Body Composition Variables as Radiographic Biomarkers of Clinical Outcomes in Metastatic Renal Cell Carcinoma Patients Receiving Immune Checkpoint Inhibitors

Impact of body composition on outcomes of immune checkpoint inhibitor combination therapy in patients with previously untreated advanced renal cell carcinoma

BACKGROUND

Data on the association between body composition and outcomes in patients with advanced renal cell carcinoma (RCC) treated with immune checkpoint inhibitor (ICI) combination therapy are limited.

METHODS

We retrospectively evaluated the clinical and radiographic data of 159 patients with advanced RCC, including 84 receiving ICI dual combination therapy (immunotherapy [IO]-IO group) and 75 receiving combinations of ICIs with tyrosine kinase inhibitors (TKIs) (IO-TKI group). Pretreatment computed tomography images were used to calculate body composition, including skeletal muscle mass and fat tissue area. Sarcopenia was defined based on skeletal muscle and psoas muscle indexes. The total fat index, subcutaneous fat index (SFI), and visceral fat index were also calculated.

RESULTS

In the IO-IO treatment group, there was no significant association between body composition and survival or tumor response (P > 0.05). In the IO-TKI treatment group, the high SFI was associated with longer progression-free survival (hazard ratio, 2.70; P = 0.0091) and overall survival (hazard ratio, 26.0; P = 0.0246) than the low SFI, which remained significant after adjusting for covariates. Furthermore, in the high-SFI population, patients treated with IO-TKI therapy had longer progression-free survival (P = 0.0019) and overall survival (P = 0.0287) than those treated with IO-IO therapy, while there was no significant survival difference between the 2 treatment groups in the low-SFI population (P > 0.05).

CONCLUSION

The SFI can be potentially utilized as an effective predictive and prognostic biomarker for first-line ICI combination therapy for advanced RCC.

Prognostic Role of Pre-Treatment Body Composition Parameters in Patients Undergoing First-Line Immunotherapy for Metastatic Renal Cell Carcinoma

Purpose

We investigated the relationship between body mass index (BMI), radiological body composition, and survival outcomes in patients with metastatic renal cell carcinoma (mRCC) underwent first-line immune checkpoint inhibitor (ICI)-based therapy.

Methods

Analyzing data from 102 patients treated between November 2019 and March 2023, pre-treatment computed tomography (CT) scans assessed fat and muscle areas. BMI and body composition indices were examined, including skeletal muscle index, subcutaneous fat index (SFI), visceral fat index, and total fat index. Kaplan-Meier curves and Log rank tests compared progression-free survival (PFS) and overall survival (OS), while multivariable Cox proportional regression analysis was performed to identify the variables significantly associated with survival outcomes.

Results

54 patients (52.9%) experienced disease progression, and 26 (25.5%) died during a median follow-up of 17.4 months. High SFI was significantly associated with improved OS (p = 0.018) but not PFS (p = 0.090). Multivariable analysis confirmed the positive impact of high SFI on OS (adjusted HR: 0.37, p = 0.029) and suggested a trend towards improved PFS (adjusted HR: 0.61, p = 0.088). Notably, in the ipilimumab + nivolumab subgroup, high SFI significantly correlated with both PFS and OS (p = 0.047 and p = 0.012, respectively).

Conclusion

High SFI predicts favorable OS in patients with mRCC receiving first-line ICI-based therapy, especially patients treated with ipilimumab + nivolumab displayed a significant association between high SFI and favorable PFS and OS.

Impact of baseline body composition on prognostic outcomes in urological malignancies treated with immunotherapy: a pooled analysis of 10 retrospective studies

OBJECTIVE

Numerous epidemiological investigations have explored the impact of body composition on the effectiveness of immune checkpoint inhibitors (ICIs) in urological malignancies (UM) patients, yielding conflicting findings. As a result, our study aims to elucidate the influence of baseline body composition on the long-term prognosis of UM patients treated with ICIs.

METHODS

We employed a rigorous systematic search across various databases, including PubMed, Embase, the Cochrane Library, and Google Scholar, to identify studies meeting our inclusion criteria. Our primary endpoints of interest encompassed overall survival (OS) and progression-free survival (PFS).

