Sub-cutaneous Fat Mass measured on multislice computed tomography of pretreatment PET/CT is a prognostic factor of stage IV non-small cell lung cancer treated by nivolumab

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.

The Influence of Obesity on Outcomes with Immune Checkpoint Blockade: Clinical Evidence and Potential Biological Mechanisms

Immune checkpoint blockade (ICB) is a mainstay of treatment for advanced cancer, yet tumor response and host toxicity are heterogenous in those patients who receive ICB. There is growing interest in understanding how host factors interact with tumor intrinsic properties and the tumor microenvironment to influence the therapeutic index with ICB. Obesity, defined by body mass index, is a host factor associated with improved outcomes in select cancers when treated with ICB. While the biological mechanism for this obesity paradox is not fully understood, pre-clinical and translational studies suggest obesity may potentially impact tumor metabolism, inflammation, and angiogenesis. Herein, we summarize clinical studies that support an obesity paradox with ICB, explore potential biological mechanisms that may account for the obesity paradox, and address methodological challenges to consider when studying obesity and treatment outcomes.

Prognostic utility of body composition parameters based on computed tomography analysis of advanced non-small cell lung cancer treated with immune checkpoint inhibitors

OBJECTIVE

The purpose of this study was to evaluate the prognostic impact of body composition parameters based on computed tomography (CT) in patients with non-small cell lung cancer (NSCLC) who received ICI treatment.

METHODS

This retrospective study analyzed the data from advanced NSCLC patients treated with ICI therapy between 2013 and 2019. We included patients with NSCLC who underwent baseline CT scans. The exclusion criteria included patients who received three or more lines of chemotherapy, those with insufficient clinical information, or those without treatment response evaluation.

RESULTS

A total of 136 patients were enrolled. Among the volumetric body composition parameters, patients in the highest quartiles (Q2-4) of the visceral fat index (VFI) exhibited a higher response rate to ICI therapy than those in the lowest quartile (Q1) of VFI (Q1 vs. Q2-4: 18.2% vs. 43.1%, p = 0.012). Patients with a VFI in Q2-4 had significantly prolonged progression-free survival (PFS) and overall survival (OS) (PFS, Q1 vs. Q2-4: 3.0 months vs. 6.4 months, p = 0.043; OS, Q1 vs. Q2-4: 5.6 months vs. 16.3 months, p = 0.004). Kaplan-Meier analysis based on the VFI and visceral fat Hounsfield unit (HU) revealed that patients with VFI in Q1 and HU in Q2-4 had the worst prognosis.

CONCLUSIONS

Visceral fat volume is significantly associated with treatment outcomes in ICI-treated patients with NSCLC. Moreover, fat quality may impact the treatment outcomes. This finding underscores the potential significance of both fat compartments and fat quality as prognostic indicators.

CRITICAL RELEVANCE STATEMENT

Visceral fat volume is significantly associated with treatment outcomes in ICI-treated patients with non-small cell lung cancer. Moreover, fat quality may impact the treatment outcomes. This finding underscores the potential significance of both fat compartments and fat quality as prognostic indicators.

KEY POINTS

• We found that visceral fat volume positively correlated with treatment response and survival in patients with non-small cell lung cancer receiving immune checkpoint inhibitors. • Additionally, a trend toward a negative correlation between visceral fat attenuation and survival was observed. • The findings highlight the prognostic utility of fat compartments and fat quality.

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).

Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer

BACKGROUND

Our aim was to explore the prognostic value of anthropometric parameters in a large population of patients treated with immunotherapy.

METHODS

We retrospectively included 623 patients with advanced non-small cell lung cancer (NSCLC) (n=318) or melanoma (n=305) treated by an immune-checkpoint-inhibitor having a pretreatment (thorax-)abdomen-pelvis CT scan. An external validation cohort of 55 patients with NSCLC was used. Anthropometric parameters were measured three-dimensionally (3D) by a deep learning software (Anthropometer3DNet) allowing an automatic multislice measurement of lean body mass, fat body mass (FBM), muscle body mass (MBM), visceral fat mass (VFM) and sub-cutaneous fat mass (SFM). Body mass index (BMI) and weight loss (WL) were also retrieved. Receiver operator characteristic (ROC) curve analysis was performed and overall survival was calculated using Kaplan-Meier (KM) curve and Cox regression analysis.

RESULTS

In the overall cohort, 1-year mortality rate was 0.496 (95% CI: 0.457 to 0.537) for 309 events and 5-year mortality rate was 0.196 (95% CI: 0.165 to 0.233) for 477 events. In the univariate Kaplan-Meier analysis, prognosis was worse (p<0.001) for patients with low SFM (<3.95 kg/m2), low FBM (<3.26 kg/m2), low VFM (<0.91 kg/m2), low MBM (<5.85 kg/m2) and low BMI (<24.97 kg/m2). The same parameters were significant in the Cox univariate analysis (p<0.001) and, in the multivariate stepwise Cox analysis, the significant parameters were MBM (p<0.0001), SFM (0.013) and WL (0.0003). In subanalyses according to the type of cancer, all body composition parameters were statistically significant for NSCLC in ROC, KM and Cox univariate analysis while, for melanoma, none of them, except MBM, was statistically significant. In multivariate Cox analysis, the significant parameters for NSCLC were MBM (HR=0.81, p=0.0002), SFM (HR=0.94, p=0.02) and WL (HR=1.06, p=0.004). For NSCLC, a KM analysis combining SFM and MBM was able to separate the population in three categories with the worse prognostic for the patients with both low SFM (<5.22 kg/m2) and MBM (<6.86 kg/m2) (p<0001). On the external validation cohort, combination of low SFM and low MBM was pejorative with 63% of mortality at 1 year versus 25% (p=0.0029).

