Cadonilimab with chemotherapy in HER2-negative gastric or gastroesophageal junction adenocarcinoma: the phase 1b/2 COMPASSION-04 trial.

Treatment with anti-programmed cell death protein 1 (PD-1) therapy and chemotherapy prolongs the survival of patients with unresectable advanced or metastatic gastric or gastroesophageal junction (GEJ) adenocarcinoma. The benefit from anti-PD-1 therapy is enriched in patients with programmed cell death 1 ligand 1 (PD-L1) combined positive score (CPS)-positive or CPS-high tumors compared with patients with PD-L1 CPS-negative or CPS-low tumors. In this phase 1b/2 study, we evaluated the efficacy and safety of cadonilimab, a bispecific antibody targeting PD-1 and cytotoxic T-lymphocyte antigen-4, plus chemotherapy as first-line treatment in patients with human epidermal growth factor receptor 2-negative unresectable advanced or metastatic gastric or GEJ adenocarcinoma. The primary endpoint was the recommended phase 2 dose (RP2D) for phase 1b and the objective response rate for phase 2. Secondary endpoints included disease control rate, duration of response, time to response, progression-free survival, overall survival (OS) and safety. The primary endpoint was met. No dose-limiting toxicities were observed during dose escalation in phase 1b; the recommended phase 2 dose was determined as 6 mg kg-1 every 2 weeks. The objective response rate was 52.1% (95% confidence interval (CI) = 41.6-62.5), consisting of complete and partial responses in 4.3% and 47.9% of patients, respectively. The median duration of response, progression-free survival and OS were 13.73 months (95% CI = 7.79-19.12), 8.18 months (95% CI = 6.67-10.48) and 17.48 months (95% CI = 12.35-26.55), respectively. The median OS in patients with a PD-L1 CPS ≥ 5 was 20.32 months (95% CI = 4.67-not estimable); in patients with a PD-L1 CPS < 1, the median OS reached 17.64 months (95% CI = 11.63-31.70). The most common treatment-related grade 3 or higher adverse events were decreased neutrophil count (19.1%), decreased platelet count (16.0%), anemia (12.8%) and decreased leukocyte count (8.5%). No new safety signal was identified. The current regimen showed promising clinical activity and manageable safety in patients with gastric or GEJ adenocarcinoma regardless of PD-L1 expression. Chinadrugtrials.org.cn registration: CTR20182027.

The potential of machine learning models to identify malnutrition diagnosed by GLIM combined with NRS-2002 in colorectal cancer patients without weight loss information.

BACKGROUND & AIMS: The key step of the Global Leadership Initiative on Malnutrition (GLIM) is nutritional risk screening, while the most appropriate screening tool for colorectal cancer (CRC) patients is yet unknown. The GLIM diagnosis relies on weight loss information, and bias or even failure to recall patients' historical weight can cause misestimates of malnutrition. We aimed to compare the suitability of several screening tools in GLIM diagnosis, and establish machine learning (ML) models to predict malnutrition in CRC patients without weight loss information. METHODS: This multicenter cohort study enrolled 4487 CRC patients. The capability of GLIM diagnoses combined with four screening tools in predicting survival probability was compared by Kaplan-Meier curves, and the most accurate one was selected as the malnutrition reference standard. Participants were randomly assigned to a training cohort (n = 3365) and a validation cohort (n = 1122). Several ML approaches were adopted to establish models for predicting malnutrition without weight loss data. We estimated feature importance and reserved the top 30% of variables for retraining simplified models. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were calculated to assess and compare model performance. RESULTS: NRS-2002 was the most suitable screening tool for GLIM diagnosis in CRC patients, with the highest hazard ratio (1.59; 95% CI, 1.43-1.77). A total of 2076 (46.3%) patients were malnourished diagnosed by GLIM combined with NRS-2002. The simplified random forest (RF) model outperformed other models with an AUC of 0.830 (95% CI, 0.805-0.854), and accuracy, sensitivity and specificity were 0.775, 0.835 and 0.742, respectively. We deployed an online application based on the simplified RF model to accurately estimate malnutrition probability in CRC patients without weight loss information (https://zzuwtt1998.shinyapps.io/dynnomapp/). CONCLUSIONS: Nutrition Risk Screening 2002 was the optimal initial nutritional risk screening tool in the GLIM process. The RF model outperformed other models, and an online prediction tool was developed to properly identify patients at high risk of malnutrition.

Identification of prognostic signatures in remnant gastric cancer through an interpretable risk model based on machine learning: a multicenter cohort study.