RESULTS

This analysis included a total of 10 articles with a combined patient cohort of 707 individuals. Our findings revealed a noteworthy association between several body composition parameters and unfavorable OS outcomes, including low psoas muscle index (PMI; HR: 3.88, p < 0.001), low skeletal muscle index (SMI; HR: 1.63, p < 0.001), sarcopenia (HR: 1.88, p < 0.001), low visceral adipose index (VAI; HR: 1.38, p = 0.018) and low subcutaneous adipose index (SAI; HR: 1.37, p = 0.018). Furthermore, our analysis demonstrated that low PMI (HR: 2.05, p = 0.006), low SMI (HR: 1.89, p = 0.002), sarcopenia (HR: 1.80, p < 0.001), and low VAI (HR:1.59, p = 0.005) were significantly correlated with inferior PFS. Conversely, SAI did not manifest a pronounced association with PFS in UM patients treated with ICIs.

CONCLUSION

Collectively, our study findings underscore a substantial relationship between baseline body composition and reduced clinical efficacy in UM patients undergoing ICI therapy.

Established and emerging biomarkers of immunotherapy in renal cell carcinoma

Immunotherapies, such as immune checkpoint inhibitors, have heralded impressive progress for patient care in renal cell carcinoma (RCC). Despite this success, some patients' disease fails to respond, and other patients experience significant side effects. Thus, development of biomarkers is needed to ensure that patients can be selected to maximize benefit from immunotherapies. Improving clinicians' ability to predict which patients will respond to immunotherapy and which are most at risk of adverse events - namely through clinical biomarkers - is indispensable for patient safety and therapeutic efficacy. Accordingly, an evolving suite of therapeutic biomarkers continues to be investigated. This review discusses biomarkers for immunotherapy in RCC, highlighting current practices and emerging innovations, aiming to contribute to improved outcomes for patients with RCC.

Effect of sex-specific abdominal fat tissue composition on WHO/ISUP nuclear grade of clear cell renal cell carcinoma

Background/aim

To investigate the relationship between sex-related visceral obesity and WHO/ISUP nuclear grade in clear cell renal cell carcinoma (ccRCC).

Materials and methods

Between January 2018 and June 2022, 95 patients (56 men and 39 women) with pathologically proven ccRCC who underwent abdominal computed tomography examination were retrospectively examined. The patients were classified into two groups: low- and high-WHO/ISUP nuclear grade ccRCC (n = 58 and n = 37), respectively. Patient height, weight, body mass index (BMI), sex, age, subcutaneous fat area (SFA), visceral fat area (VFA), total fat area (TFA), and percentage of visceral fat (VF%) were recorded for the two groups.

Results

No significant differences were found in age, BMI, SFA, or TFA, but VFA and VF% were significantly higher in the high-grade patient group. In males, maximal tumor diameter (MTD) (67.8% sensitivity and 76.9% specificity) had the highest area under the curve (AUC), while in females, VF% (70.0% sensitivity and 73.7% specificity) had the highest AUC. VF% revealed an odds ratio (OR) of 1.09 in females with high-grade ccRCC, and in males, MTD was an independent predictor of ccRCC with an OR of 1.03.

Conclusions

Sex-related body fat tissue, including VFA and VF%, could be used for estimating WHO/ISUP nuclear grade in patients with ccRCC, especially in females.

Prognostic value of obesity in patients with cancer treated with immune checkpoint inhibitors: An updated meta‑analysis and systematic review

