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Previous studies suggested that smoking and passive smoking could increase the risk of breast cancer, but the results were inconsistent, especially for Chinese females. Thus, we systematically searched cohort and case-control studies investigating the associations of active and passive smoking with breast cancer risk among Chinese females in four English databases (PubMed, Embase, ScienceDirect, and Wiley) and three Chinese databases (CNKI, WanFang, and VIP). Fifty-one articles (3 cohort studies and 48 case-control studies) covering 17 provinces of China were finally included in this systematic review. Among Chinese females, there was significant association between passive smoking and this risk of breast cancer [odds ratio (OR): 1.62; 95% confidence interval (CI): 1.39-1.85; I2 = 75.8%, P < 0.001; n = 26] but no significant association between active smoking and the risk of breast cancer (OR: 1.04; 95% CI: 0.89-1.20; I2 = 13.9%, P = 0.248; n = 31). The OR of exposure to husband's smoking and to smoke in the workplace was 1.27 (95% CI: 1.07-1.50) and 1.66 (95% CI: 1.07-2.59), respectively. The OR of light and heavy passive smoking was 1.11 and 1.41, respectively, for women exposed to their husband's smoke (< 20 and ≥ 20 cigarettes per day), and 1.07 and 1.87, respectively, for those exposed to smoke in the workplace (< 300 and ≥ 300 min of exposure per day). These results imply that passive smoking is associated with an increased risk of breast cancer, and the risk seems to increase as the level of passive exposure to smoke increases among Chinese females. Women with passive exposure to smoke in the workplace have a higher risk of breast cancer than those exposed to their husband's smoking.
Depression considerably influences the clinical outcomes, treatment compliance, quality of life, and mortality of hemodialysis patients. Exercise plays a beneficial role in depressive patients, but its quantitative effects remain elusive. This study aimed to summarize the effects of exercise training on depression in patients with end-stage renal disease undergoing hemodialysis.
Modifiable risky health behaviors, such as tobacco use, excessive alcohol use, being overweight, lack of physical activity, and unhealthy eating habits, are some of the major factors for developing chronic health conditions. Social media platforms have become indispensable means of communication in the digital era. They provide an opportunity for individuals to express themselves, as well as share their health-related concerns with peers and health care providers, with respect to risky behaviors. Such peer interactions can be utilized as valuable data sources to better understand inter-and intrapersonal psychosocial mediators and the mechanisms of social influence that drive behavior change.
Genetic mutations may play an important role in the progression and invasion of thyroid carcinoma (TC), and their coexistence may result in mutational synergy. The presence of the BRAFV600E mutation, as well as mutations affecting the TERT promoter, RAS, CHEK2 and RET/PTC, may all have an impact on prognosis. The aim of this study was to explore whether synergy between the coexistent mutations predicts histopathological prognostic factors that influence disease outcome.
Background: Success has been reported in PD-1/PD-L1 blockade via pembrolizumab, atezolizumab, or avelumab monotherapy in manifold malignancies including metastatic breast cancer. Due to lack of large-scale study, here we present interim analyses to evaluate the safety and efficacy of these promising strategies in patients with advanced breast cancer. Methods: Six studies including 586 advanced breast cancer patients treated with anti-PD-1/PD-L1 monotherapy agents before July 1, 2020, were included. The anti-PD-1/PD-L1 agents include pembrolizumab, atezolizumab, land avelumab. Statistics was analyzed by R software and IBM SPSS Statistics 22. Results: Global analysis showed that for this monotherapy, the complete response was 1.26%, partial response was 7.65%, objective response rate (ORR) was 9.85%, and disease control rate (DCR) was 18.33%. 1-year overall survival rate and 6-month progression-free survival rate were 43.34 and 17.24%. Overall incidence of adverse events (AEs) was 64.18% in any grade and 12.94% in severe grade, while the incidence of immune-related AEs (irAEs) was approximately 14.75%: the most common treatment-related AEs of any grade that occurred in at least 5% of patients were arthralgia and asthenia; the most common severe treatment-related AEs occurred in at least 1% of patients were anemia and autoimmune hepatitis; the most common irAEs were hypothyroidism. Besides, the incidence of discontinue and death due to treatment-related AEs was about 3.06 and 0.31%, respectively. Additionally, by comparing efficacy indicators between PD-L1-positive and PD-L1-negative groups, an implicated correspondence between efficacy and the expression of PD-L1 biomarker was found: the PR was 9.93 vs 2.69%; the ORR was 10.62 vs. 3.07%; the DCR was 17.95 vs. 4.71%. Conclusion: Anti-PD-1/PD-L1 monotherapy showed a manageable safety profile and had a promising and durable anti-tumor efficacy in metastatic breast cancer patients. Higher PD-L1 expression may be closely correlated to a better clinical efficacy.
