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Background and aims: The impact of lipids on the overall survival (OS) of patients with malignancy has not yet been clarified. This study aimed to evaluate the effect of hyperlipidemia on the OS among Chinese patients based on Body Mass Index (BMI) stratifications and hyperlipidemia types. Method: The patients in this study were derived from the Investigation of the Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) trial. Kaplan–Meier was used to draw the survival curve, and the log-rank test was used to estimate the survival rates between each group. Cox proportional hazards regression models were used to estimate the hazard ratios (HR) and 95% confidence intervals (CI). Results: A total of 9054 patients were included in the final study, with a median age of 59 years, and 55.3% (5004) of them were males. Regarding types of hyperlipidemia, only low high-density lipoprotein was an independent risk factor for the prognosis of all patients (HR = 1.35, 95% CI: 1.25–1.45, P < 0.001), while high total cholesterol (HR = 1.01, 95% CI: 0.90–1.15, P = 0.839) and high low-density lipoprotein (HR = 1.03, 95%CI: 0.91–1.16, P = 0.680) were not. In terms of BMI stratification, the effect of triglycerides on prognosis varied; high triglycerides were an independent risk factor for the prognosis of underweight patients (HR = 1.56, 95% CI:1.05–2.32, P = 0.027) and a protective factor for overweight patients (HR = 0.75, 95% CI: 0.63–0.89, P = 0.001). However, for normal-weight patients, there was no significant statistical difference (HR = 0.88, 95%CI: 0.75–1.03, P = 0.108). Conclusions: The impact of hyperlipidemia on the OS among patients with cancer varied by different BMI and hyperlipidemia types. BMI and hyperlipidemia type ought to be considered in combination to estimate the prognosis of patients with malignancy. [ABSTRACT FROM AUTHOR]

Background: As gastric cancer patients aged ≥ 85 years have a short life expectancy and often die from other diseases such as pneumonia, indications for surgery are controversial. In this study, we retrospectively analyzed the prognostic factors of elderly patients with gastric cancer who are candidates for curative gastrectomy. Methods: Among 114 patients aged ≥ 85 years with gastric cancer at our hospital between 2010 and 2019, prognostic factors were examined using the Cox proportional hazards model in 76 patients excluding those with cStage IVB or endoscopic submucosal dissection. We also analyzed the factors of pneumonia death. Results: cStage was I/IIA/IIB/III/IVA in 37/6/14/14/5 patients, respectively. Treatment included distal gastrectomy in 28 patients, total gastrectomy in 6, local resection in 9, others in 3, and no surgery in 30. In univariate analyses of overall survival, Eastern Cooperative Oncology Group Performance Status, physiological score of Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM), Onodera's prognostic nutritional index, cStage, and treatment were prognostic factors. In a multivariate analysis, POSSUM physiological score, cStage, treatment method {no surgery vs. distal gastrectomy: hazard ratio (HR) 5.78, 95% confidence interval (CI) 2.33–14.3}, (total gastrectomy vs. distal gastrectomy: HR 4.26, 95% CI 1.22–14.9) were independent prognostic factors. In univariate analyses of pneumonia-specific survival, treatment (total gastrectomy vs. distal gastrectomy: HR 6.98, 95% CI 1.18–41.3) was the only prognostic factor. Conclusions: The prognosis of distal gastrectomy was better than that of non-surgery even in patients aged ≥ 85 years. However, total gastrectomy was considered to be avoidable due to the high rate of postoperative pneumonia death. [ABSTRACT FROM AUTHOR]