Accumulating interest has been surging over the past few years regarding the effects of obesity on immunotherapy. In addition to the body mass index (BMI), imaging-quantified body fat compartments have been investigated. The present study aimed to evaluate the predictive value of the BMI and computed tomography (CT)-based body fat in patients with cancer receiving immunotherapy. For this purpose, the PubMed, MEDLINE, EMBASE and Cochrane databases were searched from January 2017 to July 2022. Clinical studies evaluating the association between BMI or body fat and survival of patients with cancer treated with immune checkpoint inhibitors (ICIs) were included. In total, 15 studies reporting on the BMI were included in the meta-analysis and 16 studies evaluating body fat were included in the systematic review. According to the classification of the World Health Organization, overweight and obese patients with ICI treatment showed improved overall survival [overweight vs. normal: Hazard ratio (HR)=0.79, 95% confidence interval (CI)=0.64-0.98, P=0.03; obese vs. normal: HR=0.75, 95% CI=0.60-0.94, P=0.013] and progression-free survival (overweight vs. normal: HR=0.82, 95% CI=0.70-0.97, P=0.02; obese vs. normal: HR=0.81, 95% CI=0.65-1.02, P=0.07). Among the articles investigating the effect of body fat composition on the efficacy of immunotherapy, a number of studies included various CT analysis techniques and cutoffs to define body fat composition. Associations of body fat with survival were contradictory in different patients with cancer treated with immunotherapy. Obesity was associated with better survival in patients with cancer treated with ICIs. Further analyses are required to demonstrate the prognostic value of body fat in patients with cancer immunotherapy.

Relationship Between Pretreatment Body Composition and Clinical Outcomes in Patients With Metastatic Renal Cell Carcinoma Receiving First-Line Ipilimumab Plus Nivolumab

INTRODUCTION

Biomarkers are needed to identify patients with metastatic renal cell carcinoma (mRCC) most likely to benefit from immune checkpoint inhibitors. We examined associations between radiographically assessed body composition (BC) variables and body mass index (BMI) with clinical outcomes for patients with mRCC receiving first-line ipilimumab + nivolumab (ipi/nivo).

PATIENTS AND METHODS

We retrospectively reviewed all patients with mRCC treated with first-line ipi/nivo at one institution before June 1, 2021 with an analyzable baseline computed tomography (CT) scan. BC variables (skeletal muscle index [SMI], subcutaneous adipose tissue index [SATI], and visceral adipose tissue index [VATI]) were measured using baseline CT scans. Relationships between BC variables and clinical outcomes were examined using Cox proportional hazard regression models.

RESULTS

Ninety-nine patients were analyzed (74% male, 64% overweight/obese, 75% low SMI). Controlling for age, IMDC risk, and sex (for BMI analyses), high vs. low SMI (HR=2.433, CI: 1.397-4.238, P=.0017), high vs. low SATI (HR=1.641, CI: 1.023-2.632, P=.0398), and obese BMI (≥ 30 kg/m2) vs. normal/overweight BMI (<30 kg/m2) (HR=1.859, CI: 1.156-2.989, P=.0105) were significantly associated with progression-free survival (PFS). Median overall survival (OS) for low SMI patients was higher (42.74 months, CI: 26.84, NR) than median OS for high SMI patients (27.01 months, CI: 15.28, NR) (adjusted HR=1.728, CI: 0.909-3.285, P=.0952). No BC variables were significantly associated with OS or objective response rate.

CONCLUSIONS

Low SMI and low SATI were associated with significantly better PFS for patients with mRCC receiving first-line ipi/nivo. Radiographic BC variables may be useful prognostic biomarkers in this setting.

Imaging-based adipose biomarkers for predicting clinical outcomes of cancer patients treated with immune checkpoint inhibitors: a systematic review

Background

Since the application of Immune checkpoint inhibitors (ICI), the clinical outcome for metastatic cancer has been greatly improved. Nevertheless, treatment response varies in patients, making it urgent to identify patients who will receive clinical benefits after ICI therapy. Adipose body composition has proved to be associated with tumor response. In this systematic review, we aimed to summarize the current evidence on imaging adipose biomarkers that predict clinical outcomes in patients treated with ICI in various cancer types.

Methods

Embase and PubMed were searched from database inception to 1st February 2023. Articles included investigated the association between imaging-based adipose biomarkers and the clinical outcomes of patients treated with ICI. The methodological quality of included studies was evaluated through Newcastle- Ottawa Quality Assessment Scale and Radiomics Quality Score tools.

Results

Totally, 22 studies including 2256 patients were selected. Non-small cell lung cancer (NSCLC) had the most articles (6 studies), followed by melanoma (5 studies), renal cell carcinoma (RCC) (3 studies), urothelial carcinoma (UC) (2 studies), head and neck squamous cell carcinoma (HNSCC) (1 study), gastric cancer (1 study) and liver cancer (1 study). The remaining 3 studies investigated metastatic solid tumors including various types of cancers. Adipose biomarkers can be summarized into 5 categories, including total fat, visceral fat, subcutaneous fat, intramuscular fat and others, which exerted diverse correlations with patients' prognosis after being treated with ICI in different cancers. Most biomarkers of body fat were positively associated with survival benefits. Nevertheless, more total fat was predictable of worse outcomes in NSCLC, while inter-muscular fat was associated with poor clinical benefits in UC.

