The Current Diagnostic Performance of MRI-Based Radiomics for Glioma Grading: A Meta-Analysis.

BACKGROUND: Multiple radiomics models have been proposed for grading glioma using different algorithms, features, and sequences of magnetic resonance imaging. The research seeks to assess the present overall performance of radiomics for grading glioma. METHODS: A systematic literature review of the databases Ovid MEDLINE PubMed, and Ovid EMBASE for publications published on radiomics for glioma grading between 2012 and 2023 was performed. The systematic review was carried out following the criteria of Preferred Reporting Items for Systematic Reviews and Meta-Analysis. RESULTS: In the meta-analysis, a total of 7654 patients from 40 articles, were assessed. R-package mada was used for modeling the joint estimates of specificity (SPE) and sensitivity (SEN). Pooled event rates across studies were performed with a random-effects meta-analysis. The heterogeneity of SPE and SEN were based on the χ2 test. Overall values for SPE and SEN in the differentiation between high-grade gliomas (HGGs) and low-grade gliomas (LGGs) were 84% and 91%, respectively. With regards to the discrimination between World Health Organization (WHO) grade 4 and WHO grade 3, the overall SPE was 81% and the SEN was 89%. The modern non-linear classifiers showed a better trend, whereas textural features tend to be the best-performing (29%) and the most used. CONCLUSIONS: Our findings confirm that present radiomics' diagnostic performance for glioma grading is superior in terms of SEN and SPE for the HGGs vs. LGGs discrimination task when compared to the WHO grade 4 vs. 3 task.

Incorporation of healthy volunteers data on receptor occupancy into a phase II proof-of-concept trial using a Bayesian dynamic borrowing design.

Receptor occupancy in targeted tissues measures the proportion of receptors occupied by a drug at equilibrium and is sometimes used as a surrogate of drug efficacy to inform dose selection in clinical trials. We propose to incorporate data on receptor occupancy from a phase I study in healthy volunteers into a phase II proof-of-concept study in patients, with the objective of using all the available evidence to make informed decisions. A minimal physiologically based pharmacokinetic modeling is used to model receptor occupancy in healthy volunteers and to predict it in the patients of a phase II proof-of-concept study, taking into account the variability of the population parameters and the specific differences arising from the pathological condition compared to healthy volunteers. Then, given an estimated relationship between receptor occupancy and the clinical endpoint, an informative prior distribution is derived for the clinical endpoint in both the treatment and control arms of the phase II study. These distributions are incorporated into a Bayesian dynamic borrowing design to supplement concurrent phase II trial data. A simulation study in immuno-inflammation demonstrates that the proposed design increases the power of the study while maintaining a type I error at acceptable levels for realistic values of the clinical endpoint.

Comparison between functional and intravascular imaging approaches guiding percutaneous coronary intervention: A network meta-analysis of randomized and propensity matching studies.

BACKGROUND: The optimal approach to guide percutaneous coronary intervention (PCI) has yet to be defined. The aim of this study was to compare functional driven (fractional flow reserve) versus intravascular imaging (intravascular ultrasound, IVUS, and/or optical coherence tomography, OCT) versus standard (coronary angiography only, CA)-guided PCI. METHODS: Randomized controlled trials (RCTs) and propensity score weight-matched studies (PSWMs) comparing FFR versus IVUS versus OCT versus CA-guided PCI were included. Major adverse cardiovascular event (MACE; a composite end point of death or myocardial infarction [MI] or revascularization) was the primary endpoint, whereas definite stent thrombosis (ST) and single components of MACE were the secondary ones. Primary analyses were performed including only RCTs, secondary also with PSWMs. RESULTS: Thirty-three studies were included in the analysis, 16 RCTs and 17 PSWMs. After 2 (1-3) years, IVUS performed better for MACE than CA (odds ratio [OR] 0.75 0.52-0.88), whereas there was just a trend for FFR (OR 0.81, 0.64-1.02). These results were mainly driven by reduced risk of all cause death, MI (FFR OR 0.74:0.57-0.99 and IVUS OR 0.82:0.54-0.94) and revascularization. IVUS reduced ST while FFR did not, and at meta-regression analysis, there was a trend for superiority of IVUS versus FFR to reduce subsequent MI in acute coronary syndrome (ACS) patients. The present results were consistent also after adding studies with PSWMs. CONCLUSIONS: Functional and intravascular imaging approaches seem to perform similarly in term of clinical outcomes, while both performed better compared with the standard approach. Imaging showed a potential benefit for ACS patients. The present results stress the need for a wider use of functional or imaging driven PCI.