Background: Human Papillomavirus-associated oropharyngeal cancer (HPV-OPC) incidence is increasing among men in the United States. Poor dental health has previously been associated with risk of head and neck cancers, oral HPV infection, and persistence but it is not understood whether dental health is associated with outcomes. We sought to determine the association of dental health with progression free survival and overall mortality among men with an HPV-OPC. Methods: A cross sectional study of men diagnosed with HPV-OPC between 2014–2020 at Moffitt Cancer Center in Tampa, FL was conducted. Dental records were abstracted for assessment of dental fitness prior to cancer treatment. Five dental factors including number of teeth lost, pocket depth, gingival score, loss of attachment, and bone loss were individually examined. Risk factor and outcome data were collected from a patient risk questionnaire and medical record. Using item response theory, an overall dental fitness score from five dental factors was developed in which missing data were multiply imputed. Cox proportional hazards model was used to assess whether dental factors were associated with progression-free survival or overall mortality. Results: Among 206 HPV-OPC cases, median follow-up was 3.4 years (IQR: 2.4–4.4) during which 40 cases involved progression or mortality and 25 deaths occurred. Overall dentition was significantly associated with progression free survival (p = 0.04) and with overall survival (p = 0.03) though findings were not significant after adjustment for age at diagnosis, stage, and smoking history (p = 0.146 and p = 0.120, respectively). A pocket depth of 7 mm or more was associated with overall survival (HR: 5.21; 95% CI: 1.43—19.11) and this remained significant after adjustment for confounding (aHR: 4.14; 95% CI: 1.72—16.26). Conclusions: Among men diagnosed with an HPV-associated OPC in the US, worse dental health was associated with reduced progression free survival and overall survival, but not after adjustment for confounders. Further studies are needed to examine whether dental health is associated with other prognostic factors and subsequent treatment-related outcomes. [ABSTRACT FROM AUTHOR]

Background: Breast cancer-related leptomeningeal disease (BC-LMD) is a dire diagnosis for 5–8% of patients with breast cancer (BC). We conducted a retrospective review of BC-LMD patients diagnosed at Moffitt Cancer Center from 2011 to 2020, to determine the changing incidence of BC-LMD, factors which are associated with the progression of BC CNS metastasis to BC-LMD, and factors which are associated with OS for patients with BC-LMD. Methods: Patients with BC and brain/spinal metastatic disease were identified. For those who eventually developed BC-LMD, we used Kaplan–Meier survival curve, log-rank test, univariable, and multivariate Cox proportional hazards regression model to identify factors affecting time from CNS metastasis to BC-LMD and OS. Results: 128 cases of BC-LMD were identified. The proportion of BC-LMD to total BC patients was higher between 2016 and 2020 when compared to 2011–2015. Patients with HR+ or HER2 + BC experienced longer times between CNS metastasis and LMD than patients with triple-negative breast cancer (TNBC). Systemic therapy and whole-brain radiation therapy (WBRT) was associated with prolonged progression to LMD in all patients. Hormone therapy in patients with HR + BC were associated with a delayed BC-CNS metastasis to LMD progression. Lapatinib treatment was associated with a delayed progression to LMD in patients with HER2 + BC. Patients with TNBC-LMD had shorter OS compared to those with HR + and HER2 + BC-LMD. Systemic therapy, intrathecal (IT) therapy, and WBRT was associated with prolonged survival for all patients. Lapatinib and trastuzumab therapy was associated with improved OS in patients with HER2 + BC-LMD. Conclusions: Increasing rates of BC-LMD provide treatment challenges and opportunities for clinical trials. Prospective trials testing lapatinib and/or similar tyrosine kinase inhibitors, IT therapies, and combination treatments are urgently needed. [ABSTRACT FROM AUTHOR]

