An overview of precision oncology basket and umbrella trials for clinicians.

With advancements in biomarkers and momentum in precision medicine, biomarker-guided trials such as basket trials and umbrella trials have been developed under the master protocol framework. A master protocol refers to a single, overarching design developed to evaluate multiple hypotheses with the general goal of improving the efficiency of trial evaluation. One type of master protocol is the basket trial, in which a targeted therapy is evaluated for multiple diseases that share common molecular alterations or risk factors that may help predict whether the patients will respond to the given therapy. Another variant of a master protocol is the umbrella trial, in which multiple targeted therapies are evaluated for a single disease that is stratified into multiple subgroups based on different molecular or other predictive risk factors. Both designs follow the core principle of precision medicine-to tailor intervention strategies based on the patient's risk factor(s) that can help predict whether they will respond to a specific treatment. There have been increasing numbers of basket and umbrella trials, but they are still poorly understood. This article reviews common characteristics of basket and umbrella trials, key trials and recent US Food and Drug Administration approvals for precision oncology, and important considerations for clinical readers when critically evaluating future publications on basket trials and umbrella trials and for researchers when designing these clinical trials.

The Inflation Reduction Act: An Opportunity to Accelerate Confidence in Real-World Evidence in the United States.

OBJECTIVES: The Inflation Reduction Act (IRA), enacted in 2022, brings substantial reforms to the US healthcare system, particularly regarding Medicare. A key aspect includes the introduction of Medicare price negotiation. The objective of this commentary is to explore the implications of the IRA for US pharmaceutical companies, with a specific focus on the role of real-world evidence (RWE) in the context of Medicare reforms. METHODS: This commentary uses a qualitative analysis of the IRA's provisions related to healthcare and pharmaceutical regulation, focusing on how these reforms change the evidence requirements for pharmaceutical companies. It discusses the methodological aspects of generating and using RWE, including techniques such as target trial emulation and quantitative bias analysis methods to address biases inherent in RWE. RESULTS: This commentary highlights that the IRA introduces a unique approach to value assessment in the United States by evaluating drug value several years after launch, as opposed to at launch, similar to health technology assessments in other regions. It underscores the central role of RWE in comparing drug effectiveness across diverse clinical scenarios to improve the accuracy of real-world data comparisons. Furthermore, this article identifies key methodologies for managing the inherent biases in RWE, which are crucial for generating credible evidence for IRA price negotiations. CONCLUSIONS: This article underscores the importance of these methodologies in ensuring credible evidence for IRA price negotiations. It advocates for an integrated approach in evidence generation, positioning RWE as pivotal for informed pricing discussions in the US healthcare landscape.

Infliximab as a second-line therapy for children with refractory Kawasaki disease: A systematic review and meta-analysis of randomized controlled trials.

AIMS: Infliximab is a tumour necrosis factor-alpha inhibitor that is used to treat children with refractory Kawasaki disease (KD). Our purpose was to evaluate the safety and impact of infliximab versus intravenous immunoglobulins on the incidence of coronary artery aneurysms (CAAs) and treatment resistance in children with refractory KD. METHODS: The Medline/PubMed, Embase, CINAHL, Cochrane Central Register of Controlled Trials and clinical trials registries were searched to December 2021. Randomized controlled trials (RCTs) comparing infliximab as second-line therapy to a second dose of intravenous immunoglobulin (IVIG) in children with refractory KD, reported in abstract or full text, were included. Studies were selected and assessed for risk of bias by two reviewers. Data were extracted and pooled using conventional random-effects meta-analysis. The certainty of evidence was assessed using the GRADE system. RESULTS: A total of 199 participants from four RCTs were included. The pooled risk ratio (RR) for the incidence of treatment resistance in patients treated with infliximab was 0.40 (95% confidence interval [CI] 0.25-0.64). For incidence of CAAs RR was 1.20 (95% CI 0.54-2.63), the incidence of adverse effect "infusion reactions" RR was 0.48, (95% CI 0.12-1.92) and for "infections" RR was 0.55 (95% CI 0.27-1.12). Overall, the GRADE strength of evidence for the primary outcomes was low. Evidence on the duration of fever and inflammatory biomarkers was sparse, heterogeneous and inconclusive. CONCLUSION: Moderate-certainty evidence indicates that infliximab may reduce the incidence of treatment resistance in children with refractory KD. However, the limited strength of evidence warrants further research.

