Associations of subcutaneous fat area and Systemic Immune-inflammation Index with survival in patients with advanced gastric cancer receiving dual PD-1 and HER2 blockade

Development of a prognostic oxidative stress-immune-inflammation score and online calculators for predicting survival and recurrence in gastric cancer: a multicenter study

BACKGROUND

Oxidative stress, immune response, and inflammation play an important role in the occurrence and progression of gastric cancer (GC). This study is to develop a novel prognostic oxidative stress-immune-inflammation score (POSII score) and to explore the clinical value of the novel nomograms incorporating this factor in survival and recurrence risk.

METHODS

This study included 3612 GC patients who underwent radical gastrectomy at three tertiary hospitals from 2009 to 2020. One hospital formed the training and internal validation cohorts, while the other two constituted the external validation cohort. Twelve hematological markers were collected and analyzed to develop the POSII score via LASSO regression. Two online calculators were developed and validated.

RESULTS

The POSII score categorized patients into low and high POSII groups, with the low POSII group showing significantly improved 5-year overall survival (OS) and disease-free survival (DFS) rates, as well as a markedly reduced risk of recurrence (all P < 0.05). Multivariate COX regression showed that the POSII score was an independent prognostic factor. Based on the POSII score, two nomograms (OS: AUC = 0.837; DFS: AUC = 0.834, respectively) for individualized prognostic prediction were constructed. To enhance clinical usability, we further developed two user-friendly online calculators. The high-risk group had an earlier, more persistent peak of recurrence and a high incidence of multiple recurrence patterns.

CONCLUSION

Two novel online calculators based on the POSII score can be used as reliable tools for predicting survival and recurrence after radical gastrectomy. Our findings provide new insights into the role of cancer-related immune dysregulation, inflammation, and oxidative stress imbalances.

Inflammatory marker cut-off points and prognosis in incurable cancer: validation study

OBJECTIVES

The study aimed to determine and validate cut-off points for selected inflammatory markers to predict 30-day, 60-day and 90-day survival in patients with incurable cancer exclusively receiving palliative care.

METHODS

Prospective cohort study with patients referred to the palliative care unit of a national reference centre for cancer in Brazil. The sample (n=2098) was randomised into development (n=1049) and validation (n=1049) groups. C-reactive protein (CRP), CRP/albumin ratio (CAR), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), lymphocyte/monocyte ratio (LMR), prognostic nutritional index (PNI) and systemic immune-inflammation index (SII) were evaluated. Time-dependent receiver operating characteristic curves were used to define the optimal cut-off points. Kaplan-Meier curves, Cox proportional hazards models and concordance statistic (C-statistic) were used to evaluate their predictive ability.

RESULTS

The optimal cut-off points related to 30-day, 60-day and 90-day mortality were, respectively, as follows: CRP ≥6.0 mg/L, ≥4.8 mg/L and ≥4.7 mg/L; CAR ≥2.0, ≥1.7 and ≥1.5; NLR ≥6.5, ≥5.8 and ≥5.7; PLR ≥298.0, ≥286.7 and ≥281.2; LMR ≥1.9, ≥2.2 and ≥2.0; PNI ≥35.5, ≥46.8 and ≥30.5; and SII ≥2254.4, ≥1983.0 and ≥1844.1. The inflammatory markers that showed discriminatory accuracy (CRP, CAR, NLR, PLR and SII) were selected for validation. These markers demonstrated predictive ability, with good discriminatory power (C-statistic ≥0.75).

CONCLUSIONS

Optimal cut-off points were validated for CRP, CAR, NLR, PLR and SII for use in the prognostic assessment of patients with incurable cancer exclusively receiving palliative care.

The impact of the muscle mass-to-fat ratio on the prognosis of patients undergoing pancreaticoduodenectomy for pancreatic cancer

To evaluate the relationship between the muscle mass-to-fat ratio (MMFR) at the third lumbar spine (L3) and overall survival (OS) as well as related complications after pancreaticoduodenectomy (PD) for pancreatic cancer. Patients who underwent PD for pancreatic cancer between March 2017 and May 2023 at the Second Affiliated Hospital of Soochow University were included. Muscle mass and fat content at the L3 were measured by computed tomography. The specific formula that was used to calculate the MMFR was total abdominal muscle area/(subcutaneous adipose tissue area + visceral adipose tissue area), and the optimal cutoff values of the MMFR based on receiver operating characteristic curves were 0.688 for males and 0.382 for females. Patient characteristics were collected, and multivariate analyses were used to evaluate the impact of the MMFR on prognosis. Kaplan-Meier survival curves and log-rank tests were used to compare OS between the high-MMFR and low-MMFR groups. On the basis of the optimal cutoff values, 191 patients were divided into two groups, with 91 patients in the low-MMFR group and 100 patients in the high-MMFR group. The incidence of POPF was significantly greater in the low-MMFR group than in the high-MMFR group. According to multivariate analysis, the MMFR was an independent factor associated with POPF and OS. Patients with low MMFRs had significantly shorter OS and a greater POPF incidence than did those with high MMFRs. The MMFR is an independent predictor of POPF and affects the OS of patients undergoing PD for pancreatic cancer.