Background: Some biomarkers collected from routine laboratory tests have shown important value in cancer prognosis. The study aimed to evaluate the prognostic significance of routine laboratory biomarkers in patients with endometrial cancer (EC) and to develop credible prognostic nomogram models for clinical application. Methods: A total of 727 patients were randomly divided into a training set and a validation set. Cox proportional hazards models were used to evaluate each biomarker's prognostic value, and independent prognostic factors were used to generate overall survival (OS) and progression-free survival (PFS) nomgrams. The efficacy of the nomograms were evaluated by Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves, decision curve analysis (DCA), calibration curves, X-tile analysis and Kaplan‒Meier curves. Results: Ten significant biomarkers in multivariate Cox analysis were integrated to develop OS and PFS nomograms. The C-indices of the OS- nomogram in the training and validation sets were 0.885 (95% confidence interval (CI), 0.810–0.960) and 0.850 (95% CI, 0.761–0.939), respectively; those of the PFS- nomogram in the training and validation sets were 0.903 (95% CI, 0.866–0.940) and 0.825 (95% CI, 0.711–0.939), respectively. ROC, DCA and calibration curves showed better clinical application value for the nomograms incorporating routine laboratory biomarkers. X-tile analysis and Kaplan‒Meier curves showed that the nomograms were stable and credible in evaluating patients at different risks. Conclusions: Nomogram models incorporating routine laboratory biomarkers, including NLR, MLR, fibrinogen, albumin and AB blood type, were demonstrated to be simple, reliable and favourable in predicting the outcomes of patients with EC. [ABSTRACT FROM AUTHOR]

Summary: Background: To compare the ability of the Cox regression and machine learning algorithms to predict the survival of patients with Anaplastic thyroid carcinoma (ATC). Methods: Patients diagnosed with ATC were extracted from the Surveillance, Epidemiology, and End Results database. The outcomes were overall survival (OS) and cancer-specific survival (CSS), divided into: (1) binary data: survival or not at 6 months and 1 year; (2): time-to-event data. The Cox regression method and machine learnings were used to construct models. Model performance was evaluated using the concordance index (C-index), brier score and calibration curves. The SHapley Additive exPlanations (SHAP) method was deployed to interpret the results of machine learning models. Results: For binary outcomes, the Logistic algorithm performed best in the prediction of 6-month OS, 12-month OS, 6-month CSS, and 12-month CSS (C-index = 0.790, 0.811, 0.775, 0.768). For time-event outcomes, traditional Cox regression exhibited good performances (OS: C-index = 0.713; CSS: C-index = 0.712). The DeepSurv algorithm performed the best in the training set (OS: C-index = 0.945; CSS: C-index = 0.834) but performs poorly in the verification set (OS: C-index = 0.658; CSS: C-index = 0.676). The brier score and calibration curve showed favorable consistency between the predicted and actual survival. The SHAP values was deployed to explain the best machine learning prediction model. Conclusions: Cox regression and machine learning models combined with the SHAP method can predict the prognosis of ATC patients in clinical practice. However, due to the small sample size and lack of external validation, our findings should be interpreted with caution. [ABSTRACT FROM AUTHOR]

