Cholesterol-modified prognostic nutritional index (CPNI) as an effective tool for assessing the nutrition status and predicting survival in patients with breast cancer.

BACKGROUND: Malnutrition is associated with poor overall survival (OS) in breast cancer patients; however, the most predictive nutritional indicators for the prognosis of patients with breast cancer are not well-established. This study aimed to compare the predictive effects of common nutritional indicators on OS and to refine existing nutritional indicators, thereby identifying a more effective nutritional evaluation indicator for predicting the prognosis in breast cancer patients. METHODS: This prospective study analyzed data from 776 breast cancer patients enrolled in the "Investigation on Nutritional Status and its Clinical Outcome of Common Cancers" (INSCOC) project, which was conducted in 40 hospitals in China. We used the time-dependent receiver operating characteristic curve (ROC), Kaplan-Meier survival curve, and Cox regression analysis to evaluate the predictive effects of several nutritional assessments. These assessments included the patient-generated subjective nutrition assessment (PGSGA), the global leadership initiative on malnutrition (GLIM), the controlling nutritional status (CONUT), the nutritional risk index (NRI), and the prognostic nutritional index (PNI). Utilizing machine learning, these nutritional indicators were screened through single-factor analysis, and relatively important variables were selected to modify the PNI. The modified PNI, termed the cholesterol-modified prognostic nutritional index (CPNI), was evaluated for its predictive effect on the prognosis of patients. RESULTS: Among the nutritional assessments (including PGSGA, GLIM, CONUT, NRI, and PNI), PNI showed the highest predictive ability for patient prognosis (time-dependent ROC = 0.58). CPNI, which evolved from PNI, emerged as the superior nutritional index for OS in breast cancer patients, with the time-dependent ROC of 0.65. It also acted as an independent risk factor for mortality (p < 0.05). Moreover, the risk of malnutrition and mortality was observed to increase gradually among both premenopausal and postmenopausal age women, as well as among women categorized as non-overweight, overweight, and obese. CONCLUSIONS: The CPNI proves to be an effective nutritional assessment tool for predicting the prognosis of patients with breast cancer.

Radiomics-based signature of breast cancer on preoperative contrast-enhanced MRI to predict axillary metastasis.

Aim: This study aimed to predict axillary metastasis using radiology features in dynamic contrast-enhanced MRI. Methods: This study included 243 breast lesions confirmed as malignant based on axillary status. Most outcome-predictive features were selected using four machine-learning algorithms. Receiver operating characteristic analysis was used to reflect diagnostic performance. Results: Least absolute shrinkage and selection operator was used to dimensionally reduce 1137 radiomics features to three features. Three optimal radiomics features were used to model construction. The logistic regression model achieved an accuracy of 97% and 85% in the training and test groups. Clinical utility was evaluated using decision curve analysis. Conclusion: The novel combination of radiomics analysis and machine-learning algorithm could predict axillary metastasis and prevent invasive manipulation.

Device-Free Multi-Location Human Activity Recognition Using Deep Complex Network.

Wi-Fi-based human activity recognition has attracted broad attention for its advantages, which include being device-free, privacy-protected, unaffected by light, etc. Owing to the development of artificial intelligence techniques, existing methods have made great improvements in sensing accuracy. However, the performance of multi-location recognition is still a challenging issue. According to the principle of wireless sensing, wireless signals that characterize activity are also seriously affected by location variations. Existing solutions depend on adequate data samples at different locations, which are labor-intensive. To solve the above concerns, we present an amplitude- and phase-enhanced deep complex network (AP-DCN)-based multi-location human activity recognition method, which can fully utilize the amplitude and phase information simultaneously so as to mine more abundant information from limited data samples. Furthermore, considering the unbalanced sample number at different locations, we propose a perception method based on the deep complex network-transfer learning (DCN-TL) structure, which effectively realizes knowledge sharing among various locations. To fully evaluate the performance of the proposed method, comprehensive experiments have been carried out with a dataset collected in an office environment with 24 locations and five activities. The experimental results illustrate that the approaches can achieve 96.85% and 94.02% recognition accuracy, respectively.

Prognostic significance of preoperative skeletal muscle status in patients with gastric cancer after radical gastrectomy.