Association of Body Composition Parameters with the Short- and Long-Term Efficacy of Neoadjuvant Immunotherapy Combined with Chemotherapy in Advanced Gastric Cancer

BACKGROUND

Immunotherapy has become a prevalent strategy in the neoadjuvant treatment of advanced gastric cancer (AGC). This study investigates the predictive value of computed tomography (CT)-derived body composition parameters on the efficacy of neoadjuvant immunotherapy for AGC.

METHODS

Data on 103 patients with resectable AGC who received neoadjuvant immunotherapy combined with chemotherapy at a teaching hospital between March 2020 and August 2022 were collected. Body composition parameters, including the subcutaneous adipose index (SAI), visceral adipose index (VAI), and skeletal muscle index (SMI), were calculated from pretreatment CT images. Logistic regression and Cox proportional hazards models assessed the impact of these parameters on pathological responses and survival outcomes following treatment.

RESULTS

Of the patients, 34 (33.0%) achieved a major pathological response (MPR). Higher SAI, VAI, and SMI values were significantly linked to an increased likelihood of achieving MPR (p < 0.05). Multivariate regression analysis revealed that only SAI independently predicted MPR (OR 1.042, 95% CI 1.009-1.077, p = 0.013). Furthermore, patients with a high SAI had significantly improved 2-year overall survival (76.9% vs. 54.9%, log-rank p = 0.012) and 2-year event-free survival (71.2% vs. 51.0%, log-rank p = 0.022) compared to those with low SAI. The survival benefit associated with high SAI was partly due to its higher MPR rate (mediating proportion: 37.5%, 95% CI: 12%-110%).

CONCLUSION

Pretreatment SAI independently correlates with MPR and better oncological outcomes in patients with AGC receiving neoadjuvant immunotherapy.

Organ-specific immune-related adverse events and prognosis in cancer patients receiving immune checkpoint inhibitors

BACKGROUND

Patients who developed immune-related adverse events (irAEs) could benefit more from treatment with immune checkpoint inhibitors (ICIs) than those who did not develop irAEs. This study was designed to assess whether the occurrence of irAEs or their characteristics are correlated with survival in advanced patients treated with ICIs.

METHODS

This retrospective cohort study enrolled a panel of cancer patients who received ICIs at a single institute. Kaplan‒Meier curves were generated to describe progression-free survival (PFS) and overall survival (OS) in patients with irAEs or specific irAE characteristics.

RESULTS

A total of 238 patients were enrolled, 83 (34.9%) of whom developed at least one irAE. Overall, irAE development was associated with prolonged OS (not reached vs. 17.8 months, P < 0.001), PFS (8.7 vs. 4.8 months, P = 0.003), and an improved objective response rate (24.1% vs. 10.3%, P = 0.005). Furthermore, only skin or endocrine toxicities were associated with improved OS and PFS. On the basis of the results from organ-specific irAEs, the first development of skin or endocrine toxicities as protective irAEs rather than other irAEs was an independent indicator for predicting OS (P < 0.001) and PFS (P < 0.001). A protective irAE burden score based on organ-specific irAEs was further developed to show the significant protective effect of total irAEs on patient outcomes.

CONCLUSIONS

Not all irAEs are associated with prolonged survival. The identification of organ-specific irAEs is useful for stratifying patients who actually respond to and benefit from ICIs across different cancer types.

The prognostic value of systemic immune-inflammation index in patients with unresectable hepatocellular carcinoma treated with immune-based therapy

BACKGROUND

Predicting the efficacy of immune-based therapy in patients with unresectable hepatocellular carcinoma (HCC) remains a clinical challenge. This study aims to evaluate the prognostic value of the systemic immune-inflammation index (SII) in forecasting treatment response and survival outcomes for HCC patients undergoing immune-based therapy.

METHODS

We analyzed a cohort of 268 HCC patients treated with immune-based therapy from January 2019 to March 2023. A training cohort of 93 patients received atezolizumab plus bevacizumab (T + A), while a validation cohort of 175 patients underwent treatment with tyrosine kinase inhibitors (TKIs) combined with anti-PD-(L)1 therapy. The SII cutoff value, determined using X-tile analysis based on overall survival (OS) in the training cohort, divided patients into high (> 752*109) and low (≤ 752*109) SII groups. Prognostic factors were identified through univariate and multivariate logistic and Cox regression analyses, and survival outcomes were assessed using Kaplan-Meier methods. The predictive accuracy of SII was evaluated using receiver operating characteristic (ROC) curves.