Conclusion

There is relatively well-supported evidence for imaging-based adipose biomarkers to predict the clinical outcome of ICI. In general, most of the studies show that adipose tissue is positively correlated with clinical outcomes. This review summarizes the significant biomarkers proven by researches for each cancer type. Further validation and large independent prospective cohorts are needed in the future. The protocol of this systematic review has been registered at the International Prospective Register of Systematic Reviews (http://www.crd.york.ac.uk/PROSPERO, registration no: CRD42023401986).

Comprehensive Systematic Review of Biomarkers in Metastatic Renal Cell Carcinoma: Predictors, Prognostics, and Therapeutic Monitoring

BACKGROUND

Challenges remain in determining the most effective treatment strategies and identifying patients who would benefit from adjuvant or neoadjuvant therapy in renal cell carcinoma. The objective of this review is to provide a comprehensive overview of biomarkers in metastatic renal cell carcinoma (mRCC) and their utility in prediction of treatment response, prognosis, and therapeutic monitoring in patients receiving systemic therapy for metastatic disease.

METHODS

A systematic literature search was conducted using the PubMed database for relevant studies published between January 2017 and December 2022. The search focused on biomarkers associated with mRCC and their relationship to immune checkpoint inhibitors, targeted therapy, and VEGF inhibitors in the adjuvant, neoadjuvant, and metastatic settings.

RESULTS

The review identified various biomarkers with predictive, prognostic, and therapeutic monitoring potential in mRCC. The review also discussed the challenges associated with anti-angiogenic and immune-checkpoint monotherapy trials and highlighted the need for personalized therapy based on molecular signatures.

CONCLUSION

This comprehensive review provides valuable insights into the landscape of biomarkers in mRCC and their potential applications in prediction of treatment response, prognosis, and therapeutic monitoring. The findings underscore the importance of incorporating biomarker assessment into clinical practice to guide treatment decisions and improve patient outcomes in mRCC.

Impact of body composition for patients with hepatocellular carcinoma who received atezolizumab plus bevacizumab therapy

OBJECTIVE

To investigate the association between body composition and prognosis in patients with advanced hepatocellular carcinoma treated with atezolizumab plus bevacizumab.

METHODS

This cohort study analysed 119 patients who received atezolizumab plus bevacizumab for unresectable hepatocellular carcinoma. We investigated the association between body composition and progression-free survival and overall survival. Body composition was quantified by the visceral fat index, subcutaneous fat index, and skeletal muscle index. A high or low index score was defined as that above or below the median of these indices.

RESULTS

Poor prognosis was observed in the low visceral fat index and low subcutaneous fat index groups. The mean progression-free survival in the low visceral fat index and low subcutaneous fat index groups vs. the other groups were 194 and 270 days, respectively [95% confidence interval (CI), 153-236 and 230-311 days, respectively; P = 0.015], while the mean overall survival was 349 vs. 422 days, respectively (95% CI, 302-396 and 387-458 days, respectively; P = 0.027). In the multivariate analysis, both a low subcutaneous fat index and low visceral fat index were statistically associated with lower progression-free and overall survival rates [hazard ratio (HR) 1.721; 95% CI, 1.101-2.688; P = 0.017; and HR 2.214; 95% CI, 1.207-4.184; P = 0.011, respectively].

CONCLUSION

Low visceral fat index and subcutaneous fat index scores were independent predictors of poor prognosis in patients with unresectable hepatocellular carcinoma treated with atezolizumab plus bevacizumab.