BACKGROUND AND OBJECTIVES: The association between skeletal muscle status and gastric cancer (GC) prognosis remains unclear. Here, we investigated the impact of the skeletal muscle index (SMI) on overall survival (OS) in GC patients after radical gastrectomy. METHODS AND STUDY DESIGN: We divided 178 patients into four groups: adult men, adult women, elderly men and elderly women. The SMI, calculated using CT images, of patients was graded using cutoff values of group-specific tertiles. Age, body mass index, SMI grade, Charlson comorbidity index, surgical method (total vs distal gastrectomy), tumor stage, and histological type and differentiation were included in Cox regression models to assess the primary outcome parameter of OS. A new prognostic score for 3- year OS was established by combining the SMI grade and tumor stage, and receiver operating characteristic (ROC) curve analyses were used to determine its predictive reliability. RESULTS: For groups with high, medium, and low SMI grades, the 3-year OS rates were 94.04, 79.08 and 59.09% and 86.09, 70.11 and 49.11% (p<0.001) in patients undergoing distal and total gastrectomy, respectively. In the multivariate analysis, low SMI (hazard ratio (HR) 1.82, 95% confidence interval (CI) 1.14-2.9), advanced stage (HR 2.89, 95% CI 1.43-5.83), and total gastrectomy (HR 1.69, 95% CI 0.95-3.01) were independent risk factors for OS (p<0.010). The areas under the ROC curves for the prognostic score were 0.77 (range 0.61-0.93) and 0.76 (range 0.65-0.86) in patients undergoing distal and total gastrectomy, respectively. CONCLUSIONS: The preoperative SMI was an independent prognostic factor for long-term survival in GC patients after radical gastrectomy.

Systemic inflammation and insulin resistance-related indicator predicts poor outcome in patients with cancer cachexia.

BACKGROUND: The C-reactive protein (CRP)-triglyceride-glucose (TyG) index (CTI), which is a measure representing the level of inflammation and insulin resistance (IR), is related to poor cancer prognosis; however, the CTI has not been validated in patients with cancer cachexia. Thus, this study aimed to explore the potential clinical value of the CTI in patients with cancer cachexia. METHODS: In this study, our prospective multicenter cohort included 1411 patients with cancer cachexia (mean age 59.45 ± 11.38, 63.3% male), which was a combined analysis of multiple cancer types. We randomly selected 30% of the patients for the internal test cohort (mean age 58.90 ± 11.22% 61.4% male). Additionally, we included 307 patients with cancer cachexia in the external validation cohort (mean age 61.16 ± 11, 58.5% male). Receiver operating characteristic (ROC) and calibration curves were performed to investigate the prognostic value of CTI. The prognostic value of the CTI was also investigated performing univariate and multivariate survival analyses. RESULTS: The survival curve indicated that the CTI showed a significant prognostic value in the total, internal, and external validation cohorts. Prognostic ROC curves and calibration curves revealed that the CTI showed good consistency in predicting the survival of patients with cancer cachexia. Multivariate survival analysis showed that an elevated CTI increased the risk of death by 22% (total cohort, 95% confidence interval [CI] = 1.13-1.33), 34% (internal test cohort, 95%CI = 1.11-1.62), and 35% (external validation cohort, 95%CI = 1.14-1.59) for each increase in the standard deviation of CTI. High CTI reliably predicted shorter survival (total cohort, hazard ratio [HR] = 1.45, 95%CI = 1.22-1.71; internal test cohort, HR = 1.62, 95%CI = 1.12-2.36; external validation cohort, HR = 1.61, 95%CI = 1.15-2.26). High CTI significantly predicted shorter survival in different tumor subgroups, such as esophageal [HR = 2.11, 95%CI = 1.05-4.21] and colorectal cancer [HR = 2.29, 95%CI = 1.42-3.71]. The mediating effects analysis found that the mediating proportions of PGSGA, ECOG PS, and EORTC QLQ-C30 on the direct effects of CTI were 21.72%, 19.63%, and 11.61%, respectively We found that there was a significant positive correlation between the CTI and 90-day [HR = 2.48, 95%CI = 1.52-4.14] and 180-day mortality [HR = 1.77,95%CI = 1.24-2.55] in patients with cancer cachexia. CONCLUSION: The CTI can predict the short- and long-term survival of patients with cancer cachexia and provide a useful prognostic tool for clinical practice.

P110α inhibitor alpelisib exhibits a synergistic effect with pyrotinib and reverses pyrotinib resistant in HER2+ breast cancer.