Background: Most lung cancer patients worldwide (stage IV non-small cell lung cancer, NSCLC) have a poor survival: 25%-30% patients die < 3 months. Yet, of those surviving > 3 months, 10%-15% patients survive (very) long. Astragali radix (AR) is an effective traditional Chinese medicine widely used for non-small cell lung cancer (NSCLC). However, the pharmacological mechanisms of AR on NSCLC remain to be elucidated. Methods: Ultra Performance Liquid Chromatography system coupled with Q-Orbitrap HRMS (UPLC-Q-Orbitrap HRMS) was performed for the qualitative analysis of AR components. Then, network module analysis and molecular docking-based approach was conducted to explore underlying mechanisms of AR on NSCLC. The target genes of AR were obtained from four databases including TCMSP (Traditional Chinese Medicine Systems Pharmacology) database, ETCM (The Encyclopedia of TCM) database, HERB (A high-throughput experiment- and reference-guided database of TCM) database and BATMAN-TCM (a Bioinformatics Analysis Tool for Molecular mechanism of TCM) database. NSCLC related genes were screened by GEO (Gene Expression Omnibus) database. The STRING database was used for protein interaction network construction (PIN) of AR-NSCLC shared target genes. The critical PIN were further constructed based on the topological properties of network nodes. Afterwards the hub genes and network modules were analyzed, and enrichment analysis were employed by the R package clusterProfiler. The Autodock Vina was utilized for molecular docking, and the Gromacs was utilized for molecular dynamics simulations Furthermore, the survival analysis was performed based on TCGA (The Cancer Genome Atlas) database. Results: Seventy-seven AR components absorbed in blood were obtained. The critical network was constructed with 1447 nodes and 28,890 edges. Based on topological analysis, 6 hub target genes and 7 functional modules were gained. were obtained including TP53, SRC, UBC, CTNNB1, EP300, and RELA. After module analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that AR may exert therapeutic effects on NSCLC by regulating JAK-STAT signaling pathway, PI3K-AKT signaling pathway, ErbB signaling pathway, as well as NFkB signaling pathway. After the intersection calculation of the hub targets and the proteins participated in the above pathways, TP53, SRC, EP300, and RELA were obtained. These proteins had good docking affinity with astragaloside IV. Furthermore, RELA was associated with poor prognosis of NSCLC patients. Conclusions: This study could provide chemical component information references for further researches. The potential pharmacological mechanisms of AR on NSCLC were elucidated, promoting the clinical application of AR in treating NSCLC. RELA was selected as a promising candidate biomarker affecting the prognosis of NSCLC patients. [ABSTRACT FROM AUTHOR]

Background: Previous studies assessed the prognostic effect of aspirin, statins, and metformin in breast cancer (BC) patients, with inconclusive results. Methods: We performed a nationwide population-based cohort study to evaluate if post-diagnostic use of low-dose aspirin, statins, and metformin was associated with BC-specific survival. Women aged ≥ 50 years and diagnosed with BC in 2004–2017, who survived ≥ 12 months after diagnosis (follow-up started 12 months after diagnosis), were identified in the Cancer Registry of Norway. The Norwegian Prescription Database provided information on prescriptions. Multivariable Cox proportional hazard models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the association between post-diagnostic use and BC-specific survival, overall and by oestrogen receptor (ER) status. Results: A total of 26,190 patients were included. Of these, 5324 (20%), 7591 (29%), and 1495 (6%) were post-diagnostic users of low-dose aspirin, statins, and metformin, respectively. The median follow-up was 6.1 years, and 2169 (8%) patients died from BC. HRs for use, compared to no use, were estimated at 0.96 (95% CI 0.85–1.08) for low-dose aspirin (ER+: HR = 0.97, 95% CI 0.83–1.13; ER−: HR = 0.97, 95% CI 0.73–1.29, p value for interaction = 0.562), 0.84 (95% CI 0.75–0.94) for statins (ER+: HR = 0.95, 95% CI 0.82–1.09; ER−: HR = 0.77, 95% CI 0.60–1.00, p value for interaction = 0.259), and 0.70 (95% CI 0.51–0.96) for metformin (compared to use of non-metformin antidiabetics) (ER+: HR = 0.67, 95% CI 0.45–1.01; ER−: HR = 1.62, 95% CI 0.72–3.62, p value for interaction = 0.077). Conclusion: We found evidence supporting an association between post-diagnostic use of statins and metformin and survival, in patients with BC. Our findings indicate potential differences according to ER status. [ABSTRACT FROM AUTHOR]

