Outcomes of patients with non-small cell lung cancer and poor performance status treated with immune checkpoint inhibitors in the real-world setting

International Journal of Clinical Oncology - Immune-checkpoint inhibitors (ICIs) are standard treatments for metastatic non-small cell lung cancer (NSCLC). Patients with poor performance status...     

PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.     

Polyvictimization and Psychiatric Sequelae Associated with Female Genital Mutilation/Cutting (FGM/C)

Female Genital mutilation/cutting (FGM/C) is associated with enduring psychiatric complications. In this study, we investigate the rates of co-morbid abuses and polyvictimization experienced by survivors of FGM/C. This is a sub-analysis of a cohort study examining the patient population at the EMPOWER Center for Survivors of Sex Trafficking and Sexual Violence in New York City. A retrospective chart-review of electronic medical records was conducted for all consenting adult patients who had FGM/C and had an intake visit between January 16, 2014 and March 6, 2020. Of the 80 participants, ages ranged from 20 to 62 years with a mean of 37.4 (SD?=?9.1) years. In addition to FGM/C, participants were victims of physical abuse (43; 53.8%), emotional abuse (35; 43.8%), sexual abuse (35; 43.8%), forced marriage (20; 25%), child marriage (13; 16.3%), and sex trafficking (1; 1.4%). There was a high degree of polyvictimization, with 41 (51.2%) experiencing 3 or more of the aforementioned abuses. Having FGM/C on or after age 13 or having a higher total abuse score was also found to be strong predictors of depression and PTSD. The high rates of polyvictimization among survivors of FGM/C are associated with development of depression and PTSD. Despite co-morbid abuses, patients still attribute substantial psychiatric symptoms to their FGM/C. Health care providers should understand the high risk of polyvictimization when caring for this patient population.

     

儿童新型冠状病毒感染诊断、治疗和预防专家共识(第二版)

自2019年12月新型冠状病毒感染暴发以来,我国政府采取了严格的防控措施,国内疫情已得到初步控制,但形势依然严峻,境外多个国家也相继出现疫情。根据世界卫生组织的报告:截至2020年3月5日,全球共报告95333例确诊病例(其中我国累计报告确诊病例80565例),85个国家有确诊病例报告,中国将面临输入性病例的传播风险,这为防治我国儿童的疾病疫情提出了新的挑战[1]。在这次疫情中,与成人病例相比,儿童病例相对较少、症状轻、预后较好。目前国内病例数据显示,18岁以下儿童占所有报告病例的2.4%,尚无死亡病例报告[2]。     

Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure

BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma(HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure(area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure(area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model(integrated discrimination improvement = 0.117, P =0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic(P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy.     

VATS解剖性肺段切除术与肺叶切除术治疗Ⅰa期NSCLC患者的手术情 况及对肺功能影响的比较

目的:探讨电视胸腔镜（VATS）解剖性肺段切除术与肺叶切除术治疗Ia 期非小细胞肺癌（NSCLC）患者的手术情况及对患者肺功能的影响。方法:选取我院手术治疗的Ⅰa期NSCLC患者，收集时间2014年1月至2016年12月，根据术式不同分为两组，均采用VATS手术治疗，A组（54例）患者采用解剖性肺段切除术、B组（60例）采用肺叶切除术治疗，对比两组患者的手术效果及术后肺功能变化。结果:A组患者的手术时间、清扫淋巴结数目与B组比较差异无统计学意义（P>0.05）；A组患者的手术出血量、术后胸腔引流量、术后拔管时间、术后住院时间均显著的低于B组患者（P<0.05）；术前，A组和B组患者的FEV1%、FVC%、MVV%测定值差异无统计学意义（P>0.05），术后3个月复查，A组患者的FEV1%、FVC%、MVV%测定值均显著高于B组患者（P<0.05）；手术后，A组患者的并发症发生率（7.41%）低于B组患者（13.33%），但是差异无统计学意义（P>0.05）。结论:VATS解剖性肺段切除术治疗Ⅰa期NSCLC患者具有手术创伤小、术后恢复快、对患者肺功能影响更小的优势。