Obesity Measured via Body Mass Index May Be Associated with Increased Incidence but Not Worse Outcomes of Immune-Mediated Diarrhea and Colitis

Obesity defined by high body mass index (BMI) has traditionally been associated with gastrointestinal inflammatory processes but has recently been correlated with better survival in patients receiving immune checkpoint inhibitors (ICI). We sought to investigate the association between BMI and immune-mediated diarrhea and colitis (IMDC) outcomes and whether BMI reflects body fat content on abdominal imaging. This retrospective, single-center study included cancer patients with ICI exposure who developed IMDC and had BMI and abdominal computed tomography (CT) obtained within 30 days before initiating ICI from April 2011 to December 2019. BMI was categorized as <25, ≥25 but <30, and ≥30. Visceral fat area (VFA), subcutaneous fat area (SFA), total fat area (TFA: VFA+SFA), and visceral to subcutaneous fat (V/S) ratio were obtained from CT at the umbilical level. Our sample comprised 202 patients; 127 patients (62.9%) received CTLA-4 monotherapy or a combination, and 75 (37.1%) received PD-1/PD-L1 monotherapy. Higher BMIs ≥ 30 were associated with a higher incidence of IMDC than BMIs ≤ 25 (11.4% vs. 7.9%, respectively; p = 0.029). Higher grades of colitis (grade 3-4) correlated with lower BMI (p = 0.03). BMI level was not associated with other IMDC characteristics or did not influence overall survival (p = 0.83). BMI is strongly correlated with VFA, SFA, and TFA (p < 0.0001). Higher BMI at ICI initiation was linked to a higher incidence of IMDC but did not appear to affect outcomes. BMI strongly correlated with body fat parameters measured by abdominal imaging, suggesting its reliability as an obesity index.

Baseline Neutrophil-to-Eosinophil Ratio Is Associated with Outcomes in Metastatic Renal Cell Carcinoma Treated with Immune Checkpoint Inhibitors

BACKGROUND

Biomarkers have the potential to guide treatment selection and clinical care in metastatic renal cell carcinoma (mRCC) in an expanding treatment landscape. We report baseline neutrophil-to-eosinophil ratios (NER) in patients with mRCC treated with immune checkpoint inhibitors (CPIs) and their association with clinical outcomes.

METHODS

We conducted a retrospective review of patients with mRCC treated with CPIs at Winship Cancer Institute from 2015 to 2020 in the United States of America (USA). Demographics, disease characteristics, and laboratory data, including complete blood counts (CBC) were described at the initiation of CPIs. Clinical outcomes were measured as overall survival (OS), progression-free survival (PFS), and clinical benefit (CB) associated with baseline lab values.

RESULTS

A total of 184 patients were included with a median follow-up time of 25.4 months. Patients with baseline NER were categorized into high or low subgroups; high group was defined as NER >49.2 and low group was defined as NER <49.2 with 25% of patients in the high NER group. Univariate analyses (UVA) and multivariable analyses (MVA) identified decreased overall survival (OS) associated with elevated NER. In MVA, patients with a high baseline NER group had a hazard ratio (HR) of 1.68 (95%CI, 1.01-2.82, P = .048) for OS; however, there was no significant difference between groups for PFS. Clinical benefit was seen in 47.3% of patients with low baseline NER and 40% with high NER.

CONCLUSIONS

We conclude that elevated baseline NER may be associated with worse clinical outcomes in mRCC. Although results require further validation, NER is a feasible biomarker in patients with CPI-treated mRCC.

Predictive genomic tools in disease stratification and targeted prevention: a recent update in personalized therapy advancements

In the current era of medical revolution, genomic testing has guided the healthcare fraternity to develop predictive, preventive, and personalized medicine. Predictive screening involves sequencing a whole genome to comprehensively deliver patient care via enhanced diagnostic sensitivity and specific therapeutic targeting. The best example is the application of whole-exome sequencing when identifying aberrant fetuses with healthy karyotypes and chromosomal microarray analysis in complicated pregnancies. To fit into today's clinical practice needs, experimental system biology like genomic technologies, and system biology viz., the use of artificial intelligence and machine learning is required to be attuned to the development of preventive and personalized medicine. As diagnostic techniques are advancing, the selection of medical intervention can gradually be influenced by a person's genetic composition or the cellular profiling of the affected tissue. Clinical genetic practitioners can learn a lot about several conditions from their distinct facial traits. Current research indicates that in terms of diagnosing syndromes, facial analysis techniques are on par with those of qualified therapists. Employing deep learning and computer vision techniques, the face image assessment software DeepGestalt measures resemblances to numerous of disorders. Biomarkers are essential for diagnostic, prognostic, and selection systems for developing personalized medicine viz. DNA from chromosome 21 is counted in prenatal blood as part of the Down's syndrome biomarker screening. This review is based on a detailed analysis of the scientific literature via a vigilant approach to highlight the applicability of predictive diagnostics for the development of preventive, targeted, personalized medicine for clinical application in the framework of predictive, preventive, and personalized medicine (PPPM/3 PM). Additionally, targeted prevention has also been elaborated in terms of gene-environment interactions and next-generation DNA sequencing. The application of 3 PM has been highlighted by an in-depth analysis of cancer and cardiovascular diseases. The real-time challenges of genome sequencing and personalized medicine have also been discussed.