A Bayesian adaptive design for clinical trials of rare efficacy outcomes with multiple definitions.

INTRODUCTION: Bayesian adaptive designs for clinical trials have gained popularity in the recent years due to the flexibility and efficiency that they offer. We consider the scenario where the outcome of interest comprises events with relatively low risk of occurrence and different case definitions resulting in varying control group risk assumptions. This is a scenario that occurs frequently for infectious diseases in global health research. METHODS: We propose a Bayesian adaptive design that incorporates different case definitions of the outcome of interest that vary in stringency. A set of stopping rules are proposed where superiority and futility may be concluded with respect to different outcome definitions and therefore maintain a realistic probability of stopping in trials with low event rates. Through a simulation study, a variety of stopping rules and design configurations are compared. RESULTS: The simulation results are provided in an interactive web application that allows the user to explore and compare the design operating characteristics for a variety of assumptions and design parameters with respect to different outcome definitions. The results for select simulation scenarios are provided in the article. DISCUSSION: Bayesian adaptive designs offer the potential for maximizing the information learned from the data collected through clinical trials. The proposed design enables monitoring and utilizing multiple composite outcomes based on rare events to optimize the trial design operating characteristics.

Sequential Monte Carlo for response adaptive randomized trials.

Response adaptive randomized clinical trials have gained popularity due to their flexibility for adjusting design components, including arm allocation probabilities, at any point in the trial according to the intermediate results. In the Bayesian framework, allocation probabilities to different treatment arms are commonly defined as functionals of the posterior distributions of parameters of the outcome distribution for each treatment. In a non-conjugate model, however, repeated updates of the posterior distribution can be computationally intensive. In this article, we propose an adaptation of sequential Monte Carlo for efficiently updating the posterior distribution of parameters as new outcomes are observed in a general adaptive trial design. An efficient computational tool facilitates implementation of more flexible designs with more frequent interim looks that can in turn reduce the required sample size and expected number of failures in clinical trials. Moreover, more complex statistical models that reflect realistic modeling assumptions can be used for analysis of trial results.

When does the use of individual patient data in network meta-analysis make a difference? A simulation study.

BACKGROUND: The use of individual patient data (IPD) in network meta-analyses (NMA) is rapidly growing. This study aimed to determine, through simulations, the impact of select factors on the validity and precision of NMA estimates when combining IPD and aggregate data (AgD) relative to using AgD only. METHODS: Three analysis strategies were compared via simulations: 1) AgD NMA without adjustments (AgD-NMA); 2) AgD NMA with meta-regression (AgD-NMA-MR); and 3) IPD-AgD NMA with meta-regression (IPD-NMA). We compared 108 parameter permutations: number of network nodes (3, 5 or 10); proportion of treatment comparisons informed by IPD (low, medium or high); equal size trials (2-armed with 200 patients per arm) or larger IPD trials (500 patients per arm); sparse or well-populated networks; and type of effect-modification (none, constant across treatment comparisons, or exchangeable). Data were generated over 200 simulations for each combination of parameters, each using linear regression with Normal distributions. To assess model performance and estimate validity, the mean squared error (MSE) and bias of treatment-effect and covariate estimates were collected. Standard errors (SE) and percentiles were used to compare estimate precision. RESULTS: Overall, IPD-NMA performed best in terms of validity and precision. The median MSE was lower in the IPD-NMA in 88 of 108 scenarios (similar results otherwise). On average, the IPD-NMA median MSE was 0.54 times the median using AgD-NMA-MR. Similarly, the SEs of the IPD-NMA treatment-effect estimates were 1/5 the size of AgD-NMA-MR SEs. The magnitude of superior validity and precision of using IPD-NMA varied across scenarios and was associated with the amount of IPD. Using IPD in small or sparse networks consistently led to improved validity and precision; however, in large/dense networks IPD tended to have negligible impact if too few IPD were included. Similar results also apply to the meta-regression coefficient estimates. CONCLUSIONS: Our simulation study suggests that the use of IPD in NMA will considerably improve the validity and precision of estimates of treatment effect and regression coefficients in the most NMA IPD data-scenarios. However, IPD may not add meaningful validity and precision to NMAs of large and dense treatment networks when negligible IPD are used.

