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Background : Currently, the reported links between olive oil intake and cardiovascular disease (CVD), cancer morbidity and mortality, and all-cause mortality are inconsistent. The aim of this meta-analysis is to study the reported correlations of olive oil intake with CVD, coronary heart disease (CHD), stroke and cancer incidence and mortality, and all-cause mortality. Methods : PubMed, Embase, and Web of Science were searched until March 7, 2024. Pooled relative risks (RRs) and 95% confidence intervals (CIs) were estimated by the random-effects model. Nonlinear dose-response relationships were modeled with restricted cubic splines. This study has been registered at PROSPERO (CRD42023419001). Results : Overall, 30 articles covering 2 710 351 participants were identified. Higher olive oil intake was linked with a reduced risk of CVD incidence (RR: 0.85; 95% CI: 0.77, 0.93), CHD incidence (RR: 0.85; 95% CI: 0.72, 0.99), CVD mortality (RR: 0.77; 95% CI: 0.67, 0.88), and all-cause mortality (RR: 0.85; 95% CI: 0.81, 0.89). For a 10 g d -1 increment of olive oil intake, the risk of CVD incidence, stroke incidence, CVD mortality, and all-cause mortality decreased by 7%, 5%, 8%, and 8%, respectively. No association was found between olive oil intake and cancer incidence and mortality. Nonlinear relationships between olive oil intake and CVD and all-cause mortality were observed, with a reduced risk from intakes ranging from 0 to 18 g d -1 and 0 to 22 g d -1 , respectively. Conclusion : Our study found that high olive oil intake was related to a lower risk of CVD and CHD incidence and CVD mortality and all-cause mortality.

To examine the independent and joint associations of dietary inflammation index (DII) and physical activity (PA) with mortality risk. We analyzed data for 20,165 study participants aged ≥ 18 from The Rural Chinese Cohort Study. The Cox proportional hazard model was used to calculate the hazard ratio (HR) and 95% confidence interval (CI) of mortality associated with DII and PA. The dose-response association between DII and mortality risk was intuitively generated by the restricted cubic splines model. During the mean 5.03-year follow-up, a total of 1110 cases of all-cause mortality were identified. Compared with people in quartile 1 of DII, positive associations were found in quartile 4 for all-cause (HR 1.27; 95%CI 1.06-1.52), CVD (HR 1.45; 95%CI 1.09-1.91), and other mortality (HR 1.52; 95%CI 1.10-2.09), while a linear association was demonstrated. Compared with people of quartile 1 of DII and high intensity of PA, those with quartile 4 of DII and low intensity of PA had higher risk of all-cause (HR 1.96; 95%CI 1.50-2.56), CVD (HR 2.68; 95%CI 1.71-4.19), and other mortality (HR 1.83; 95%CI 1.19-2.83). A pro-inflammatory diet was significantly associated with increased risk of mortality and lower PA may strengthen the effect., Competing Interests: Conflict of interest There are no conflicts of interest., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Although the association of dietary inflammatory potential, evaluated by the dietary inflammatory index (DII), with all-cause and cause-specific mortality has been reported, evidence remains equivocal, with no relevant dose-response meta-analysis having been conducted. To examine the dose-response association of dietary inflammatory potential with risk of all-cause, cancer, and cardiovascular disease (CVD) mortality, PubMed, Embase, and Web of Science were systematically searched up to August 9, 2021. Cohort studies were included if DII was reported as ≥3 levels or per incremental increase, and if the associations of DII with all-cause, cancer, and CVD mortality were assessed. Generalized least squares regression was used to estimate study-specific dose-response associations, and the random effect model was used to pool the RRs and 95% CIs of all-cause, cancer, and CVD mortality per 1-unit increase in DII. Restricted cubic splines were used to intuitively display the dose-response association between dietary inflammatory potential and mortality. Of the 1415 studies retrieved, 15 articles (17 cohort studies involving 397,641 participants) were included in this meta-analysis. With per 1-unit increase in DII, the risks were significantly increased for all-cause mortality (RR: 1.04; 95% CI: 1.03, 1.05, I2 = 51.8%; P-heterogeneity = 0.009), cancer mortality (RR: 1.02; 95% CI: 1.00, 1.04, I2 = 58.6%; P-heterogeneity = 0.013), and CVD mortality (RR: 1.04; 95% CI: 1.02, 1.06, I2 = 85.7%; P-heterogeneity <0.001), respectively. Restricted cubic splines showed significant positive linear associations between DII and the above 3 outcomes. Our study indicated that proinflammatory diets can increase the risk of all-cause, cancer, and CVD mortality in a linear manner., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society for Nutrition.)

Purpose: Tumor genomic features have been of particular interest because of their potential impact on the tumor immune microenvironment and response to immunotherapy. Due to the substantial heterogeneity, an integrative approach incorporating diverse molecular features is needed to characterize immunologic features underlying primary resistance to immunotherapy and for the establishment of novel predictive biomarkers., Experimental Design: We developed a pan-cancer deep machine learning model integrating tumor mutation burden, microsatellite instability, and somatic copy-number alterations to classify tumors of different types into different genomic clusters, and assessed the immune microenvironment in each genomic cluster and the association of each genomic cluster with response to immunotherapy., Results: Our model grouped 8,646 tumors of 29 cancer types from The Cancer Genome Atlas into four genomic clusters. Analysis of RNA-sequencing data revealed distinct immune microenvironment in tumors of each genomic class. Furthermore, applying this model to tumors from two melanoma immunotherapy clinical cohorts demonstrated that patients with melanoma of different genomic classes achieved different benefit from immunotherapy. Interestingly, tumors in cluster 4 demonstrated a cold immune microenvironment and lack of benefit from immunotherapy despite high microsatellite instability burden., Conclusions: Our study provides a proof for principle that deep learning modeling may have the potential to discover intrinsic statistical cross-modality correlations of multifactorial input data to dissect the molecular mechanisms underlying primary resistance to immunotherapy, which likely involves multiple factors from both the tumor and host at different molecular levels., (©2020 American Association for Cancer Research.)

Background: The objective of this study was to develop and validate a nomogram to predict 1-year overall survival (OS) and 2-year OS in patients with high-grade digestive neuroendocrine neoplasms (NENs) as well as to guide selection of subgroups that could benefit from systemic chemotherapy., Subjects, Materials, and Methods: We performed a retrospective analysis of 223 patients with NENs of the gut and hepato-biliary-pancreatic system from four centers included in the development cohort. The nomogram was externally validated in a cohort of 90 patients from another one., Results: The final model included lactate dehydrogenase, performance status, stage, Ki67, and site of primary tumor, all of which had a significant effect on OS. The uncorrected C-index was 0.761 for OS, and the bias-corrected C-index was 0.744. Predictions correlated well with observed 1-year and 2-year outcomes (judged by eye). The area under the time-dependent receiver operating characteristic curve at 12 months and 24 months was 0.876 and 0.838, respectively. The nomogram performed well in terms of both discrimination and calibration when applied to the validation cohort, and OS was significantly different between the two groups classified by nomogram score (log-rank p < .001)., Conclusion: The validated nomogram provided useful prediction of OS, which can be offered for clinicians to improve their abilities to assess patient prognosis, to create clinical risk groups for informing treatment or for patient stratification by disease severity in clinical trials., Implications for Practice: The high-grade neuroendocrine neoplasms of the digestive system are rare malignancies with great heterogeneity. An overall survival nomogram was developed and externally validated in this study. Two subgroups were classified by the nomogram score, and platinum-based chemotherapy may not bring clinical benefit for the low-risk patients., (© AlphaMed Press 2019.)