Real-world effectiveness of HPV vaccination against cervical neoplasia among birth cohorts ineligible for routine vaccination

Human papillomavirus (HPV) vaccine effectiveness may differ between settings. Here we present the first real-world effectiveness study of HPV vaccination on high-grade cervical lesions from Norway, among women who received HPV vaccine outside the routine program. We performed an observational study of all Norwegian women born 1975 to 1996 and retrieved individual data from nationwide registries on HPV vaccination status and incidence of histologically verified high-grade cervical neoplasia during 2006 to 2016. We estimated the incidence rate ratio (IRR) and 95% confidence intervals (CI) for vaccination vs no vaccination by Poisson regression stratified by age at vaccination <20 years and ≥20 years. The cohort consisted of 832 732 women, of which 46 381 (5.6%) received at least one dose of HPV vaccine by the end of 2016. The incidence rate of cervical intraepithelial neoplasia grade 2 or worse (CIN2+) increased with age regardless of vaccination status and was highest at age 25 to 29, at 637/100 000 among unvaccinated women, 487/100 000 among women vaccinated before age 20 and 831/100 000 among women vaccinated at age 20 or older. The adjusted IRR of CIN2+ between vaccinated and unvaccinated women was 0.62 (95% CI: 0.46-0.84) for women vaccinated below age 20, and 1.22 (95% CI: 1.03-1.43) for women vaccinated at age 20 or older. These findings indicate that HPV vaccination among women too old to be eligible for routine HPV vaccination is effective among women who are vaccinated below age 20 but may not have the desired impact among women who are vaccinated at age 20 or older.     

Personal comorbidities and their subsequent risks for liver,gallbladder and bile duct cancers

Many environmental risk factors for hepatobiliary cancers are known but whether they are associated with specific cancer types is unclear. We present here a novel approach of assessing standardized incidence ratios (SIRs) of previously diagnosed comorbidities for hepatocellular carcinoma (HCC), gallbladder cancer (GBC), cholangiocarcinoma (CCA) and ampullary cancer. The 13 comorbidities included alcohol and nonalcohol related liver disease, chronic obstructive pulmonary disease, gallstone disease, viral and other kinds of hepatitis, infection of bile ducts, hepatic and other autoimmune diseases, obesity and diabetes. Patients were identified from the Swedish Inpatient Register from 1987 to 2018, and their cancers were followed from 1997 onwards. SIRs for HCC were 80 to 100 in men and women diagnosed with hepatitis C virus and they were also >10 in patients diagnosed with hepatitis B virus, other kind of hepatitis, hepatic autoimmune disease and nonalcohol related liver disease. Many of these risks, as well as alcohol related liver disease, were either specific to HCC or were shared with intrahepatic CCA. For GBC, CCA and ampullary cancer infection of bile ducts was the main risk factor. Gallstone disease, nonhepatic autoimmune diseases and diabetes were associated with all hepatobiliary cancers. The limitations of the study include inability to cover some rare risk factors and limited follow-up time. Many of the considered comorbidities are characterized by chronic inflammation and/or overt immune disturbance in autoimmune diseases. The results suggest that local chronic inflammation and a related immune disturbance is the carcinogenic trigger for all these cancers.     

乳腺癌随访和药物副作用管理策略的研究进展

乳腺癌是全球女性发病率最高的恶性肿瘤,随着诊断技术及治疗手段的不断提高,乳腺癌患者接受系统治疗后生存期明显延长。乳腺癌患者需要长时间的随访以便及早监测到局部复发和远处转移。此外,激素敏感性乳腺癌患者还需要给予5~10年的内分泌治疗,针对其副作用的全程管理也需要随访,进而提高患者的生活质量,减轻患者疾病负担。本文就近年来乳腺癌随访相关方面进行简要综述。     

Experimental study on the biocompatibility and osteogenesis induction ability of PLLA/DDM scaffolds

Odontology - To investigate the characterization and function of a novel porous osteogenic material (PLLA / DDM) containing polylactic acid and demineralized dentin matrix. The surface morphology...     

医疗领域人工智能应用的研究进展＊

人工智能引发了医疗领域的数字革命，在推动行业发展方面具有极大潜力。本研究围绕临床诊疗、医学研究和公共卫生三个基本场景，聚焦人工智能与传统中医药的交叉与融合，并着重介绍人工智能在疾病诊断、决策支持、医学研究以及重大公共卫生事件中的应用。虽然人工智能在诸多方面显示出独特优势，但仍存在透明度不高、缺乏安全性评估和相关法律法规监管等问题需要谨慎解决，以促进人工智能技术在医疗领域的推广。