OBJECTIVE: The purpose of this study was to develop an individual survival prediction model based on multiple machine learning (ML) algorithms to predict survival probability for remnant gastric cancer (RGC). METHODS: Clinicopathologic data of 286 patients with RGC undergoing operation (radical resection and palliative resection) from a multi-institution database were enrolled and analyzed retrospectively. These individuals were split into training (80%) and test cohort (20%) by using random allocation. Nine commonly used ML methods were employed to construct survival prediction models. Algorithm performance was estimated by analyzing accuracy, precision, recall, F1-score, area under the receiver operating characteristic curve (AUC), confusion matrices, five-fold cross-validation, decision curve analysis (DCA), and calibration curve. The best model was selected through appropriate verification and validation and was suitably explained by the SHapley Additive exPlanations (SHAP) approach. RESULTS: Compared with the traditional methods, the RGC survival prediction models employing ML exhibited good performance. Except for the decision tree model, all other models performed well, with a mean ROC AUC above 0.7. The DCA findings suggest that the developed models have the potential to enhance clinical decision-making processes, thereby improving patient outcomes. The calibration curve reveals that all models except the decision tree model displayed commendable predictive performance. Through CatBoost-based modeling and SHAP analysis, the five-year survival probability is significantly influenced by several factors: the lymph node ratio (LNR), T stage, tumor size, resection margins, perineural invasion, and distant metastasis. CONCLUSIONS: This study established predictive models for survival probability at five years in RGC patients based on ML algorithms which showed high accuracy and applicative value.

Exploring the optimal indicator of short-term peridiagnosis weight dynamics to predict cancer survival: A multicentre cohort study.

BACKGROUND: Body weight and its changes have been associated with cancer outcomes. However, the associations of short-term peridiagnosis weight dynamics in standardized, clinically operational time frames with cancer survival remain largely unknown. This study aimed to screen for and evaluate the optimal indicator of short-term peridiagnosis weight dynamics to predict overall survival (OS) in patients with cancer. METHODS: This multicentre cohort study prospectively collected data from 7460 patients pathologically diagnosed with cancer between 2013 and 2019. Body weight data were recorded 1 month before, at the time of and 1 month following diagnosis. By permuting different types (point value in kg, point height-adjusted value in kg/m2, absolute change in kg or relative change in percentage) and time frames (prediagnosis, postdiagnosis or peridiagnosis), we generated 12 different weight-related indicators and compared their prognostic performance using Harrell's C-index, integrated discrimination improvement, continuous net reclassification improvement and time-dependent C-index. We analysed associations of peridiagnosis relative weight change (RWC) with OS using restricted cubic spine (RCS), Kaplan-Meier analysis and multivariable-adjusted Cox regression models. RESULTS: The study enrolled 5012 males and 2448 females, with a median age of 59 years. During a median follow-up of 37 months, 1026 deaths occurred. Peridiagnosis (1 month before diagnosis to 1 month following diagnosis) RWC showed higher prognostic performance (Harrell's C-index = 0.601, 95% confidence interval [CI] = [0.583, 0.619]) than other types of indicators including body mass index (BMI), absolute weight change, absolute BMI change, prediagnosis RWC and postdiagnosis RWC in the study population (all P < 0.05). Time-dependent C-index analysis also indicated that peridiagnosis RWC was optimal for predicting OS. The multivariable-adjusted RCS analysis revealed an N-shaped non-linear association between peridiagnosis RWC and OS (PRWC < 0.001, Pnon-linear < 0.001). Univariate survival analysis showed that the peridiagnosis RWC groups could represent distinct mortality risk stratifications (P < 0.001). Multivariable survival analysis showed that, compared with the maintenance group (weight change < 5%), the significant (gain >10%, hazard ratio [HR] = 0.530, 95% CI = [0.413, 0.680]) and moderate (gain 5-10%, HR = 0.588, 95% CI = [0.422, 0.819]) weight gain groups were both associated with improved OS. In contrast, the moderate (loss 5-10%, HR = 1.219, 95% CI = [1.029, 1.443]) and significant (loss >10%, HR = 1.280, 95% CI = [1.095, 1.497]) weight loss groups were both associated with poorer OS. CONCLUSIONS: The prognostic performance of peridiagnosis RWC is superior to other weight-related indicators in patients with cancer. The findings underscore the importance of expanding the surveillance of body weight from at diagnosis to both past and future, and conducting it within clinically operational time frames, in order to identify and intervene with patients who are at risk of weight change-related premature deaths.

Integrated neutrophil-to-lymphocyte ratio and handgrip strength better predict survival in patients with cancer cachexia.

