Conservative Point Estimate Research Articles

Adaptive Multiple Comparison Sequential Design (AMCSD) for clinical trials

ABSTRACT We propose an adaptive sequential testing procedure for clinical trials that test the efficacy of multiple treatment options, such as dose/regimen, different drugs, sub-populations, endpoints, or a mixture of them in one trial. At any interim analyses, sample size re-estimation can be conducted, and any option can be dropped for lack of efficacy or unsatisfactory safety profile. Inference after the trial, including p-value, conservative point estimate and confidence intervals, are provided.

Intention-to-treat analysis may be more conservative than per protocol analysis in antibiotic non-inferiority trials: a systematic review

BackgroundIn non-inferiority trials, there is a concern that intention-to-treat (ITT) analysis, by including participants who did not receive the planned interventions, may bias towards making the treatment and control arms look similar and lead to mistaken claims of non-inferiority. In contrast, per protocol (PP) analysis is viewed as less likely to make this mistake and therefore preferable in non-inferiority trials. In a systematic review of antibiotic non-inferiority trials, we compared ITT and PP analyses to determine which analysis was more conservative.MethodsIn a secondary analysis of a systematic review, we included non-inferiority trials that compared different antibiotic regimens, used absolute risk reduction (ARR) as the main outcome and reported both ITT and PP analyses. All estimates and confidence intervals (CIs) were oriented so that a negative ARR favored the control arm, and a positive ARR favored the treatment arm. We compared ITT to PP analyses results. The more conservative analysis between ITT and PP analyses was defined as the one having a more negative lower CI limit.ResultsThe analysis included 164 comparisons from 154 studies. In terms of the ARR, ITT analysis yielded the more conservative point estimate and lower CI limit in 83 (50.6%) and 92 (56.1%) comparisons respectively. The lower CI limits in ITT analysis favored the control arm more than in PP analysis (median of − 7.5% vs. -6.9%, p = 0.0402). CIs were slightly wider in ITT analyses than in PP analyses (median of 13.3% vs. 12.4%, p < 0.0001). The median success rate was 89% (interquartile range IQR 82 to 93%) in the PP population and 44% (IQR 23 to 60%) in the patients who were included in the ITT population but excluded from the PP population (p < 0.0001).ConclusionsContrary to common belief, ITT analysis was more conservative than PP analysis in the majority of antibiotic non-inferiority trials. The lower treatment success rate in the ITT analysis led to a larger variance and wider CI, resulting in a more conservative lower CI limit. ITT analysis should be mandatory and considered as either the primary or co-primary analysis for non-inferiority trials.Trial registrationPROSPERO registration number CRD42020165040.

Glucocorticosteroids for people with alcoholic hepatitis.

Glucocorticosteroids for people with alcoholic hepatitis.

Use of multiple lines of evidence to provide a realistic toxic substances control act ecological risk evaluation based on monitoring data: D4 case study

D4 (octamethylcyclotetrasiloxane) is a high-production-volume cyclic volatile methyl siloxane with a wide range of industrial and consumer applications. This study conducted a robust ecological risk evaluation for D4 using exposure data collected under a nation-wide environmental monitoring program facilitated under the Toxic Substances Control Act (TSCA). This ecological risk evaluation was conducted consistent with the principles outlined in the U.S. Environmental Protection Agency's (EPA's) Guidance to Assist Interested Persons in Developing and Submitting Draft Risk Evaluations under TSCA (U.S. EPA 2017a). The evaluation examined multiple lines of evidence (LoEs) to determine the potential risks from D4 to aquatic receptors in rivers and streams in the United States from municipal wastewater treatment plant (WWTP) discharges and discharges from manufacturing, processing, and/or formulating (MPF) facilities after onsite wastewater treatment. The LoEs consisted of comparing D4 concentrations measured in water and sediment to toxicity thresholds derived from laboratory studies; comparing D4 concentrations measured in biota tissue to critical target lipid body burdens (CTLBBs); comparing fugacity-based chemical activities between toxicity thresholds and measured environmental concentrations; and assessing benthic macroinvertebrate community structure and habitat suitability. The approach taken moves beyond a standard deterministic hazard quotient approach to incorporate more advanced methods for risk prediction, using distributions rather than conservative point estimates of exposure to obtain a realistic view of the probability of harm, consistent with EPA's stated intent to “strive to utilize probabilistic approaches for exposure assessments included in a risk evaluation” (U.S. EPA 2017b). The risk evaluation concluded there is negligible risk to water column and sediment receptors from D4 discharged from MPF facilities after onsite wastewater treatment or from municipal WWTPs that may treat a mix of industrial and consumer wastewater.

