Screening for lung cancer: 2023 guideline update from the American Cancer Society.

Lung cancer is the leading cause of mortality and person-years of life lost from cancer among US men and women. Early detection has been shown to be associated with reduced lung cancer mortality. Our objective was to update the American Cancer Society (ACS) 2013 lung cancer screening (LCS) guideline for adults at high risk for lung cancer. The guideline is intended to provide guidance for screening to health care providers and their patients who are at high risk for lung cancer due to a history of smoking. The ACS Guideline Development Group (GDG) utilized a systematic review of the LCS literature commissioned for the US Preventive Services Task Force 2021 LCS recommendation update; a second systematic review of lung cancer risk associated with years since quitting smoking (YSQ); literature published since 2021; two Cancer Intervention and Surveillance Modeling Network-validated lung cancer models to assess the benefits and harms of screening; an epidemiologic and modeling analysis examining the effect of YSQ and aging on lung cancer risk; and an updated analysis of benefit-to-radiation-risk ratios from LCS and follow-up examinations. The GDG also examined disease burden data from the National Cancer Institute's Surveillance, Epidemiology, and End Results program. Formulation of recommendations was based on the quality of the evidence and judgment (incorporating values and preferences) about the balance of benefits and harms. The GDG judged that the overall evidence was moderate and sufficient to support a strong recommendation for screening individuals who meet the eligibility criteria. LCS in men and women aged 50-80 years is associated with a reduction in lung cancer deaths across a range of study designs, and inferential evidence supports LCS for men and women older than 80 years who are in good health. The ACS recommends annual LCS with low-dose computed tomography for asymptomatic individuals aged 50-80 years who currently smoke or formerly smoked and have a ≥20 pack-year smoking history (strong recommendation, moderate quality of evidence). Before the decision is made to initiate LCS, individuals should engage in a shared decision-making discussion with a qualified health professional. For individuals who formerly smoked, the number of YSQ is not an eligibility criterion to begin or to stop screening. Individuals who currently smoke should receive counseling to quit and be connected to cessation resources. Individuals with comorbid conditions that substantially limit life expectancy should not be screened. These recommendations should be considered by health care providers and adults at high risk for lung cancer in discussions about LCS. If fully implemented, these recommendations have a high likelihood of significantly reducing death and suffering from lung cancer in the United States.

Co-condensation between transcription factor and coactivator p300 modulates transcriptional bursting kinetics.

The coactivator p300/CREB-binding protein (CBP) regulates genes by facilitating the assembly of transcriptional machinery and by acetylating histones and other factors. However, it remains mostly unclear how both functions of p300 are dynamically coordinated during gene control. Here, we showed that p300 can orchestrate two functions through the formation of dynamic clusters with certain transcription factors (TFs), which is mediated by the interactions between a TF's transactivation domain (TAD) and the intrinsically disordered regions of p300. Co-condensation can enable spatially defined, all-or-none activation of p300's catalytic activity, priming the recruitment of coactivators, including Brd4. We showed that co-condensation can modulate transcriptional initiation rate and burst duration of target genes, underlying nonlinear gene regulatory functions. Such modulation is consistent with how p300 might shape gene bursting kinetics globally. Altogether, these results suggest an intriguing gene regulation mechanism, in which TF and p300 co-condensation contributes to transcriptional bursting regulation and cooperative gene control.

An encoding generative modeling approach to dimension reduction and covariate adjustment in causal inference with observational studies.

In this article, we develop CausalEGM, a deep learning framework for nonlinear dimension reduction and generative modeling of the dependency among covariate features affecting treatment and response. CausalEGM can be used for estimating causal effects in both binary and continuous treatment settings. By learning a bidirectional transformation between the high-dimensional covariate space and a low-dimensional latent space and then modeling the dependencies of different subsets of the latent variables on the treatment and response, CausalEGM can extract the latent covariate features that affect both treatment and response. By conditioning on these features, one can mitigate the confounding effect of the high dimensional covariate on the estimation of the causal relation between treatment and response. In a series of experiments, the proposed method is shown to achieve superior performance over existing methods in both binary and continuous treatment settings. The improvement is substantial when the sample size is large and the covariate is of high dimension. Finally, we established excess risk bounds and consistency results for our method, and discuss how our approach is related to and improves upon other dimension reduction approaches in causal inference.

