In this article, three research cases are introduced to show the rationale of analysis of papers cited in evidence-based guidelines and the implementation steps. The ultimate goal of medical research is to promote health; evidence-based guidelines are of most importance to medical practice, which can be directly used in clinical practice and health prevention. One of the ways in which research can influence practice is through its contribution to being references of guidelines, and it’s a new way to evaluate biomedical research’s “payback” on health.
ObjectivesTo analyze the trend of incidence and mortality of bladder cancer from 1990 to 2017 and the effects of age, time period and birth cohort on bladder cancer incidence and mortality.MethodsData on age-standardized incidence rate (ASIR) and age-standardized death rate (ASDR) of bladder cancer from 1990 to 2017 were extracted from the Global Burden of Disease 2017 (GBD 2017) database. Joinpoint regression model was used to analyze the average annual percentage change of ASIR and ASDR of bladder cancer. The age-period-cohort model was established to analyze the age, period and birth cohort effects on ASIR and ASDR of bladder cancer.ResultsFrom 1990 to 2017, both ASIR and ASDR of bladder cancer decreased slightly. ASIR decreased from 6.42 per 100 000 in 1990 to 6.04 per 100 000 in 2017, with an average annual percentage change of −0.9% (−1.0% to −0.8%), and ASDR decreased from 3.15 per 100 000 in 1990 to 2017 2.57/100 000, with an average annual percentage change of −0.4% (−0.4% to −0.3%). The age-period-cohort model results showed that as age increased, the risk of bladder cancer incidence and mortality increased; as the birth cohort progressed, the risk of bladder cancer morbidity and mortality decreased. The time period had little effect on the incidence and mortality of bladder cancer.ConclusionsThe incidence and mortality of bladder cancer are declining globally. On the other hand, the increase of the aging global population could reverse the incidence and mortality trend, active measures should be taken to address the adverse effects of aging.
ObjectiveTo investigate the clinical value of artificial intelligence (AI)-assisted chest computed tomography (CT) in the diagnosis of peripheral lung shadow. MethodsThe CT image data of 810 patients with peripheral pulmonary shadow treated by thoracic surgery in Tianjin Chest Hospital Affiliated to Tianjin University from January 2018 to July 2019 were retrospectively analyzed using AI-assisted chest CT imaging diagnosis system. There were 339 males and 471 females with a median age of 63 years. The malignant probability of preoperative AI-assisted diagnosis of peripheral pulmonary shadow was compared with the results of postoperative pathology. ResultsThe pathological diagnosis of 810 patients with peripheral pulmonary shadow was lung cancer in 627 (77.4%) patients, precancerous lesion in 30 (3.7%) patients and benign lesion in 153 (18.9%) patients. The median probability of malignant AI diagnosis before operation was 86.0% (lung cancer), 90.0% (precancerous lesion) and 37.0% (benign lesion), respectively. According to the analysis of receiver operating characteristic (ROC) curve of AI malignant probability distribution in this group of patients, the area under the ROC curve was 0.882. The critical value of malignant probability for diagnosis of lung cancer was 75.0% with a sensitivity of 0.856 and specificity of 0.814. A total of 571 patients were diagnosed with AI malignancy probability≥75.0%, among whom 537 patients were pathologically diagnosed as lung cancer with a positive predictive value of 94.0% (537/571). ConclusionThe AI-assisted chest CT diagnosis system has a high accuracy in the diagnosis of peripheral lung cancer with malignant probability≥75.0% as the diagnostic threshold.
Trial sequential analysis (TSA) can identify inclusive results of apparently conclusive of meta-analyses by providing require information size and monitoring boundary. Certain methods of calculating information size are existed. Our objective was to give a brief introduction of four methods to help readers to better perform TSA in making meta-analyses.
Objectives To analyze the risk factors of secondary infections in breast cancer or lung cancer patients with chemotherapy-induced degree Ⅳ neutropenia, so as to provide reference for clinical treatment. Methods The case-control study design was used. Thirty-seven in-patients of breast cancer or lung cancer with secondary infections and 87 in-patients without secondary infection in the First Affiliated Hospital of Xi’an Jiaotong University from January to December 2014 were enrolled as study population. We collected the retrospective information and analyzed the risk factors of secondary infection with chemotherapy-induced degree Ⅳ neutropenia using factors under univariate analysis and logistic regression analysis. Results Single factor analysis showed that the patients whose MASCC<21 the had higher infection risks (P<0.05). For breast cancer patients with degree Ⅳ neutropenia, secondary infection risk of first two chemotherapy cycles was 2.87 times of subsequent cycles of chemotherapy. For lung cancer patients with degree Ⅳ neutropenia, invasive procedures and preventive use of antibiotics increased risk of infection (P<0.05). Logistic regression analysis showed MASCC score and chemotherapy cycles were significantly associated with secondary infection in breast cancer degree Ⅳ neutropenia patients (P<0.05). Invasive procedures were significantly correlated to secondary infection of patients with lung cancer degree Ⅳ neutropenia (P<0.05). Conclusions MASCC score and chemotherapy cycles are the risk factors of infection in breast cancer patients with degree Ⅳ neutropenia, and invasive procedures are the independent risk factors of infection in lung cancer patients with degree Ⅳ neutropenia.
Most statistical data in observational studies is expressed as the effect value and its 95% confidence interval (95% CI), which do not correspond to the data format used for traditional meta-analyses, so special data conversion is to be needed when Review Manager software is applied to do a meta-analysis for this type of data, which will make the operation complicated and cumbersome. In addition, Stata software is such a powerful statistical software that can be used directly to conduct a meta-analysis with the effect value and its 95% CI. Therefore, it is an indispensable statistical tool for meta-analysis in observational studies. And this study will give a brief introduction how to use Stata software to conduct a meta-analysis with effect value and its 95% CI based on the published meta-analysis data.
With the increasing popularity of smart phones, the electronic test of clinical trials has become a common means of investigation research. The APP of REDCap system can quickly construct a multi-center questionnaire system and obtain a large quantity of reliable and complete questionnaire data, shortening the cost and cycle of research. This paper primarily introduces how to conduct research on electronic questionnaire based on mobile APPs of REDCap system.
UK Biobank is an extensive biomedical database and research resource. It contains in-depth genetic and health information from 500 000 UK subjects, comprising a wealth of basic structured data, high-throughput genomic and genetic data, and multimodal imaging data. However, difficulties in accessing the large amount of data mean that the database has not been widely used in China. We first introduced the health-related structural data, genetic data, and imaging data in the UK Biobank. We then described methods for using different types of data downloaded from UK Biobank, and explored recent research based on these data. We also discussed classic research focusing on applying artificial intelligence technology to UK Biobank data. Finally, we predicted future research trends in the utilization of UK Biobank data in areas such as anatomy, physiology, genetic variation, and phenotypic characteristics.