Glucocorticosteroids for people with alcoholic hepatitis.

Glucocorticosteroids for people with alcoholic hepatitis.

Control-Based Imputation and Delta-Adjustment Stress Test for Missing Data Analysis in Longitudinal Clinical Trials

ABSTRACTSensitivity analyses using multiple imputation (MI) provide a flexible approach to assess the impact of missing data on clinical trial results. An approach that imputes missing data in the test drug group using a model built from the control group has gained attention in recent research. This control-based imputation (CBI) approach typically provides a conservative point estimate for treatment difference. However, the combined variance using Rubin's rule may over-estimate the variability. In this article, we investigate the statistical properties for some specific CBI methods, and show the relationship between CBI and delta-adjustment tipping point analysis. This relationship helps us to understand and interpret the results from CBI using MI with Rubin's rule. In addition, we propose a new sensitivity measure for assessing the robustness of the result obtained under a missing at random (MAR) assumption. Results from simulation studies and applications to longitudinal clinical trial datasets are presented as illustration.

Hepatitis B immunoglobulin during pregnancy for prevention of mother-to-child transmission of hepatitis B virus.

Hepatitis B immunoglobulin during pregnancy for prevention of mother-to-child transmission of hepatitis B virus.

The Development of Risk-Based Remediation Target Value for Lead Contaminated Soils

With the rapid economic development, China is experiencing increased land contamination and lead poisoning problem in recent years, which is no longer restricted to isolated incidents and locations. There is an urgent need to remediate the lead contaminated soils to protect the publics health. However, contaminated land remediation and determination of remediation target value has been neglected for years. In order to accommodate uncertainties within the conservative point estimation of remediation target value for lead contaminated soils, Monte Carlo simulation technique is integrated into the traditional calculation model from a probabilistic perspective. Risk-based remediation target values for lead contaminated soils of different land use types (including school/hospital, residential, business and industrial use) are developed preliminarily. Furthermore, this study highlights the necessity to determine the remediation target value on the basis of actual (i.e. site-specific) risks to humans and, besides, actual risks due to contaminant migration.

Outcomes in Seriously Head-Injured Patients Undergoing Pre-Hospital Tracheal Intubation vs. Emergency Department Tracheal Intubation

Background: The optimal treatment of major head injuries in the resuscitative phase of care post-injury has yet to be determined. This study measured the effect on mortality of pre-hospital intubation (PHI) vs. emergency department in tubation (EDI) of patients suffering serious head injury. Methods: In the single emergency medical services system for this Canadian province, we used a population-based trauma database, conventional logistic regression (with and without the use of a propensity score to control for selection effect bias) to evaluate the effect of PHI vs. EDI on in-hospital mortality. Inclusion criteria were age ≥ 16 years, serious head injury (Abbreviated Injury Score ≥ 3, non-penetrating trauma) and resuscitative intubation (PHI or EDI). Results: Over 5 years, 283 patients (2000-2005) met inclusion crite ria. Conventional unconditional logistic regression modelled on mortality with “PHI vs. EDI” as the intervention of interest showed an odds ratio of 2.015 (95% CI 1.062 3.825) for improved survival if these patients were intubated in the emergency department rather than in the pre-hospital phase of care. A propensity score adjustment demonstrated a similar but more conservative point estimate (OR 1.727, 95% CI: 0.993 3.004). Conclusions: This observational study demonstrated a survival advantage with EDI (versus PHI) in seriously head-injured patients in a mature, province-wide emergency medical services system.

Adaptive and Dynamic Adaptive Procedures for False Discovery Rate Control and Estimation

SummaryMany methods for estimation or control of the false discovery rate (FDR) can be improved by incorporating information about π0, the proportion of all tested null hypotheses that are true. Estimates of π0 are often based on the number of p-values that exceed a threshold λ. We first give a finite sample proof for conservative point estimation of the FDR when the λ-parameter is fixed. Then we establish a condition under which a dynamic adaptive procedure, whose λ-parameter is determined by data, will lead to conservative π0- and FDR estimators. We also present asymptotic results on simultaneous conservative FDR estimation and control for a class of dynamic adaptive procedures. Simulation results show that a novel dynamic adaptive procedure achieves more power through smaller estimation errors for π0 under independence and mild dependence conditions. We conclude by discussing the connection between estimation and control of the FDR and show that several recently developed FDR control procedures can be cast in a unifying framework where the strength of the procedures can be easily evaluated.