Global impacts of an extreme solar particle event under different geomagnetic field strengths.

Solar particle events (SPEs) are short-lived bursts of high-energy particles from the solar atmosphere and are widely recognized as posing significant economic risks to modern society. Most SPEs are relatively weak and have minor impacts on the Earth's environment, but historic records contain much stronger SPEs which have the potential to alter atmospheric chemistry, impacting climate and biological life. The impacts of such strong SPEs would be far more severe when the Earth's protective geomagnetic field is weak, such as during past geomagnetic excursions or reversals. Here, we model the impacts of an extreme SPE under different geomagnetic field strengths, focusing on changes in atmospheric chemistry and surface radiation using the atmosphere-ocean-chemistry-climate model SOCOL3-MPIOM and the radiation transfer model LibRadtran. Under current geomagnetic conditions, an extreme SPE would increase NOx concentrations in the polar stratosphere and mesosphere, causing reductions in extratropical stratospheric ozone lasting for about a year. In contrast, with no geomagnetic field, there would be a substantial increase in NOx throughout the entire atmosphere, resulting in severe stratospheric ozone depletion for several years. The resulting ground-level ultraviolet (UV) radiation would remain elevated for up to 6 y, leading to increases in UV index up to 20 to 25% and solar-induced DNA damage rates by 40 to 50%. The potential evolutionary impacts of past extreme SPEs remain an important question, while the risks they pose to human health in modern conditions continue to be underestimated.

Thrombospondin-1 in drug activity and tumor response to therapies.

Thrombospondins (TSPs) have numerous different roles in cancer, regulating the behavior of cancer cells and non-neoplastic cells, and defining the responses of tumor cells to environmental changes, thorough their ability to orchestrate cellular and molecular interactions in the tumor microenvironment (TME). As a result of these activities, TSPs can also control drug delivery and activity, tumor response and resistance to therapies, with different outcomes depending on the nature of TSP-interacting cell types, receptors, and ligands, in a highly context-dependent manner. This review, focusing primarily on TSP-1, discusses the effects of TSPs on tumor response to chemotherapy, antiangiogenic, low-dose metronomic chemotherapy, immunotherapy, and radiotherapy, by analyzing TSP activity on different cell compartments - tumor cells, vascular endothelial cells and immune cells. We review evidence of the value of TSPs, specifically TSP-1 and TSP-2, as biomarkers of prognosis and tumor response to therapy. Finally, we examine possible approaches to develop TSP-based compounds as therapeutic tools to potentiate the efficacy of anticancer therapy.

Innate immune responses yield tissue-specific bottlenecks that scale with pathogen dose.

To cause infection, pathogens must overcome bottlenecks imposed by the host immune system. These bottlenecks restrict the inoculum and largely determine whether pathogen exposure results in disease. Infection bottlenecks therefore quantify the effectiveness of immune barriers. Here, using a model of Escherichia coli systemic infection, we identify bottlenecks that tighten or widen with higher inoculum sizes, revealing that the efficacy of innate immune responses can increase or decrease with pathogen dose. We term this concept "dose scaling". During E. coli systemic infection, dose scaling is tissue specific, dependent on the lipopolysaccharide (LPS) receptor TLR4, and can be recapitulated by mimicking high doses with killed bacteria. Scaling therefore depends on sensing of pathogen molecules rather than interactions between the host and live bacteria. We propose that dose scaling quantitatively links innate immunity with infection bottlenecks and is a valuable framework for understanding how the inoculum size governs the outcome of pathogen exposure.

Mechanistic model for booster doses effectiveness in healthy, cancer, and immunosuppressed patients infected with SARS-CoV-2.

SARS-CoV-2 vaccines are effective at limiting disease severity, but effectiveness is lower among patients with cancer or immunosuppression. Effectiveness wanes with time and varies by vaccine type. Moreover, previously prescribed vaccines were based on the ancestral SARS-CoV-2 spike-protein that emerging variants may evade. Here, we describe a mechanistic mathematical model for vaccination-induced immunity. We validate it with available clinical data and use it to simulate the effectiveness of vaccines against viral variants with lower antigenicity, increased virulence, or enhanced cell binding for various vaccine platforms. The analysis includes the omicron variant as well as hypothetical future variants with even greater immune evasion of vaccine-induced antibodies and addresses the potential benefits of the new bivalent vaccines. We further account for concurrent cancer or underlying immunosuppression. The model confirms enhanced immunogenicity following booster vaccination in immunosuppressed patients but predicts ongoing booster requirements for these individuals to maintain protection. We further studied the impact of variants on immunosuppressed individuals as a function of the interval between multiple booster doses. Our model suggests possible strategies for future vaccinations and suggests tailored strategies for high-risk groups.

