Patient navigation across the cancer care continuum: An overview of systematic reviews and emerging literature

Patient navigation is a strategy for overcoming barriers to reduce disparities and to improve access and outcomes. The aim of this umbrella review was to identify, critically appraise, synthesize, and present the best available evidence to inform policy and planning regarding patient navigation across the cancer continuum. Systematic reviews examining navigation in cancer care were identified in the Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, Embase, Cumulative Index of Nursing and Allied Health (CINAHL), Epistemonikos, and Prospective Register of Systematic Reviews (PROSPERO) databases and in the gray literature from January 1, 2012, to April 19, 2022. Data were screened, extracted, and appraised independently by two authors. The JBI Critical Appraisal Checklist for Systematic Review and Research Syntheses was used for quality appraisal. Emerging literature up to May 25, 2022, was also explored to capture primary research published beyond the coverage of included systematic reviews. Of the 2062 unique records identified, 61 systematic reviews were included. Fifty-four reviews were quantitative or mixed-methods reviews, reporting on the effectiveness of cancer patient navigation, including 12 reviews reporting costs or cost-effectiveness outcomes. Seven qualitative reviews explored navigation needs, barriers, and experiences. In addition, 53 primary studies published since 2021 were included. Patient navigation is effective in improving participation in cancer screening and reducing the time from screening to diagnosis and from diagnosis to treatment initiation. Emerging evidence suggests that patient navigation improves quality of life and patient satisfaction with care in the survivorship phase and reduces hospital readmission in the active treatment and survivorship care phases. Palliative care data were extremely limited. Economic evaluations from the United States suggest the potential cost-effectiveness of navigation in screening programs.     

Matrine,oxymatrine, and compound Kushen injection from the roots of Sophora flavescens: an overview of their anticancer activities

In the present review, we updated current information on the chemistry, contents, and anticancer properties of matrine (MT), oxymatrine (OMT), and compound Kushen injection (CKI). The anticancer properties were focused on lung, breast, and liver cancer cells because they are most susceptible. Sources of information were from Google, Google Scholar, PubMed, PubMed Central, Science Direct, PubChem, J-Stage, Directory of Open Access Journals (DOAJ), and China National Knowledge Infrastructure (CNKI). Reference was also made on botanical websites, such as Flora of China and World Flora Online. MT and OMT are dominant quinolizidine alkaloids from the roots of Sophora flavescens (Kushen) of the family Fabaceae. Against lung, breast, and liver cancer cells, MT and OMT inhibit cell proliferation; induce cell cycle arrest, apoptosis, and autophagy; restrict angiogenesis; and inhibit cell metastasis, invasion, and migration. The processes involve various molecular targets and signaling pathways. CKI is a traditional Chinese medicine (TCM) composed of root extracts of S. flavescens and Smilax glabra (Baituling) of the family Smilacaceae. With MT and OMT as major components, CKI has been approved for the treatment of cancer in China more than 20 years ago. In recent years, systematic reviews and meta-analysis have been undertaken to evaluate the anticancer effects of CKI. When CKI is used alone and in combination with chemotherapy of western medicine, there is much to be learned concerning their interactions besides their individual and integrated efficacy. Some perspectives of MT, OMT, and CKI are discussed, and their suggestions for future research are provided.     

Machine learning to predict myocardial injury and death after non-cardiac surgery

Myocardial injury due to ischaemia within 30 days of non-cardiac surgery is prognostically relevant. We aimed to determine the discrimination, calibration, accuracy, sensitivity and specificity of single-layer and multiple-layer neural networks for myocardial injury and death within 30 postoperative days. We analysed data from 24,589 participants in the Vascular Events in Non-cardiac Surgery Patients Cohort Evaluation study. Validation was performed on a randomly selected subset of the study population. Discrimination for myocardial injury by single-layer vs. multiple-layer models generated areas (95%CI) under the receiver operating characteristic curve of: 0.70 (0.69–0.72) vs. 0.71 (0.70–0.73) with variables available before surgical referral, p < 0.001; 0.73 (0.72–0.75) vs. 0.75 (0.74–0.76) with additional variables available on admission, but before surgery, p < 0.001; and 0.76 (0.75–0.77) vs. 0.77 (0.76–0.78) with the addition of subsequent variables, p < 0.001. Discrimination for death by single-layer vs. multiple-layer models generated areas (95%CI) under the receiver operating characteristic curve of: 0.71 (0.66–0.76) vs. 0.74 (0.71–0.77) with variables available before surgical referral, p = 0.04; 0.78 (0.73–0.82) vs. 0.83 (0.79–0.86) with additional variables available on admission but before surgery, p = 0.01; and 0.87 (0.83–0.89) vs. 0.87 (0.85–0.90) with the addition of subsequent variables, p = 0.52. The accuracy of the multiple-layer model for myocardial injury and death with all variables was 70% and 89%, respectively.