OBJECTIVES: Systemic inflammation and skeletal muscle strength play crucial roles in the development and progression of cancer cachexia. In this study we aimed to evaluate the combined prognostic value of neutrophil-to-lymphocyte ratio (NLR) and handgrip strength (HGS) for survival in patients with cancer cachexia. METHODS: This multicenter cohort study involved 1826 patients with cancer cachexia. The NLR-HGS (NH) index was defined as the ratio of neutrophil-to-lymphocyte ratio to handgrip strength. Harrell's C index and receiver operating characteristic (ROC) curve analysis were used to assess the prognosis of NH. Kaplan-Meier analysis and Cox regression models were used to evaluate the association of NH with all-cause mortality. RESULTS: Based on the optimal stratification, 380 women (NH > 0.14) and 249 men (NH > 0.19) were classified as having high NH. NH has shown greater predictive value compared to other indicators in predicting the survival of patients with cancer cachexia according to the 1-, 3-, and 5-y ROC analysis and Harrell's C index calculation. Multivariate survival analysis showed that higher NH was independently associated with an increased risk of death (hazard ratio = 1.654, 95% confidence interval = 1.389-1.969). CONCLUSION: This study demonstrates that the NH index, in combination with NLR and HGS, is an effective predictor of the prognosis of patients with cancer cachexia. It can offer effective prognosis stratification and guidance for their treatment.

Value of the modified Patient-Generated Subjective Global Assessment in indicating the need for nutrition intervention and predicting overall survival in patients with malignant tumors in at least two organs.

BACKGROUND: Although the Patient-Generated Subjective Global Assessment (PG-SGA) is a reference standard used to assess a patient's nutrition status, it is cumbersome to administer. The aim of the present study was to estimate the value of a simpler and easier-to-use modified PG-SGA (mPG-SGA) to evaluate the nutrition status and need for intervention in patients with malignant tumors present in at least two organs. METHODS: A total of 591 patients (343 male and 248 female) were included from the INSCOC study. A Pearson correlation analysis was conducted to assess the correlation between the mPG-SGA and nutrition-related factors, with the optimal cut-off defined by a receiver operating characteristic curve (ROC). The consistency between the mPG-SGA and PG-SGA was compared in a concordance analysis. A survival analysis was used to determine the effects of nutritional intervention among different nutrition status groups. Univariable and multivariable Cox analyses were applied to evaluate the association of the mPG-SGA with the all-cause mortality. RESULTS: The mPG-SGA showed a negative association with nutrition-related factors. Individuals with an mPG-SGA ≥ 5 (rounded from 4.5) were considered to need nutritional intervention. Among the malnourished patients (mPG-SGA ≥ 5), the overall survival (OS) of those who received nutrition intervention was significantly higher than that of patients who did not. However, the OS was not significantly different in the better-nourished patients (mPG-SGA < 5). CONCLUSION: Our findings support that the mPG-SGA is a feasible tool that can be used to guide nutritional interventions and predict the survival of patients with malignant tumors affecting at least two organs.

Efficacy, Safety, and Population Pharmacokinetics of MW032 Compared With Denosumab for Solid Tumor-Related Bone Metastases: A Randomized, Double-Blind, Phase 3 Equivalence Trial.

Importance: The bioequivalence of denosumab biosimilar has yet to be studied in a 53-week, multicenter, large-scale, and head-to-head trial. A clinically effective biosimilar may help increase access to denosumab in patients with solid tumor-related bone metastases. Objectives: To establish the biosimilarity of MW032 to denosumab in patients with solid tumor-related bone metastases based on a large-scale head-to-head study. Design, Setting, and Participants: In this 53-week, randomized, double-blind, phase 3 equivalence trial, patients with solid tumors with bone metastasis were recruited from 46 clinical sites in China. Overall, 856 patients were screened and 708 eligible patients were randomly allocated to receive either MW032 or denosumab. Interventions: Patients were randomly assigned (1:1) to receive MW032 or reference denosumab subcutaneously every 4 weeks until week 49. Main Outcomes and Measures: The primary end point was percentage change from baseline to week 13 of natural logarithmic transformed urinary N-telopeptide/creatinine ratio (uNTx/uCr). Results: Among the 701 evaluable patients (350 in the MW032 group and 351 in the denosumab group), the mean (range) age was 56.1 (22.0-86.0) years and 460 patients were women (65.6%). The mean change of uNTx/uCr from baseline to week 13 was -72.0% (95% CI, -73.5% to -70.4%) in the MW032 group and -72.7% (95% CI, -74.2% to -71.2%) in the denosumab group. These percent changes corresponded to mean logarithmic ratios of -1.27 and -1.30, or a difference of 0.02. The 90% CI for the difference (-0.04 to 0.09) was within the equivalence margin (-0.13 to 0.13); the mean changes of uNTx/uCr and bone-specific alkaline phosphatase (s-BALP) at each time point were also similar during 53 weeks. The differences of uNTx/uCr change were 0.015 (95% CI, -0.06 to 0.09), -0.02 (95% CI, -0.09 to 0.06), -0.05 (95% CI, -0.13 to 0.03) and 0.001 (95% CI, -0.10 to 0.10) at weeks 5, 25, 37, and 53, respectively. The differences of s-BALP change were -0.006 (95% CI, 0.06 to 0.05), 0.00 (95% CI, -0.07 to 0.07), -0.085 (95% CI, -0.18 to 0.01), -0.09 (95% CI, -0.20 to 0.02), and -0.13 (95% CI, -0.27 to 0.004) at weeks 5, 13, 25, 37 and 53, respectively. No significant differences were observed in the incidence of skeletal-related events (-1.4%; 95% CI, -5.8% to 3.0%) or time to first on-study skeletal-related events (unadjusted HR, 0.86; P = .53; multiplicity adjusted HR, 0.87; P = .55) in the 2 groups. Conclusions and Relevance: MW032 and denosumab were biosimilar in efficacy, population pharmacokinetics, and safety profile. Availability of denosumab biosimilars may broaden the access to denosumab and reduce the drug burden for patients with advanced tumors. Trial Registration: ClinicalTrials.gov Identifier: NCT04812509.