Human epidermal growth factor receptor 2 (HER2) plays a critical role in breast cancer progression in patients with HER2 overexpression, thereby driving the development of targeted drugs and advancing therapy strategies targeting this gene. Pyrotinib is a novel irreversible pan-ErbB kinase inhibitor, primarily suppresses the downstream MAPK and PI3K/AKT pathways. Alpelisib, a selective PI3K p110α inhibitor, has been approved for clinical application in HR+, HER2-, PIK3CA mutated breast cancers and is also being developed for use in other breast cancer subtypes. In this study, we hypothesised that combining pyrotinib with alpelisib would yield superior results compared to single-drug treatment. Our data demonstrated that the combination of alpelisib and pyrotinib exhibited a synergistic effect in HER2+ breast cancer both in vitro and in vivo. This combination led to decreased cell proliferation and migration, G0-G1 cell cycle arrest, and increased apoptosis rates. Additionally, the deactivation of ErbB receptors and sustained activation of PI3K/AKT pathway by upstream compensatory pathways induced acquired pyrotinib resistant cells resistant to pyrotinib treatment, thus alpelisib combined with pyrotinib showed a tremendous synergistic effect and reverse pyrotinib resistance in acquired pyrotinib resistant cells by suppressing the activated PI3K/AKT pathway. Our results revealed a combination of pyrotinib and alpelisib as an effective therapeutic strategy in treating HER2+ breast cancer, whether sensitive or resistant to pyrotinib treatment.

LINC00891 promotes tumorigenesis and metastasis of thyroid cancer by regulating SMAD2/3 via EZH2.

BACKGROUND: Thyroid cancer (TC), the most common endocrine malignant tumor, is increasingly causing a huge threat to our health nowadays. METHODS: To explore the tumorigenesis mechanism of thyroid cancer, we identified that long intergenic non-coding RNA-00891 (LINC00891) was upregulated in TC using the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and local databases. LINC00891 expression correlated with histological type and lymph node metastasis (LNM). The high expression of LINC00891 could serve as a diagnostic marker for TC and its LNM. In vitro experiments demonstrated that LINC00891 knockdown could inhibit cell proliferation, migration, invasion apoptosis, and of TC cells. We also investigated the related mechanisms of LINC00891 promoting TC progression using RNA sequencing, Gene Set Enrichment Analysis, and Western blotting. RESULTS: Our experiments demonstrated that LINC00891 promoted TC progression via the EZH2-SMAD2/3 signaling axis. In addition, overexpression of EZH2 could reverse the suppressive epithelial-to-mesenchymal transition (EMT) caused by LINC00891 knockdown. CONCLUSION: In conclusion, the LINC00891/EZH2/SMAD2/3 regulatory axis participated in tumorigenesis and metastasis of thyroid cancer, which may provide a novel target for treatment.

Prognostic Power of Nutrition-Inflammation Indicators in Patients With Breast Cancer.

BACKGROUND: Inflammation and nutritional statuses are closely related to the survival of patients with cancer. Breast cancer is the one with low level of inflammation and low risk of malnutrition. Does inflammation burden and nutrition status affect the prognosis of patients with breast cancer? METHODS: Totally 1158 patients with breast cancer from Nutrition Status and its Clinical Outcome of Common Cancers study were included, 15 nutrition-inflammation indicators (NIIs) from literatures were adopted in this study. Area under the curve and C-index were used to compare the predictive value of 15 NIIs in overall patients and subgroup in different menstrual statuses. RESULTS: Nutrition status indicators prognostic nutritional index, controlling nutritional status score, glucose-to-lymphocyte ratio among 15 NIIs were found to be significantly associated with prognosis of breast cancer, and remained stable in patients in different menstrual statuses. The C-index of inflammation indicators lymphocyte-to-C-reactive protein ratio, lymphocyte-C-reactive protein ratio score, and C-reaction protein (CRP) increased with age, but the predictive value of 3 inflammation indicators did not exceed the value of nutritional indicators throughout the whole life of patients with breast cancer. CONCLUSIONS: Prognostic nutritional index, controlling nutritional status score, glucose-to-lymphocyte ratio had better predictive value for the survival of patients with breast cancer. Nutritional indicators surpassed inflammation indicators in prognostic ability for patients in different menstrual statuses. These results provide an important insight for the care of patients with breast cancer.

In silico development and in vitro validation of a novel five-gene signature for prognostic prediction in colon cancer.

