Nutritional therapy for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer and presents together with cirrhosis in most cases. In addition to commonly recognized risk factors for HCC development, such as hepatitis B virus/hepatitis C virus infection, age and alcohol/tobacco consumption, there are nutritional risk factors also related to HCC development including high intake of saturated fats derived from red meat, type of cooking (generation of heterocyclic amines) and contamination of foods with aflatoxins. On the contrary, protective nutritional factors include diets rich in fiber, fruits and vegetables, n-3 polyunsaturated fatty acids and coffee. While the patient is being evaluated for staging and treatment of HCC, special attention should be paid to nutritional support, including proper nutritional assessment and therapy by a multidisciplinary team. It must be considered that these patients usually develop HCC on top of long-lasting cirrhosis, and therefore they could present with severe malnutrition. Cirrhosis-related complications should be properly addressed and considered for nutritional care. In addition to traditional methods, functional testing, phase angle and computed tomography scan derived skeletal muscle index-L3 are among the most useful tools for nutritional assessment. Nutritional therapy should be centered on providing enough energy and protein to manage the increased requirements of both cirrhosis and cancer. Supplementation with branched-chain amino acids is also recommended as it improves response to treatment, nutritional status and survival, and finally physical exercise must be encouraged and adapted to individual needs.     

替考拉宁在中国成人患者中的群体药动学研究

目的建立中国成年患者的替考拉宁(teicoplanin,TEC)群体药动学(population pharmacokinetics,PPK)模型,考察TEC药动学参数的影响因素。方法前瞻性收集139例革兰阳性球菌感染患者静脉注射TEC后的222份常规监测血药浓度和相关信息,采用一级消除的一室模型进行数据拟合,并应用非线性混合效应模型(nonlinear mixed effect model,NONMEM)程序建立PPK模型。采用Bootstrap、正态预测分布误差法(normalized predictive distribution error,NPDE)进行最终模型评价。利用蒙特卡洛模拟法对给药方案进行优化。结果确定了肌酐清除率(creatinine clearance,CLcr)、白蛋白(albumin,ALB)为影响TEC清除率的主要因素。最终模型为:CL(L·h^-1)=1.24×(CLcr/77)0.564×31/ALB;V(L)=69.2。验证表明,模型稳定、有效,且有较好的预测效能。对于不同ALB和CLcr的多数患者起始负荷剂量400 mg/q12h,iv,3次,维持剂量400~800 mg·d^-1的给药方案可达有效治疗谷浓度。严重感染者需调整负荷剂量至800 mg/q12h,iv,3次,维持剂量400~800 mg·d^-1的给药方案来确保血药浓度达到15 mg·L^-1以上。结论本实验报道了CLcr、ALB对TEC清除率有显著影响,所建模型对TEC在中国成人患者中实现个体化给药具有重要应用价值。     

以医院登记为基础的20万例恶性肿瘤患者生存报告

背景与目的：恶性肿瘤是全球重大的公共健康问题，患者生存率是评价恶性肿瘤诊治水平的重要指标。通过描述以医院登记为基础的20万例恶性肿瘤患者的生存情况，以真实世界数据从一个侧面反映我国恶性肿瘤的治疗效果。方法：纳入2008年1月1日—2017年12月31日之间在复旦大学附属肿瘤医院确诊为恶性肿瘤并接受住院治疗的患者共计202 542例。通过患者复诊病史资料、电话随访及死因数据链接等方式收集生存随访信息，随访统计时间截至2019年11月30日。应用寿命表法估计各个病种1年、3年和5年总生存率（overall survival，OS），以性别、年龄组、首次治疗时间分层。采用Kaplan-Meier生存曲线绘制各病种的总体生存曲线。结果：患者总体的1年、3年、5年OS分别为89.8%、77.4%和71.0%；男性患者5年OS为58.8%，女性患者为78.7%。在常见的恶性肿瘤中，甲状腺癌患者的5年OS最高，为98.6%；胰腺癌患者最低，为11.4%。2013—2017年首次治疗的乳腺癌、肺癌和肾癌患者5年OS分别为90.0%、55.9%和80.7%，显著高于2008—2012年首次治疗患者，其他肿瘤未见显著上升。结论：大部分恶性肿瘤患者经规范诊治可以获得较为理想的预后，女性生存情况显著优于男性，乳腺癌和肺癌患者的生存改善可能归功于新的临床治疗和早诊手段。     

Penile Prosthesis Implantation and Timing Disparities After Radical Prostatectomy: Results From a Statewide Claims Database

BackgroundMany patients with erectile dysfunction (ED) after radical prostatectomy (RP) improve with conservative therapy but some do not; penile prosthesis implantation rates have been sparsely reported, and have used nonrepresentative data sets.AimTo characterize rates and timing of penile prosthesis implantation after RP and to identify predictors of implantation using a more representative data set.MethodsThe Healthcare Cost and Utilization Project State Inpatient and State Ambulatory Surgery databases for Florida from 2006 to 2015 were used. Patients undergoing RP (2006–2012) were tracked longitudinally for penile prosthesis implantation. Patient and clinical data were analyzed using multivariable logistic regression.OutcomesThe primary outcome was risk-adjusted predictors of prosthesis implantation, and the secondary outcome was predictors of the highest quartile of time between RP and penile prosthesis.ResultsOf 29,288 men who had RP, 1,449 (4.9%) patients underwent subsequent prosthesis. The mean time from RP to prosthesis was 2.6 years (median: 2.1; interquartile range [IQR]: 1.2–3.5). Adjusted predictors of prosthesis implantation included open RP (odds ratio [OR]: 1.5, P < .01), African American race (OR: 1.7, P < .01) or Hispanic ethnicity (OR: 3.2, P < .01), and Medicare (OR: 1.4, P < .01) insurance. Oler patients (age >70 years; OR: 0.7, P < .01) and those from the highest income quartile relative to the lowest (OR: 0.8, P < .05) were less likely to be implanted. Adjusted predictors of longer RP-to-implantation time (highest quartile: median: 4.7 years; IQR: 3.9–6.0 years) included open RP (OR: 1.78, P < .01), laparoscopic RP (OR: 4.67, P < .01), Medicaid (OR: 3.03, P < .05), private insurance (OR: 2.57, P < .01), and being in the highest income quartile (OR: 2.52, P < .01).Clinical ImplicationsThese findings suggest ED treatment healthcare disparities meriting further investigation; upfront counseling on all ED treatment modalities and close monitoring for conservative treatment failure may reduce lost quality of life years.Strengths & LimitationsThis study is limited by its use of administrative data, which relies on accurate coding and lacks data on ED questionnaires/prior treatments, patient-level cost, and oncologic outcomes. Quartile-based analysis of income and time between RP and prosthesis limits the conclusions that can be drawn.ConclusionLess than 5% of post-RP patients undergo penile prosthesis implantation, with open RP, Medicare, African American race, and Hispanic ethnicity predicting post-RP implantation; living in the wealthiest residential areas predicts lower likelihood of implantation compared to the least wealthy areas. Patients with the longest time between RP and prosthesis are more likely to live in the wealthiest areas or have undergone open/laparoscopic RP relative to robotic RP.Bajic P, Patel PM, Nelson MH, et al. Penile Prosthesis Implantation and Timing Disparities After Radical Prostatectomy: Results From a Statewide Claims Database. J Sex Med 2020;17:1175–1181.