Confounded association between proton pump inhibitor use and risk of biliary tract cancer: Result from three cohorts

Recent epidemiological studies suggested that proton pump inhibitor (PPI) use was associated with an increased risk of biliary tract cancer (BTC), however, confounders were not adequately controlled. Our study aimed to evaluate PPI use and subsequent risk of BTC and its subtypes in three well-established cohorts. We conducted a pooled analysis of the subjects free of cancers in UK Biobank (n = 463 643), Nurses' Health Study (NHS, n = 80 235) and NHS II (n = 95 869). Propensity score weighted Cox models were used to estimate marginal HRs of PPIs use on BTC risk, accounting for potential confounders. We documented 284 BTC cases in UK Biobank (median follow-up: 7.6 years), and 91 cases in NHS and NHS II cohorts (median follow-up: 15.8 years). In UK biobank, PPI users had a 96% higher risk of BTC compared to nonusers in crude model (HR 1.96, 95% CI 1.44-2.66), but the effect was attenuated to null after adjusting for potential confounders (HR 0.95, 95% CI 0.60-1.49). PPI use was not associated with risk of BTC in the pooled analysis of three cohorts (HR 0.93, 95% CI 0.60-1.43). We also observed no associations between PPI use with risk of intrahepatic (HR 1.00, 95% CI 0.49-2.04), extrahepatic bile duct (HR 1.09, 95% CI 0.52-2.27) and gallbladder cancers (HR 0.66, 95% CI 0.26-1.66) in UK Biobank. In summary, regular use of PPIs was not associated with the risk of BTC and its subtypes.     

Measuring Psychological Inflexibility of Suicidal Thoughts: The Acceptance and Action Questionnaire for Suicidal Ideation (AAQ-SI)

Cognitive Therapy and Research - Despite interest in psychological inflexibility as a marker of suicide risk, no measure of psychological inflexibility specific to SI exists. The present study...     

重症患者再喂养综合征危险因素的Meta分析

目的 分析重症患者营养支持期间发生再喂养综合征的危险因素，为早期识别及预防再喂养综合征提供参考。方法 检索中国知网、万方数据库、中华医学期刊全文数据库、中国生物医学文献数据库、维普网、PubMed、Embase、Cochrane Library、Elsevier关于重症患者再喂养综合征危险因素的文献，检索时间为各数据库建库至2021年12月，采用RevMan5.3进行Meta分析。结果 纳入13篇文献，包括2 519例患者，其中病例组793例，对照组1 726例；Meta分析合并效应值显示年龄(WMD=4.69)、APACHEⅡ评分(WMD=2.50)、BMI(WMD=-0.94)、白蛋白水平(OR=4.61)、前白蛋白水平(WMD=-53.46)、基线血镁水平(WMD=-0.05)、基线血钾水平(WMD=0.18)、基线血磷水平(WMD=-0.07)是重症患者发生再喂养综合征的危险因素(P<0.05,P<0.01)。结论 基于现有证据，重症患者再喂养综合征的危险因素包括年龄、APACHEⅡ评分、营养状况及电解质水平，医护人员需密切关注重症患者营养支持期间能量、蛋白质及电解...     

Venetoclax alone or in combination with other regimens treatment achieve deep and sustained remission of relapsed/refractory chronic lymphocytic leukemia: a meta-analysis

Clinical and Experimental Medicine - Recently, the use of novel targeted drugs significantly improved the overall response rate (ORR) and survival of patients with relapsed/refractory chronic...     

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.