Circulating microRNAs combined with PSA for accurate and non-invasive prostate cancer detection.

The dosage of prostate-specific antigen (PSA), an easily evaluable and non-invasive biomarker, has made early detection of prostate cancer (PCa) possible. However, it leads to high percentages of unnecessary biopsies and may miss aggressive tumors in men with PSA levels below 4 ng/ml. Therefore, we propose to combine circulating microRNAs (miRs) with PSA, to improve the diagnostic route for PCa. Plasma miR profiling identified candidate diagnostic miRs in a discovery cohort of 60 tumors and 60 controls (men with benign prostatic hyperplasia or healthy donors). Linear models with an empirical Bayesian approach and multivariate penalized logistic regression were applied to select tumor-associated miRs and/or clinical variables. A classifier was developed and tested on a validation cohort of 68 tumors and 174 controls consecutively collected, where miRs were evaluated by quantitative real-time polymerase chain reaction. A classifier based on miR-103a-3p, let-7a-5p and PSA could detect both overall and clinically significant tumors better than PSA alone, even in 50-69 years aged men with PSA ≤ 4 ng/ml. Even in the validation cohort, the classifier performed better than PSA alone in terms of specificity and positive predictive value, allowing to correctly identify eight out of nine tumors undetected by PSA, including three high-risk and three tumors in 50-69 years old men. Of carriers of non-malignant lesions with PSA in the 4-16 ng/ml interval, who may avoid unnecessary biopsies, 34% were correctly identified. Coupling two circulating miRs with PSA could be a useful strategy to diagnose clinically significant PCa and avoid an important fraction of unnecessary biopsies.

Predictive probability of success using surrogate endpoints.

The predictive probability of success of a future clinical trial is a key quantitative tool for decision-making in drug development. It is derived from prior knowledge and available evidence, and the latter typically comes from the accumulated data on the clinical endpoint of interest in previous clinical trials. However, a surrogate endpoint could be used as primary endpoint in early development and, usually, no or limited data are collected on the clinical endpoint of interest. We propose a general, reliable, and broadly applicable methodology to predict the success of a future trial from surrogate endpoints, in a way that makes the best use of all the available evidence. The predictions are based on an informative prior, called surrogate prior, derived from the results of past trials on one or several surrogate endpoints. If available, in a Bayesian framework, this prior could be combined with data from past trials on the clinical endpoint of interest. Two methods are proposed to address a potential discordance between the surrogate prior and the data on the clinical endpoint. We investigate the patterns of behavior of the predictions in a comprehensive simulation study, and we present an application to the development of a drug in Multiple Sclerosis. The proposed methodology is expected to support decision-making in many different situations, since the use of predictive markers is important to accelerate drug developments and to select promising drug candidates, better and earlier.

Cancer phase I trial design using drug combinations when a fraction of dose limiting toxicities is attributable to one or more agents.

Drug combination trials are increasingly common nowadays in clinical research. However, very few methods have been developed to consider toxicity attributions in the dose escalation process. We are motivated by a trial in which the clinician is able to identify certain toxicities that can be attributed to one of the agents. We present a Bayesian adaptive design in which toxicity attributions are modeled via copula regression and the maximum tolerated dose (MTD) curve is estimated as a function of model parameters. The dose escalation algorithm uses cohorts of two patients, following the continual reassessment method (CRM) scheme, where at each stage of the trial, we search for the dose of one agent given the current dose of the other agent. The performance of the design is studied by evaluating its operating characteristics when the underlying model is either correctly specified or misspecified. We show that this method can be extended to accommodate discrete dose combinations.