CONCLUSIONS

3D measured low SFM and MBM are significant prognosis factors of NSCLC treated by immune checkpoint inhibitors and can be combined to improve the prognostic value.

Body composition and lung cancer-associated cachexia in TRACERx

Cancer-associated cachexia (CAC) is a major contributor to morbidity and mortality in individuals with non-small cell lung cancer. Key features of CAC include alterations in body composition and body weight. Here, we explore the association between body composition and body weight with survival and delineate potential biological processes and mediators that contribute to the development of CAC. Computed tomography-based body composition analysis of 651 individuals in the TRACERx (TRAcking non-small cell lung Cancer Evolution through therapy (Rx)) study suggested that individuals in the bottom 20th percentile of the distribution of skeletal muscle or adipose tissue area at the time of lung cancer diagnosis, had significantly shorter lung cancer-specific survival and overall survival. This finding was validated in 420 individuals in the independent Boston Lung Cancer Study. Individuals classified as having developed CAC according to one or more features at relapse encompassing loss of adipose or muscle tissue, or body mass index-adjusted weight loss were found to have distinct tumor genomic and transcriptomic profiles compared with individuals who did not develop such features. Primary non-small cell lung cancers from individuals who developed CAC were characterized by enrichment of inflammatory signaling and epithelial-mesenchymal transitional pathways, and differentially expressed genes upregulated in these tumors included cancer-testis antigen MAGEA6 and matrix metalloproteinases, such as ADAMTS3. In an exploratory proteomic analysis of circulating putative mediators of cachexia performed in a subset of 110 individuals from TRACERx, a significant association between circulating GDF15 and loss of body weight, skeletal muscle and adipose tissue was identified at relapse, supporting the potential therapeutic relevance of targeting GDF15 in the management of CAC.

Survival and immunotoxicities in association with sex-specific body composition patterns of cancer patients undergoing immune-checkpoint inhibitor therapy - A systematic review and meta-analysis

BACKGROUND

Imbalanced body composition is mechanistically connected to dysregulated immune activities. Whether overweight/obesity or sarcopenia has an impact on treatment results in cancer patients undergoing immune checkpoint inhibitor (ICI) therapy is currently under debate. We aimed to answer if survival rates and occurrence of immune-related adverse events (irAEs) were different in obese or sarcopenic patients.

METHODS

A systematic search was conducted in PubMed, Embase and CENTRAL for all records published until July 2022 using specific search terms for body composition in combination with terms for ICI regimens. Two authors screened independently. All studies that reported on body mass index or sarcopenia measures were selected for further analysis.

RESULTS

48 studies reporting on overweight/obesity comprising of 19,767 patients, and 32 studies reporting on sarcopenia comprising of 3193 patients fulfilled the inclusion criteria. In the entire cohort, overweight/obesity was significantly associated with better progression-free survival (PFS; p = 0.009) and overall survival (OS; p <0.00001). Subgroup analyses stratified by sex revealed that overweight/obese males had the strongest survival benefit (PFS: p = 0.05; OS: p = 0.0005), and overweight/obese female patients did not show any. However, overweight/obese patients of both sexes had a higher risk to develop irAEs grade ≥3 (p = 0.0009). Sarcopenic patients showed significantly shorter PFS (p <0.0001) and OS (p <0.0001). The frequency of irAEs did not differ between sarcopenic and non-sarcopenic patients.

CONCLUSION

This meta-analysis suggests that body composition is associated in a sex-specific manner with survival and irAEs in cancer patients undergoing ICI treatment.

Body Composition to Define Prognosis of Cancers Treated by Anti-Angiogenic Drugs

Background: Body composition could help to better define the prognosis of cancers treated with anti-angiogenics. The aim of this study is to evaluate the prognostic value of 3D and 2D anthropometric parameters in patients given anti-angiogenic treatments. Methods: 526 patients with different types of cancers were retrospectively included. The software Anthropometer3DNet was used to measure automatically fat body mass (FBM3D), muscle body mass (MBM3D), visceral fat mass (VFM3D) and subcutaneous fat mass (SFM3D) in 3D computed tomography. For comparison, equivalent two-dimensional measurements at the L3 level were also measured. The area under the curve (AUC) of the receiver operator characteristics (ROC) was used to determine the parameters’ predictive power and optimal cut-offs. A univariate analysis was performed using Kaplan−Meier on the overall survival (OS). Results: In ROC analysis, all 3D parameters appeared statistically significant: VFM3D (AUC = 0.554, p = 0.02, cutoff = 0.72 kg/m2), SFM3D (AUC = 0.544, p = 0.047, cutoff = 3.05 kg/m2), FBM3D (AUC = 0.550, p = 0.03, cutoff = 4.32 kg/m2) and MBM3D (AUC = 0.565, p = 0.007, cutoff = 5.47 kg/m2), but only one 2D parameter (visceral fat area VFA2D AUC = 0.548, p = 0.034). In log-rank tests, low VFM3D (p = 0.014), low SFM3D (p < 0.0001), low FBM3D (p = 0.00019) and low VFA2D (p = 0.0063) were found as a significant risk factor. Conclusion: automatic and 3D body composition on pre-therapeutic CT is feasible and can improve prognostication in patients treated with anti-angiogenic drugs. Moreover, the 3D measurements appear to be more effective than their 2D counterparts.