Colon cancer is one of the most common cancers in digestive system, and its prognosis remains unsatisfactory. Therefore, this study aimed to identify gene signatures that could effectively predict the prognosis of colon cancer patients by examining the data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. LASSO-Cox regression analysis generated a five-gene signature (DCBLD2, RAB11FIP1, CTLA4, HOXC6 and KRT6A) that was associated with patient survival in the TCGA cohort. The prognostic value of this gene signature was further validated in two independent GEO datasets. GO enrichment revealed that the function of this gene signature was mainly associated with extracellular matrix organization, collagen-containing extracellular matrix, and extracellular matrix structural constituent. Moreover, a nomogram was established to facilitate the clinical application of this signature. The relationships among the gene signature, mutational landscape and immune infiltration cells were also investigated. Importantly, this gene signature also reliably predicted the overall survival in IMvigor210 anti-PD-L1 cohort. In addition to the bioinformatics study, we also conducted a series of in vitro experiments to demonstrate the effect of the signature genes on the proliferation, migration, and invasion of colon cancer cells. Collectively, our data demonstrated that this five-gene signature might serve as a promising prognostic biomarker and shed light on the development of personalized treatment in colon cancer patients.

Inflammatory geriatric nutritional risk index stratified the survival of older adults with cancer sarcopenia.

BACKGROUND: Aging is accompanied by muscle loss. In older adults with cancer sarcopenia (OACS), systemic inflammation, reduced food intake, and reduced physical activity led to a poor prognosis. This study was to investigate the prognostic ability of the inflammatory Geriatric Nutritional Risk Index (GNRI), which combines patient's inflammation, diet status, and physical activity status to predict overall survival of OACS. METHODS: This prospective multi-center study enrolled 637 OACS, with an average age of 72.78 ± 5.98 years, of which 408 (64.1%) were males. We constructed the Inflammatory Functional Prognostic Index (IFPI) of OACS based on inflammatory GNRI scores, reduced food intake, and reduced physical activity. According to the IFPI, OACS was divided into high-, moderate-, and low-risk groups. Univariate and multivariate survival analyses analyzed the prognostic ability of the clinical parameters. RESULTS: Compared with OACS with a high GNRI score, the 1-, 3-, and 5-year hazard ratios (95% confidence interval) of OACS with a low GNRI score was 1.816 (1.076-3.063), 1.678 (1.118-2.518), and 1.627 (1.101-2.407), respectively. This result was consistent with that of the calibration curve. The subgroup analysis showed that the low GNRI score had a significant positive relation with patients with gastrointestinal cancer (Pinteraction < 0.001). Notably, the survival analysis of IFPI showed that the mortality risk of moderate- and high-risk patients was 1.722-and 2.509-fold higher, respectively, than that of low-risk patients. CONCLUSION: The GNRI score was a short-term and long-term inflammatory prognostic indicator for OACS. The IFPI score could improve patient survival prediction.

Systemic inflammation with sarcopenia predicts survival in patients with gastric cancer.

OBJECTIVE: The levels of platelet-related inflammation indicators and sarcopenia have been reported to affect the survival of patients with cancer. To evaluate the prognostic influence of platelet count (PLT), platelet lymphocyte ratio (PLR), and systemic immune inflammation index (SII), and SII combined with sarcopenia on the survival of patients with gastric cancer (GC). METHODS: A total of 1133 patients with GC (812 male and 321 female, average age: 59.43 years) were evaluated. Receiver-operating characteristic curves were used to determine the best cutoff values of PLT, PLR, and SII, and univariate and multivariate Cox risk regression models were used to evaluate whether SII is an independent predictor of overall survival (OS). The prognostic SS (SII-sarcopenia) was established based on SII and sarcopenia. Finally, a comprehensive analysis of the prognostic SS was performed. RESULTS: SII had the strongest prognostic effect. The SII and OS of patients with GC were in an inverted U-shape (adjusted HR = 1.07; 95% CI 0.97-1.19; adjusted P = 0.179). In patients with SII > 1800, SII was negatively correlated with OS (adjusted HR = 0.57; 95% CI 0.29-1.12; adjusted P = 0.102), however, there is no statistical difference. Interestingly, a high SS was associated with a poorer prognosis. The higher the SS score was, the worse the OS (P < 0.001). CONCLUSION: SII is an independent prognostic indicator of GC, and high SII is related to poor prognosis. A higher SS score had worse survival. Thus, the prognostic SS is a reliable predictor of OS in patients with GC.

The prognostic value of the combination of body composition and systemic inflammation in patients with cancer cachexia.