Associations between Pretreatment Body Composition Features and Clinical Outcomes among Patients with Metastatic Clear Cell Renal Cell Carcinoma Treated with Immune Checkpoint Blockade

PURPOSE

High body mass index (BMI) may lead to improved immune-checkpoint blockade (ICB) outcomes in metastatic clear cell renal cell carcinoma (mccRCC). However, BMI is a crude body size measure. We investigated BMI and radiographically assessed body composition (BC) parameters association with mccRCC ICB outcomes.

EXPERIMENTAL DESIGN

Retrospective study of ICB-treated patients with mccRCC. BMI and BC variables [skeletal muscle index (SMI) and multiple adiposity indexes] were determined using pretreatment CT scans. We examined the associations between BMI and BC variables with ICB outcomes. Therapeutic responses per RECIST v1.1 were determined. We compared whole-transcriptomic patterns with BC variables in a separate cohort of 62 primary tumor samples.

RESULTS

205 patients with mccRCC were included in the cohort (74% were male, 71% were overweight/obese, and 53% were classified as low SMI). High-BMI patients experienced longer overall survival (OS) than normal-weight patients [unadjusted HR, 0.66; 95% confidence interval (CI), 0.45-0.97; P = 0.035]. The only BC variable associated with OS was SMI [unadjusted HR comparing low vs. high SMI 1.65 (95% CI: 1.13-2.43); P = 0.009]. However, this OS association became nonsignificant after adjusting for International Metastatic Renal Cell Carcinoma Database Consortium score and line of therapy. No OS association was seen for adiposity and no BC variable was associated with progression-free survival or radiological responses. Tumors from patients with low SMI displayed increased angiogenic, inflammatory, and myeloid signals.

CONCLUSIONS

Our findings highlight the relevance of skeletal muscle in the BMI paradox. Future studies should investigate if addressing low skeletal muscle in metastatic patients treated with ICB can improve survival.

Imaging to predict checkpoint inhibitor outcomes in cancer. A systematic review

BACKGROUND

Checkpoint inhibition has radically improved the perspective for patients with metastatic cancer, but predicting who will not respond with high certainty remains difficult. Imaging-derived biomarkers may be able to provide additional insights into the heterogeneity in tumour response between patients. In this systematic review, we aimed to summarise and qualitatively assess the current evidence on imaging biomarkers that predict response and survival in patients treated with checkpoint inhibitors in all cancer types.

METHODS

PubMed and Embase were searched from database inception to 29th November 2021. Articles eligible for inclusion described baseline imaging predictive factors, radiomics and/or imaging machine learning models for predicting response and survival in patients with any kind of malignancy treated with checkpoint inhibitors. Risk of bias was assessed using the QUIPS and PROBAST tools and data was extracted.

RESULTS

In total, 119 studies including 15,580 patients were selected. Of these studies, 73 investigated simple imaging factors. 45 studies investigated radiomic features or deep learning models. Predictors of worse survival were (i) higher tumour burden, (ii) presence of liver metastases, (iii) less subcutaneous adipose tissue, (iv) less dense muscle and (v) presence of symptomatic brain metastases. Hazard rate ratios did not exceed 2.00 for any predictor in the larger and higher quality studies. The added value of baseline fluorodeoxyglucose positron emission tomography parameters in predicting response to treatment was limited. Pilot studies of radioactive drug tracer imaging showed promising results. Reports on radiomics were almost unanimously positive, but numerous methodological concerns exist.