Background: Litigation for health care, also known as health judicialization, is frequent in Brazil. It involves recourse to the court system to access health services. The study aimed to evaluate whether cancer patients in Belo Horizonte, Minas Gerais, Brazil, increased their overall survival by increasing access to certain drugs or treatments through litigation, controlling for the effect of demographic and disease-related variables. Methods: A retrospective cohort study was conducted. Patients with breast, prostate, brain, lung, or colon cancers from 2014 to 2019 were included. Survival analysis was performed using the Cox proportional hazards model. Results: In the multivariate analysis, litigation was significantly associated with increased survival in cancers of breast (HR = 0.51, 95%CI 0.33–0.80), prostate (HR = 0.50, 95%CI 0.30–0.85), colon (HR = 0.59, 95%CI 0.38–0.93), and lung (HR = 0.36, 95%CI 0.22–0.60). Five-year survival rates of patients who sued for treatment were 97.8%, 88.7%, 59.3%, and 26.0%, compared to median survival of 95.7%, 78.7%, 41.2%, and 2.4%, respectively, among patient that did not resort to court action. The study suggests that litigation for access to cancer treatment may represent a step forward in obtaining more effective treatment. This study´s main limitations are the lack of patients´ clinical information for use as control variables and the lack of variables to assess patients´ quality of life. The study also found that many cases involved claims that could have been solved by administrative rather than legal action. Some claims thus reflect the lack of adequate administrative procedures. Conclusion: When based on scientific evidence, access to new therapies, combined with other technologies already available, can favor patient survival. Access to new therapies through litigation may increase health inequalities since low-income patients have limited access to legal recourse against the State to meet their needs. The timely approval of new effective therapies can mitigate the judicialization of cancer treatment. [ABSTRACT FROM AUTHOR]

Background: Current clinical guidelines recommend surgery only for cT1-2N0M0 small cell lung cancer (SCLC) patients. In light of recent studies, the role of surgery in the treatment of SCLC needs to be reconsidered. Methods: We reviewed all SCLC patients who underwent surgery from November 2006 to April 2021. Clinicopathological characteristics were retrospectively collected from medical records. Survival analysis was performed by the Kaplan–Meier method. Independent prognostic factors were evaluated by Cox proportional hazard model. Results: 196 SCLC patients undergoing surgical resection were enrolled. The 5-year overall survival for the entire cohort was 49.0% (95% CI: 40.1–58.5%). PN0 patients had significantly superior survival to pN1–2 patients (p < 0.001). The 5-year survival rate of pN0 and pN1–2 patients were 65.5% (95% CI: 54.0–80.8%) and 35.1% (95% CI: 23.3–46.6%), respectively. Multivariate analysis revealed that smoking, older age, and advanced pathological T and N stages were independently associated with poor prognosis. Subgroup analyses demonstrated similar survival among pN0 SCLC patients regardless of pathological T stages (p = 0.416). Furthermore, multivariate analysis showed factors, including age, smoking history, type of surgery, and range of resection, were not independently prognostic factors for the pN0 SCLC patients. Conclusion: Pathological N0 stage SCLC patients have significantly superior survival to pN1–2 patients, regardless of features, including T stage. Thorough preoperative evaluation should be applied to estimate the status of lymph node involvement to achieve better selection of patients who might be candidate for surgery. Studies with larger cohort might help verify the benefit of surgery, especially for T3/4 patients. [ABSTRACT FROM AUTHOR]

Background: Few models about the personalized prognosis evaluation of buccal mucosa cancer (BMC) patients were reported. We aimed to establish predictive models to forecast the prognosis of BMC patients. Methods: The complete clinicopathological information of BMC patients from the surveillance, epidemiology and end results program was collected and reviewed retrospectively. Two nomograms were established and validated to predict long-term overall survival (OS) and cancer-specific survival (CSS) of BMC patients based on multivariate Cox regression survival analysis. Results: 1155 patients were included. 693 and 462 patients were distributed into modeling and validation groups with 6:4 split-ratio via a random split-sample method. Based on the survival analysis, independent prognostic risk factors (variables that can be used to estimate disease recovery and relapse chance) influencing OS and CSS were obtained to establish nomograms. Then, we divided the modeling group into high- and low-risk cohorts. The low-risk cohort had improved OS and CSS compared to the high-risk cohort, which was statistically significant after the Log-rank test (p < 0.05). Furthermore, we used the concordance index (C-index), calibration curve to validate the nomograms, showing high accuracy. The decision curve analyses (DCA) revealed that the nomograms had evident clinical value. Conclusions: We constructed two credible nomogram models, which would give the surgeons reference to provide an individualized assessment of BMC patients. [ABSTRACT FROM AUTHOR]