RESULTS

An optimal SII cutoff of 752*109 stratified patients into high and low SII groups. Univariate and multivariate logistic regression indicated that SII was a significant predictor of the objective response rate (ORR), which was markedly different between the low and high SII subgroups (34.72% vs. 9.52%, P = 0.019). This finding was consistent in the validation cohort (34.09% vs. 16.28%, P = 0.026). SII also demonstrated prognostic value in Cox regression and Kaplan-Meier analyses. ROC curves confirmed that SII had superior predictive accuracy compared to common clinical indicators, with predictive relevance even in AFP-negative patients. Furthermore, a lower SII was associated with a higher T cell ratio and an increased number of CD8+ T cells and Granzyme B+ CD8+ T cells in peripheral blood.

CONCLUSION

SII is a promising predictor of both therapeutic efficacy and prognosis in HCC patients undergoing immune-based treatments. Its application may enhance clinical decision-making, thereby improving patient outcomes from immune-based therapy.

Explanation of the obesity paradox of immunotherapy in cancer patients using CT-derived adipose composition parameters: A systematic review and meta-analysis

BACKGROUND

Although recent studies have reported that obesity is a protective factor for survival in patients with advanced cancers treated with immune checkpoint inhibitors (ICIs), the prognostic value of CT-derived adipose composition parameters remains unclear. This study aimed to assess the association between CT-derived adipose composition parameters and clinical outcomes in cancer patients undergoing ICIs treatment.

METHODS

A comprehensive search was conducted until May 2024 across several databases to gather relevant studies, including PubMed, Embase, Web of Science and Cochrane Library. Hazard ratios (HR) or odds ratios (OR) were used to assess the correlation between adiposity composition and clinical outcomes. The primary outcomes were overall survival (OS) and progression-free survival (PFS). The secondary outcomes were immune-related adverse events (irAEs).

RESULTS

A total of 2118 patients in 17 studies were included in the meta-analysis. Systemic analysis of all collected evidence revealed that high subcutaneous fat area (SFA) (OS: HR = 0.61, 95 % CI = 0.46-0.81, P < 0.001; PFS: HR = 0.65, 95 % CI = 0.50-0.85, P = 0.001) and high visceral fat index (VFI) (OS: HR = 0.68, 95 % CI = 0.56-0.83, P < 0.001; PFS: HR = 0.79, 95 % CI = 0.67-0.92, P = 0.003) were significantly associated with OS and PFS in cancer patients treated with ICIs. High subcutaneous fat index (SFI) was associated with better OS (HR = 0.64, 95 % CI = 0.48-0.86, P = 0.003) but not PFS (HR = 0.78, 95 % CI = 0.59-1.03, P = 0.083). However, no significant correlation was found between inter-muscular fat index (IFI) (OS: HR = 0.94, 95 % CI = 0.56-1.60, P = 0.833; PFS: HR = 1.00, 95 % CI = 0.62-1.62, P = 0.998) and OS or PFS in cancer patients under ICIs treatment.

CONCLUSION

CT-derived adipose composition parameters such as SFA, SFI and VFI are predictive of clinical outcomes in cancer patients treated with ICIs. Prospective cohorts with larger samples are needed to validate this hypothesis-generating data in the future.

Myopenia and body fat distribution in hospitalized ulcerative colitis patients: correlations with clinical characteristics and response to vedolizumab

Background

Ulcerative colitis (UC) patients often suffer from impaired nutritional conditions. However, there are few studies focused on muscle loss in UC patients as well as its impact on therapeutic response. This study aimed to investigate the prevalence of myopenia in hospitalized patients with active UC, analyze the relationship between body composition including both skeletal muscle and fat with clinical characteristics, and explore the association between body composition and clinical response to vedolizumab.

Methods

A retrospective cohort study was conducted in hospitalized patients with active UC in Peking Union Medical College Hospital from November 2014 to October 2022. Computed tomography (CT) scans were used to measure skeletal muscle area, visceral fat area (VFA), subcutaneous fat area (SFA), and intramuscular fat infiltration at the third lumbar vertebrae (L3) level. These measurements were standardized by height (m) squared. Myopenia was defined as a skeletal muscle index (SMI) < 44.77 cm2/m2 for males and <32.50 cm2/m2 for females. The VFA/SFA ratio (VSR) served as an indicator of visceral obesity, while intramuscular fat infiltration was evaluated using the mean Hounsfield Unit (HU) value of the L3 skeletal muscle section.