Association of possible sarcopenia with all-cause mortality in patients with solid cancer: A nationwide multicenter cohort study.

OBJECTIVES: The concept of possible sarcopenia (PS) was recently introduced to enable timely intervention in settings without the technologies required to make a full diagnosis of sarcopenia. This study aimed to investigate the association between PS and all-cause mortality in patients with solid cancer. DESIGN: Retrospective observational study. SETTING AND PARTICIPANTS: 13,736 patients with 16 types of solid cancer who were ≥18 years old. MEASUREMENTS: The presence of both a low calf circumference (men <34 cm or women <33 cm) and low handgrip strength (men <28 kg or women <18 kg) was considered to indicate PS. Harrell's C-index was used to assess prognostic value and the association of PS with mortality was estimated by calculating multivariable-adjusted hazard ratios (HRs). RESULTS: The study enrolled 7207 men and 6529 women (median age = 57.8 years). During a median follow-up of 43 months, 3150 deaths occurred. PS showed higher Harrell's C-index (0.549, 95%CI = [0.541, 0.557]) than the low calf circumference (0.541, 95%CI = [0.531, 0.551], P = 0.037) or low handgrip strength (0.542, 95%CI = [0.532, 0.552], P = 0.026). PS was associated with increased mortality risk in both univariate (HR = 1.587, 95%CI = [1.476, 1.708]) and multivariable-adjusted models (HR = 1.190, 95%CI = [1.094, 1.293]). Sensitivity analyses showed that the association of PS with mortality was robust in different covariate subgroups, which also held after excluding those patients who died within the first 3 months (HR = 1.162, 95%CI = [1.060, 1.273]), 6 months (HR = 1.150, 95%CI = [1.039, 1.274]) and 12 months (HR = 1.139, 95%CI = [1.002, 1.296]) after enrollment. CONCLUSION: PS could independently and robustly predict all-cause mortality in patients with solid cancer. These findings imply the importance of including PS assessment in routine cancer care to provide significant prognostic information to help mitigate sarcopenia-related premature deaths.

Discovery of distinct cancer cachexia phenotypes using an unsupervised machine-learning algorithm.

OBJECTIVES: Cancer cachexia is a debilitating condition with widespread negative effects. The heterogeneity of clinical features within patients with cancer cachexia is unclear. The identification and prognostic analysis of diverse phenotypes of cancer cachexia may help develop individualized interventions to improve outcomes for vulnerable populations. The aim of this study was to show that the machine learning-based cancer cachexia classification model generalized well on the external validation cohort. METHODS: This was a nationwide multicenter observational study conducted from October 2012 to April 2021 in China. Unsupervised consensus clustering analysis was applied based on demographic, anthropometric, nutritional, oncological, and quality-of-life data. Key characteristics of each cluster were identified using the standardized mean difference. We used logistic and Cox regression analysis to evaluate 1-, 3-, 5-y, and overall mortality. RESULTS: A consensus clustering algorithm was performed for 4329 patients with cancer cachexia in the discovery cohort, and four clusters with distinct phenotypes were uncovered. From clusters 1 to 4, the clinical characteristics of patients showed a transition from almost unimpaired to mildly, moderately, and severely impaired. Consistently, an increase in mortality from clusters 1 to 4 was observed. The overall mortality rate was 32%, 40%, 54%, and 68%, and the median overall survival time was 21.9, 18, 16.7, and 13.6 mo for patients in clusters 1 to 4, respectively. Our machine learning-based model performed better in predicting mortality than the traditional model. External validation confirmed the above results. CONCLUSIONS: Machine learning is valuable for phenotype classifications of patients with cancer cachexia. Detection of clinically distinct clusters among cachexic patients assists in scheduling personalized treatment strategies and in patient selection for clinical trials.