Statins and renovascular disease in the elderly: a population-based cohort study

More than 90% of cases of renovascular disease (RVD) are caused by atherosclerosis; thus patients with this condition are at high risk for vascular events. We examined the association of statins with prognosis in patients with RVD. We performed a population-based cohort study in 4040 patients with RVD older than 65 years using province-wide health data in Ontario, Canada. The primary outcome was time to first cardiorenal event, specifically myocardial infarction, stroke, heart failure, acute renal failure, dialysis or death; the primary analysis used a time-dependent covariate for statin exposure. Despite having a greater burden of cardiovascular and renal comorbidity, the risk of the primary outcome was significantly lower in statin users than in non-users [unadjusted hazard ratio (HR) 0.51, 95% confidence interval (CI) 0.47-0.57; P < 0.0001]. This association was materially unchanged after adjusting for demographic characteristics, cardiovascular risk factors, other comorbidities, measures of health-care utilization, screening, and concomitant medications (adjusted HR 0.51, 95% CI 0.46-0.57). An analysis using the same endpoint in a propensity-matched cohort without time-dependent statin exposure revealed a lower risk of the primary outcome in statin-treated patients but with a substantially more conservative point estimate (HR 0.82, 95% CI 0.71-0.95). These data suggest that statins are associated with improved prognosis in elderly patients with RVD.

Biological Variation of the Platelet Proteome in the Elderly Population and Its Implication for Biomarker Research

Knowledge about the extent of total variation experienced between samples from different individuals is of great importance for the design of not only proteomics but every clinical study. This variation defines the smallest statistically significant detectable signal difference when comparing two groups of individuals. We isolated platelets from 20 healthy human volunteers aged 56-100 years because this age group is most commonly encountered in the clinics. We determined the technical and total variation experienced in a proteome analysis using two-dimensional DIGE with IPGs in the pI ranges 4-7 and 6-9. Only spots that were reproducibly detectable in at least 90% of all gels (n = 908) were included in the study. All spots had a similar technical variation with a median coefficient of variation (cv) of about 7%. In contrast, spots showed a more diverse total variation between individuals with a surprisingly low median cv of only 18%. Because most known biomarkers show an effect size in a 1-2-fold range of their cv, any future clinical proteomics study with platelets will require an analytical method that is able to detect such small quantitative differences. In addition, we calculated the minimal number of samples (sample size) needed to detect given protein expression differences with statistical significance.

Two-stage stepup procedures controlling FDR

A two-stage stepup procedure is defined and an explicit formula for the FDR of this procedure is derived under any distributional setting. Sets of critical values are determined that provide a control of the FDR of a two-stage stepup procedure under iid mixture model. A class of two-stage FDR procedures modifying the Benjamini–Hochberg (BH) procedure and containing the one given in Storey et al. [2004. Strong control, conservative point estimation and simultanaeous conservative consistency of false discovery rates: a unified approach. J. Roy. Statist. Soc. Ser. B 66, 187–205] is obtained. The FDR controlling property of the Storey–Taylor–Siegmund procedure is proved only under the independence, which is different from that presented by these authors. A single-stage stepup procedure controlling the FDR under any form of dependence, which is different from and in some situations performs better than the Benjamini–Yekutieli (BY) procedure, is given before discussing how to obtain two-stage versions of the BY and this new procedures. Simulations reveal that procedures proposed in this article under the mixture model can perform quite well in terms of improving the FDR control of the BH procedure. However, the similar idea of improving the FDR control of a stepup procedure under any form dependence does not seem to work.