Background: Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only "curative" treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC. Methods: In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database. Results: LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19. Conclusions: In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs. [ABSTRACT FROM AUTHOR]

Background: The overall survival of patients with pancreatic cancer is extremely low. Despite multiple large-scale studies, identification of predictors of patient survival remains challenging. This study aimed to investigate the prognostic factors for pancreatic cancer. Methods: The clinical data of 625 patients with pancreatic cancer treated at Shengjing Hospital of China Medical University from January 2013 to December 2017 were collected. Results: Of 625 patients, 569 were followed from 1 to 75 months. The median overall survival was 9.3 months. The overall 1-, 3-, and 5-year survival rates were 37.8%, 15.1%, and 10.5%, respectively. Cox proportional hazards model indicated that baseline carbohydrate antigen 199 level, neutrophil-lymphocyte ratio, operative procedure, lymph node metastasis, number of distant organ metastasis, and postoperative adjuvant chemotherapy were independent prognostic factors of patients with pancreatic cancer. Baseline carbohydrate antigen 199 level, degree of weight loss, operative procedure, lymph node metastasis, number of distant organ metastasis, and postoperative adjuvant chemotherapy were independent prognostic factors of pancreatic head cancer subgroup. Baseline carbohydrate antigen 199 level, carcinoembryonic antigen level, total bilirubin level, neutrophil-lymphocyte ratio, peripancreatic invasion, number of distant organ metastasis, and postoperative adjuvant chemotherapy were independent prognostic factors of the pancreatic body/tail cancer subgroup. Conclusions: Higher carbohydrate antigen 199 levels, neutrophil-lymphocyte ratio, lymph node metastasis and distant organ metastasis predict a poor prognosis in patients with pancreatic cancer. Early detection, early radical surgery and adjuvant chemotherapy are needed to improve prognosis for this deadly disease. [ABSTRACT FROM AUTHOR]

Background: Gastric cancer (GC) is the third leading cause of cancer-related mortality worldwide. Therefore, identifying the predictive factors for surgical morbidity, disease recurrence, and long-term survival is necessary for preventing GC patient mortality. We aimed to evaluate the factors that contribute to the poor prognoses of GC patients.Methods: In this retrospective cohort study, the data of 182 patients who underwent curative gastrectomy for GC was reviewed. The data included patients' cancer stage and preoperative prognostic nutritional index (PNI) score. We identified the prognostic factors using a univariate analysis and the multivariable Cox proportional hazards model. The associations between PNI and other clinicopathologic factors for GC were compared via logistic regression analysis. Kaplan-Meier curves were used to evaluate patients' survival in relation to these factors. The median follow-up period was 3.5 years. Multivariable cumulative incidence method based on Fine and Gray's method was performed to evaluate the association between non GC-related death and potential prognostic factors.Results: There were significant differences in overall survival (OS) between comorbidities (myocardial infarction: P = 0.040, liver disease: P = 0.017), cancer stages (I vs. II: P = 0.049, I vs. III: P < 0.001), tumor size (P = 0.002), lymphatic vessel infiltration (P < 0.001), serum CA 19-9 (P = 0.024), and PNI scores (P = 0.002). Moreover, only PNI score was determined to be an independent prognostic factor for survival. Furthermore, stage I GC patients with high PNI scores had significantly longer OS than those with low PNI scores (P < 0.001), but these groups were not significantly different in terms of recurrence-free survival (P = 0.756). Stage II and III GC patients showed no significant difference in terms of OS and recurrence-free survival, regardless of PNI scores. Finally, Fine and Gray's method revealed that PNI score was an independent prognostic factor for non-GC-related death (P < 0.001).Conclusions: Preoperative PNI is effective in predicting the prognosis of post-curative gastrectomy GC patients and can be used to predict non-GC-related death and the OS of post-curative gastrectomy patients with stage I GC. [ABSTRACT FROM AUTHOR]