Emerging and Evolving Concepts in Cancer Immunotherapy Imaging

Criteria based on measurements of lesion diameter at CT have guided treatment with historical therapies due to the strong association between tumor size and survival. Clinical experience with immune checkpoint modulators shows that editing immune system function can be effective in various solid tumors. Equally, novel immune-related phenomena accompany this novel therapeutic paradigm. These effects of immunotherapy challenge the association of tumor size with response or progression and include risks and adverse events that present new demands for imaging to guide treatment decisions. Emerging and evolving approaches to immunotherapy highlight further key issues for imaging evaluation, such as dissociated response following local administration of immune checkpoint modulators, pseudoprogression due to immune infiltration in the tumor environment, and premature death due to hyperprogression. Research that may offer tools for radiologists to meet these challenges is reviewed. Different modalities are discussed, including immuno-PET, as well as new applications of CT, MRI, and fluorodeoxyglucose PET, such as radiomics and imaging of hematopoietic tissues or anthropometric characteristics. Multilevel integration of imaging and other biomarkers may improve clinical guidance for immunotherapies and provide theranostic opportunities.

Volumetric parameters of the primary tumor and whole-body tumor burden derived from baseline 18F-FDG PET/CT can predict overall survival in non-small cell lung cancer patients: initial results from a single institution

BACKGROUND

Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) are volumetric parameters derived from ¹⁸F-FDG PET/CT, suggested to have a prognostic value in cancer patients. Our study aimed to test whether these volumetric parameters of the primary tumor and whole-body tumor burden (WBTB) can predict overall survival (OS) in non-small cell lung cancer (NSCLC) patients.

MATERIALS AND METHODS

Thirty biopsy-proven NSCLC patients who had not begun anti-tumor therapy were included in this prospective study. A baseline ¹⁸F-FDG PET/CT study was acquired. Scans were interpreted visually and semi-quantitatively by drawing a 3D volume of interest (VOI) over the primary tumor and all positive lesions to calculate metabolic, volumetric parameters, and WBTB. The PET parameters were used to stratify patients into high- and low-risk categories. The overall survival was estimated from the date of scanning until the date of death or last follow-up.

RESULTS

At a median follow-up of 22.73 months, the mean OS was shorter among patients with higher tu MTV and tu TLG and high WBTB. High WB TLG was independently associated with the risk of death (p < 0.025). Other parameters, e.g., SUV_max, SUV_peak, and SUV_mean, were not predictive of outcomes in these patients.

CONCLUSION

In patients with NSCLC, tu MTV, tu TLG, and WBTB determined on initial staging ¹⁸F-FDG PET/CT seems to be a strong, independent imaging biomarker to predict OS, superior to the clinical assessment of the primary tumor. The WB TLG was found to be the best predictor of OS.

Adiposity and cancer survival: a systematic review and meta-analysis

PURPOSE

The increasing availability of clinical imaging tests (especially CT and MRI) that directly quantify adipose tissue has led to a rapid increase in studies examining the relationship of visceral, subcutaneous, and overall adiposity to cancer survival. To summarize this emerging body of literature, we conducted a systematic review and meta-analysis of imaging-measured as well as anthropometric proxies for adipose tissue distribution and cancer survival across a wide range of cancer types.

METHODS

Using keywords related to adiposity, cancer, and survival, we conducted a systematic search of the literature in PubMed and MEDLINE, Embase, and Web of Science Core Collection databases from database inception to 30 June 2021. We used a random-effect method to calculate pooled hazard ratios (HR) and corresponding 95% confidence intervals (CI) within each cancer type and tested for heterogeneity using Cochran's Q test and the I2 test.

RESULTS

We included 203 records for this review, of which 128 records were utilized for quantitative analysis among 10 cancer types: breast, colorectal, gastroesophageal, head and neck, hepatocellular carcinoma, lung, ovarian, pancreatic, prostate, and renal cancer. We found that imaging-measured visceral, subcutaneous, and total adiposity were not significantly associated with increased risk of overall mortality, death from primary cancer, or cancer progression among patients diagnosed with these 10 cancer types; however, we found significant or high heterogeneity for many cancer types. For example, heterogeneity was similarly high when the pooled HRs (95% CI) for overall mortality associated with visceral adiposity were essentially null as in 1.03 (0.55, 1.92; I2 = 58%) for breast, 0.99 (0.81, 1.21; I2 = 71%) for colorectal, versus when they demonstrated a potential increased risk 1.17 (0.85, 1.60; I2 = 78%) for hepatocellular carcinoma and 1.62 (0.90, 2.95; I2 = 84%) for renal cancer.

