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.     

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。     

脑卒中患者急性应激障碍及影响因素研究

目的探讨脑卒中患者急性应激障碍发生现状及影响因素。方法采用斯坦福急性应激反应问卷对349例脑卒中住院患者进行调查。结果共163例(46.70%)患者发生急性应激障碍;Logistic回归分析结果显示,患者性格、是否存在偏瘫及是否吞咽功能障碍是脑卒中患者发生急性应激障碍的主要影响因素(P0.05,P0.01)。结论脑卒中患者急性应激障碍发生率较高,内向性格及存在偏瘫和吞咽功能障碍的患者更容易发生急性应激障碍。医护人员应及时为高危患者提供个体化治疗及预见性护理,防止脑卒中患者发生急性应激障碍。     

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.

组织气氛在护士知识与行为间的中介效应:以脑卒中吞咽障碍护理为例

目的探究组织气氛在护士吞咽障碍知识水平与护理行为之间的中介效应。方法2019年6-7月,便利抽样法选取15个省市33所医院及医疗机构神经科、康复科具有吞咽障碍护理经验的231名护士为研究对象采用脑卒中吞咽障碍知识水平问卷、脑卒中吞咽障碍护理行为问卷及团队创新气氛量表对其进行调查。结果护士吞咽障碍知识水平总分为(56.69±13.50)分、护理行为得分为(140.65土32.02)分、组织气氛得分为(157.63±26.56)分。组织气氛与吞咽障碍知识水平(r=0.49,P<0.01)、护理行为(r=0.50,P<0.01)均呈正相关。组织气氛在知识水平和护理行为之间起中介作用,中介效应占总效应的83.18%。结论组织气氛在护士吞咽障碍知识水平与护理行为之间起中介作用,临床管理者可在提升护士吞咽障碍知识水平的基础上,通过提高组织气氛水平推进其护理行为。     

Rare patients in routine care: Treatment and outcome in advanced papillary renal cell carcinoma in the prospective German clinical RCC-Registry

Non-clear cell renal cell carcinoma is a very rare malignancy that includes several histological subtypes. Each subtype may need to be addressed separately regarding prognosis and treatment; however, no Phase III clinical trial data exist. Thus, treatment recommendations for patients with non-clear cell metastatic RCC (mRCC) remain unclear. We present first prospective data on choice of first- and second-line treatment in routine practice and outcome of patients with papillary mRCC. From the prospective German clinical cohort study (RCC-Registry), 99 patients with papillary mRCC treated with systemic first-line therapy between December 2007 and May 2017 were included. Prospectively enrolled patients who had started first-line treatment until May 15, 2016, were included into the outcome analyses (n = 82). Treatment was similar to therapies used for clear cell mRCC and consisted of tyrosine kinase inhibitors, mechanistic target of rapamycin inhibitors and recently checkpoint inhibitors. Median progression-free survival from start of first-line treatment was 5.4 months (95% confidence interval [CI], 4.1–9.2) and median overall survival was 12.0 months (95% CI, 8.1–20.0). At data cutoff, 73% of the patients died, 6% were still observed, 12% were lost to follow-up, and 9% were alive at the end of the individual 3-year observation period. Despite the lack of prospective Phase III evidence in patients with papillary mRCC, our real-world data reveal effectiveness of systemic clear cell mRCC therapy in papillary mRCC. The prognosis seems to be inferior for papillary compared to clear cell mRCC. Further studies are needed to identify drivers of effectiveness of systemic therapy for papillary mRCC.