Results

A total of 457 patients were enrolled. The prevalence of myopenia was 49.7% in this cohort. Female patients had significantly higher levels of subcutaneous fat and intramuscular fat but a lower level of visceral fat than male patients. SMI and mean HU showed positive correlations with serum albumin (ALB) and negative correlations with serum high-sensitivity C-reactive protein (hsCRP), whereas VSR showed the opposite trend. Among the 92 patients who received vedolizumab treatment, myopenia was significantly associated with a lower clinical response rate, and this association remained significant after adjusting for vedolizumab duration, ALB, and hsCRP (OR = 3.458, 95% CI 1.238-9.659, p = 0.018). Visceral obesity, defined as VSR ≥ 75th centile of gender-specific VSR, tended to diminish the clinical response rate but did not reach statistical significance.

Conclusion

This study underscores the significance of assessing body composition in UC patients. Optimizing body composition should be considered an integral component of managing UC patients in the future.

Prognostic value of inflammatory and nutritional indexes among patients with unresectable advanced gastric cancer receiving immune checkpoint inhibitors combined with chemotherapy-a retrospective study

Background

Recent studies have revealed that inflammatory factors and nutritional status of patients with advanced gastric cancer (AGC) are related to the efficacy of drug therapy and patient prognosis. This study seeks to evaluate the correlation between inflammatory markers, nutritional status, and clinical outcomes of immune checkpoint inhibitor (ICI)-based therapies among inoperable AGC patients.

Method

This retrospective study included 88 AGC patients who received ICIs combined with chemotherapy. Inflammatory and nutritional indicators from patients before and after two cycles of treatment were collected. Finally, the correlations between these indicators and the clinical response and survival of AGC patients with ICI treatment were examined.

Results

The results revealed that an Eastern Cooperative Oncology Group performance status (ECOG PS) score of 0, neutrophil count to lymphocyte count ratio (NLR) < 2.84, platelet count to lymphocyte count ratio (PLR) < 82.23, lymphocyte count to monocyte count ratio ≥ 2.35, the hemoglobin, albumin, lymphocyte and platelet score (HALP) ≥ 31.17, prognostic nutritional index (PNI) ≥ 46.53, albumin ≥ 41.65, the decreased HALP group and the decreased PNI group were significantly correlated with improved objective response rate. Additionally, an ECOG PS score of 0, NLR < 2.84 and the decreased HALP group was associated with a superior disease control rate. Meanwhile, an ECOG PS score of 0 (progression-free survival (PFS): P = 0.003; overall survival (OS): P = 0.001) and decreased PLR following treatment (PFS: P = 0.011; OS: P = 0.008) were significant independent predictors of PFS and OS. Lastly, a systemic immune inflammation index ≥ 814.8 was also a positive independent predictor of OS among AGC patients.

Conclusion

Our study supports the potential of inflammatory and nutritional factors to serve as predictors of the efficacy and prognosis in patients undergoing ICI-based therapies for AGC. However, further investigations are necessary to validate these findings.

Clinical implications of CT-detected ascites in gastric cancer: association with peritoneal metastasis and systemic inflammatory response

OBJECTIVES

This study aimed to evaluate the diagnostic significance of computed tomography (CT) detected ascites in gastric cancer (GC) with peritoneal metastasis (PM) and investigate its association with systemic inflammatory response.

METHODS

This retrospective study included 111 GCs with ascites (PM: n = 51; No PM: n = 60). Systemic inflammatory indexes, tumor markers, and the CT-assessed characteristics of ascites were collected. The differences in parameters between the two groups were analyzed. Diagnostic performance was obtained by receiver operating characteristic curve analysis. The association between the volume of ascites and clinical characteristics was evaluated with correlation analysis.

RESULTS

In this study, over half of GCs with ascites were not involved with PM. The systemic immune-inflammation index (SII), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), five tumor markers, and the characteristics of ascites showed significant differences between the two groups (all p < 0.05). Among them, SII, NLR, PLR, and the volume of ascites achieved the areas under the curve of 0.700, 0.698, 0.704, and 0.903, respectively. Moreover, the volumes of ascites showed positive correlations with SII, NLR, and PLR in GCs with PM, and the volumes of ascites detected in the upper abdomen were more strongly correlated with CA125 level (all p < 0.05).

CONCLUSION

Many GCs with CT-detected ascites did not occur with synchronous PM. The presence of upper abdominal ascites had certain clinical significance for diagnosing PM in GCs. Systemic inflammatory indexes were elevated and positively correlated with the volume of ascites in GCs with PM, which might suggest the enhanced systemic inflammatory response.

CRITICAL RELEVANCE STATEMENT

CT-detected ascites in the upper abdomen played an indicative role in identifying synchronous PM in GCs, and the systemic inflammatory response was enhanced in GCs with PM, which might be helpful for clinical evaluation.