BACKGROUND: Changes in body composition and systemic inflammation are important characteristics of cancer cachexia. This multi-centre retrospective study aimed to explore the prognostic value of the combination of body composition and systemic inflammation in patients with cancer cachexia. METHODS: The modified advanced lung cancer inflammation index (mALI), which combines body composition and systemic inflammation, was defined as appendicular skeletal muscle index (ASMI) × serum albumin/neutrophil-lymphocyte ratio. The ASMI was estimated according to a previously validated anthropometric equation. Restricted cubic splines were used to evaluate the relationship between mALI and all-cause mortality in patients with cancer cachexia. Kaplan-Meier analysis and Cox proportional hazard regression analysis were used to evaluate the prognostic value of mALI in cancer cachexia. A receiver operator characteristic curve was used to compare the effectiveness of mALI and nutritional inflammatory indicators in predicting all-cause mortality in patients with cancer cachexia. RESULTS: A total of 2438 patients with cancer cachexia were enrolled, including 1431 males and 1007 females. The sex-specific optimal cut-off values of mALI for males and females were 7.12 and 6.52, respectively. There was a non-linear relationship between mALI and all-cause mortality in patients with cancer cachexia. Low mALI was significantly associated with poor nutritional status, high tumour burden, and high inflammation. Patients with low mALI had significantly lower overall survival (OS) than those with high mALI (39.5% vs. 65.5%, P < 0.001). In the male population, OS was significantly lower in the low mALI group than in the high group (34.3% vs. 59.2%, P < 0.001). Similar results were also observed in the female population (46.3% vs. 75.0%, P < 0.001). mALI was an independent prognostic factor for patients with cancer cachexia (hazard ratio [HR] = 0.974, 95% confidence interval [CI] = 0.959-0.990, P = 0.001). For every standard deviation [SD] increase in mALI, the risk of poor prognosis for patients with cancer cachexia was reduced by 2.9% (HR = 0.971, 95%CI = 0.943-0.964, P < 0.001) in males and 8.9% (HR = 0.911, 95%CI = 0.893-0.930, P < 0.001) in females. mALI is an effective complement to the traditional Tumour, Lymph Nodes, Metastasis (TNM) staging system for prognosis evaluation and a promising nutritional inflammatory indicator with a better prognostic effect than the most commonly used clinical nutritional inflammatory indicators. CONCLUSIONS: Low mALI is associated with poor survival in both male and female patients with cancer cachexia and is a practical and valuable prognostic assessment tool.

Association between C-reactive protein-albumin-lymphocyte (CALLY) index and overall survival in patients with colorectal cancer: From the investigation on nutrition status and clinical outcome of common cancers study.

Background: Colorectal cancer (CRC) is among the most common malignant cancers worldwide, and its development is influenced by inflammation, nutrition, and the immune status. Therefore, we combined C-reactive protein (CRP), albumin, and lymphocyte, which could reflect above status, to be the CRP-albumin-lymphocyte (CALLY) index, and evaluated its association with overall survival (OS) in patients with CRC. Methods: The clinicopathological and laboratory characteristics of 1260 patients with CRC were collected from the Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) study. Cox regression analysis was performed to assess the association between the CALLY index and OS. A nomogram including sex, age, the CALLY index and TNM stage was constructed. The Concordance Index (C-index) was utilized to evaluate the prognostic value of the CALLY index and classical CRC prognostic factors, such as modified Glasgow prognostic score (mGPS), neutrocyte to lymphocyte ratio (NLR), systemic immune inflammation index (SII), and platelet to lymphocyte ratio (PLR), as well as to assess the prognostic value of the nomogram and TNM stage. Results: Multivariate Cox regression analyses demonstrated that the CALLY index was independently associated with OS in patients with CRC [Hazard ratio (HR) = 0.91, 95% confidence interval (CI) = 0.87-0.95, P<0.001]. The CALLY index showed the highest prognostic value (C-index = 0.666, 95% CI = 0.638-0.694, P<0.001), followed by mGPS, NLR, SII, and PLR. The nomogram demonstrated higher prognostic value (C-index = 0.784, 95% CI = 0.762-0.807, P<0.001) than the TNM stage. Conclusion: The CALLY index was independently associated with OS in patients with CRC and showed higher prognostic value than classical CRC prognostic factors. The nomogram could provide more accurate prognostic prediction than TNM stage.

Comprehensive prognostic effects of systemic inflammation and Insulin resistance in women with breast cancer with different BMI: a prospective multicenter cohort.