Background: Overall survival (OS) is a key endpoint measure in the management of patients with cancer. Immunotherapy has become a dominant strategy in cancer therapy. To investigate the relationship between OS and the immune system, we assessed the role of immune genes in OS in 8648 patients across 22 cancer types.Methods: Gene expression data and clinical information were collected from The Cancer Genome Atlas (TCGA) and cBioPortal. Survival analysis was performed with a Cox proportional hazards regression model.Results: (1) The number of prognostic genes, prognostic immune genes (PIGs) and the hazard ratio (HR) of PIGs in different cancer types all varied greatly; (2) KEGG pathway enrichment analyses indicated that the prognostic genes of 6 cancer types were significantly enriched in multiple (≥5) immune system-related pathways. Of the PIGs in these 6 cancer types, we screened 48 common PIGs in at least 5 cancer types. Eleven out of the 48 PIGs were found to participate in the T cell receptor (TCR) signaling pathway according to the STRING database. Among these genes, ZAP70, CD3E, CD3G, CD3D, and CD247 were part of the TCR 'signal-triggering module'; (3) High expression of the PIGs involved in the TCR signaling pathway was associated with improved OS in 5 cancer types (breast invasive carcinoma (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), head and neck squamous cell carcinoma (HNSC), lung adenocarcinoma (LUAD), and sarcoma (SARC)), but was associated with decreased OS in brain lower-grade glioma (LGG).Conclusions: The TCR signaling pathway played a distinct role in the OS of these 6 cancer types. [ABSTRACT FROM AUTHOR]

Background: Lymphatic vessel density and lymphovascular invasion are commonly assessed to identify the clinicopathological outcomes in breast cancer. However, the prognostic values of them on patients' survival are still uncertain.Methods: Databases of PubMed, Embase, and Web of Science were searched from inception up to 30 June 2016. The hazard ratio with its 95% confidence interval was used to determine the prognostic effects of lymphatic vessel density and lymphovascular invasion on disease-free survival and overall survival in breast cancer.Results: Nineteen studies, involving 4215 participants, were included in this study. With the combination of the results of lymphatic vessel density, the pooled hazard ratios and 95% confidence intervals were 2.02 (1.69-2.40) for disease-free survival and 2.88 (2.07-4.01) for overall survival, respectively. For lymphovascular invasion study, the pooled hazard ratios and 95% confidence intervals were 1.81 (1.57-2.08) for disease-free survival and 1.64 (1.43-1.87) for overall survival, respectively. In addition, 29.56% (827/2798) of participants presented with lymphovascular invasion in total.Conclusions: Our study demonstrates that lymphatic vessel density and lymphovascular invasion can predict poor prognosis in breast cancer. Standardized assessments of lymphatic vessel density and lymphovascular invasion are needed. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study was to evaluate the survival outcome for middle ear cancer and to construct prognostic models to provide patients and clinicians with more accurate estimates of individual survival probability. Methods: Patients diagnosed with middle ear cancer between 1983 and 2011 were selected for the study from the Surveillance Epidemiology and End Results Program. We used the Kaplan-Meier product limit method to describe overall survival and cause-specific survival. Cox proportional hazards models were fitted to model the relationships between patient characteristics and prognosis. Nomograms for predicting overall survival and cause-specific survival were built using the Cox models established. Results: The entire cohort comprised 247 patients with malignant middle ear cancer. Median duration of follow-up until censoring or death was 25 months (range, 1-319 months). Five-year overall survival and cause-specific survival were 47.4% (95% Confidence Interval (CI), 41.2% to 54.6%) and 58.0% (95% CI, 51.6% to 65.3%), respectively. In multivariable analysis, age, histological subtype, stage, surgery and radiotherapy were predictive of survival. The bootstrap corrected c-index for model predicting overall and cause-specific survival was 0.73 and 0.74, respectively. Calibration plots showed that the predicted survival reasonably approximated observed outcomes. Conclusion: The models represent an objective analysis of all currently available data. The resulting models demonstrated good accuracy in predicting overall survival and cause-specific survival. Nomograms should thus be considered as a useful tool for predicting clinical prognosis. [ABSTRACT FROM AUTHOR]