KEY POINTS

Many GCs with CT-detected ascites did not occur with synchronous PM. CT-detected ascites in the upper abdomen help in identifying PM in GCs. GCs with PM showed elevated systemic inflammatory indexes and enhanced systemic inflammatory response.

Molecular subtypes and prognostic factors of lung large cell neuroendocrine carcinoma

Background

Lung large cell neuroendocrine carcinoma (LCNEC) is an aggressive disease with poor prognosis and short-term survival, which lacks effective prognostic indicators. The study aims to investigate the molecular subtypes and prognostic markers of lung LCNEC.

Methods

Patients diagnosed with lung LCNEC at Sun Yat-sen University Cancer Center (SYSUCC) between November 2007 and January 2021 were screened. Baseline clinical data were collected and routine blood indexes including lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic immune-inflammation index (SII) were calculated. Immunohistochemistry (IHC) of ASCL1, NEUROD1, POU2F3, YAP1 were done to perform molecular subtyping, while CD56, Syn, CgA, CD3, CD8, CD20, CD68, and CD163 were also stained on tissue samples. Then prognostic factors of lung LCNEC were explored.

Results

One hundred and fifty-one lung LCNEC patients were identified, 103 of whom had complete clinical information, available routine blood and biochemical indexes were eventually included in the present study. Tumor tissue specimens were available from 64 patients. Positive expression rates of ASCL1, NEUROD1, and YAP1 were 82.8%, 50.0%, and 28.1%, respectively. No POU2F3+ cases were detected. Forty (62.5%) patients co-expressed with two or three markers. High LMR (>3.3) was an independent predictor of favorable prognosis of disease-free survival (DFS) [hazard ratio (HR), 0.391; 95% confidence interval (CI): 0.161-0.948; P=0.04] and overall survival (OS) (HR, 0.201; 95% CI: 0.071-0.574; P=0.003). Notably, high LMR was correlated with higher intra-tumoral CD3+ (P=0.004), CD8+ (P=0.01), and CD68+ (P<0.001) immune cell infiltration compared to low LMR in lung LCNEC.

Conclusions

Our study validated molecular subtypes by IHC in lung LCNEC, and co-expression was found among different subtypes, with no prognostic effect. High blood LMR level was associated with a favorable prognosis in lung LCNEC, which might partly reflect a hot tumor tissue immune microenvironment. Our findings may benefit clinical practice, and further studies are warranted.

Visceral fat area and subcutaneous fat area as measures of body composition in soft tissue sarcoma

BACKGROUND AND OBJECTIVES

Soft tissue sarcomas (STS) are a heterogenous group of malignancies of mesenchymal origin. Given recent data linking obesity as well as the pattern of fat distribution with cancer outcomes, we sought to investigate the association of visceral fat area (VFA) and subcutaneous fat area (SFA) with oncologic outcomes in patients with STS undergoing surgery.

METHODS

We analyzed data from 88 patients with STS diagnosed from 2008 to 2022. Predictor variables included body mass index (BMI), VFA, and SFA. VFA and SFA were obtained from computed tomography of the abdomen and pelvis. Univariable and multivariable Cox regression analysis was used to analyze associations between predictor variables and overall survival and recurrence-free survival.

RESULTS

Although BMI was closely correlated with VFA (r = 0.69, p < 0.0001) and SFA (r = 0.80, p < 0.0001), there was no significant association between high BMI, VFA or SFA, and worse oncologic outcomes.

CONCLUSIONS

Although VFA and SFA are strongly correlated with BMI, we did not observe BMI nor imaging metrics of fat composition to be associated with worse oncologic outcomes. Further research is needed to elucidate any links between body fat content and metabolic or immune factors governing oncologic outcomes in STS.

Predicting gastric cancer response to anti-HER2 therapy or anti-HER2 combined immunotherapy based on multi-modal data

The sole use of single modality data often fails to capture the complex heterogeneity among patients, including the variability in resistance to anti-HER2 therapy and outcomes of combined treatment regimens, for the treatment of HER2-positive gastric cancer (GC). This modality deficit has not been fully considered in many studies. Furthermore, the application of artificial intelligence in predicting the treatment response, particularly in complex diseases such as GC, is still in its infancy. Therefore, this study aimed to use a comprehensive analytic approach to accurately predict treatment responses to anti-HER2 therapy or anti-HER2 combined immunotherapy in patients with HER2-positive GC. We collected multi-modal data, comprising radiology, pathology, and clinical information from a cohort of 429 patients: 310 treated with anti-HER2 therapy and 119 treated with a combination of anti-HER2 and anti-PD-1/PD-L1 inhibitors immunotherapy. We introduced a deep learning model, called the Multi-Modal model (MuMo), that integrates these data to make precise treatment response predictions. MuMo achieved an area under the curve score of 0.821 for anti-HER2 therapy and 0.914 for combined immunotherapy. Moreover, patients classified as low-risk by MuMo exhibited significantly prolonged progression-free survival and overall survival (log-rank test, P < 0.05). These findings not only highlight the significance of multi-modal data analysis in enhancing treatment evaluation and personalized medicine for HER2-positive gastric cancer, but also the potential and clinical value of our model.