Transgenerational phenotypic responses to herbicide stress are more rapid than to shade and simulated herbivory in Arabidopsis.

Weeds in agricultural settings continually adapt to stresses from ecological and anthropogenic sources, in some cases leading to resistant populations. However, consequences of repeated sub-lethal exposure of these stressors on fitness and stress "memory" over generations remain poorly understood. We measured plant performance over a transgenerational experiment with Arabidopsis thaliana where plants were exposed to sub-lethal stress induced by the herbicides glyphosate or trifloxysulfuron, stresses from clipping or shading in either one (G1) or four successive generations (G1-G4), and control plants that never received stress. We found that fourth-generation (G4) plants that had been subjected to three generations of glyphosate or trifloxysulfuron stress produced higher post-stress biomass, seed weight, and rosette area as compared to that produced by plants that experienced stress only in the first generation (G1). By the same measure, clipping and shade were more influential on floral development time (shade) and seed weight (clipping) but did not show responsive phenotypes for vegetative metrics after multiple generations. Overall, we found that plants exhibited more rapid transgenerational vegetative "stress memory" to herbicides while reproductive plasticity was stressor dependent and similar between clipping/shade and anthropogenic stressors. Our study suggests that maternal plant stress memory aids next-generation plants to respond and survive better under the same stressors.

In vitro modulation of T cells in myasthenia gravis by low-dose IL-2.

Follicular helper (Tfh), peripheral helper (Tph), and regulatory (Treg) T cells are involved in myasthenia gravis (MG) pathogenesis, an autoimmune disorder arising from autoantibodies targeting neuromuscular junction proteins. This study explores the impact of low-dose IL-2 on Tfh, Tph, and Treg cells in vitro in MG. Acetylcholine-receptor antibody-positive MG (AChR-MG), muscle-specific kinase antibody-positive MG (MuSK-MG) patients, and healthy controls (HC) were studied. Blood cells were cultured with/without IL-2 and compared by the ratios of IL-2 stimulated/unstimulated cultures. In both AChR-MG and MuSK-MG patients, CD25+FoxP3+Tregs were lower, while CXCR5+PD-1+ or ICOS+Tfh and CXCR5-PD-1+ or ICOS+Tph cells were higher compared with HC. Among the MG group, the FoxP3+ Treg cells in AChR-MG patients were even lower compared with MuSK-MG patients. In vitro IL-2 stimulation increased Tregs in all groups while decreasing PD-1+/ICOS+Tfh and PD-1+/ICOS+Tph populations. The fold-increase ratio of Tregs and the fold-decrease ratio of PD-1+ or ICOS+Tfh and ICOS+Tph cells in AChR-MG and MuSK-MG patients were greater than in HCs. Low-dose IL-2 treatment may balance Tfh, Tph, and Treg cells in MG patients, offering a potential opportunity for disease modulation.

A Bayesian pharmacokinetics integrated phase I-II design to optimize dose-schedule regimes.

The schedule of administering a drug has profound impact on the toxicity and efficacy profiles of the drug through changing its pharmacokinetics (PK). PK is an innate and indispensable component of the dose-schedule optimization. Motivated by this, we propose a Bayesian PK integrated dose-schedule finding (PKIDS) design to identify the optimal dose-schedule regime by integrating PK, toxicity, and efficacy data. Based on the causal pathway that dose and schedule affect PK, which in turn affects efficacy and toxicity, we jointly model the three endpoints by first specifying a Bayesian hierarchical model for the marginal distribution of the longitudinal dose-concentration process. Conditional on the drug concentration in plasma, we jointly model toxicity and efficacy as a function of the concentration. We quantify the risk-benefit of regimes using utility-continuously updating the estimates of PK, toxicity, and efficacy based on interim data-and make adaptive decisions to assign new patients to appropriate dose-schedule regimes via adaptive randomization. The simulation study shows that the PKIDS design has desirable operating characteristics.

A marginal structural model for normal tissue complication probability.