CONCLUSION

Greater adiposity at diagnosis (directly measured by imaging) is not associated with worse survival among cancer survivors. However, heterogeneity and other potential limitations were noted across studies, suggesting differences in study design and adiposity measurement approaches, making interpretation of meta-analyses challenging. Future work to standardize imaging measurements and data analyses will strengthen research on the role of adiposity in cancer survival.

No association between BMI and immunotoxicity or clinical outcomes for immune checkpoint inhibitors

Background: The impact of BMI on immune checkpoint inhibitor toxicity and efficacy has not been clearly characterized. Methods: The authors conducted a retrospective single-center study of patients with advanced unresectable/metastatic cancer initiated on immune checkpoint inhibitors. Results: Of the 409 patients included in the study, 115 (28%) had a BMI ≥30. There was no difference in the development of immune-related adverse events, treatment response or overall survival with respect to BMI <30 versus ≥30 for the whole study population or the melanoma subgroup. Conclusion: Patients with BMI in the obese range (≥30) were not at increased risk of immunotoxicity. Furthermore, BMI was not correlated with treatment response or overall survival in patients receiving immune checkpoint inhibitors.

Efficacy of immunotherapy in obese patients with cancer

Obesity is a condition of excessive fat tissue and high body mass index (BMI ≥30), which is increasing worldwide. Excess body weight is associated with poorer results in cancer treatments; however, recent studies emphasized that elevated BMI was associated with improved outcomes in cases treated by immune checkpoint inhibitor (ICI) therapies, which is called the obesity paradox. In this review, we discuss the correlation between obesity and cancer immunotherapy, especially ICIs, the underlying mechanisms, and the outcomes in different types of cancers. In addition, we describe the occurrence of immune-related adverse events (irAE) and the effect of gender in obese patients during immunotherapy using all relevant studies with available full texts.

The ambiguous role of obesity in oncology by promoting cancer but boosting antitumor immunotherapy

Obesity is nowadays considered a pandemic which prevalence's has been steadily increasingly in western countries. It is a dynamic, complex, and multifactorial disease which propitiates the development of several metabolic and cardiovascular diseases, as well as cancer. Excessive adipose tissue has been causally related to cancer progression and is a preventable risk factor for overall and cancer-specific survival, associated with poor prognosis in cancer patients. The onset of obesity features a state of chronic low-grade inflammation and secretion of a diversity of adipocyte-derived molecules (adipokines, cytokines, hormones), responsible for altering the metabolic, inflammatory, and immune landscape. The crosstalk between adipocytes and tumor cells fuels the tumor microenvironment with pro-inflammatory factors, promoting tissue injury, mutagenesis, invasion, and metastasis. Although classically established as a risk factor for cancer and treatment toxicity, recent evidence suggests mild obesity is related to better outcomes, with obese cancer patients showing better responses to treatment when compared to lean cancer patients. This phenomenon is termed obesity paradox and has been reported in different types and stages of cancer. The mechanisms underlying this paradoxical relationship between obesity and cancer are still not fully described but point to systemic alterations in metabolic fitness and modulation of the tumor microenvironment by obesity-associated molecules. Obesity impacts the response to cancer treatments, such as chemotherapy and immunotherapy, and has been reported as having a positive association with immune checkpoint therapy. In this review, we discuss obesity's association to inflammation and cancer, also highlighting potential physiological and biological mechanisms underlying this association, hoping to clarify the existence and impact of obesity paradox in cancer development and treatment.

Progress and future prospective of FDG-PET/CT imaging combined with optimized procedures in lung cancer: toward precision medicine

With a 5-year overall survival of approximately 20%, lung cancer has always been the number one cancer-specific killer all over the world. As a fusion of positron emission computed tomography (PET) and computed tomography (CT), PET/CT has revolutionized cancer imaging over the past 20 years. In this review, we focused on the optimization of the function of ¹⁸F-flurodeoxyglucose (FDG)-PET/CT in diagnosis, prognostic prediction and therapy management of lung cancers by computer programs. FDG-PET/CT has demonstrated a surprising role in development of therapeutic biomarkers, prediction of therapeutic responses and long-term survival, which could be conducive to solving existing dilemmas. Meanwhile, novel tracers and optimized procedures are also developed to control the quality and improve the effect of PET/CT. With the continuous development of some new imaging agents and their clinical applications, application value of PET/CT has broad prospects in this area.

Body composition and inflammation impact in non-small-cell lung cancer patients treated by first-line immunotherapy

Background: Immunotherapy changed the landscape of non-small-cell lung cancer (NSCLC). Efforts were made to implement its action. This study aims to describe body composition, nutritional and inflammatory status in NSCLC patients treated by first-line immunotherapy, their correlation, variation and impact. Patients and methods: We retrospectively analyzed 44 consecutive patients who received pembrolizumab treatment. Results: During the therapy, inflammation and visceral fat increased, whereas muscle and subcutaneous fat decreased. Parameters related to inflammation had an interesting prognostic impact. High numbers of white blood cells remained significantly correlated with a high risk of death in multivariate model. Conclusion: For the best treatment choice, a combination of clinical and biological factors will be most likely be necessary. Prospective and larger studies with a multidimensional approach are needed.