Bayesian knowledge integration for an in vitro-in vivo correlation model.

The primary goal of "in vitro-in vivo correlation" (IVIVC) is the reliable prediction of the in vivo serum concentration-time course, based on the in vitro drug dissolution or release profiles. IVIVC methods are particularly appropriate for formulations that are released over an extended period of time or with a lag in absorption and may support approving a change in formulation of a drug without additional bioequivalence trials in human subjects. Most of the current IVIVC models are assessed using frequentist methods, such as linear regression, based on averaged data and entail complex and potentially unstable mathematical deconvolution. The proposed IVIVC approach includes (a) a nonlinear-mixed effects model for the in vitro release data; (b) a population pharmacokinetic (PK) compartment model for the in vivo immediate release (IR) data; and (c) a system of ordinal differential equations (ODEs), containing the submodels (a) and (b), which approximates and predicts the in vivo controlled release (CR) data. The innovation in this paper consists of splitting the parameter space between submodels (a) and (b) versus (c). Subsequently, the uncertainty on these parameters is accounted for using a Bayesian framework, that is estimates from the first two submodels serve as priors for the Bayesian hierarchical third submodel. As such, the Bayesian method explained ensures a natural integration and transfer of knowledge between various sources of information, balancing possible differences in sample size and parameter uncertainty of in vitro and in vivo studies. Consequently, it is a very flexible approach yielding results for a broad range of data situations. The application of the method is demonstrated for a transdermal patch (TD).

Impact of design of coronary stents and length of dual antiplatelet therapies on ischaemic and bleeding events: a network meta-analysis of 64 randomized controlled trials and 102 735 patients.

AIMS: The differential impact on ischaemic and bleeding events of the type of drug-eluting stent [durable polymer stents [DES] vs. biodegradable polymer stents vs. bioresorbable scaffolds (BRS)] and length of dual antiplatelet therapy (DAPT) remains to be defined. METHODS AND RESULTS: Randomized controlled trials comparing different types of DES and/or DAPT durations were selected. The primary endpoint was Major Adverse Cardiovascular Events (MACE) [a composite of death, myocardial infarction (MI), and target vessel revascularization]. Definite stent thrombosis (ST) and single components of MACE were secondary endpoints. The arms of interest were: BRS with 12 months of DAPT (12mDAPT), biodegradable polymer stent with 12mDAPT, durable polymer stent [everolimus-eluting (EES), zotarolimus-eluting (ZES)] with 12mDAPT, EES/ZES with <12 months of DAPT, and EES/ZES with >12 months of DAPT (DAPT > 12 m). Sixty-four studies with 150 arms and 102 735 patients were included. After a median follow-up of 20 months, MACE rates were similar in the different arms of interest. EES/ZES with DAPT > 12 m reported a lower incidence of MI than the other groups, while BRS showed a higher rate of ST when compared to EES/ZES, irrespective of DAPT length. A higher risk of major bleedings was observed for DAPT > 12 m as compared to shorter DAPT. CONCLUSION: Durable and biodegradable polymer stents along with BRS report a similar rate of MACE irrespective of DAPT length. Fewer MI are observed with EES/ZES with DAPT > 12 m, while a higher rate of ST is reported for BRS when compared to EES/ZES, independently from DAPT length. Stent type may partially affect the outcome together with DAPT length.

Decision-making in drug development using a composite definition of success.