The goal of radiation therapy for cancer is to deliver prescribed radiation dose to the tumor while minimizing dose to the surrounding healthy tissues. To evaluate treatment plans, the dose distribution to healthy organs is commonly summarized as dose-volume histograms (DVHs). Normal tissue complication probability (NTCP) modeling has centered around making patient-level risk predictions with features extracted from the DVHs, but few have considered adapting a causal framework to evaluate the safety of alternative treatment plans. We propose causal estimands for NTCP based on deterministic and stochastic interventions, as well as propose estimators based on marginal structural models that impose bivariable monotonicity between dose, volume, and toxicity risk. The properties of these estimators are studied through simulations, and their use is illustrated in the context of radiotherapy treatment of anal canal cancer patients.

CrossFuse-XGBoost: accurate prediction of the maximum recommended daily dose through multi-feature fusion, cross-validation screening and extreme gradient boosting.

In the drug development process, approximately 30% of failures are attributed to drug safety issues. In particular, the first-in-human (FIH) trial of a new drug represents one of the highest safety risks, and initial dose selection is crucial for ensuring safety in clinical trials. With traditional dose estimation methods, which extrapolate data from animals to humans, catastrophic events have occurred during Phase I clinical trials due to interspecies differences in compound sensitivity and unknown molecular mechanisms. To address this issue, this study proposes a CrossFuse-extreme gradient boosting (XGBoost) method that can directly predict the maximum recommended daily dose of a compound based on existing human research data, providing a reference for FIH dose selection. This method not only integrates multiple features, including molecular representations, physicochemical properties and compound-protein interactions, but also improves feature selection based on cross-validation. The results demonstrate that the CrossFuse-XGBoost method not only improves prediction accuracy compared to that of existing local weighted methods [k-nearest neighbor (k-NN) and variable k-NN (v-NN)] but also solves the low prediction coverage issue of v-NN, achieving full coverage of the external validation set and enabling more reliable predictions. Furthermore, this study offers a high level of interpretability by identifying the importance of different features in model construction. The 241 features with the most significant impact on the maximum recommended daily dose were selected, providing references for optimizing the structure of new compounds and guiding experimental research. The datasets and source code are freely available at https://github.com/cqmu-lq/CrossFuse-XGBoost.

Lighting up the tumor fire with low-dose irradiation.

Current efforts combining immunotherapy and radiation have focused on high-dose radiation delivered to few tumor lesions, aiming to generate diffuse abscopal effects; however, these effects are uncommon in patients. Three recent studies in mouse tumor models and human cancer patients show that low-dose radiation (LDRT) delivered to all tumor lesions effectively mobilizes innate and adaptive immunity and synergizes with immunotherapy. These new findings suggest LDRT's potential as an immune amplifier capable of reprogramming the tumor microenvironment, instigating inflammation, and sensitizing 'cold' tumors to immune checkpoint blockade responsiveness.

Single-dose HPV vaccine immunity: is there a role for non-neutralizing antibodies?

A single dose of human papillomavirus (HPV) vaccine against HPV infection (prerequisite for cervical cancer) appears to be as efficacious as two or three doses, despite inducing lower antibody titers. Neutralizing antibodies are thought to be the primary mediator of protection, but the threshold for protection is unknown. Antibody functions beyond neutralization have not been explored for HPV vaccines. Here, we discuss the immune mechanisms of HPV vaccines, with a focus on non-neutralizing antibody effector functions. In the context of single-dose HPV vaccination where antibody is limiting, we propose that non-neutralizing antibody functions may contribute to preventing HPV infection. Understanding the immunological basis of protection for single-dose HPV vaccination will provide a rationale for implementing single-dose HPV vaccine regimens.

Metformin in elderly type 2 diabetes mellitus: dose-dependent dementia risk reduction.