Segmentation and characterization of visceral and abdominal subcutaneous adipose tissue on CT with and without contrast medium: influence of 2D- and 3D-segmentation

Background

Adipose tissue is a valuable biomarker. Although validation and correlation to clinical data have mostly been performed on non-enhanced scans (NES), a previous study has shown conversion of values of contrast enhanced scan (CES) into those of NES to be feasible with segmentation of the entire abdomen (3D-segmentation). In this study we analyzed if density and area of abdominal adipose tissue segmented in a single slice (2D-segmentation) of CES may be converted into that of NES. Furthermore, we compared the precision of conversion between 2D- and 3D-segmentation.

Methods

Thirty-one multi-phasic abdominal CT examinations at identical scan settings were retrospectively included. Exams included NES (n=31), arterial (ART) (n=23), portal-venous (PVN) (n=10), and/or venous scan (VEN) (n=31). Density and area of visceral (VAT) and subcutaneous adipose tissue (SAT) were quantified semi-automatically with fixed thresholds. For conversion of values from CES into those of NES regression analyses were performed and tested. 2D- and 3D-segmentation were compared with respect to conversion accuracy (normalized deviations of converted NES values from original measurements).

Results

After the application of contrast medium 2D-segmented adipose tissue increased in density (max. +5.6±2.4 HU) and decreased in area (max. -10.91%) (10.47%), with few exceptions (P<0.05). This was more pronounced in later scans (VEN ≈ PVN > ART) and more marked in VAT than SAT. Density and area in CES correlated very well with NES, allowing for conversion with only small error. While converted density is slightly more precise applying 3D-segmentation, conversion error of quantity was occasionally smaller with 2D-segmentation.

Conclusions

Contrast medium changes density and quantity of segmented adipose tissue in differing degrees between compartments, contrast phases and 2D- and 3D-segmentation. However, changes are fairly constant for a given compartment, contrast phase and mode of segmentation. Therefore, conversion of values into those of NES may be achieved with comparable precision for 2D- and 3D-segmentation.

Fat mass assessment using the triceps skinfold thickness enhances the prognostic value of the Global Leadership Initiative on Malnutrition criteria in patients with lung cancer

The present study evaluated whether fat mass assessment using the triceps skinfold (TSF) thickness provides additional prognostic value to the Global Leadership Initiative on Malnutrition (GLIM) framework in patients with lung cancer (LC). We performed an observational cohort study including 2672 LC patients in China. Comprehensive demographic, disease and nutritional characteristics were collected. Malnutrition was retrospectively defined using the GLIM criteria, and optimal stratification was used to determine the best thresholds for the TSF. The associations of malnutrition and TSF categories with survival were estimated independently and jointly by calculating multivariable-adjusted hazard ratios (HR). Malnutrition was identified in 808 (30·2 %) patients, and the best TSF thresholds were 9·5 mm in men and 12 mm in women. Accordingly, 496 (18·6 %) patients were identified as having a low TSF. Patients with concurrent malnutrition and a low TSF had a 54 % (HR = 1·54, 95 % CI = 1·25, 1·88) greater death hazard compared with well-nourished individuals, which was also greater compared with malnourished patients with a normal TSF (HR = 1·23, 95 % CI = 1·06, 1·43) or malnourished patients without TSF assessment (HR = 1·31, 95 % CI = 1·14, 1·50). These associations were concentrated among those patients with adequate muscle mass (as indicated by the calf circumference). Additional fat mass assessment using the TSF enhances the prognostic value of the GLIM criteria. Using the population-derived thresholds for the TSF may provide significant prognostic value when used in combination with the GLIM criteria to guide strategies to optimise the long-term outcomes in patients with LC.

Association between Body Mass Index and Survival Outcome in Metastatic Cancer Patients Treated by Immunotherapy: Analysis of a French Retrospective Cohort

The response to immunotherapy has been little investigated in overweight and obese cancer patients. We evaluated the relationships between BMI, toxicity, and survival in patients treated by immunotherapy for metastatic cancer. We included metastatic cancer patients treated by immunotherapy between January 2017 and June 2020 at the Centre Léon Bérard. In total, 272 patients were included: 64% men and 36% women, with a median age of 61.4 years. BMI ≥ 25 in 34.2% and 50% had non-small cell lung cancer (n = 136). Most received monotherapy, with nivolumab in 41.9% and pembrolizumab in 37.9%. Toxicity, mostly dysthyroiditis, occurred in 41%. Median overall survival (OS), estimated by Kaplan-Meier analysis, was significantly longer for patients with a BMI ≥ 25 than for those with a BMI < 25 (24.8 versus 13.7 months HR = 0.63; 95% CI 0.44-0.92, p = 0.015), and for patients experiencing toxicity than for those without toxicity (NR versus 7.8 months, HR = 0.22; 95% CI 0.15-0.33, p < 0.001). Adjusted OS was associated with toxicity, and the occurrence of toxicity was associated with sex and histological features but not with BMI. Thus, being overweight and experiencing toxicity was associated with longer overall survival in patients treated by immunotherapy. More attention should be paid to body composition in the care of cancer patients.