Evidence-based quantitative methodologies have been proposed to inform decision-making in drug development, such as metrics to make go/no-go decisions or predictions of success, identified with statistical significance of future clinical trials. While these methodologies appropriately address some critical questions on the potential of a drug, they either consider the past evidence without predicting the outcome of the future trials or focus only on efficacy, failing to account for the multifaceted aspects of a successful drug development. As quantitative benefit-risk assessments could enhance decision-making, we propose a more comprehensive approach using a composite definition of success based not only on the statistical significance of the treatment effect on the primary endpoint but also on its clinical relevance and on a favorable benefit-risk balance in the next pivotal studies. For one drug, we can thus study several development strategies before starting the pivotal trials by comparing their predictive probability of success. The predictions are based on the available evidence from the previous trials, to which new hypotheses on the future development could be added. The resulting predictive probability of composite success provides a useful summary to support the discussions of the decision-makers. We present a fictive, but realistic, example in major depressive disorder inspired by a real decision-making case.

Asymptotic distributions of kappa statistics and their differences with many raters, many rating categories and two conditions.

In clinical research and in more general classification problems, a frequent concern is the reliability of a rating system. In the absence of a gold standard, agreement may be considered as an indication of reliability. When dealing with categorical data, the well-known kappa statistic is often used to measure agreement. The aim of this paper is to obtain a theoretical result about the asymptotic distribution of the kappa statistic with multiple items, multiple raters, multiple conditions, and multiple rating categories (more than two), based on recent work. The result settles a long lasting quest for the asymptotic variance of the kappa statistic in this situation and allows for the construction of asymptotic confidence intervals. A recent application to clinical endoscopy and to the diagnosis of inflammatory bowel diseases (IBDs) is shortly presented to complement the theoretical perspective.

Comparative safety and efficacy of statins for primary prevention in human immunodeficiency virus-positive patients: a systematic review and meta-analysis.

The efficacy and safety of different statins for human immunodeficiency virus (HIV)-positive patients in the primary prevention setting remain to be established. In the present meta-analysis, 18 studies with 736 HIV-positive patients receiving combination antiretroviral therapy (cART) and treated with statins in the primary prevention setting were included (21.0% women, median age 44.1 years old). The primary endpoint was the effect of statin therapy on total cholesterol (TC) levels. Rosuvastatin 10 mg and atorvastatin 10 mg provided the largest reduction in TC levels [mean -1.67, 95% confidence interval (CI) (-1.99, -1.35) mmol/L; and mean -1.44, 95% CI (-1.85, -1.02) mmol/L, respectively]. Atorvastatin 80 mg and simvastatin 20 mg provided the largest reduction in low-density lipoprotein (LDL) [mean -2.10, 95% CI (-3.39, -0.81) mmol/L; and mean -1.57, 95% CI (-2.67, -0.47) mmol/L, respectively]. Pravastatin 10-20 mg [mean 0.24, 95% CI (0.10, 0.38) mmol/L] and atorvastatin 10 mg [mean 0.15, 95% CI (0.007, 0.23) mmol/L] had the largest increase in high-density lipoprotein, whereas atorvastatin 80 mg [mean -0.60, 95% CI (-1.09, -0.11) mmol/L] and simvastatin 20 mg [mean -0.61, 95% CI (-1.14, -0.08) mmol/L] had the largest reduction in triglycerides. The mean discontinuation rate was 0.12 per 100 person-years [95% CI (0.05, 0.20)], and was higher with atorvastatin 10 mg [26.5 per 100 person-years, 95% CI (-13.4, 64.7)]. Meta-regression revealed that nucleoside reverse transcriptase inhibitors-sparing regimens were associated with reduced efficacy for statin's ability to lower TC. Statin therapy significantly lowers plasma TC and LDL levels in HIV-positive patients and is associated with low rates of adverse events. Statins are effective and safe when dose-adjusted for drug-drug interactions with cART.

A simple way to unify multicriteria decision analysis (MCDA) and stochastic multicriteria acceptability analysis (SMAA) using a Dirichlet distribution in benefit-risk assessment.

