A review of spatial causal inference methods for environmental and epidemiological applications

The scientific rigor and computational methods of causal inference have had great impacts on many disciplines, but have only recently begun to take hold in spatial applications. Spatial casual inference poses analytic challenges due to complex correlation structures and interference between the treatment at one location and the outcomes at others. In this paper, we review the current literature on spatial causal inference and identify areas of future work. We first discuss methods that exploit spatial structure to account for unmeasured confounding variables. We then discuss causal analysis in the presence of spatial interference including several common assumptions used to reduce the complexity of the interference patterns under consideration. These methods are extended to the spatiotemporal case where we compare and contrast the potential outcomes framework with Granger causality, and to geostatistical analyses involving spatial random fields of treatments and responses. The methods are introduced in the context of observational environmental and epidemiological studies, and are compared using both a simulation study and analysis of the effect of ambient air pollution on COVID-19 mortality rate. Code to implement many of the methods using the popular Bayesian software OpenBUGS is provided

mTOR kinase inhibition reduces tissue factor expression and growth of pancreatic neuroendocrine tumors

EssentialsTissue factor (TF) isoforms are expressed in pancreatic neuroendocrine tumors (pNET). TF knockdown inhibits proliferation of human pNET cells in vitro. mTOR kinase inhibitor sapanisertib/MLN0128 suppresses TF expression in human pNET cells. Sapanisertib suppresses TF expression and activity and reduces the growth of pNET tumors in vivo. Background Full-length tissue factor (flTF) and alternatively spliced TF (asTF) contribute to growth and spread of pancreatic ductal adenocarcinoma. It is unknown, however, if flTF and/or asTF contribute to the pathobiology of pancreatic neuroendocrine tumors (pNETs). Objective To assess TF expression in pNETs and the effects of mTOR complex 1/2 (mTORC1/2) inhibition on pNET growth. Methods Human pNET specimens were immunostained for TF. Human pNET cell lines QGP1 and BON were evaluated for TF expression and responsiveness to mTOR inhibition. shRNA were used to knock down TF in BON. TF cofactor activity was assessed using a two-step FXa generation assay. TF promoter activity was assessed using transient transfection of human TF promoter-driven reporter constructs into cells. Mice bearing orthotopic BON tumors were treated with the mTORC1/2 ATP site competitive inhibitor sapanisertib/MLN0128 (3 mg kg(-1), oral gavage) for 34 days. Results Immunostaining of pNET tissue revealed flTF and asTF expression. BON and QGP1 expressed both TF isoforms, with BON exhibiting higher levels. shRNA directed against TF suppressed BON proliferation in vitro. Treatment of BON with sapanisertib inhibited mTOR signaling and suppressed TF levels. BON tumors grown in mice treated with sapanisertib had significantly less TF protein and cofactor activity, and were smaller compared with tumors grown in control mice. Conclusions TF isoforms are expressed in pNETs. Sapanisertib suppresses TF mRNA and protein expression as well as TF cofactor activity in vitro and in vivo. Thus, further studies are warranted to evaluate the clinical utility of TF-suppressing mTORC1/2 inhibitor sapanisertib in pNET management.Thrombosis and Hemostasi

Risk of heart failure and death after prolonged smoking cessation: Role of amount and duration of prior smoking

Background-According to the 2004 Surgeon General's Report on Health Consequences of Smoking, after >15 years of abstinence, the cardiovascular risk of former smokers becomes similar to that of never-smokers. Whether this health benefit of smoking cessation varies by amount and duration of prior smoking remains unclear. Methods and Results-Of the 4482 adults ≥65 years without prevalent heart failure (HF) in the Cardiovascular Health Study, 2556 were never-smokers, 629 current smokers, and 1297 former smokers with >15 years of cessation, of whom 312 were heavy smokers (highest quartile; ≥32 pack-years). Age-sex-race-Adjusted hazard ratios (aHR) and 95% confidence intervals (CI) for centrally adjudicated incident HF and mortality during 13 years of follow-up were estimated using Cox regression models. Compared with never-smokers, former smokers as a group had similar risk for incident HF (aHR, 0.99; 95% CI, 0.85-1.16) and all-cause mortality (aHR, 1.08; 95% CI, 0.96-1.20), but former heavy smokers had higher risk for both HF (aHR, 1.45; 95% CI, 1.15-1.83) and mortality (aHR, 1.38; 95% CI, 1.17-1.64). However, when compared with current smokers, former heavy smokers had lower risk of death (aHR, 0.64; 95% CI, 0.53-0.77), but not of HF (aHR, 0.97; 95% CI, 0.74-1.28). Conclusions-After >15 years of smoking cessation, the risk of HF and death for most former smokers becomes similar to that of never-smokers. Although this benefit of smoking cessation is not extended to those with ≥32 packyears of prior smoking, they have lower risk of death relative to current smokers. © 2015 American Heart Association, Inc