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.     

Pre-COVID-19 Social Determinants of Health Among Mexican Migrants in Los Angeles and New York City and Their Increased Vulnerability to Unfavorable Health Outcomes During the COVID-19 Pandemic

Journal of Immigrant and Minority Health - COVID-19 has disproportionally affected underrepresented minorities (URM) and low-income immigrants in the United States. The aim of the study is to...     

A case report of pseudoaneurysm after a core needle biopsy of breast cancer

Breast pseudoaneurysms after a core needle biopsy are a rare complication with a low incidence. However, it is important to be aware of the possibility of complications that require treatment.     

甲状腺疾病患者血清 Tg-CIC 中 Tg-Ab 水平检测及相关临床研究

目的　对血清甲状腺球蛋白免疫复合物 (thyroglobulin circulating immune complex, Tg-CIC) 中抗甲状腺球蛋白抗体 (anti-thyroglobulin antibody, Tg-Ab) 含量检测，探讨 Tg-CIC 在甲状腺疾病中的临床以及流行病学意义。方法　收集甲状腺疾病患者血清标本 187 例，每例血清标本分为两组 ( 实验组和空白对照组 )，采用免疫复合物解离专利技术对甲状腺疾病患者血清标本 Tg-CIC 进行分离、解离，通过检测 Tg-CIC 解离后的 Tg-Ab 含量来间接反映甲状腺疾病患者血清中Tg-CIC 水平，按照不同的甲状腺疾病进行分组并对实验结果分析讨论。结果　不同甲状腺患者血清中 Tg-CIC 总阳性率达 92.51%，不同甲状腺疾病血清中 Tg-CIC 的阳性率差异无统计学意义 (χ?=2.917, P>0.05)。不同甲状腺疾病患者间血清游离 Tg-Ab 含量差异无统计学意义 (H=3.882, P>0.05)，不同甲状腺疾病患者间血清 CIC 中 Tg-Ab 含量差异无统计学意义(H=5.5842, P>0.05)。不同甲状腺疾病患者中，甲状腺功能亢进、甲状腺炎以及甲状腺结节患者血清游离 Tg-Ab 的含量与血清 CIC 中的 Tg-Ab 含量呈正相关 (P<0.05)，甲状腺功能减退、甲状腺肿瘤患者血清游离 Tg-Ab 的含量与血清 CIC 中的Tg-Ab 含量不相关 (P>0.05)。结论　在甲状腺疾病患者血清中，大部分可检出 Tg-CIC，与疾病类型无关。而甲状腺疾病患者中，甲状腺功能亢进、甲状腺炎以及甲状腺结节患者血清游离 Tg-Ab 含量与血清 CIC 中 Tg-Ab 含量存在相关性，为我们进一步了解 Tg-CIC 与甲状腺疾病的发生、发展的相关性研究奠定了基础，提供了新的研究视角。