Comparing the use of aggregate data and various methods of integrating individual patient data to network meta-analysis and its application to first-line ART.

BACKGROUND: The 2018 World Health Organization HIV guidelines were based on the results of a network meta-analysis (NMA) of published trials. This study employed individual patient-level data (IPD) and aggregate data (AgD) and meta-regression methods to assess the evidence supporting the WHO recommendations and whether they needed any refinements. METHODS: Access to IPD from three trials was granted through ClinicalStudyDataRequest.com (CSDR). Seven modelling approaches were applied and compared: 1) Unadjusted AgD network meta-analysis (NMA) - the original analysis; 2) AgD-NMA with meta-regression; 3) Two-stage IPD-AgD NMA; 4) Unadjusted one-stage IPD-AgD NMA; 5) One-stage IPD-AgD NMA with meta-regression (one-stage approach); 6) Two-stage IPD-AgD NMA with empirical-priors (empirical-priors approach); 7) Hierarchical meta-regression IPD-AgD NMA (HMR approach). The first two were the models used previously. Models were compared with respect to effect estimates, changes in the effect estimates, coefficient estimates, DIC and model fit, rankings and between-study heterogeneity. RESULTS: IPD were available for 2160 patients, representing 6.5% of the evidence base and 3 of 24 edges. The aspect of the model affected by the choice of modeling appeared to differ across outcomes. HMR consistently generated larger intervals, often with credible intervals (CrI) containing the null value. Discontinuations due to adverse events and viral suppression at 96 weeks were the only two outcomes for which the unadjusted AgD NMA would not be selected. For the first, the selected model shifted the principal comparison of interest from an odds ratio of 0.28 (95% CrI: 10.17, 0.44) to 0.37 (95% CrI: 0.23, 0.58). Throughout all outcomes, the regression estimates differed substantially between AgD and IPD methods, with the latter being more often larger in magnitude and statistically significant. CONCLUSIONS: Overall, the use of IPD often impacted the coefficient estimates, but not sufficiently as to necessitate altering the final recommendations of the 2018 WHO Guidelines. Future work should examine the features of a network where adjustments will have an impact, such as how much IPD is required in a given size of network.

Utilizing Bayesian predictive power in clinical trial design.

The Bayesian paradigm provides an ideal platform to update uncertainties and carry them over into the future in the presence of data. Bayesian predictive power (BPP) reflects our belief in the eventual success of a clinical trial to meet its goals. In this paper we derive mathematical expressions for the most common types of outcomes, to make the BPP accessible to practitioners, facilitate fast computations in adaptive trial design simulations that use interim futility monitoring, and propose an organized BPP-based phase II-to-phase III design framework.

Comparative tolerability of treatments for acute migraine: A network meta-analysis.

Introduction Migraine headache is a neurological disorder whose attacks are associated with nausea, vomiting, photophobia and phonophobia. Treatments for migraine aim to either prevent attacks before they have started or relieve attacks (abort) after onset of symptoms and range from complementary therapies to pharmacological interventions. A number of treatment-related adverse events such as somnolence, fatigue, and chest discomfort have previously been reported in association with triptans. The comparative tolerability of available agents for the abortive treatment of migraine attacks has not yet been systematically reviewed and quantified. Methods We performed a systematic literature review and Bayesian network meta-analysis for comparative tolerability of treatments for migraine. The literature search targeted all randomized controlled trials evaluating oral abortive treatments for acute migraine over a range of available doses in adults. The primary outcomes of interest were any adverse event, treatment-related adverse events, and serious adverse events. Secondary outcomes were fatigue, dizziness, chest discomfort, somnolence, nausea, and vomiting. Results Our search yielded 141 trials covering 15 distinct treatments. Of the triptans, sumatriptan, eletriptan, rizatriptan, zolmitriptan, and the combination treatment of sumatriptan and naproxen were associated with a statistically significant increase in odds of any adverse event or a treatment-related adverse event occurring compared with placebo. Of the non-triptans, only acetaminophen was associated with a statistically significant increase in odds of an adverse event occurring when compared with placebo. Overall, triptans were not associated with increased odds of serious adverse events occurring and the same was the case for non-triptans. For the secondary outcomes, with the exception of vomiting, all triptans except for almotriptan and frovatriptan were significantly associated with increased risk for all outcomes. Almotriptan was significantly associated with an increased risk of vomiting, whereas all other triptans yielded non-significant lower odds compared with placebo. Generally, the non-triptans were not associated with decreased tolerability for the secondary outcomes. Discussion In summary, triptans were associated with higher odds of any adverse event or a treatment-related adverse event occurring when compared to placebo and non-triptans. Non-significant results for non-triptans indicate that these treatments are comparable with one another and placebo regarding tolerability outcomes.

