflammatory markers and sarcopenia, stands as one of the most comprehensive investigations in the existing literature.^9,24,25

Previous studies have demonstrated the association between sarcopenia and survival in ICI treatments.^9,19,26 Sarcopenia was significantly associated with worse OS and PFS in advanced-stage cancer treated with immunotherapy.⁹ Similarly, within our study, we observed a significant correlation between sarcopenia and reduced PFS in patients diagnosed with advanced urothelial carcinoma. However, this association did not extend to overall survival.¹⁹ It’s plausible that this observation may be attributed to factors such as the limited patient cohort and the inherent heterogeneity in various cancer groups. Furthermore, Petrova et al. highlighted that individuals affected by sarcopenia exhibit an elevated risk of hyperprogression along with diminished overall survival.²⁶

Our findings and prior research suggest a strong connection between skeletal muscle, the immune system, and chronic inflammation. Skeletal muscle cells regulate immune processes through IL-6, IL-7, and IL-15 cytokines. For example, IL-15 promotes the activation of NK and T cells, vital for enhancing antitumor responses, while IL-7 supports the development of immature lymphocytes and thymic function.^27,28 As in sarcopenia, reducing these cytokines may weaken immune systems and decrease effectiveness in responding to tumors.

Sarcopenia has been closely linked to chronic inflammation, which contributes to muscle breakdown via cytokines like IL-6 and TNF-α. It also induces T-cell exhaustion through the effects of cytokines such as TGF-β and IL-10, along with inhibitory receptors like PD-1 expressed on CD8⁺ T-cells.^29-33 CD8⁺ T-cells play a crucial role in tumor cell elimination, and their loss of function in chronic inflammation can significantly impair immune responses. Studies have demonstrated that PD-1 and IL-10 are critical factors in T-cell suppression and exhaustion, further inhibiting effective immune responses in tumor settings.^34-37 In addition, IL-6 promotes the expansion of immunosuppressive cells, including myeloid-derived suppressor cells (MDSCs) and T regulatory cells, further impairing the immune system’s ability to combat tumors. These cells suppress T-cell activity and contribute to tumor progression by remodeling the tumor microenvironment and promoting angiogenesis through factors such as VEGF and MMP-9.^38-45 Due to these complex interactions, sarcopenia significantly impacts the effectiveness of immune checkpoint inhibitors in cancer patients, potentially weakening the body’s ability to generate a robust antitumor immune response. Several studies show a relationship between sarcopenia and cancer treatment response. In light of the relationship between sarcopenia and cancer, many factors can contribute to sarcopenia in cancer patients. For instance, immunity to cancer-testis antigens (CTAs) may contribute to sarcopenia through immune-driven inflammation, which can lead to muscle wasting. In cancer patients, immune responses targeting CTAs might exacerbate sarcopenia by promoting catabolic pathways and impairing muscle protein synthesis. This immune activity, especially in the context of cancer cachexia, can further drive muscle loss and weakness.⁴⁶ In a study, sarcopenic patients with colorectal cancer have poorer PFS than the nonsarcopenic group (5-year PFS, 48.34 vs 58.80%, P = 0.003).⁴⁷ In another study, in locally advanced head and neck squamous cell carcinoma, sarcopenia serves as a potential biomarker for predicting prognosis and treatment-related side effects. Sarcopenia is associated with lower overall survival rates and more treatment-related side effects.⁴⁸ These results related to OS and PFS are consistent with our findings.

The systemic inflammatory markers we used—CRP, ESR, NLR, PLR, albumin, and LDH—were chosen for their broad clinical relevance, accessibility, and ability to reflect inflammation and immune response. CRP, ESR, and albumin measure acute and chronic inflammation, NLR and PLR assess immune balance, and LDH reflects tumor activity.⁴⁹ These markers allowed us to understand inflammation comprehensively and may reflect the response to cancer treatment. In research, a higher NLR ratio and increased NLR values under treatment are associated with lower survival in cancer patients.⁵⁰ Moreover, previous studies figured out that hypoalbuminemia is associated with a worse prognosis in cancer patients.^51-54 These results were similar to those of our research. Serum albumin is utilized as one of the prognostic indicators in patients with hepatocellular carcinoma and colorectal cancer with liver metastases.^55,56 Hypoalbuminemia’s implications might extend to encompass suboptimal nutritional status, chronic inflammation, and even the presence of liver metastases. Irrespective of the underlying triggers for hypoalbuminemia, all these factors collectively contribute to a diminished prognosis in patients with cancer.^56-60

ECOG PS is an important prognostic factor in cancer patients. ECOG PS not only reflects prognosis but also indicates the patient’s status regarding who can undergo cancer treatment. In a study, 257 patients treated with ICI were separated into two groups according to their ECOG PS status. The median OS is higher for ECOG PS 0-1 than for ECOG PS ≥2 (12.6 months and 3.1 months, respectively). This result is similar to our research. While the rationale for administering immunotherapy to patients with poor ECOG PS may seem justified, certain studies have presented evidence linking deteriorating ECOG PS to diminished immune responses.^61,62 Unfortunately, a reliable predictive model for gauging immunotherapy responses has yet to be discovered. However, by leveraging the combined predictive potential of ECOG PS and sarcopenia, we have formulated a predictive model capable of anticipating ICI responses before treatment initiation. Remarkably, patients grappling with both unfavorable ECOG PS and sarcopenia exhibit a marked inclination toward poorer prognoses, and this observation reached statistical significance (log-rank test, P < 0.001). This innovative model may provide oncologists a valuable tool for proactively anticipating ICI responses.

The first limitation of our study is the retrospective design, which may lead to selection bias. To avoid selection bias, we included all patients with clinical data and an abdominal CT, regardless of primary malignancies and baseline characteristics. Secondly, our cohort was heterogeneous, including melanoma, lung cancer, and renal carcinoma. This may affect our results. Furthermore, various cancer treatment patients were given additional interventions, such as steroids and antibiotics, at different points during their treatment. This may indirectly affect the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, CRP, and sedimentation rate. Unfortunately, the intricate interactions of these medications could not be fully accounted for in our analysis. In non-cancer patients, sarcopenia is generally considered a negative prognostic factor, and this observation extends to the population studied in this research.

Conclusion

In conclusion, baseline sarcopenia was an independent prognostic factor for PFS in patients treated with ICIs. Prevention of sarcopenia through physical activity and nutritional support in this group of patients may be an essential strategy to improve survival. Our composite model, which includes ECOG PS and sarcopenia status, may help predict responses to immunotherapy. Further prospective studies in sarcopenic cancer patients are needed to guide treatment options.

Footnotes

Author contributions

All authors contributed to the study's conception and design. Material preparation, data collection and analysis were performed by Enes Ucgul, Deniz Can Guven, Aybala Nur Ucgul and Serkan Akin. The first draft of the manuscript was written by Enes Ucgul, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical Statement

ORCID iD

Enes Ucgul

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Factors Influencing Immunotherapy Outcomes in Cancer: Sarcopenia and Systemic Inflammation

Abstract

Background

Methods

Results

Conclusions

Plain Language Summary

Keywords

Introduction

Methods

Statistics

Results

Efficacy

Discussion

Conclusion

Footnotes

Author contributions

Declaration of conflicting interests

Funding

Ethical Statement

ORCID iD

References