Impact of BMI on Survival Outcomes of Immunotherapy in Solid Tumors: A Systematic Review

Growing research has focused on obesity as a prognostic factor during therapy with immune-checkpoint inhibitors (ICIs). The role of body-mass index (BMI) in predicting response and toxicity to ICIs is not clear, as studies have shown inconsistent results and significant interpretation biases. We performed a systematic review to evaluate the relationship between BMI and survival outcomes during ICIs, with a side focus on the incidence of immune-related adverse events (irAEs). A total of 17 studies were included in this systematic review. Altogether, the current evidence does not support a clearly positive association of BMI with survival outcomes. Regarding toxicities, available studies confirm a superimposable rate of irAEs among obese and normal weight patients. Intrinsic limitations of the analyzed studies include the retrospective nature, the heterogeneity of patients’ cohorts, and differences in BMI categorization for obese patients across different studies. These factors might explain the heterogeneity of available results, and the subsequent absence of a well-established role of baseline BMI on the efficacy of ICIs among cancer patients. Further prospective studies are needed, in order to clarify the role of obesity in cancer patients treated with immunotherapy.

Impact of body composition, nutritional and inflammatory status on outcome of non-small cell lung cancer patients treated with immunotherapy

BACKGROUND AND AIMS

Body composition and balance of nutritional and inflammatory status are important for the immune system. Alterations of these aspects may impact on response, outcome and toxicities of immunotherapy. In this review we try to clarify some definitions and tools used for the assessment of the different aspects of nutritional disorders, body composition and inflammatory status with a focus on lung cancer.

METHODS

We primary investigate the definitions of malnutrition, cachexia, sarcopenia and overweight. Secondary, tools used to measure body composition, nutritional and inflammatory status, mainly in lung cancer are reviewed.

RESULTS

All these features, in the time of precision medicine may improve assessment and selection of patients, incorporating also early palliative care in standard therapy.

CONCLUSIONS

A multimodal approach based on nutrition assessment and physical exercise should be evaluated to improve aspects of the immune response against cancer and to propose the best treatment to every patient.

3D-segmentation and characterization of visceral and abdominal subcutaneous adipose tissue on CT: influence of contrast medium and contrast phase

Background

Adipose tissue as part of body composition analysis may serve as a powerful biomarker. Validation of segmented adipose tissue and correlation to clinical data has been performed on non-enhanced scans (NES). As many patients require a contrast enhanced scan (CES) for other aspects of clinical decision making, the utility of CES for body composition analysis would be most useful. Therefore, we analyzed the influence of iodinated contrast medium (ICM) and contrast phase on the characterization and segmentation of adipose tissue.

Methods

Exams of 31 patients undergoing multi-phasic CT at identical scan settings containing an NES were retrospectively included. In addition to NES, patients received an arterial (ART) (n=23), portal-venous (PVN) (n=10), and/or venous scan (VEN) (n=31) after intravenous injection of 90 mL ICM. Density and volume of adipose tissue were quantified semi-automatically with thresholds between -190 HU and -30 HU and recorded separately for visceral (VAT) and subcutaneous adipose tissue (SAT). Density and volume of total adipose tissue (TAT) were computed. For conversion of values from CES into those of NES regression analyses were performed and tested.

Results

Density of adipose tissue increased after application of ICM more on later scans (VEN ≈ PVN > ART) and more markedly in VAT than SAT (VAT > TAT > SAT). Except in SAT on ART, all changes were significant (P<0.001). Measured volume of adipose tissue decreased on all CES (VEN ≈ PVN > ART) (P<0.001), but only reached statistical significance for VAT and TAT (VAT > TAT) on all CES (P<0.05). Density and volume in CES correlate extremely well with NES and may be calculated from one another [root-mean-square error (RMSE): <6 HU; <0.85 dm³].

Conclusions

Density and volume of segmented adipose tissue are altered by the injection of ICM in differing degrees between compartments and contrast phases. However, as the effect of ICM is fairly constant for a given compartment and contrast phase, values may be converted into those of NES with relative precession. This conversion allows body composition analysis to be carried out also in contrast enhanced CT examinations, e.g., for risk stratification and the comparison of the obtained results to previous studies.

Nutritional Support in Lung Cancer Patients: The State of the Art

Lung cancer (LC) represents the most commonly diagnosed neoplasm worldwide for both sexes and is the leading cause of cancer mortality. Malnutrition is a comorbidity frequently found in neoplastic patients, but it remains often underestimated and thus undertreated. In this review, we aimed to investigate the incidence of malnutrition among LC patients according to different screening and assessment tools, to evaluate the impact of weight loss and body composition on survival, and to analyze the efficacy of different nutritional interventions in this setting. Although malnutrition, weight loss, and body composition changes can affect survival and other clinical outcomes in LC patients, the role of nutritional interventions is not yet strongly proven, and further studies are recommended. Nevertheless, screening, assessing, and eventually treating malnutrition in LC patients are strongly recommended, according to the most recent nutritional intervention guidelines for oncology patients.

