Predicting Survival for Chimeric Antigen Receptor T-Cell Therapy: A Validation of Survival Models Using Follow-Up Data From ZUMA-1

ObjectivesSurvival extrapolation for chimeric antigen receptor T-cell therapies is challenging, owing to their unique mechanistic properties that translate to complex hazard functions. Axicabtagene ciloleucel is indicated for the treatment of relapse or refractory diffuse large B-cell lymphoma after 2 or more lines of therapy based on the ZUMA-1 trial. Four data snapshots are available, with minimum follow-up of 12, 24, 36, and 48 months. This analysis explores how survival extrapolations for axicabtagene ciloleucel using ZUMA-1 data can be validated and compared.MethodsThree different parametric modeling approaches were applied: standard parametric, spline-based, and cure-based models. Models were compared using a range of metrics, across the 4 data snapshot, including visual fit, plausibility of long-term estimates, statistical goodness of fit, inspection of hazard plots, point-estimate accuracy, and conditional survival estimates.ResultsStandard and spline-based parametric extrapolations were generally incapable of fitting the ZUMA-1 data well. Cure-based models provided the best fit based on the earliest data snapshot, with extrapolations remaining consistent as data matured. At 48 months, the maximum survival overestimate was 8.3% (Gompertz mixture-cure model) versus the maximum underestimate of 33.5% (Weibull standard parametric model).ConclusionsWhere a plateau in the survival curve is clinically plausible, cure-based models may be helpful in making accurate predictions based on immature data. The ability to reliably extrapolate from maturing data may reduce delays in patient access to potentially lifesaving treatments. Additional research is required to understand how models compare in broader contexts, including different treatments and therapeutic areas.     

不完全契约理论视阈下某跨区域医联体核心医院运行效率评价研究

目的对某跨区域医联体核心医院的运行效率进行评价，以不完全契约理论为分析视角探讨影响因素，为深化医联体建设提供借鉴和参考。方法收集2014年-2021年核心医院相关数据，采用DEA数据分析方法，计算运行效率变化情况。结果核心医院各项投入明显增加，医疗业务产出同步增长，医院运行效率经历了动态波动后持续向好。结论通过构建管理共同体，逐步优化契约，争取医保政策支持，合作共建初见成效。     

SARIMA模型在苏州市肺结核发病预测中的应用

目的 建立苏州市肺结核发病的SARIMA模型并预测发病,为苏州市肺结核防控提供参考。方法 收集结核病信息管理系统（新）中苏州市2010年1月—2018年12月肺结核月发病数,通过时间序列分析建立SARIMA模型并预测苏州市2019年肺结核的发病情况。结果 苏州市肺结核发病数具有明显的季节周期性,每年的发病最高峰为5月,发病最低谷为2月。苏州市肺结核发病数的最佳拟合模型为SARIMA (0,1,1)×(0,1,1)₁₂,AIC=9.590,SBC=9.644,模型参数均具有统计学意义,模型残差为白噪声序列,模型的预测值与实际值平均绝对百分比误差MAPE=7.943%,模型预测精度较高。预测苏州市2019年肺结核发病数为3 467例,月发病数平均值为289例,发病水平较2018年略有下降。结论 SARIMA(0,1,1)×(0,1,1)₁₂模型能较好拟合出苏州市肺结核发病数的时间变化趋势,可应用于苏州市肺结核月发病数的短期预测。     

大承气汤加减治疗脑病医案3则

通过病案举例,介绍大承气汤在中医脑病治疗中的使用技巧,说明大承气汤可以运用于出血性中风头痛、癫痫、失眠等多种脑病的治疗,疗效显著。大承气汤具有通腑泄热、祛邪外出的作用。对于六经辨证属阳明腑实证者,无论病种,皆可用大承气汤加味化裁。     

个体化健康教育对糖尿病抑郁症运动依从性影响

目的研究糖尿病并发抑郁症患者运动依从性的影响因素,探讨有效的干预措施。方法选择2018年11月-2019年8月天津市公安医院收治的糖尿病患者158例为研究对象,根据抑郁自评量表(CES-D)调查情况分为糖尿病抑郁(DDM)组和糖尿病非抑郁(NDDM)组各79例,采用问卷的形式分析个体化健康教育指导前后患者运动依从性影响因素。结果 NDDM组患者运动依从性量表评分为(78.4±3.3)分,高于DDM组的(52.7±4.1)分;重度抑郁患者较轻度抑郁患者运动治疗依从性明显降低;两组患者个体化健康教育后运动依从性量表评分较教育前均提高,差异均有统计学意义(P<0.01)。不同运动依从性的糖尿病患者性别、婚姻状况、文化程度、家庭支持、医患关系、并发症数量、住院次数、BMI、HbA1c比较差异有统计学意义(P<0.05)。结论抑郁症对糖尿病患者的运动依从性有明显影响,且抑郁程度越重运动依从性越差。个体化健康教育能有效改善糖尿病并发抑郁症患者的运动依从性,值得临床进一步研究。     

Fine particulate matter and incidence of metabolic syndrome in non-CVD patients: A nationwide population-based cohort study

Background

It has been reported that particulate matter (PM) is associated with cardiovascular diseases (CVD) while metabolic syndrome is also an important risk factor for CVD. However, few studies have investigated the epidemiological association between PM and metabolic syndrome.