Quantitative methodologies have been proposed to support decision making in drug development and monitoring. In particular, multicriteria decision analysis (MCDA) and stochastic multicriteria acceptability analysis (SMAA) are useful tools to assess the benefit-risk ratio of medicines according to the performances of the treatments on several criteria, accounting for the preferences of the decision makers regarding the relative importance of these criteria. However, even in its probabilistic form, MCDA requires the exact elicitations of the weights of the criteria by the decision makers, which may be difficult to achieve in practice. SMAA allows for more flexibility and can be used with unknown or partially known preferences, but it is less popular due to its increased complexity and the high degree of uncertainty in its results. In this paper, we propose a simple model as a generalization of MCDA and SMAA, by applying a Dirichlet distribution to the weights of the criteria and by making its parameters vary. This unique model permits to fit both MCDA and SMAA, and allows for a more extended exploration of the benefit-risk assessment of treatments. The precision of its results depends on the precision parameter of the Dirichlet distribution, which could be naturally interpreted as the strength of confidence of the decision makers in their elicitation of preferences.

Exact and asymptotic inference in clinical trials with small event rates under inverse sampling.

In this paper, we discuss statistical inference for a 2 × 2 table under inverse sampling, where the total number of cases is fixed by design. We demonstrate that the exact unconditional distributions of some relevant statistics differ from the distributions under conventional sampling, where the sample size is fixed by design. This permits us to define a simple unconditional alternative to Fisher's exact test. We provide an asymptotic argument including simulations to demonstrate that there is little power loss associated with the alternative test when the expected event rates are very small. We then apply the method to design a clinical trial in cataract surgery, where a rare side effect occurs in one in 1000 patients. The objective of the trial is to demonstrate that adjuvant treatment with an antibiotic will reduce this risk to one in 2000. We use an inverse sampling design and demonstrate how to set this up in a sequential manner. Particularly simple stopping rules can be defined when using the unconditional alternative to Fisher's exact test.

Epidemiology of musculoskeletal injuries in a population of harness Standardbred racehorses in training.

BACKGROUND: There is a substantial paucity of studies concerning musculoskeletal injuries in harness Standardbred racehorses. Specifically, little is known about the epidemiology of exercise-related musculoskeletal injuries. Most studies on this subject involve Thoroughbred racehorses, whose biomechanics and racing speed differ from Standardbred, making comparisons difficult. Here, a population of Standardbred racehorses trained at the same racecourse was studied over four years and a classification system for exercise-related musculoskeletal injuries was designed. The incidence rates of musculoskeletal injuries causing horses' withdrawal from training for 15 days or longer were investigated. A mixed-effects Poisson regression model was used to estimate musculoskeletal injury rates and to describe significance of selected risk factors for exercise-related injuries in this population. RESULTS: A total of 356 trotter racehorses from 10 different stables contributed 8961 months at risk of musculoskeletal injuries. Four-hundred-and-twenty-nine injuries were reported and classified into 16 categories, based on their aetiology and anatomical localisation. The overall exercise-related injury rate was 4.79 per 100 horse months. When considering risk factors one by one in separate univariable analyses, we obtained the following results: rates did not differ significantly between genders and classes of age, whereas one driver seemed to cause fewer injuries than the others. Racing speed and racing intensity, as well as recent medical history, seemed to be significant risk factors (p < 0.001), while being shod or unshod during racing was not. On the other hand, when pooling several risk factors in a multivariable approach, only racing intensity turned out to be significant (p < 0.001), since racing speed and the racing intensity were partially confounded, being strongly correlated to one another. CONCLUSION: Characterizing epidemiology of exercise-related musculoskeletal injuries in trotter racehorses provides baseline incidence rate values. Incidence rates of stress fracture are lower in Standardbreds compared to Thoroughbreds, whereas the opposite is true for tendon and suspensory ligament injuries. In addition to identification of risk factors for musculoskeletal injuries among Standardbred racehorses, results suggest that racing intensity seems to be a protective predictor of risk and recent medical history could be used to identify horses at risk of injury.

De-escalation of dual antiplatelet therapy for patients with acute coronary syndrome after percutaneous coronary intervention: a systematic review and network meta-analysis.