Obesity, Sarcopenia, and Outcomes in Non-Small Cell Lung Cancer Patients Treated With Immune Checkpoint Inhibitors and Tyrosine Kinase Inhibitors

Body composition refers to the proportional content of body fat mass and lean body mass that can lead to a continuum of different phenotypes ranging from cachectic/sarcopenic state to obesity. The heterogenetic phenotypes of body composition can contribute to formation of some cancer types and can sometimes lead to disparate outcomes. Both of these extremes of the spectrum exist in patients with non-small cell lung carcinoma (NSCLC). The discovery of new pathways that drive tumorigenesis contributing to cancer progression and resistance have expanded our understanding of cancer biology leading to development of new targeted therapies including tyrosine kinase inhibitors (TKI) and immune checkpoint inhibitors (ICI) that have changed the landscape of NSCLC treatment. However, in the new era of precision medicine, the impact of body composition phenotypes on treatment outcomes and survival is now being elucidated. In this review, we will discuss the emerging evidence of a link between body composition and outcomes in patients with NSCLC treated with TKI and ICI. We will also discuss suggested mechanisms by which body composition can impact tumor behavior and anti-tumor immunological response.

Baseline BMI and BMI variation during first line pembrolizumab in NSCLC patients with a PD-L1 expression ≥ 50%: a multicenter study with external validation

BACKGROUND

The association between obesity and outcomes in patients receiving programmed death-1/programmed death ligand-1 (PD-L1) checkpoint inhibitors has already been confirmed in pre-treated non-small cell lung cancer (NSCLC) patients, regardless of PD-L1 tumor expression.

METHODS

We present the outcomes analysis according to baseline body mass index (BMI) and BMI variation in a large cohort of metastatic NSCLC patients with a PD-L1 expression ≥50%, receiving first line pembrolizumab. We also evaluated a control cohort of metastatic NSCLC patients treated with first line platinum-based chemotherapy. Normal weight was set as control group.

RESULTS

962 patients and 426 patients were included in the pembrolizumab and chemotherapy cohorts, respectively. Obese patients had a significantly higher objective response rate (ORR) (OR=1.61 (95% CI: 1.04-2.50)) in the pembrolizumab cohort, while overweight patients had a significantly lower ORR (OR=0.59 (95% CI: 0.37-0.92)) within the chemotherapy cohort. Obese patients had a significantly longer progression-free survival (PFS) (HR=0.61 (95% CI: 0.45-0.82)) in the pembrolizumab cohort. Conversely, they had a significantly shorter PFS in the chemotherapy cohort (HR=1.27 (95% CI: 1.01-1.60)). Obese patients had a significantly longer overall survival (OS) within the pembrolizumab cohort (HR=0.70 (95% CI: 0.49-0.99)), while no significant differences according to baseline BMI were found in the chemotherapy cohort. BMI variation significantly affected ORR, PFS and OS in both the pembrolizumab and the chemotherapy cohorts.

CONCLUSIONS

Baseline obesity is associated to significantly improved ORR, PFS and OS in metastatic NSCLC patients with a PD-L1 expression of ≥50%, receiving first line pembrolizumab, but not among patients treated with chemotherapy. BMI variation is also significantly related to clinical outcomes.

Pretreatment body mass index and clinical outcomes in cancer patients following immune checkpoint inhibitors: a systematic review and meta-analysis

BACKGROUND

This systematic review and meta-analysis aimed to evaluate the association between pretreatment body mass index (BMI) and clinical outcomes in cancer patients treated with immune checkpoint inhibitors (ICIs).

METHODS

Systematical searches of PubMed, Embase, and the Cochrane Library databases were carried out. Studies reporting on the association between BMI and outcomes of ICIs were included. The intended outcomes included overall survival (OS), progression-free survival (PFS), objective response rate (ORR) and immune-related adverse events (irAEs). Quantitative analyses and dose-response meta-analyses were performed under random effect models.

RESULTS

Twenty-two eligible studies involving 5686 cancer patients treated with ICIs were identified. Compared to those with lower BMI, patients with higher BMI obtained a significant benefit on OS (HR = 0.698, 95% CI 0.614-0.794, P < 0.001; I² = 45.9%) and PFS (HR = 0.760, 95% CI 0.672-0.861, P < 0.001; I² = 37.9%). Most stratified analyses for OS and PFS also showed similar pooled risk estimates. For an increment of every 5 kg/m² in BMI, the risk for death reduced by approximately 15.6% (HR = 0.844, 95% CI 0.752-0.945, P = 0.003). Moreover, patients with higher BMI had a remarkably better ORR (OR = 0.468, 95% CI 0.263-0.833, P = 0.010; I² = 73.6%) than that of those with lower BMI. However, no statistically significant differences were found in the incidence of any grade irAEs (P = 0.073) and ≥ 3 grade irAEs (P = 0.105) between higher and lower BMI.

CONCLUSION

Higher BMI is significantly associated with improved outcomes in patients treated with ICIs. Further large-scale prospective research is warranted to better illuminate the association between BMI and outcomes from ICIs.

Association between body mass index and survival outcomes for cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis

BACKGROUND

Immune checkpoint inhibitors (ICIs) have been increasingly applied in the treatment of several kinds of malignancies. Some clinical demographic characteristics were reported to be associated with the ICIs efficacy. The purpose of our current meta-analysis was to clearly evaluated the relationship between BMI and ICIs efficacy for cancer patients receiving immunotherapy.