Safety and antitumour activity of cadonilimab, an anti-PD-1/CTLA-4 bispecific antibody, for patients with advanced solid tumours (COMPASSION-03): a multicentre, open-label, phase 1b/2 trial.

BACKGROUND: Immune checkpoint inhibitors targeting PD-1 or CTLA-4 individually have shown substantial clinical benefits in the treatment of malignancies. We aimed to assess the safety and antitumour activity of cadonilimab monotherapy, a bispecific PD-1/CTLA-4 antibody, in patients with advanced solid tumours. METHODS: This multicentre, open-label, phase 1b/2 trial was conducted across 30 hospitals in China. Patients aged 18 years or older with histologically or cytologically confirmed, unresectable advanced solid tumours, unsuccessful completion of at least one previous systemic therapy, and an Eastern Cooperative Oncology Group performance status of 0 or 1 were eligible for inclusion. Patients who had previously received anti-PD-1, anti-PD-L1, or anti-CTLA-4 treatment were not eligible for inclusion. In the dose escalation phase of phase 1b, patients received intravenous cadonilimab at 6 mg/kg and 10 mg/kg every 2 weeks. In the dose expansion phase of phase 1b, cadonilimab at 6 mg/kg and a fixed dose of 450 mg were given intravenously every 2 weeks. In phase 2, cadonilimab at 6 mg/kg was administered intravenously every 2 weeks in three cohorts: patients with cervical cancer, oesophageal squamous cell carcinoma, and hepatocellular carcinoma. The primary endpoints were the safety of cadonilimab in phase 1b and objective response rate in phase 2, based on the Response Evaluation Criteria in Solid Tumors (RECIST), version 1.1. The safety analysis was done in all patients who received at least one dose of cadonilimab. Antitumour activity was assessed in the full analysis set for the cervical cancer cohort, and in all patients with measurable disease at baseline and who received at least one dose of cadonilimab in the oesophageal squamous cell carcinoma and hepatocellular carcinoma cohorts. The study is registered on ClinicalTrial.gov, NCT03852251, and closed to new participants; follow-up has been completed. FINDINGS: Between Jan 18, 2019, and Jan 8, 2021, 240 patients (83 [43 male and 40 female] in phase 1b and 157 in phase 2) were enrolled. Phase 2 enrolled 111 female patients with cervical cancer, 22 patients with oesophageal squamous cell carcinoma (15 male and seven female), and 24 patients with hepatocellular carcinoma (17 male and seven female). During dose escalation, no dose-limiting toxicities occurred. Grade 3-4 treatment-related adverse events occurred in 67 (28%) of 240 patients; the most frequent grade 3 or worse treatment-related adverse events were anaemia (seven [3%]), increased lipase (four [2%]), decreased bodyweight (three [1%]), decreased appetite (four [2%]), decreased neutrophil count (three [1%]), and infusion-related reaction (two [1%]). 17 (7%) patients discontinued treatment due to treatment-related adverse events. 54 (23%) of 240 patients reported serious treatment-related adverse events, including five patients who died (one due to myocardial infarction; cause unknown for four). In phase 2, in the cervical cancer cohort, with a median follow-up of 14·6 months (IQR 13·1-17·5), the objective response rate was 32·3% (32 of 99; 95% CI 23·3-42·5). In the oesophageal squamous cell carcinoma cohort, with a median follow-up of 17·9 months (IQR 4·0-15·1), the objective response rate was 18·2% (four of 22; 95% CI 5·2-40·3). In the hepatocellular carcinoma cohort, with a median follow-up of 19·6 months (IQR 8·7-19·8), the objective response rate was 16·7% (four of 24; 95% CI 4·7-37·4). INTERPRETATION: Cadonilimab showed an encouraging tumour response rate, with a manageable safety profile, suggesting the potential of cadonilimab for the treatment of advanced solid tumours. FUNDING: Akeso Biopharma. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

SETD2 variation correlates with tumor mutational burden and MSI along with improved response to immunotherapy.