Unraveling the obesity paradox in small cell lung cancer immunotherapy: unveiling prognostic insights through body composition analysis

Background

The advent of immunotherapy has changed the landscape of SCLC treatment, although the identification of reliable prognostic biomarkers remains a formidable challenge. Our objective was to investigate the prognostic implications of obesity and body composition in SCLC immunotherapy while seeking a straightforward anthropometric measure.

Methods

This retrospective study analyzed data from patients with SCLC who underwent immunotherapy between 2019 and 2023. Body composition and waist circumference (WC) were analyzed using 3D slicer software on baseline CT images. Quantitative measures, including skeletal muscle index (SMI), total adipose tissue index (TATI), and other indicators at the L3 level, along with body shape index (BSI) and additional indicators based on WC, were obtained. The relationships between these indicators, response, PFS, OS, and their interconnections were examined.

Results

A total of 145 SCLC patients who received immunotherapy were identified, of whom 133 met the inclusion criteria. In univariate analysis, a BMI≥28 kg/m2 was associated with a PFS advantage (HR 0.42, p=0.04), but this trend vanished in multivariate analysis. Body measurements exhibited stronger correlations with adipose tissue content, with BSI showing the highest correlation with muscle. In multivariate analysis, lower BSI was associated with poorer OS (HR 1.79, p=0.02). The association between muscle composition and prognosis was robust in univariate analysis but dissipated in multivariate analysis. However, accounting for a high TATI background significantly heightened the adverse effect of SMI on prognosis in the multivariate model.

Conclusion

No clear association between BMI and SCLC immunotherapy prognosis was observed. However, high adiposity exacerbated the adverse effects of sarcopenia in SCLC immunotherapy, and BSI demonstrated potential as a straightforward prognostic measure.

Systemic immunoinflammatory index and prognostic nutrition index for predicting pathologic responses of patients with advanced gastric cancer after neoadjuvant therapy for advanced gastric cancer

To investigate the value of prognostic nutrition index (PNI) and systemic immunoinflammatory index (SII) for predicting pathological responses of patients with advanced gastric cancer (GC) after neo-adjuvant chemotherapy (NACT). The clinicopathological data of 326 patients with advanced GC who received NACT in Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City) from January 2017 to December 2021 were retrospectively collected. The SII and PNI of patients were calculated. The receiver operating characteristics (ROC) curve was leveraged for getting the optimal cutoff values of SII and PNI. The pathological response of patients after NACT, as obtained from their postoperative pathological examinations, was evaluated based on the tumor regression grade (TRG) criteria. Multivariate regression analysis was employed for identifying factors that led to various pathological responses after NACT in advanced GC patients. The log-rank test was utilized for between-group comparison of patients' survival curves. The SII and PNI were 507.45 and 48.48 respectively, and their levels were divided into high and low groups. Pathological response (TRG 0-1) was observed in 66 cases (20.25%), while non-pathological response (TRG 2-3) was observed in 260 cases (79.75%). The results of multivariate logistic regression analysis showed that tumor diameter < 5 cm, ypT T0-T2, ypN N0, chemotherapy regimen XELOX (capecitabine combined with oxaliplatin), SII < 507.45 (P=0.002), PNI > 48.48 were all independent factors affecting the pathological responses of advanced GC patients after NACT (all P < 0.05). With SII and PNI being included, the AUC was 0.821 (95% CI: 0.765-0.876), and the specificity was 87.90% and the sensitivity was 64.20%. The Kaplan-Meier survival curve analysis showed that NACT patients with tumor diameter < 5 cm, ypT T0-T2, ypN N0, XELOX chemotherapy regimen, SII < 507.45 and SII ≥ 507.45 had a higher survival rate. (P < 0.001). Before treatment, tumor diameter < 5 cm, ypT T0-T2, ypN N0, chemotherapy regimen XELOX, SII < 507.45, PNI > 48.48 were all independent factors affecting the pathological response of advanced GC patients after NACT. Moreover, the inclusion of SII and PNI increased the accuracy of predicting the pathological response of patients after NACT.