Cancer patients are particularly vulnerable to COVID-19, partially owing to their compromised immune systems and curbed or cut cancer healthcare services caused by the pandemic. As a result, cancer caregivers may have to shoulder triple crises: the COVID-19 pandemic, pronounced healthcare needs from the patient, and elevated need for care from within. While technology-based health interventions have the potential to address unique challenges cancer caregivers face amid COVID-19, limited insights are available. Thus, to bridge this gap, we aim to identify technology-based interventions designed for cancer caregivers and report the characteristics and effects of these interventions concerning cancer caregivers' distinctive challenges amid COVID-19.
Despite the evidence supporting the efficacy of the ketogenic diet (KD) on weight and type 2 diabetes (T2D) management, adherence to the KD is challenging. Additionally, no studies have reported changes in PA among individuals with overweight/obesity and T2D who have followed KD. We mapped out the methods used to assess adherence to the KD and level of physical activity (PA) in lifestyle interventions for weight and T2D management in individuals with overweight/obesity and T2D and compared levels of KD adherence and PA in these interventions.
With advances in science and technology, biotechnology is becoming more accessible to people of all demographics. These advances inevitably hold the promise to improve personal and population well-being and welfare substantially. It is paradoxical that while greater access to biotechnology on a population level has many advantages, it may also increase the likelihood and frequency of biodisasters due to accidental or malicious use. Similar to "Disease X" (describing unknown naturally emerging pathogenic diseases with a pandemic potential), we term this unknown risk from biotechnologies "Biodisaster X." To date, no studies have examined the potential role of information technologies in preventing and mitigating Biodisaster X.
Deep learning techniques are gaining momentum in medical research. Evidence shows that deep learning has advantages over humans in image identification and classification, such as facial image analysis in detecting people's medical conditions. While positive findings are available, little is known about the state-of-the-art of deep learning-based facial image analysis in the medical context. For the consideration of patients' welfare and the development of the practice, a timely understanding of the challenges and opportunities faced by research on deep-learning-based facial image analysis is needed. To address this gap, we aim to conduct a systematic review to identify the characteristics and effects of deep learning-based facial image analysis in medical research. Insights gained from this systematic review will provide a much-needed understanding of the characteristics, challenges, as well as opportunities in deep learning-based facial image analysis applied in the contexts of disease detection, diagnosis and prognosis.
Cancer patients are particularly vulnerable to COVID-19, partially owing to their compromised immune systems and curbed or cut cancer healthcare services caused by the pandemic. As a result, cancer caregivers may have to shoulder triple crises: the COVID-19 pandemic, pronounced healthcare needs from the patient, and elevated need for care from within. While technology-based health interventions have the potential to address unique challenges cancer caregivers face amid COVID-19, limited insights are available. Thus, to bridge this gap, we aim to identify technology-based interventions designed for cancer caregivers and report the characteristics and effects of these interventions concerning cancer caregivers' distinctive challenges amid COVID-19.
Platinum-based chemotherapy is one of the first line therapies for the advanced non-small cell lung cancer (NSCLC), even though its high toxicity and limited clinical effects cannot be neglected. Huisheng oral solution (HSOS) has been widely used as an adjuvant chemotherapy drug for NSCLC in China. To systematically analyze the therapeutic effects of the combination of HSOS and platinum-based chemotherapy, a comprehensive meta-analysis was performed.
Polycystic ovarian syndrome (PCOS) is an endocrine disorder syndrome with reproductive dysfunction and abnormal glucose metabolism. Persistent non-ovulation, excessive androgens and insulin resistance are important features and they are the most common causes of menstrual disorders in women during childbearing years. At present, the cause of PCOS is not clinically clear. Current studies suggest that it may be due to the interaction of certain genetic genes with environmental factors. It is an important cause of infertility or early miscarriage with the characteristics of various causes and complex clinical manifestations. At present, for the treatment of PCOS patients, clinical treatment mainly includes hypoglycemia, insulin and menstrual regulation and other symptomatic and supportive treatment. Drospirone ethinyl estradiol and ethinyl estradiol cyproterone are 2 of the most commonly used drugs in clinical treatment of PCOS, but there is lack of the evidence of evidence-based medicine. Therefore, this study systematically evaluates the therapeutic effect and safety of PCOS patients with 2 short-acting oral contraceptives, drospirone ethinyl estradiol and ethinyl estradiol cyproterone, which provides the guidance for clinically selecting the appropriate drug to treat PCOS.
Natural language processing (NLP) is an important traditional field in computer science, but its application in medical research has faced many challenges. With the extensive digitalization of medical information globally and increasing importance of understanding and mining big data in the medical field, NLP is becoming more crucial.
Assessing drug and alcohol inpatient withdrawal treatment programs is important, as these represent a first step of treatment among people with alcohol and drug problems. However, there are many ways of measuring outcomes making it difficult for service providers to decide which domains and methods to use. This narrative review aims to clarify frequencies of the domains and methods used to assess withdrawal treatment outcomes.
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