Cardiovascular events and all-cause mortality associated with sulphonylureas compared with other antihyperglycaemic drugs: A Bayesian meta-analysis of survival data.

AIM: To conduct a systematic review and meta-analysis to determine the risk of cardiovascular events and all-cause mortality associated with sulphonylureas (SUs) vs other glucose lowering drugs in patients with T2DM (T2DM). MATERIALS AND METHODS: A systematic review of Medline, Embase, Cochrane and clinicaltrials.gov was conducted for studies comparing SUs with placebo or other antihyperglycaemic drugs in patients with T2DM. A cloglog model was used in the Bayesian framework to obtain comparative hazard ratios (HRs) for the different interventions. For the analysis of observational data, conventional fixed-effect pairwise meta-analyses were used. RESULTS: The systematic review identified 82 randomized controlled trials (RCTs) and 26 observational studies. Meta-analyses of RCT data showed an increased risk of all-cause mortality and cardiovascular-related mortality for SUs compared with all other treatments combined (HR 1.26, 95% confidence interval [CI] 1.10-1.44 and HR 1.46, 95% CI 1.21-1.77, respectively). The risk of myocardial infarction was significantly higher for SUs compared with dipeptidyl peptidase-4 (DPP-4) inhibitors and sodium-glucose co-transporter-2 inhibitors (HR 2.54, 95% CI 1.14-6.57 and HR 41.80, 95% CI 1.64-360.4, respectively). The risk of stroke was significantly higher for SUs than for DPP-4 inhibitors, glucagon-like peptide-1 agonists, thiazolidinediones and insulin. CONCLUSIONS: The present meta-analysis showed an association between SU therapy and a higher risk of major cardiovascular disease-related events compared with other glucose lowering drugs. Results of ongoing RCTs, which should be available in 2018, will provide definitive results on the risk of cardiovascular events and all-cause mortality associated with SUs vs other antihyperglycaemic drugs.

Landscape review of current HIV 'kick and kill' cure research - some kicking, not enough killing.

BACKGROUND: Current antiretroviral therapy (ART) used to treat human immunodeficiency virus (HIV) patients is life-long because it only suppresses de novo infections. Recent efforts to eliminate HIV have tested the ability of a number of agents to reactivate ('Kick') the well-known latent reservoir. This approach is rooted in the assumption that once these cells are reactivated the host's immune system itself will eliminate ('Kill') the virus. While many agents have been shown to reactivate large quantities of the latent reservoir, the impact on the size of the latent reservoir has been negligible. This suggests that the immune system is not sufficient to eliminate reactivated reservoirs. Thus, there is a need for more emphasis on 'kill' strategies in HIV cure research, and how these might work in combination with current or future kick strategies. METHODS: We conducted a landscape review of HIV 'cure' clinical trials using 'kick and kill' approaches. We identified and reviewed current available clinical trial results in human participants as well as ongoing and planned clinical trials. We dichotomized trials by whether they did not include or include a 'kill' agent. We extracted potential reasons why the 'kill' is missing from current 'kick and kill' strategies. We subsequently summarized and reviewed current 'kill' strategies have entered the phase of clinical trial testing in human participants and highlighted those with the greatest promise. RESULTS: The identified 'kick' trials only showed promise on surrogate measures activating latent T-cells, but did not show any positive effects on clinical 'cure' measures. Of the 'kill' agents currently being tested in clinical trials, early results have shown small but meaningful proportions of participants remaining off ART for several months with broadly neutralizing antibodies, as well as agents for regulating immune cell responses. A similar result was also recently observed in a trial combining a conventional 'kick' with a vaccine immune booster ('kill'). CONCLUSION: While an understanding of the efficacy of each individual component is crucial, no single 'kick' or 'kill' agent is likely to be a fully effective cure. Rather, the solution is likely found in a combination of multiple 'kick and kill' interventions.