OBJECTIVES: To compare dual antiplatelet therapy (DAPT) de-escalation with five alternative DAPT strategies in patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI). DESIGN: We conducted a systematic review and network meta-analysis (NMA). Parallel-arm randomised controlled trials (RCTs) comparing DAPT strategies were included and arms of interest were compared via NMA. Partial ranking of each identified arm and for each investigated endpoint was also performed. SETTING AND PARTICIPANTS: Adult patients with ACS (≥18 years) undergoing PCI with indications for DAPT. SEARCH METHODS: A comprehensive search covered several databases (PubMed, Embase, Cochrane Central, MEDLINE, Conference Proceeding Citation Index-Science) from inception to 15 October 2023. Medical subject headings and keywords related to ACS, PCI and DAPT interventions were used. Reference lists of included studies were screened. Clinical trials registers were searched for ongoing or unpublished trials. INTERVENTIONS: Six strategies were assessed: T1 arm: acetylsalicylic acid (ASA) and prasugrel for 12 months; T2 arm: ASA and low-dose prasugrel for 12 months; T3 arm: ASA and ticagrelor for 12 months; T4 arm: DAPT de-escalation (ASA+P2Y12 inhibitor for 1-3 months, then single antiplatelet therapy with potent P2Y12 inhibitor or DAPT with clopidogrel); T5 arm: ASA and clopidogrel for 12 months; T6 arm: ASA and clopidogrel for 3-6 months. MAIN OUTCOME MEASURES: Primary outcome: Cardiovascular mortality. SECONDARY OUTCOMES: bleeding events (all, major, minor), stent thrombosis (ST), stroke, myocardial infarction (MI), all-cause mortality, major adverse cardiovascular events (MACE). RESULTS: 23 RCTs (75 064 patients with ACS) were included. No differences in cardiovascular mortality, all-cause death, recurrent MI or MACE were found when the six strategies were compared, although with different levels of certainty of evidence. ASA and clopidogrel for 12 or 3-6 months may result in a large increase of ST risk versus ASA plus full-dose prasugrel (OR 2.00, 95% CI 1.14 to 3.12, and OR 3.42, 95% CI 1.33 to 7.26, respectively; low certainty evidence for both comparisons). DAPT de-escalation probably results in a reduced risk of all bleedings compared with ASA plus full-dose 12-month prasugrel (OR 0.49, 95% CI 0.26 to 0.81, moderate-certainty evidence) and ASA plus 12-month ticagrelor (OR 0.52, 95% CI 0.33 to 0.75), while it may not increase the risk of ST. ASA plus 12-month clopidogrel may reduce all bleedings versus ASA plus full-dose 12-month prasugrel (OR 0.66, 95% CI 0.42 to 0.94, low certainty) and ASA plus 12-month ticagrelor (OR 0.70, 95% CI 0.52 to 0.89). CONCLUSIONS: DAPT de-escalation and ASA-clopidogrel regimens may reduce bleeding events compared with 12 months ASA and potent P2Y12 inhibitors. 3-6 months or 12-month aspirin-clopidogrel may increase ST risk compared with 12-month aspirin plus potent P2Y12 inhibitors, while DAPT de-escalation probably does not.

Reduced Mortality With Antiplatelet Therapy Deescalation After Percutaneous Coronary Intervention in Acute Coronary Syndromes: A Meta-Analysis.