BACKGROUND: SETD2 protects against genomic instability via maintenance of homologous recombination repair (HRR) and mismatch repair (MMR) in neoplastic cells. However, it remains unclear whether SETD2 dysfunction is a complementary or independent factor to microsatellite instability-high (MSI-H) and tumor mutational burden-high (TMB-H) for immunocheckpoint inhibitor (ICI) treatment, and little is known regarding whether this type of dysfunction acts differently in various types of cancer. METHODS: This cohort study used multidimensional genomic data of 6726 sequencing samples from our cooperative and non-public GenePlus institute from April 1 through April 10, 2020. MSIsensor score, HRD score, RNAseq, mutational data, and corresponding clinical data were obtained from the TCGA and MSKCC cohort for seven solid tumor types. RESULTS: A total of 1021 genes underwent target panel sequencing reveal that SETD2 mutations were associated with a higher TMB. SETD2 deleterious mutation dysfunction affected ICI treatment prognosis independently of TMB-H (p < 0.01) and had a lower death hazard than TMB-H in pancancer patients (0.511 vs 0.757). Significantly higher MSI and lower homologous recombination deficiency were observed in the SETD2 deleterious mutation group. Improved survival rate was found in the MSKCC-IO cohort (P < 0.0001) and was further confirmed in our Chinese cohort. CONCLUSION: We found that SETD2 dysfunction affects ICI treatment prognosis independently of TMB-H and has a lower death hazard than TMB-H in pancancer patients. Therefore, SETD2 has the potential to serve as a candidate biomarker for ICI treatment. Additionally, SETD2 should be considered when dMMR is detected by immunohistochemistry.

Sarcopenia prevalence in patients with cancer and association with adverse prognosis: A nationwide survey on common cancers.

OBJECTIVE: Although previous studies have implicated the negative outcomes of sarcopenia, evidence is limited to one or a few types of cancer. The aim of this study was to evaluate the distribution and influencing factors of sarcopenia, and explore the relationship between sarcopenia and cancer prognosis in a large oncological population. METHODS: This observational cohort study included patients diagnosed with malignant cancer between May 2011 and January 2019. Hematologic and anthropometric parameters were collected prospectively. Low skeletal muscle mass and radiodensity were diagnosed using clinical indicators, according to the two prediction models. The importance of potential risk factors for sarcopenia was estimated by subtracting the predicted degrees of freedom from the partial χ2 statistic. Hazard rates of death were calculated using the hazard function and Cox regression analyses. RESULTS: We included 13 761 patients with cancer; the prevalence of sarcopenia was 33%. The median age was 58 y and 7135 patients (52%) were men. Patients with sarcopenia had a worse nutritional status and quality of life than those without sarcopenia. Age was the most important risk factor for sarcopenia compared with body mass index or TNM stage. Additionally, patients with sarcopenia had a significantly higher and earlier peak risk for mortality. After adjusting for baseline characteristics, sarcopenia was independently associated with mortality in the research population (hazard ratio, 1.429; P < 0.001) and most cancer types. CONCLUSION: Age is the most important risk factor for sarcopenia even in patients with cancer. Sarcopenia is strongly associated with a poor quality of life and reduced overall survival.

Comparison of the performance of the GLIM criteria, PG-SGA and mPG-SGA in diagnosing malnutrition and predicting survival among lung cancer patients: A multicenter study.

BACKGROUND & AIMS: The present study aimed to compare the ability of the GLIM criteria, PG-SGA and mPG-SGA to diagnose malnutrition and predict survival among Chinese lung cancer (LC) patients. METHODS: This was a secondary analysis of a multicenter, prospective, nationwide cohort study, 6697 LC inpatients were enrolled between July 2013 and June 2020. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under the curve (AUC), and quadratic weighted Kappa coefficients were calculated to compare the ability to diagnose malnutrition. There were 754 patients who underwent follow-up for a median duration of 4.5 years. The associations between the nutritional status and survival were analyzed by the Kaplan-Meier method and multivariable Cox proportional hazard regression models. RESULTS: The median age of LC patients was 60 (53, 66), and 4456 (66.5%) were male. There were 617 (9.2%), 752 (11.2%), 1866 (27.9%), and 3462 (51.7%) patients with clinical stage Ⅰ, Ⅱ, Ⅲ, and Ⅳ LC, respectively. Malnutrition was present in 36.1%-54.2% (as evaluated using different tools). Compared with the PG-SGA (used as the diagnostic reference), the sensitivity of the mPG-SGA and GLIM was 93.7% and 48.3%; the specificity was 99.8% and 78.4%; and the AUC was 0.989 and 0.633 (P < 0.001). The weighted Kappa coefficients were 0.41 for the PG-SGA vs. GLIM, 0.44 for the mPG-SGA vs. GLIM, and 0.94 for the mPG-SGA vs PG-SGA in patients with stage Ⅰ-Ⅱ LC. These values were respectively 0.38, 0.39, and 0.93 in patients with stage Ⅲ-Ⅳ of LC. In a multivariable Cox analysis, the mPG-SGA (HR = 1.661, 95%CI = 1.348-2.046, P < 0.001), PG-SGA (HR = 1.701, 95%CI = 1.379-2.097, P < 0.001) and GLIM (HR = 1.657, 95%CI = 1.347-2.038, P < 0.001) showed similar death hazard ratios. CONCLUSIONS: The mPG-SGA provides nearly equivalent power to predict the survival of LC patients as the PG-SGA and the GLIM, indicating that all three tools are applicable for LC patients. The mPG-SGA has the potential to be an alternative replacement for quick nutritional assessment among LC patients.