A study predicting long-term survival capacity in postoperative advanced gastric cancer patients based on MAOA and subcutaneous muscle fat characteristics

BACKGROUND

The prognosis of advanced gastric cancer (AGC) is relatively poor, and long-term survival depends on timely intervention. Currently, predicting survival rates remains a hot topic. The application of radiomics and immunohistochemistry-related techniques in cancer research is increasingly widespread. However, their integration for predicting long-term survival in AGC patients has not been fully explored.

METHODS

We Collected 150 patients diagnosed with AGC at the Affiliated Zhongshan Hospital of Dalian University who underwent radical surgery between 2015 and 2019. Following strict inclusion and exclusion criteria, 90 patients were included in the analysis. We Collected postoperative pathological specimens from enrolled patients, analyzed the expression levels of MAOA using immunohistochemical techniques, and quantified these levels as the MAOAHScore. Obtained plain abdominal CT images from patients, delineated the region of interest at the L3 vertebral body level, and extracted radiomics features. Lasso Cox regression was used to select significant features to establish a radionics risk score, convert it into a categorical variable named risk, and use Cox regression to identify independent predictive factors for constructing a clinical prediction model. ROC, DCA, and calibration curves validated the model's performance.

RESULTS

The enrolled patients had an average age of 65.71 years, including 70 males and 20 females. Multivariate Cox regression analysis revealed that risk (P = 0.001, HR = 3.303), MAOAHScore (P = 0.043, HR = 2.055), and TNM stage (P = 0.047, HR = 2.273) emerged as independent prognostic risk factors for 3-year overall survival (OS) and The Similar results were found in the analysis of 3-year disease-specific survival (DSS). The nomogram developed could predict 3-year OS and DSS rates, with areas under the ROC curve (AUCs) of 0.81 and 0.797, respectively. Joint calibration and decision curve analyses (DCA) confirmed the nomogram's good predictive performance and clinical utility.

CONCLUSION

Integrating immunohistochemistry and muscle fat features provides a more accurate prediction of long-term survival in gastric cancer patients. This study offers new perspectives and methods for a deeper understanding of survival prediction in AGC.

Development and validation of a prognostic immunoinflammatory index for patients with gastric cancer

BACKGROUND

Studies have demonstrated the influence of immunity and inflammation on the development of tumors. Although single biomarkers of immunity and inflammation have been shown to be clinically predictive, the use of biomarkers integrating both to predict prognosis in patients with gastric cancer remains to be investigated.

AIM

To investigate the prognostic and clinical significance of inflammatory biomarkers and lymphocytes in patients undergoing surgical treatment for gastric cancer.

METHODS

Univariate COX regression analysis was performed to identify potential prognostic factors for patients with gastric cancer undergoing surgical treatment. Least absolute shrinkage and selection operator-COX (LASSO-COX) regression analysis was performed to integrate these factors and formulate a new prognostic immunoinflammatory index (PII). The correlation between PII and clinical characteristics was statistically analyzed. Nomograms incorporating the PII score were devised and validated based on the time-dependent area under the curve and decision curve analysis.

RESULTS

Patients exhibiting elevated neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and systemic immune inflammatory index displayed inferior progression-free survival (PFS) and overall survival (OS). Conversely, low levels of CD3(+), CD3(+) CD8(+), CD4(+)CD8(+), and CD3(+)CD16(+)CD56(+) T lymphocytes were associated with improved PFS and OS, while high CD19(+) T lymphocyte levels were linked to worse PFS and OS. The PII score demonstrated associations with tumor characteristics (primary tumor site and tumor size), establishing itself as an independent prognostic factor for both PFS and OS. Time-dependent area under the curve and decision curve analysis affirmed the effectiveness of the PII-based nomogram as a robust prognostic predictive model.

CONCLUSION

PII may be a reliable predictor of prognosis in patients with gastric cancer undergoing surgical treatment, and it offers insights into cancer-related immune-inflammatory responses, with potential significance in clinical practice.

The Influence of Visceral Adiposity on Overall Survival: Exploring "Obesity Paradox" Among Hepatocellular Carcinoma Patients Who Receiving Immunotherapy

Purpose

The impact of visceral adiposity on overall survival (OS) in hepatocellular carcinoma (HCC) receiving immunotherapy was unclear. We aimed to determine how visceral adiposity affected OS and explore the interrelationships between visceral adiposity, body mass index (BMI), and other body compositions.

Patients and Methods

Data from three centers were retrospectively analyzed. Skeletal muscle index (SMI), skeletal muscle density (SMD), visceral adipose tissue index (VATI), and subcutaneous adipose tissue index (SATI) were used to define each body composition. The BMI subgroups included the underweight, the normal weight, and the obesity. The Log rank test compared survival curves calculated by the Kaplan-Meier method. The relationships between body compositions and BMI with OS were examined using Cox proportional risk regression models.