Metastatic Spread Emerging From Liver Metastases of Colorectal Cancer: Does the Seed Leave the Soil Again?

OBJECTIVE: To investigate whether liver metastases contribute to metastatic spread of colorectal cancer (CRC) by shedding intact tumor cells. BACKGROUND: Metastases represent the primary cause of death in CRC. Understanding the metastatic activity of metastases and which patients are at high risk for tumor cell dissemination may, therefore, have significant influence on cancer care in the future. METHODS: Circulating tumor cells (CTCs) were detected in the hepatic inflow (portal venous blood [PVB]) and outflow compartment (hepatic venous blood [HVB]) of a training (n = 55) and validation (n = 50) set using the CellSearch system. Isolated CTC from the HVB were subjected to gene expression analyses by quantitative polymerase chain reaction. RESULTS: CTC detection rate (37.2% vs 19.6%; P = 0.04) and count (mean: 12.7, SEM: ±â€Š5.9 vs 1.9; ±â€Š1.2; P = 0.01) were significantly higher in HVB compared to PVB. The increased CTC detection rate (54% vs 11.4%; P < 0.001) and CTC count (14.7 ±â€Š5.1 vs 1.1 ±â€Š0.6; P < 0.001) in the HVB compared to the PVB compartment was confirmed in the validation cohort. Expression of epithelial markers and genes involved in cell-to-cell and cell-to-matrix adhesion was reduced in CTC compared to tumor cells in liver metastases. Metastasis size greater than 5 cm was associated with CTC shedding from established liver metastases in the training and validation cohorts. CONCLUSIONS: Colorectal liver metastases shed intact tumor cells with an invasive phenotype. Metastasis size serves as a surrogate marker for metastatic activity of colorectal liver metastases.

Prolactin-related adverse events and change in prolactin levels in pediatric patients given antipsychotics for schizophrenia and schizophrenia spectrum disorders: A systematic review.

BACKGROUND: Second-generation antipsychotics are commonly prescribed for pediatric patients with schizophrenia and schizophrenia spectrum disorders despite their lack of approval for use in children. Although considered a safer alternative to first-generation antipsychotics, there is evidence to suggest that second-generation antipsychotics may be associated with some adverse events as well as an increase in prolactin levels. The purpose of this review is to examine the risk of prolactin-related adverse events in pediatric patients using antipsychotics and to quantify changes in prolactin for this population. METHODS: Literature searches were conducted in Medline, Embase, the Cochrane Central Register of Controlled Trials, and PsycINFO databases, supplemented with review of select gray literature to identify both randomized controlled trials and observational studies on pediatric patients prescribed antipsychotic medications for schizophrenia or schizophrenia spectrum disorders. Using a narrative approach, data on adverse events were recorded and changes from baseline in prolactin were pooled, where possible, from the randomized trials. Change from baseline in prolactin was evaluated for each treatment, as well as in comparison to placebo and to other treatments. Where data was available, these changes were evaluated separately for male and female patients. RESULTS: Six randomized controlled trials and five observational studies, all examining the effects of second-generation antipsychotics, were selected. Literature reporting the effects of risperidone, quetiapine, aripiprazole, olanzapine, and paliperidone was identified, with varying doses. Prolactin-related adverse events were sparsely reported across studies. In evidence gathered from randomized controlled trials, risperidone, olanzapine, and two doses of paliperidone (3-5 mg/day and 6-12 mg/day) were associated with increased prolactin levels compared to baseline. With the exception of paliperidone, similar trends were observed in males and females, separately. The findings of the observational evidence served to both complement and run contrary to the randomized trials, with discrepancies attributed to differences in patient and treatment characteristics. CONCLUSIONS: No definitive conclusions between second-generation antipsychotic use and prolactin-related adverse events can be made based on the available literature. While some trends in prolactin level changes emerged, this was based on few trials with small sample sizes. Future investigations should emphasize reporting on treatment safety. TRIAL REGISTRATION: PROSPERO CRD42014009506 .