To investigate the prognostic value of systemic inflammation and insulin resistance in women with breast cancer with different body mass index (BMI). This multicenter, prospective study included 514 women with breast cancer. Multivariate survival analysis showed that patients with high C-reactive protein (CRP), high CRP to albumin ratio (CAR), high lymphocyte to CRP ratio (LCR), high low-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (LHR), and high triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-c) were significantly associated with worse prognosis. The mortality rate of patients with both high CAR and high LHR or both low LCR and high LHR were 3.91-fold or 3.89-fold higher than patients with both low CAR and low LHR or both high LCR and low LHR, respectively. Furthermore, the combination of LCR and LHR significantly predicted survival in patients within the high BMI group. The CRP, CAR, LCR, LHR, and TG/HDL-c were associated with poor survival in women with breast cancer. The combination of CAR and LHR or LCR and LHR could better predict the prognostic outcomes of women with breast cancer, while the combination of LCR and LHR could better predict the prognosis of those patients with overweight or obese patients.

The combination of hand grip strength and modified Glasgow prognostic score predicts clinical outcomes in patients with liver cancer.

Purpose: Previous studies have shown that both hand grip strength (HGS) and the modified Glasgow Prognostic Score (mGPS) are associated with poor clinical outcomes in patients with liver cancer. In spite of this, no relevant studies have been conducted to determine whether the combination of HGS and mGPS can predict the prognosis of patients with liver cancer. Accordingly, this study sought to explore this possibility. Methods: This was a multicenter study of patients with liver cancer. Based on the optimal HGS cutoff value for each sex, we determined the HGS cutoff values. The patients were divided into high and low HGS groups based on their HGS scores. An mGPS of 0 was defined as low mGPS, whereas scores higher than 0 were defined as high mGPS. The patients were combined into HGS-mGPS groups for the prediction of survival. Survival analysis was performed using Kaplan-Meier curves. A Cox regression model was designed and adjusted for confounders. To evaluate the nomogram model, receiver operating characteristic curves and calibration curves were used. Results: A total of 504 patients were enrolled in this study. Of these, 386 (76.6%) were men (mean [SD] age, 56.63 [12.06] years). Multivariate analysis revealed that patients with low HGS and high mGPS had a higher risk of death than those with neither low HGS nor high mGPS (hazard ratio [HR],1.50; 95% confidence interval [CI],1.14-1.98; p = 0.001 and HR, 1.55; 95% CI, 1.14-2.12, p = 0.001 respectively). Patients with both low HGS and high mGPS had 2.35-fold increased risk of death (HR, 2.35; 95% CI, 1.52-3.63; p < 0.001). The area under the curve of HGS-mGPS was 0.623. The calibration curve demonstrated the validity of the HGS-mGPS nomogram model for predicting the survival of patients with liver cancer. Conclusion: A combination of low HGS and high mGPS is associated with poor prognosis in patients with liver cancer. The combination of HGS and mGPS can predict the prognosis of liver cancer more accurately than HGS or mGPS alone. The nomogram model developed in this study can effectively predict the survival outcomes of liver cancer.

Prognostic value of systemic inflammation and for patients with colorectal cancer cachexia.

BACKGROUND: The development and progression of cancer cachexia are connected to systemic inflammation and physical performance. However, few relevant studies have reported the survival outcomes prediction of systemic inflammation and physical performance in patients with colorectal cancer (CRC) cachexia. This study investigated the prognostic prediction value of systemic inflammation and performance status in patients with CRC cachexia. METHODS: This multicentre cohort study prospectively collected 905 patients with CRC (58.3% males, 59.3 ± 11.5 years old). Cancer cachexia was diagnosed according to the 2011 Fearon Cachexia Diagnostic Consensus. The prognostic value of systematic inflammatory indicators was determined using the area under the curve, concordance index, and multivariate survival analysis. Performance status was evaluated with Eastern Coopertive Oncology Group performance score (ECOG-PS). Survival data were analysed using univariate and multivariate Cox regression analyses. RESULTS: The area under the curve, concordance index and survival analysis showed that C-reactive protein (CRP), lymphocyte to CRP ratio (LCR) and CRP to albumin ratio (CAR) were more stable and consistent with the survival of patients with CRC, both in non-cachexia and cachexia populations. Among patients with CRC cachexia, high inflammation [low LCR, hazard ratio (HR) 95% confidence interval (95% CI) = 3.33 (2.08-5.32); high CAR, HR (95% CI) = 2.92 (1.88-4.55); high CRP, HR (95% CI) = 3.12 (2.08-4.67)] indicated a worse prognosis, compared with non-cachexia patients [low LCR, HR (95% CI) = 2.28 (1.65-3.16); high CAR, HR (95% CI) = 2.36 (1.71-3.25); high CRP, HR (95% CI) = 2.58 (1.85-3.60)]. Similarly, among patients with CRC cachexia, high PS [ECOG-PS 2, HR (95% CI) = 1.61 (1.04-2.50); ECOG-PS 3/4, HR (95% CI) = 2.91 (1.69-5.00]) indicated a worse prognosis, compared with patients with CRC without cachexia [ECOG-PS 2, HR (95% CI) = 1.28 (0.90-1.81); ECOG-PS 3/4, HR (95% CI) = 2.41 (1.32-4.39]). Patients with CRC cachexia with an ECOG-PS score of 2 or 3-4 and a high inflammation had a shorter median survival time, compared with patients with an ECOG-PS score of 0/1 and a low inflammation. CONCLUSIONS: The systemic inflammatory markers LCR, CAR and CRP have stable prognostic values in patients with CRC. The ECOG-PS may be an independent risk factor for CRC. Combined evaluation of systemic inflammation and ECOG-PS in patients with CRC cachexia could provide a simple survival prediction.