CONCLUSIONS

There is well-supported evidence for several imaging biomarkers that can be used in clinical decision making. Further research, however, is needed into biomarkers that can more accurately identify which patients who will not benefit from checkpoint inhibition. Radiomics and radioactive drug labelling appear to be promising approaches for this purpose.

Association between sarcopenia based on psoas muscle index and the response to nivolumab in metastatic renal cell carcinoma: A retrospective study

Purpose

Two methods are used to identify sarcopenia by calculating skeletal muscle area on computed tomography: the skeletal muscle index (SMI) and the psoas muscle index (PMI). Programmed death (PD)-1 inhibitors are helpful in treating metastatic renal cell carcinoma (mRCC). However, there remains insufficient information regarding a clear and easy-to-use biomarker for predicting the response to PD-1 inhibitors in patients with mRCC. Therefore, we investigated the influence of sarcopenia on clinical outcomes in patients with mRCC undergoing treatment with nivolumab.

Materials and Methods

This study evaluated 96 patients with RCC who received nivolumab. The SMI and PMI were calculated for each patient and normalized for stature by use of the following formulas: SMI (cm²/m²)=([skeletal muscle cross-sectional area at the level of L3]/[height]²) and PMI (cm²/m²) = ([left-right sum of the psoas muscle areas at the level of L3]/[height]²). The relationship of the clinical variables with progression-free survival and overall survival (OS) was examined using a Cox proportional hazards model.

Results

According to the SMI-based definition of sarcopenia, 74.0% of patients had sarcopenia. However, according to the PMI-based definition of sarcopenia, only 34.3% of patients were diagnosed with sarcopenia. Multivariate analysis identified sarcopenia based on PMI (hazard ratio [HR], 3.85; 95% confidence interval [CI], 2.04–7.26; p<0.001) and International Metastatic RCC Database Consortium poor risk status (HR, 1.90; 95% CI, 1.03–3.50; p=0.041) as significant and independent prognostic factors of OS.

Conclusions

PMI-based sarcopenia is a significant prognostic factor for OS in patients with RCC who receive nivolumab therapy.

Skeletal muscle radiodensity and visceral adipose tissue index are associated with survival in renal cell cancer - A multicenter population-based cohort study

INTRODUCTION

Body composition has been associated with disease outcome in several cancer types. Results for localized and metastatic renal cell cancer (RCC) are limited and inconsistent. Our aim was to examine the association between body composition and survival in RCC.

METHODS

We conducted a population-based historical cohort study including patients diagnosed with RCC from 2008 to 2012. Diagnostic Computed Tomography images at the third lumbar vertebra (L3) were assessed for skeletal muscle index (SMI), skeletal muscle density (SMD), visceral adipose tissue index (VATI) and subcutaneous adipose tissue index (SATI). Clinical data was retrieved from medical records. Multivariable Cox regressions with restricted cubic splines were used to determine hazard ratios (HRs) and 95% confidence intervals (95%CIs) for 10-unit increases in body composition features with overall survival (OS) and recurrence-free survival (RFS).

RESULTS

We included 719 stage I-III (of whom 254 (35.3%) died and 148 (21.9%) experienced recurrence) and 320 stage IV RCC patients (of whom 298 (93.1%) died). Median follow-up was 6.35 years (interquartile range; 1.41-8.23). For stage I-III, higher SMD was associated with better OS (men: HR 0.86; 95% CI 0.68-1.08; women: HR 0.69; 95% CI 0.50-0.95). Lower compared to median VATI was associated with worse OS for both men (HR 1.38; 95%CI 1.05-1.83 for VATI = 25) and women (HR 1.67; 95%CI 1.01-2.78 for VATI = 20). For stage IV, higher SMD and higher VATI were associated with better OS among men (HR 0.74; 95% CI 0.59-0.94 and HR 0.93; 95% CI 0.88-0.99, respectively). Results for women were similar but non-significant. No statistically significant associations were found for SMI or SATI.

CONCLUSION

Higher SMD and higher VATI were marginally associated with better survival in RCC patients and might be useful for better prognostication. However, the added value to current prognostic scores needs to be investigated.