The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations.

The PRISMA statement is a reporting guideline designed to improve the completeness of reporting of systematic reviews and meta-analyses. Authors have used this guideline worldwide to prepare their reviews for publication. In the past, these reports typically compared 2 treatment alternatives. With the evolution of systematic reviews that compare multiple treatments, some of them only indirectly, authors face novel challenges for conducting and reporting their reviews. This extension of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) statement was developed specifically to improve the reporting of systematic reviews incorporating network meta-analyses. A group of experts participated in a systematic review, Delphi survey, and face-to-face discussion and consensus meeting to establish new checklist items for this extension statement. Current PRISMA items were also clarified. A modified, 32-item PRISMA extension checklist was developed to address what the group considered to be immediately relevant to the reporting of network meta-analyses. This document presents the extension and provides examples of good reporting, as well as elaborations regarding the rationale for new checklist items and the modification of previously existing items from the PRISMA statement. It also highlights educational information related to key considerations in the practice of network meta-analysis. The target audience includes authors and readers of network meta-analyses, as well as journal editors and peer reviewers.

Risk of medication overuse headache across classes of treatments for acute migraine.

BACKGROUND: The most commonly prescribed medications used to treat migraine acutely are single analgesics, ergots, opioids, and triptans. Due to varying mechanisms of action across drug classes, there is reason to believe that some classes may be less likely than others to elicit Medication Overuse Headache (MOH) than others. We therefore aimed to determine whether certain classes of acute migraine drugs are more likely to elicit MOH than others. METHODS: A comprehensive systematic literature was conducted to identify studies of varying designs that reported on MOH within the considered treatment classes. Only studies that reported MOH according to the International Classification of Headache Disorders (ICHD) were considered. Since no causal comparative design studies were identified; data from prevalence studies and surveys were retrieved. Prevalence-based relative risks between treatment classes were calculated by integrating both medication overuse and medication use from published studies. For each pair wise comparison, pooled relative risks were calculated as the inverse variance weighted average. RESULTS: A total of 29 studies informed the relative risk between treatment classes, all of which reported country-specific data. Five studies reported country-specific medication use data. For triptans versus analgesics the study relative risks generally favored triptans. The pooled relative risk was 0.65 (i.e., relative risk reduction of 35 %). For ergots versus analgesics, a similar trend was observed in favor of ergots with a relative risk of 0.41. For triptans versus ergots, the direction of effect was mixed, and the pooled relative risk was 1.07. Both triptans and ergots appeared favorable when compared to opioids, with pooled relative risks of 0.35 and 0.76, respectively. However, the evidence was limited for these comparisons. Analgesics and opioids also appeared to yield similar risk of MOH (pooled relative risk 1.09). CONCLUSION: Our study suggests that in patients receiving acute migraine treatment, analgesics and opioids are associated with a higher risk of developing MOH compared with other treatments. These findings provide incentive for better monitoring of use of analgesics and opioids for treating acute migraine, and suggest possible clinical preference for use of so-called "migraine-specific" treatments, that is, triptans and ergots.

Cardiovascular events associated with smoking cessation pharmacotherapies: a network meta-analysis.