AIWW: a new nutrition-screening tool for the oncologic population.

Malnutrition is a common comorbidity among patients with cancer. However, no nutrition-screening tool has been recognized in this population. A quick and easy screening tool for nutrition with high sensitivity and easy-to-use is needed. Based on the previous 25 nutrition-screening tools, the Delphi method was made by the members of the Chinese Society of Nutritional Oncology to choose the most useful item from each category. According to these results, we built a nutrition-screening tool named age, intake, weight, and walking (AIWW). Malnutrition was defined based on the scored patient-generated subjective global assessment (PG-SGA). Concurrent validity was evaluated using the Kendall tau coefficient and kappa consistency between the malnutrition risks of AIWW, nutritional risk screening 2002 (NRS-2002), and malnutrition screening tool (MST). Clinical benefit was calculated by the decision curve analysis (DCA), integrated discrimination improvement (IDI), and continuous net reclassification improvement (cNRI). A total of 11,360 patients (male, n=6,024 (53.0%) were included in the final study cohort, and 6,363 patients had malnutrition based on PG-SGA. Based on AIWW, NRS-2002, and MST, 7,545, 3,469, and 1,840 patients were at risk of malnutrition, respectively. The sensitivities of AIWW, NRS-2002, and MST risks were 0.910, 0.531, and 0.285, and the specificities were 0.768, 0.946, and 0.975. The Kendall tau coefficients of AIWW, NRS-2002, and MST risks were 0.588, 0.501, and 0.326, respectively. The area under the curve of AIWW, NRS-2002, and MST risks were 0.785, 0.739, and 0.630, respectively. The IDI, cNRI, and DCA showed that AIWW is non-inferior to NRS-2002 (IDI: 0.002 (-0.009, 0.013), cNRI: -0.015 (-0.049, 0.020)). AIWW scores can also predict the survival of patients with cancer. The missed diagnosis rates of AIWW, NRS-2002, and MST were 0.09%, 49.0%, and 73.2%, respectively. AIWW showed a better nutrition-screening effect than NRS-2002 and MST for patients with cancer and could be recommended as an alternative nutrition-screening tool for this population.

Novel Diagnostic and Prognostic Tools for Lung Cancer Cachexia: Based on Nutritional and Inflammatory Status.

Background: Cachexia is one of the most common complications affecting lung cancer patients that seriously affects their quality-of-life and survival time. This study aimed to analyze the predictors and prognostic factors of lung cancer cachexia as well as to develop a convenient and accurate clinical prediction tool for oncologists. Methods: In this multicenter cohort study, 4022 patients with lung cancer were retrospectively analyzed. The patients were randomly categorized into training and verification sets (7:3 ratio). Univariate and multivariate logistic regression analyses were performed to determine the risk factors of cachexia in patients with lung cancer. Cox regression analysis was applied to determine independent prognostic factors in the patients with lung cancer cachexia. Meanwhile, two nomograms were established and evaluated by time-dependent receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA). Results: Stage, serum albumin, ALI, anemia, and surgery were independent risk factors for cachexia in patients with lung cancer. Patients with lung cancer cachexia have a shorter survival time. Sex, stage, serum albumin, ALI, KPS score, and surgery served as independent prognostic factors for patients with lung cancer cachexia. The area under the curves (AUCs) of diagnostic nomogram in the training and validation sets were 0.702 and 0.688, respectively, the AUCs of prognostic nomogram in the training set for 1-, 3-, and 5-year were 0.70, 0.72, and 0.75, respectively, while in the validation set the AUCs were 0.71, 0.75, and 0.79, respectively. The calibration curves and DCA of the two nomograms were consistent and the clinical benefit rate was high. Conclusion: Cachexia brings an additional economic burden and worsens the prognosis of lung cancer patients. The two nomograms can accurately screen and predict the probability of occurrence of cachexia in lung cancer and the prognosis of patients with lung cancer cachexia, and guide clinical work.