This study aimed to investigate the controversial association between metformin use and diabetes-associated dementia in elderly patients with type 2 diabetes mellitus (T2DM) and evaluate the potential protective effects of metformin, as well as its intensity of use and dose-dependency, against dementia in this population. The study used a time-dependent Cox hazards model to evaluate the effect of metformin use on the incidence of dementia. The case group included elderly patients with T2DM (≥60 years old) who received metformin, while the control group consisted of elderly patients with T2DM who did not receive metformin during the follow-up period. Our analysis revealed a significant reduction in the risk of dementia among elderly individuals using metformin, with an adjusted hazard ratio of 0.34 (95% confidence interval: 0.33 to 0.36). Notably, metformin users with a daily intensity of 1 defined daily dose (DDD) or higher had a lower risk of dementia, with an adjusted hazard ratio (95% confidence interval) of 0.46 (0.22 to 0.6), compared to those with a daily intensity of <1 DDD. Additionally, the analysis of cumulative DDDs of metformin showed a dose-response relationship, with progressively lower adjusted hazard ratio across quartiles (0.15, 0.21, 0.28, and 0.53 for quartiles 4, 3, 2 and 1, respectively), compared to never metformin users (P for trend < 0.0001). Metformin use in elderly patients with T2DM is significantly associated with a substantial reduction in the risk of dementia. Notably, the protective effect of metformin demonstrates a dose-dependent relationship, with higher daily and cumulative dosages of metformin showing a greater risk reduction.

Low blood concentration of alcohol enhances activity related to stopping failure in the right inferior frontal cortex.

This study investigated the effects of low doses of alcohol, which are acceptable for driving a car, on inhibitory control and neural processing using the stop-signal task (SST) in 17 healthy right-handed social drinkers. The study employed simultaneous functional magnetic resonance imaging and electromyography (EMG) recordings to assess behavioral and neural responses under conditions of low-dose alcohol (breath-alcohol concentration of 0.15 mg/L) and placebo. The results demonstrated that even a small amount of alcohol consumption prolonged Go reaction times in the SST and modified stopping behavior, as evidenced by a decrease in the frequency and magnitude of partial response EMG that did not result in button pressing during successful inhibitory control. Furthermore, alcohol intake enhanced neural activity during failed inhibitory responses in the right inferior frontal cortex, suggesting its potential role in behavioral adaptation following stop-signal failure. These findings suggest that even low levels of alcohol consumption within legal driving limits can greatly impact both the cognitive performance and brain activity involved in inhibiting responses. This research provides important evidence on the neurobehavioral effects of low-dose alcohol consumption, with implications for understanding the biological basis of impaired motor control and decision-making and potentially informing legal guidelines on alcohol consumption.

Extracellular vesicles from differentiated stem cells contain novel proangiogenic miRNAs and induce angiogenic responses at low doses.

Extracellular vesicles (EVs) released from healthy endothelial cells (ECs) have shown potential for promoting angiogenesis, but their therapeutic efficacy remains poorly understood. We have previously shown that transplantation of a human embryonic stem cell-derived endothelial cell product (hESC-ECP), promotes new vessel formation in acute ischemic disease in mice, likely via paracrine mechanism(s). Here, we demonstrated that EVs from hESC-ECPs (hESC-eEVs) significantly increased EC tube formation and wound closure in vitro at ultralow doses, whereas higher doses were ineffective. More important, EVs isolated from the mesodermal stage of the differentiation (hESC-mEVs) had no effect. Small RNA sequencing revealed that hESC-eEVs have a unique transcriptomic profile and are enriched in known proangiogenic microRNAs (miRNAs, miRs). Moreover, an in silico analysis identified three novel hESC-eEV-miRNAs with potential proangiogenic function. Differential expression analysis suggested that two of those, miR-4496 and miR-4691-5p, are highly enriched in hESC-eEVs. Overexpression of miR-4496 or miR-4691-5p resulted in increased EC tube formation and wound closure in vitro, validating the novel proangiogenic function of these miRNAs. In summary, we demonstrated that hESC-eEVs are potent inducers of EC angiogenic response at ultralow doses and contain a unique EV-associated miRNA repertoire, including miR-4496 and miR-4691-5p, with novel proangiogenic function.

Pyrazinamide Safety, Efficacy, and Dosing for Treating Drug-Susceptible Pulmonary Tuberculosis: A Phase 3, Randomized, Controlled Clinical Trial.