Acknowledgement of Priority: Strong Control, Conservative Point Estimation and Simultaneous Conservative Consistency of False Discovery Rates: a Unified Approach

Journal of the Royal Statistical Society: Series B (Statistical Methodology)Volume 67, Issue 1 p. 197-197 Acknowledgement of priority: Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach John D. Storey, John D. Storey University of Washington, Seattle, USASearch for more papers by this authorJonathan E. Taylor, Jonathan E. Taylor Stanford University, Stanford, USASearch for more papers by this authorDavid Siegmund, David Siegmund Stanford University, Stanford, USASearch for more papers by this author John D. Storey, John D. Storey University of Washington, Seattle, USASearch for more papers by this authorJonathan E. Taylor, Jonathan E. Taylor Stanford University, Stanford, USASearch for more papers by this authorDavid Siegmund, David Siegmund Stanford University, Stanford, USASearch for more papers by this author First published: 13 December 2004 https://doi.org/10.1111/j.1467-9868.2005.00496.xCitations: 2 John D. Storey, Department of Biostatistics, University of Washington, Box 357232, Seattle, WA 98195-7232, USA. E-mail: jstorey@u.washington.edu Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article.Citing Literature Volume67, Issue1February 2005Pages 197-197 RelatedInformation

Strong Control, Conservative Point Estimation and Simultaneous Conservative Consistency of False Discovery Rates: A Unified Approach

Summary The false discovery rate (FDR) is a multiple hypothesis testing quantity that describes the expected proportion of false positive results among all rejected null hypotheses. Benjamini and Hochberg introduced this quantity and proved that a particular step-up p-value method controls the FDR. Storey introduced a point estimate of the FDR for fixed significance regions. The former approach conservatively controls the FDR at a fixed predetermined level, and the latter provides a conservatively biased estimate of the FDR for a fixed predetermined significance region. In this work, we show in both finite sample and asymptotic settings that the goals of the two approaches are essentially equivalent. In particular, the FDR point estimates can be used to define valid FDR controlling procedures. In the asymptotic setting, we also show that the point estimates can be used to estimate the FDR conservatively over all significance regions simultaneously, which is equivalent to controlling the FDR at all levels simultaneously. The main tool that we use is to translate existing FDR methods into procedures involving empirical processes. This simplifies finite sample proofs, provides a framework for asymptotic results and proves that these procedures are valid even under certain forms of dependence.

Validation analysis of probabilistic models of dietary exposure to food additives

The validity of a range of simple conceptual models designed specifically for the estimation of food additive intakes using probabilistic analysis was assessed. Modelled intake estimates that fell below traditional conservative point estimates of intake and above ‘true’ additive intakes (calculated from a reference database at brand level) were considered to be in a valid region. Models were developed for 10 food additives by combining food intake data, the probability of an additive being present in a food group and additive concentration data. Food intake and additive concentration data were entered as raw data or as a lognormal distribution, and the probability of an additive being present was entered based on the per cent brands or the per cent eating occasions within a food group that contained an additive. Since the three model components assumed two possible modes of input, the validity of eight (23) model combinations was assessed. All model inputs were derived from the reference database. An iterative approach was employed in which the validity of individual model components was assessed first, followed by validation of full conceptual models. While the distribution of intake estimates from models fell below conservative intakes, which assume that the additive is present at maximum permitted levels (MPLs) in all foods in which it is permitted, intake estimates were not consistently above ‘true’ intakes. These analyses indicate the need for more complex models for the estimation of food additive intakes using probabilistic analysis. Such models should incorporate information on market share and/or brand loyalty.

What Level of Fixed Costs Can Reconcile Consumption and Stock Returns?

This paper proposes a lower bound on the level of fixed transaction costs that is required for observations on consumption choices to be consistent with data on asset returns and a given set of preferences. The bound is derived from necessary conditions for the optimality of consumption choices in the presence of fixed transaction costs. These conditions reduce to standard Euler equations when transaction costs are zero. Conservative point estimates suggest that a consumer with log utility who consumes U. S. per capita consumption and who can trade in U. S. Treasury bills and an index of New York Stock Exchange stocks must face a fixed transaction cost of at least 3 percent of monthly per capita consumption. This lower bound declines rapidly with increases in risk aversion or when certain restrictions on short selling are included.

Monte Carlo techniques for quantitative uncertainty analysis in public health risk assessments.

Most public health risk assessments assume and combine a series of average, conservative, and worst-case values to derive a conservative point estimate of risk. This procedure has major limitations. This paper demonstrates a new methodology for extended uncertainty analyses in public health risk assessments using Monte Carlo techniques. The extended method begins as do some conventional methods--with the preparation of a spreadsheet to estimate exposure and risk. This method, however, continues by modeling key inputs as random variables described by probability density functions (PDFs). Overall, the technique provides a quantitative way to estimate the probability distributions for exposure and health risks within the validity of the model used. As an example, this paper presents a simplified case study for children playing in soils contaminated with benzene and benzo(a)pyrene (BaP).