METHODS

A systematic search of Pubmed, EMBASE and conference proceedings was performed to investigate the influence of BMI on ICIs efficacy. Pooled analysis for overall survival (OS), progression-free survival (PFS) and immune-related adverse effects (IRAEs) were analyzed in current study.

RESULTS

A total of 13 eligible studies comprising 5279 cancer patients treated with ICIs were included in the analysis. The pooled analysis showed there is positive association between high BMI and improved OS and PFS among patients with ICIs treatment (OS: HR = 0.62, 95% CI 0.55-0.71, P < 0.0001; I2 = 26.3%, P = 0.202); PFS: HR = 0.71, 95% CI 0.61-0.83, P < 0.0001; I2 = 0%, P = 0.591). There is no significant difference between the incidence of all grade IRAEs between obese, overweight patients and normal patients (Overweight vs Normal: pooled RR = 1.28, 95% CI 0.76- 2.18, P = 0.356; Obese vs Normal: pooled RR = 1.36, 95% CI 0.85- 2.17, P = 0.207).

CONCLUSION

An improved OS and PFS were observed in patients with high BMI after receiving ICIs treatment compared with patients of low BMI. No significant association between BMI and incidence of IRAEs was found in cancer patients after ICIs treatment.

Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer

INTRODUCTION

The aim of the study was to extract anthropometric measures from CT by deep learning and to evaluate their prognostic value in patients with non-small-cell lung cancer (NSCLC).

METHODS

A convolutional neural network was trained to perform automatic segmentation of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and muscular body mass (MBM) from low-dose CT images in 189 patients with NSCLC who underwent pretherapy PET/CT. After a fivefold cross-validation in a subset of 35 patients, anthropometric measures extracted by deep learning were normalized to the body surface area (BSA) to control the various patient morphologies. VAT/SAT ratio and clinical parameters were included in a Cox proportional-hazards model for progression-free survival (PFS) and overall survival (OS).

RESULTS

Inference time for a whole volume was about 3 s. Mean Dice similarity coefficients in the validation set were 0.95, 0.93, and 0.91 for SAT, VAT, and MBM, respectively. For PFS prediction, T-stage, N-stage, chemotherapy, radiation therapy, and VAT/SAT ratio were associated with disease progression on univariate analysis. On multivariate analysis, only N-stage (HR = 1.7 [1.2-2.4]; p = 0.006), radiation therapy (HR = 2.4 [1.0-5.4]; p = 0.04), and VAT/SAT ratio (HR = 10.0 [2.7-37.9]; p < 0.001) remained significant prognosticators. For OS, male gender, smoking status, N-stage, a lower SAT/BSA ratio, and a higher VAT/SAT ratio were associated with mortality on univariate analysis. On multivariate analysis, male gender (HR = 2.8 [1.2-6.7]; p = 0.02), N-stage (HR = 2.1 [1.5-2.9]; p < 0.001), and the VAT/SAT ratio (HR = 7.9 [1.7-37.1]; p < 0.001) remained significant prognosticators.

CONCLUSION

The BSA-normalized VAT/SAT ratio is an independent predictor of both PFS and OS in NSCLC patients.

KEY POINTS

• Deep learning will make CT-derived anthropometric measures clinically usable as they are currently too time-consuming to calculate in routine practice. • Whole-body CT-derived anthropometrics in non-small-cell lung cancer are associated with progression-free survival and overall survival. • A priori medical knowledge can be implemented in the neural network loss function calculation.

Immunotherapy by Immune Checkpoint Inhibitors and Nuclear Medicine Imaging: Current and Future Applications

Immunotherapy by using immune checkpoint inhibitors is a revolutionary development in oncology. Medical imaging is also impacted by this new therapy, particularly nuclear medicine imaging (also called radionuclide imaging), which uses radioactive tracers to visualize metabolic functions. Our aim was to review the current applications of nuclear medicine imaging in immunotherapy, along with their limitations, and the perspectives offered by this imaging modality. Method: Articles describing the use of radionuclide imaging in immunotherapy were researched using PubMed by April 2019 and analyzed. Results: More than 5000 articles were analyzed, and nearly 100 of them were retained. Radionuclide imaging, notably 18F-FDG PET/CT, already has a major role in many cancers for pre-therapeutic and therapeutic evaluation, diagnoses of adverse effects, called immune-related adverse events (IrAE), and end-of-treatment evaluations. However, these current applications can be hindered by immunotherapy, notably due to atypical response patterns such as pseudoprogression, which is defined as an increase in the size of lesions, or the visualization of new lesions, followed by a response, and hyperprogression, which is an accelerated tumor growth rate after starting treatment. To overcome these difficulties, new opportunities are offered, particularly therapeutic evaluation criteria adapted to immunotherapy and immuno-PET allowing us to predict responses to immunotherapy. Moreover, some new technological solutions are also promising, such as radiomic analyses and body composition on associated anatomical images. However, more research has to be done, notably for the diagnosis of hyperprogression and pseudoprogression. Conclusion: Immunotherapy, by its major impact on cancer and by the new patterns generated on images, is revolutionary in the field of medical images. Nuclear medicine imaging is already established and will be able to help meet new challenges through its plasticity.