BACKGROUND: Stopping smoking is associated with many important improvements in health and quality of life. The use of cessation medications is recommended to increase the likelihood of quitting. However, there is historical and renewed concern that smoking cessation therapies may increase the risk of cardiovascular disease events associated within the quitting period. We aimed to examine whether the 3 licensed smoking cessation therapies-nicotine replacement therapy, bupropion, and varenicline-were associated with an increased risk of cardiovascular disease events using a network meta-analysis. METHODS AND RESULTS: We searched 10 electronic databases, were in communication with authors of published randomized, clinical trials (RCTs), and accessed internal US Food and Drug Administration reports. We included any RCT of the 3 treatments that reported cardiovascular disease outcomes. Among 63 eligible RCTs involving 21 nicotine replacement therapy RCTs, 28 bupropion RCTs, and 18 varenicline RCTs, we found no increase in the risk of all cardiovascular disease events with bupropion (relative risk [RR], 0.98; 95% confidence interval [CI], 0.54-1.73) or varenicline (RR, 1.30; 95% CI, 0.79-2.23). There was an elevated risk associated with nicotine replacement therapy that was driven predominantly by less serious events (RR, 2.29; 95% CI, 1.39-3.82). When we examined major adverse cardiovascular events, we found a protective effect with bupropion (RR, 0.45; 95% CI, 0.21-0.85) and no clear evidence of harm with varenicline (RR, 1.34; 95% CI, 0.66-2.66) or nicotine replacement therapy (RR, 1.95; 95% CI, 0.26-4.30). CONCLUSION: Smoking cessation therapies do not appear to raise the risk of serious cardiovascular disease events.

The architecture of diagnostic research: from bench to bedside--research guidelines using liver stiffness as an example.

UNLABELLED: The diagnostic research process can be divided into five phases, designed to establish the clinical utility of a new diagnostic test--the index test. The aim of the present review is to illustrate the study designs that are appropriate for each diagnostic phase, using clinical examples regarding liver fibrosis diagnosed with transient elastography, when possible. Phase 0 is the preclinical pilot phase during which the validity, reliability, and reproducibility of the index test are assessed in healthy and diseased people. Phase I is designed to describe the distribution of the index test results in healthy people and its normal values. Phase IIA comprises studies designed to estimate the accuracy (sensitivity and specificity) of the index test in discriminating between diseased and nondiseased people in a clinically relevant population. Phase IIB studies allow the comparison of the accuracy of different index tests; Phase IIC studies aim to evaluate the possible harms of incorporating the index test in a diagnostic-therapeutic strategy. In phase III, diagnostic test-therapeutic randomized clinical trials aim to assess the benefits and harms of the new diagnostic-therapeutic strategy versus the present strategy. Phase IV comprises large surveillance cohort studies that aim to assess the effectiveness of the new diagnostic-therapeutic strategy in clinical practice. CONCLUSION: As common in clinical research, giving excessive weight to the results of single studies and trials is likely to divert from the totality of evidence obtained through the systematic reviews of these studies, conducted with rigorous methodology and statistical methods. (Hepatology 2014;60:408-418).

What drives the comparative effectiveness of biologics vs. methotrexate in rheumatoid arthritis? Meta-regression and graphical inspection of suspected clinical factors.

OBJECTIVE: The aim of this study was to explore which clinical factors and patient characteristics are associated with the magnitude of comparative efficacy between biologics vs. MTX in RA patients with inadequate response to MTX. METHODS: We included randomized controlled trials assessing the efficacy of a biologic plus MTX vs. MTX alone. We examined several clinical factors and patient characteristics potentially associated with magnitude of response, measured as ACR20 (20% improvement in ACR criteria) and ACR50 (16-26 weeks). We employed meta-regression for formal estimates and statistical significance of effect modification. We produced regression and forest plots to further inspect potential associations. RESULTS: For ACR50, a 1-year increment on the average patient disease duration was statistically significantly associated with a 16% relative increase in the pooled odds ratio (OR) estimate (P = 0.003). A 1-year increment in patient age and a 1 mg/week increment in MTX dose were marginally statistically significantly associated with a 9% (P = 0.056) and 22% (P = 0.092) relative increase in the OR. For ACR20, the average number of swollen and tender joints was marginally statistically associated with a 3% relative decrease. The associations for age and MTX dose appeared to be partly driven by significant negative associations between these two factors and the control group response. CONCLUSION: Our analyses identified key variables associated with the magnitude of comparative effects for ACR outcomes. Our findings provide valuable insights for future trial designs and systematic reviews as well as decision-making and clinical practice.