BACKGROUND: Antiplatelet therapy deescalation has been suggested as an alternative to standard treatment with potent dual antiplatelet therapy (DAPT) for 1 year in low bleeding risk patients with acute coronary syndromes undergoing percutaneous coronary intervention to mitigate the increased risk of bleeding. Whether this strategy preserves the ischemic and survival benefits of potent DAPT is uncertain. METHODS: We performed a pairwise meta-analysis in patients with acute coronary syndrome undergoing percutaneous coronary intervention treated with either 1-year standard potent DAPT versus deescalation therapy (potent DAPT for 1-3 months followed by either reduced potency DAPT or ticagrelor monotherapy for up to 1 year). Randomized trials comparing standard DAPT versus deescalation therapy in patients with acute coronary syndrome undergoing percutaneous coronary intervention were searched through MEDLINE, EMBASE, Cochrane databases, and proceedings of international meetings. The primary end point was 1-year all-cause mortality. RESULTS: The meta-analysis included 6 trials in which 20 837 patients were randomized to potent DAPT for 1 to 3 months followed by deescalation therapy for up to 1 year (n=10 392) or standard potent DAPT for 1 year (n=10 445). Deescalation therapy was associated with lower 1-year rates of all-cause mortality compared with standard therapy (odds ratio, 0.75 [95% CI, 0.59-0.95]; P=0.02). Deescalation therapy was also associated with lower rates of major bleeding (odds ratio, 0.59 [95% CI, 0.48-0.72]; P<0.0001), with no significant difference in major adverse cardiac events (major adverse cardiovascular events; odds ratio, 0.89 [95% CI, 0.77-1.04]; P=0.14). CONCLUSIONS: In low bleeding risk patients with acute coronary syndrome undergoing percutaneous coronary intervention, compared with 1-year of potent DAPT, antiplatelet therapy deescalation therapy after 1 to 3 months was associated with decreased mortality and major bleeding with similar rates of major adverse cardiovascular events.

Risk-Benefit of 1-Year DAPT After DES Implantation in Patients Stratified by Bleeding and Ischemic Risk.

BACKGROUND: Although a 1-year duration of dual antiplatelet therapy (DAPT) is used in many patients after drug-eluting stent (DES) implantation, the evidence supporting this duration is uncertain. OBJECTIVES: The authors investigated the risk-benefit profile of 1-year vs ≤6-month DAPT after DES using 2 novel scores to risk stratify bleeding and ischemic events. METHODS: Ischemic and bleeding risk scores were generated from ADAPT-DES (Assessment of Dual Antiplatelet Therapy With Drug-Eluting Stents), a multicenter, international, "all-comers" registry that enrolled 8,665 patients treated with DES. The risk-benefit profile of 1-year vs ≤6-month DAPT was then investigated across risk strata from an individual patient data pooled dataset of 7 randomized trials that enrolled 15,083 patients treated with DES. RESULTS: In the derivation cohort, the ischemic score and the bleeding score had c-indexes of 0.76 and 0.66, respectively, and both were well calibrated. In the pooled dataset, no significant difference was apparent in any ischemic endpoint between 1-year and ≤6-month DAPT, regardless of the risk strata. In the overall dataset, there was no significant difference in the risk of clinically relevant bleeding between 1-year and ≤6-month DAPT; however, among 2,508 patients at increased risk of bleeding, 1-year compared with ≤6-month DAPT was associated with greater bleeding (HR: 2.80; 95% CI: 1.12-7.13) without a reduced risk of ischemic events in any risk strata, including those with acute coronary syndromes. These results were consistent in a network meta-analysis. CONCLUSIONS: In the present large-scale study, compared with ≤6-month DAPT, a 1-year duration of DAPT was not associated with reduced adverse ischemic events in any risk strata (including acute coronary syndromes) but was associated with greater bleeding in patients at increased risk of bleeding.

A surface-free design for phase I dual-agent combination trials.

In oncology, there is a growing number of therapies given in combination. Recently, several dose-finding designs for Phase I dose-escalation trials for combinations were proposed. The majority of novel designs use a pre-specified parametric model restricting the search of the target combination to a surface of a particular form. In this work, we propose a novel model-free design for combination studies, which is based on the assumption of monotonicity within each agent only. Specifically, we parametrise the ratios between each neighbouring combination by independent Beta distributions. As a result, the design does not require the specification of any particular parametric model or knowledge about increasing orderings of toxicity. We compare the performance of the proposed design to the model-based continual reassessment method for partial ordering and to another model-free alternative, the product of independent beta design. In an extensive simulation study, we show that the proposed design leads to comparable or better proportions of correct selections of the target combination while leading to the same or fewer average number of toxic responses in a trial.