Background: The number of elderly patients with gastric cancer has been increasing. Most elderly patients have associated reduced physiologic functions that can sometimes become an obstacle to safe surgical treatment. The National Clinical Database Risk Calculator, which based on a large Japanese surgical database, provides predicted mortality and morbidity in each case as the surgical-related risks. The purpose of this study was to investigate the clinical significance of the risk for operative mortality (NRC-mortality), as calculated by the National Clinical Database Risk Calculator, during long-term follow-up after gastrectomy for elderly patients with gastric cancer. Methods: We enrolled 73 patients aged ≥ 80 years and underwent gastrectomy at our institution. Their surgical risk was evaluated based on the NRC-mortality. Several clinicopathologic factors, including NRC-mortality, were selected and analyzed as the possible prognostic factors for elderly patients who have undergone gastrectomy for gastric cancer. Statistical analysis was performed using the log-rank test and Cox proportional hazard model. Results: NRC-mortality ranged from 0.5 to 10.6%, and the median value was 1.7%. Dividing the patients according to mortality, the overall survival was significantly worse in the high mortality group (≥ 1.7%, n = 38) than in the low mortality group (< 1.7%, n = 35), whereas disease-specific survival was not different between the two groups. In the Cox proportional hazard model, multivariate analysis revealed NRC-mortality, performance status, and surgical procedure as the independent prognostic factors for overall survival. For disease-specific survival, the independent prognostic factors were performance status and pathological stage but not NRC-mortality. Conclusion: The NRC-mortality might be clinically useful for predicting both surgical mortality and overall survival after gastrectomy in elderly patients with gastric cancer. [ABSTRACT FROM AUTHOR]

Background: Cervical cancer has long been a common malignance troubling women. However, there are few studies developing nomogram with comprehensive factors for the prognosis of cervical cancer. Hence, we aimed to build a nomogram to calculate the overall survival (OS) probability in patients with cervical cancer.Methods: Data of 9876 female patients in SEER database and diagnosed as cervical cancer during 2010-2015, was retrospectively analyzed. Univariate and multivariate Cox proportional hazard regression model were applied to select predicted factors and a nomogram was developed to visualize the prediction model. The nomogram was compared with the FIGO stage prediction model. Harrell's C-index, receiver operating curve, calibration plot and decision curve analysis were used to assess the discrimination, accuracy, calibration and clinical utility of the prediction models.Result: Eleven independent prognostic variables, including age at diagnosis, race, marital status at diagnosis, grade, histology, tumor size, FIGO stage, primary site surgery, regional lymph node surgery, radiotherapy and chemotherapy, were used to build the nomogram. The C-index of the nomogram was 0.826 (95% CI: 0.818 to 0.834), which was better than that of the FIGO stage prediction model (C-index: 0.785, 95% CI: 0.776 to 0.793). Calibration plot of the nomogram was well fitted in 3-year overall OS prediction, but overfitting in 5-year OS prediction. The net benefit of the nomogram was higher than the FIGO prediction model.Conclusion: A clinical useful nomogram for calculating the overall survival probability in cervical cancer patients was developed. It performed better than the FIGO stage prediction model and could help clinicians to choose optimal treatments and precisely predict prognosis in clinical care and research. [ABSTRACT FROM AUTHOR]