RATIONALE: Optimizing pyrazinamide dosing is critical to improve treatment efficacy while minimizing toxicity during tuberculosis treatment. Study 31/ACTG A5349 represents the largest Phase 3 randomized controlled therapeutic trial to date for such investigation. OBJECTIVES: We sought to report pyrazinamide pharmacokinetic parameters, risk factors for lower pyrazinamide exposure, and relationships between pyrazinamide exposure with efficacy and safety outcomes. We aimed to determine pyrazinamide dosing strategies that optimize risks and benefits. METHODS: We analyzed pyrazinamide steady-state pharmacokinetic data using population nonlinear mixed-effects models. We evaluated the contribution of pyrazinamide exposure to long-term efficacy using parametric time-to-event models and safety outcomes using logistic regression. We evaluated optimal dosing with therapeutic windows targeting ≥95% durable cure and safety within the observed proportion of the primary safety outcome. MEASUREMENTS AND MAIN RESULTS: Among 2255 participants with 6978 plasma samples, pyrazinamide displayed 7-fold exposure variability (151-1053 mg·h/L). Body weight was not a clinically relevant predictor of drug clearance and thus did not justify the need for weight-banded dosing. Both clinical and safety outcomes were associated with pyrazinamide exposure, resulting in a therapeutic window of 231-355 mg·h/L for the control and 226-349 mg·h/L for the rifapentine-moxifloxacin regimen. Flat dosing of pyrazinamide at 1000 mg would have permitted an additional 13.1% (n=96) participants allocated to the control and 9.2% (n=70) to the rifapentine-moxifloxacin regimen dosed within the therapeutic window, compared to the current weight-banded dosing. CONCLUSIONS: Flat dosing of pyrazinamide at 1000 mg daily would be readily implementable and could optimize treatment outcomes in drug-susceptible tuberculosis. Clinical trial registration available at www. CLINICALTRIALS: gov, ID: NCT02410772. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Testing fractional doses of COVID-19 vaccines.

Due to the enormous economic, health, and social costs of the COVID-19 pandemic, there are high expected social returns to investing in parallel in multiple approaches to accelerating vaccination. We argue there are high expected social returns to investigating the scope for lowering the dosage of some COVID-19 vaccines. While existing evidence is not dispositive, available clinical data on the immunogenicity of lower doses combined with evidence of a high correlation between neutralizing antibody response and vaccine efficacy suggests that half or even quarter doses of some vaccines could generate high levels of protection, particularly against severe disease and death, while potentially expanding supply by 450 million to 1.55 billion doses per month, based on supply projections for 2021. An epidemiological model suggests that, even if fractional doses are less effective than standard doses, vaccinating more people faster could substantially reduce total infections and deaths. The costs of further testing alternative doses are much lower than the expected public health and economic benefits. However, commercial incentives to generate evidence on fractional dosing are weak, suggesting that testing may not occur without public investment. Governments could support either experimental or observational evaluations of fractional dosing, for either primary or booster shots. Discussions with researchers and government officials in multiple countries where vaccines are scarce suggests strong interest in these approaches.

Thromboxane biosynthesis and future events in diabetes: the ASCEND trial.

BACKGROUND AND AIMS: Thromboxane (TX) A2, released by activated platelets, plays an important role in atherothrombosis. Urinary 11-dehydro-TXB2 (U-TXM), a stable metabolite reflecting the whole-body TXA2 biosynthesis, is reduced by ∼70% by daily low-dose aspirin. The U-TXM represents a non-invasive biomarker of in vivo platelet activation and is enhanced in patients with diabetes. This study assessed whether U-TXM is associated with the risk of future serious vascular events or revascularizations (SVE-R), major bleeding, or cancer in patients with diabetes. METHODS: The U-TXM was measured pre-randomization to aspirin or placebo in 5948 people with type 1 or 2 diabetes and no cardiovascular disease, in the ASCEND trial. Associations between log U-TXM and SVE-R (n = 618), major bleed (n = 206), and cancer (n = 700) during 6.6 years of follow-up were investigated by Cox regression; comparisons of these associations with the effects of randomization to aspirin were made. RESULTS: Higher U-TXM was associated with older age, female sex, current smoking, type 2 diabetes, higher body size, urinary albumin/creatinine ratio of ≥3 mg/mmol, and higher estimated glomerular filtration rate. After adjustment for these, U-TXM was marginally statistically significantly associated with SVE-R and major bleed but not cancer [hazard ratios per 1 SD higher log U-TXM (95% confidence interval): 1.09 (1.00-1.18), 1.16 (1.01-1.34), and 1.06 (0.98-1.14)]. The hazard ratio was similar to that implied by the clinical effects of randomization to aspirin for SVE-R but not for major bleed. CONCLUSIONS: The U-TXM was log-linearly independently associated with SVE-R in diabetes. This is consistent with the involvement of platelet TXA2 in diabetic atherothrombosis.