Triceps skinfold-albumin index significantly predicts the prognosis of cancer cachexia: A multicentre cohort study.

BACKGROUND: The fat mass and nutritional status play important roles in the onset and progression of cancer cachexia. The present study evaluated the joint prognostic value of the fat mass, as indicated by the triceps skinfold thickness (TSF), and the serum albumin level, for mortality in patients with cancer cachexia. METHODS: We performed a multicentre cohort study including 5134 patients with cancer cachexia from January 2013 to April 2019. The sum of the TSF (mm) and serum albumin (g/L) was defined as the triceps skinfold-albumin index (TA). Harrell's C index, a time-dependent receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC) were used to evaluate the prognostic performance of the TA and other indices. Optimal stratification was used to identify the thresholds to define a low TA, and the association of the TA with all-cause mortality was evaluated using Kaplan-Meier analysis and Cox proportional hazard regression models. RESULTS: The study enrolled 2408 women and 2726 men with a median age of 58.6 years and a median follow-up of 44 months. A total of 607 women (TA < 49.9) and 817 men (TA < 45.6) were classified as having a low TA. The TA showed better discrimination performance (C index = 0.621, 95% confidence interval [CI] = 0.607-0.636) to predict mortality in patients with cancer cachexia than the handgrip strength, the nutritional risk index, the prognostic nutritional index, the controlling nutritional status index, the systemic immune-inflammation index, the modified Glasgow prognostic score, and the TSF or albumin alone in the study population (all P < 0.05). The 1-, 3- and 5-year time-dependent ROC analyses (AUC = 0.647, 0.625 and 0.630, respectively) showed that the TA had the highest prognostic value among all indices investigated (all P < 0.05). Univariate analysis showed that a lower TA was associated with an increased death hazard (hazard ratio [HR] = 1.859, 95% CI = 1.677-2.062), regardless of the sex and cancer type. Multivariable survival analysis showed that a lower TA was independently associated with an increased death hazard (HR = 1.381, 95% CI = 1.223-1.560). This association was significantly strengthened in patients who did not receive curative chemotherapy (HR = 1.491, 95% CI = 1.298-1.713), those who had higher serum total protein levels (HR = 1.469, 95% CI = 1.284-1.681) and those with better physical performance (HR = 1.453, 95% CI = 1.271-1.662). CONCLUSIONS: This study defined and evaluated a new prognostic index, the TA, which may improve the selection of intervention strategies to optimize the survival of patients with cancer cachexia.

IL-6, TNF-α and IL-12p70 levels in patients with colorectal cancer and their predictive value in anti-vascular therapy.

We aimed to analyze the levels of interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α) and interleukin-12 (IL-12p70) in colorectal cancer and evaluate the predictive significance of clinical efficacy of patients with colorectal cancer treated with anti-vascular therapy combined with chemotherapy. A retrospective study of 162 patients with colorectal cancer in Fujian Medical University Hospital was conducted from January 2019 to December 2020. A comparative analysis of the levels of IL-6, TNF-α and IL-12p70 between the two groups were studied. The relationship between the levels and the clinical characteristics of patients was observed; the factors affecting the levels of IL-6, TNF-α, and IL-12p70 in colorectal cancer patients were analyzed, and the predictive validity of the efficacy of anti-vascular therapy was evaluated. We observed that the individual expression levels of IL-6, TNF-α and IL-12p70 in the patients with colorectal cancer are related to lymph node metastasis, TNM staging, and degree of differentiation (P<0.05); however, they are irrelevant to the age, sex, and tumor location of patients with colorectal cancer (P>0.05). The multiple stepwise regression analysis indicates that lymph node metastasis and TNM staging are independent risk factors that correlate with IL-6 and IL-12p70 levels in colorectal cancer patients (P<0.01). The degree of differentiation was found to be an independent risk factor connected to TNF- α levels of patients with colorectal cancer. The change of IL-12p70 level could predict the validity of anti-vascular treatment for advanced colorectal cancer. When evaluated for combined expression, IL-6 and IL-12p70 in patients with colorectal cancer closely related to lymph node metastasis and TNM staging. IL-12p70 can be used as a predictor of anti-vascular therapy with colorectal cancer.

Time Trend of Upper Gastrointestinal Cancer Incidence in China from 1990 to 2019 and Analysis Using an Age-Period-Cohort Model.