Comprehensive comparative analysis of prognostic value of serum systemic inflammation biomarkers for colorectal cancer: Results from a large multicenter collaboration.

Background: The incidence of colorectal cancer (CRC) is common and reliable biomarkers are lacking. We aimed to systematically and comprehensively compare the ability of various combinations of serum inflammatory signatures to predict the prognosis of CRC. Moreover, particular attention has been paid to the clinical feasibility of the newly developed inflammatory burden index (IBI) as a prognostic biomarker for CRC. Methods: The discrimination capacity of the biomarkers was compared using receiver operating characteristic curves and Harrell's C-index. Kaplan-Meier curves and log-rank tests were used to compare survival differences between the groups. Cox proportional hazard regression analysis was used to determine the independent prognostic factors. Logistic regression analysis was used to assess the relationship between IBI, short-term outcomes, and malnutrition. Results: IBI had the optimal prediction accuracy among the systemic inflammation biomarkers for predicting the prognosis of CRC. Taking IBI as a reference, none of the remaining systemic inflammation biomarkers showed a gain. Patients with high IBI had significantly worse overall survival than those with low IBI (56.7% vs. 80.2%; log-rank P<0.001). Multivariate Cox regression analysis showed that continuous IBI was an independent risk factor for the prognosis of CRC patients (hazard ratio = 1.165, 95% confidence interval [CI] = 1.043-1.302, P<0.001). High IBI was an independent risk factor for short-term outcomes (odds ratio [OR] = 1.537, 95% CI = 1.258-1.878, P<0.001), malnutrition (OR = 2.996, 95% CI = 1.471-6.103, P=0.003), and recurrence (OR = 1.744, 95% CI = 1.176-2.587, p = 0.006) in CRC patients. Conclusions: IBI, as a reflection of systemic inflammation, is a feasible and promising biomarker for assessing the prognosis of CRC patients.

Prognostic Roles of Inflammation- and Nutrition-Based Indicators for Female Patients with Cancer.

Purpose: The incidence, progression, and prognosis of cancer could be affected by inflammation and nutrition. Female patients have different inflammatory and nutritional states depending on their age and tumor types. It is important to screen for suitable prognostic indicators in female patients with cancer of different ages and tumor types. Patients and Methods: Baseline clinicopathologic and laboratory characteristics of 1502 female patients with cancer were obtained from a multicenter cohort study. Concordance indices (C-indices) were used to evaluate the prediction accuracy of following inflammation- and nutrition-based indicators: advanced lung cancer inflammation index (ALI), systemic immune inflammation index (SII), modified geriatric nutritional risk index (mGNRI), albumin-to-globulin ratio (AGR), prognostic nutritional index (PNI), lymphocyte-to-C-reactive protein ratio (LCR), controlling nutritional status score (CONUT), modified Glasgow prognostic score (mGPS), and lymphocyte-to-C-reactive protein score (LCS). Results: The most suitable indicators in different female populations with cancer had C-indices as follows: LCR (0.668; 95% CI, 0.644-0.693) for all females; AGR (0.681; 95% CI, 0.619-0.743) for young females; LCR (0.667; 95% CI, 0.628-0.706) for middle-aged females; ALI (0.597; 95% CI, 0.574-0.620) for elderly females; LCR (0.684; 95% CI, 0.621-0.747) for females with reproductive system cancer; and ALI (0.652; 95% CI, 0.624-0.680) for females with non-reproductive system cancer. Conclusion: The most suitable indicators for the different female populations with cancer are summarized as follows: LCR for all females, AGR for young females, LCR for middle-aged females, ALI for elderly females, LCR for females with reproductive system cancer, and ALI for females with non-reproductive system cancer.