Results

A total of 305 patients who met the criteria were included. Patients with low VATI had significantly worse OS (P = 0.001). The protections of VATI (P = 0.011) on OS were independent of covariates. However, after additional adjustment of SMI, the effect of VATI on OS disappeared (P = 0.146), but the effect of SMD on OS did not (P = 0.021). BMI has a significant U-shaped relationship with OS, and the effect of BMI on OS equally disappeared after additional adjustment by SMI.

Conclusion

This study first demonstrated that high VATI and mid-level BMI were protective for the survival of patients with HCC receiving immunotherapy. Skeletal muscle status (including SMI and SMD) may be the better predictor for outcomes of patients with HCC receiving immunotherapy.

Creatinine-to-cystatin C ratio and body composition predict response to PD-1 inhibitors-based combination treatment in metastatic gastric cancer

Background

Creatinine-to-cystatin C ratio (CCR) and body composition (BC) parameters have emerged as significant prognostic factors in cancer patients. However, the potential effects of CCR in gastric cancer (GC) remains to be elucidated. This multi-center retrospective study explored the predictive and prognostic value of CCR and BC-parameters in patients with metastatic GC receiving PD-1 inhibitors-based combination therapy.

Methods

One hundred and thirteen GC patients undergoing PD-1 inhibitors-based combination therapy were enrolled at three academic medical centers from January 2021 to July 2023. A deep-learning platform based on U-Net was developed to automatically segment skeletal muscle index (SMI), subcutaneous adipose tissue index (SATI) and visceral adipose tissue index (VATI). Patients were divided into two groups based on the median of CCR or the upper tertile of BC-parameters. Logistic and Cox regression analysis were used to determine the effect of CCR and BC-parameters in predicting response rates and survival rates.

Results

The CCR was positively correlated with SMI (r=0.43; P<0.001), but not with SATI or VATI (P>0.05). Multivariable logistic analysis identified that both low CCR (OR=0.423, P=0.066 for ORR; OR=0.026, P=0.005 for DCR) and low SATI (OR=0.270, P=0.020 for ORR; OR=0.149, P=0.056 for DCR) were independently associated with worse objective response rate (ORR) and disease control rate (DCR). Patients with low CCR or low SATI had significantly lower 8-month progression-free survival (PFS) rate and 16-month overall survival (OS) rate than those with high CCR (PFS rate, 37.6% vs. 55.1%, P=0.011; OS rate, 19.4% vs. 44.9%, P=0.002) or those with high SATI (PFS rate, 37.2% vs. 53.8%, P=0.035; OS rate, 8.0% vs. 36.0%, P<0.001). Multivariate Cox analysis showed that low CCR (HR=2.395, 95% CI: 1.234-4.648, P=0.010 for PFS rate; HR=2.528, 95% CI: 1.317-4.854, P=0.005 for OS rate) and low SATI (HR=2.188, 95% CI: 1.050-4.560, P=0.037 for PFS rate; HR=2.818, 95% CI: 1.381-5.752, P=0.004 for OS rate) were both independent prognostic factors of poor 8-month PFS rate and 16-month OS rate. A nomogram based on CCR and BC-parameters showed a good performance in predicting the 12- and 16-month OS, with a concordance index of 0.756 (95% CI, 0.722-0.789).

Conclusions

Low pre-treatment CCR and SATI were independently associated with lower response rates and worse survival in patients with metastatic GC receiving PD-1 inhibitors-based combination therapy.

Development and validation of a preoperative CT-based risk scoring system for predicting recurrence-free survival in patients undergoing curative surgery for gastric cancer

PURPOSE

The objective of this study was to establish and validate a preoperative risk scoring system that incorporated both clinical and computed tomography(CT) variables to predict recurrence-free survival (RFS) in gastric cancer(GC) patients who underwent curative resection.

METHOD

We retrospectively included consecutive patients with surgically confirmed GC who underwent preoperative CT scans between October 2017 and January 2022. Multivariate Cox regression analysis was employed in the derivation set to identify clinical and CT variables associated with RFS and to construct a risk score. This risk score was subsequently validated in an independent test set.

RESULTS

A total of 346 patients were included in the study, with 213 in the derivation set and 133 in the test set. Five variables, namely ctEMVI, ctBorrmann, visceral obesity, sarcopenia, and NLR, were independently associated with RFS. In the test set, the preoperative risk score exhibited a c-index of 0.741, which outperformed the predictive accuracy of pathological tumor staging (c-index of 0.673, p = 0.021) at various time points. The preoperative risk score effectively stratified patients into low and high-risk groups.

CONCLUSION

The developed preoperative risk scoring system demonstrated the ability to predict RFS following curative resection in GC patients.