The aim of this study was to investigate the upper gastrointestinal cancer incidence trend in China from 1990 to 2019 with Joinpoint software and to evaluate the age effect, cohort effect, and period effect using the age-period-cohort model, with the data obtained from the Global Burden of Disease, Injuries, and Risk Factors Study. The crude incidence rate (CR) of upper gastrointestinal cancer in China increased from 41.48/100,000 in 1990 to 62.64/100,000 in 2019, and the average annual percent change (AAPC) was 1.42 (p < 0.05). The age-standardized incidence rate (ASIR) decreased from 50.77/100,000 to 37.42/100,000, and the AAPC was -1.12 (p < 0.05). The net drift was -0.83 (p < 0.05), and the local drifts in the 35-79 age groups of males and all age groups of females were less than 0 (p < 0.05). The age effect showed that the upper gastrointestinal cancer onset risk gradually increased with age, the period effect was fundamentally manifested as a downward trend in onset risk after 2000, and the cohort effect indicated the decreased onset risk of the overall birth cohort after 1926. The ASIR of upper gastrointestinal cancer in China from 1990 to 2019 showed a downward trend, and the onset risk indicated the age, period, and cohort effects.

Identifying cancer cachexia in patients without weight loss information: machine learning approaches to address a real-world challenge.

BACKGROUND: Diagnosing cancer cachexia relies extensively on patient-reported historic weight, and failure to accurately recall this information can lead to severe underestimation of cancer cachexia. OBJECTIVES: The present study aimed to develop inexpensive tools to facilitate the identification of cancer cachexia in patients without weight loss information. METHODS: This multicenter cohort study included 12,774 patients with cancer. Cachexia was retrospectively diagnosed using Fearon et al.'s framework. Baseline clinical features, excluding weight loss, were modeled to mimic a situation where the patient is unable to recall their weight history. Multiple machine learning (ML) models were trained using 75% of the study cohort to predict cancer cachexia, with the remaining 25% of the cohort used to assess model performance. RESULTS: The study enrolled 6730 males and 6044 females (median age = 57.5 y). Cachexia was diagnosed in 5261 (41.2%) patients and most diagnoses were made based on the weight loss criterion. A 15-variable logistic regression (LR) model mainly comprising cancer types, gastrointestinal symptoms, tumor stage, and serum biochemistry indexes was selected among the various ML models. The LR model showed good performance for predicting cachexia in the validation data (AUC = 0.763; 95% CI: 0.747, 0.780). The calibration curve of the model demonstrated good agreement between predictions and actual observations (accuracy = 0.714, κ = 0.396, sensitivity = 0.580, specificity = 0.808, positive predictive value = 0.679, negative predictive value = 0.733). Subgroup analyses showed that the model was feasible in patients with different cancer types. The model was deployed as an online calculator and a nomogram, and was exported as predictive model markup language to permit flexible, individualized risk calculation. CONCLUSIONS: We developed an ML model that can facilitate the identification of cancer cachexia in patients without weight loss information, which might improve decision-making and lead to the development of novel management strategies in cancer care. This trial was registered at https://www.chictr.org.cn as ChiCTR1800020329.

A Randomized, Open-Label, Multicenter, Phase 3 Study of High-Dose Vitamin C Plus FOLFOX ± Bevacizumab versus FOLFOX ± Bevacizumab in Unresectable Untreated Metastatic Colorectal Cancer (VITALITY Study).

PURPOSE: To compare the efficacy and safety of high-dose vitamin C plus FOLFOX ± bevacizumab versus FOLFOX ± bevacizumab as first-line treatment in patients with metastatic colorectal cancer (mCRC). PATIENTS AND METHODS: Between 2017 and 2019, histologically confirmed patients with mCRC (n = 442) with normal glucose-6-phosphate dehydrogenase status and no prior treatment for metastatic disease were randomized (1:1) into a control (FOLFOX ± bevacizumab) and an experimental [high-dose vitamin C (1.5 g/kg/d, intravenously for 3 hours from D1 to D3) plus FOLFOX ± bevacizumab] group. Randomization was based on the primary tumor location and bevacizumab prescription. RESULTS: The progression-free survival (PFS) of the experimental group was not superior to the control group [median PFS, 8.6 vs. 8.3 months; HR, 0.86; 95% confidence interval (CI), 0.70-1.05; P = 0.1]. The objective response rate (ORR) and overall survival (OS) of the experimental and control groups were similar (ORR, 44.3% vs. 42.1%; P = 0.9; median OS, 20.7 vs. 19.7 months; P = 0.7). Grade 3 or higher treatment-related adverse events occurred in 33.5% and 30.3% of patients in the experimental and control groups, respectively. In prespecified subgroup analyses, patients with RAS mutation had significantly longer PFS (median PFS, 9.2 vs. 7.8 months; HR, 0.67; 95% CI, 0.50-0.91; P = 0.01) with vitamin C added to chemotherapy than with chemotherapy only. CONCLUSIONS: High-dose vitamin C plus chemotherapy failed to show superior PFS compared with chemotherapy in patients with mCRC as first-line treatment but may be beneficial in patients with mCRC harboring RAS mutation.