scholarly journals Independence estimators for re-randomisation trials in multi-episode settings: a simulation study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Brennan C. Kahan ◽  
Ian R. White ◽  
Sandra Eldridge ◽  
Richard Hooper
Keyword(s):  
Simulation Study ◽  
Treatment Effect ◽  
Standard Errors ◽  
Average Effect ◽  
Treatment Allocation ◽  
Treatment Groups ◽  
Different Types ◽  
Added Benefit ◽  
Nominal Coverage ◽  
New Treatment

Abstract Background Re-randomisation trials involve re-enrolling and re-randomising patients for each new treatment episode they experience. They are often used when interest lies in the average effect of an intervention across all the episodes for which it would be used in practice. Re-randomisation trials are often analysed using independence estimators, where a working independence correlation structure is used. However, research into independence estimators in the context of re-randomisation has been limited. Methods We performed a simulation study to evaluate the use of independence estimators in re-randomisation trials. We focussed on a continuous outcome, and the setting where treatment allocation does not affect occurrence of subsequent episodes. We evaluated different treatment effect mechanisms (e.g. by allowing the treatment effect to vary across episodes, or to become less effective on re-use, etc), and different non-enrolment mechanisms (e.g. where patients who experience a poor outcome are less likely to re-enrol for their second episode). We evaluated four different independence estimators, each corresponding to a different estimand (per-episode and per-patient approaches, and added-benefit and policy-benefit approaches). Results We found that independence estimators were unbiased for the per-episode added-benefit estimand in all scenarios we considered. We found independence estimators targeting other estimands (per-patient or policy-benefit) were unbiased, except when there was differential non-enrolment between treatment groups (i.e. when different types of patients from each treatment group decide to re-enrol for subsequent episodes). We found the use of robust standard errors provided close to nominal coverage in all settings where the estimator was unbiased. Conclusions Careful choice of estimand can ensure re-randomisation trials are addressing clinically relevant questions. Independence estimators are a useful approach, and should be considered as the default estimator until the statistical properties of alternative estimators are thoroughly evaluated.

scholarly journals Integrating informative hypotheses into the EffectLiteR framework

Methodology ◽  
2021 ◽  
Vol 17 (4) ◽  
pp. 307-325
Author(s):  
Caroline Keck ◽  
Axel Mayer ◽  
Yves Rosseel
Keyword(s):  
Null Hypothesis ◽  
Simulated Data ◽  
Wald Test ◽  
Wald Statistic ◽  
Average Effect ◽  
Treatment Groups ◽  
Stochastic Nature ◽  
Classical Test ◽  
Non Linear ◽  
New Treatment

Using the EffectLiteR framework, researchers can test classical null hypotheses about effects of interest via Wald and F-tests, while taking into account the stochastic nature of group sizes. This paper aims at extending EffectLiteR to test informative hypotheses, assuming for example that the average effect of a new treatment is greater than the average effect of an old treatment, which in turn is greater than zero. We present a simulated data example to show two methodological novelties. First, we illustrate how to use the Fbar- and generalized linear Wald test to assess informative hypotheses. While the classical test did not reach significance, the informative test correctly rejected the null hypothesis, indicating the need to take into account the order of the treatment groups. Second, we demonstrate how to account for stochastic group sizes in informative hypotheses using the generalized non-linear Wald statistic. The paper concludes with a short data example.

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

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Steve Kanters ◽  
Mohammad Ehsanul Karim ◽  
Kristian Thorlund ◽  
Aslam Anis ◽  
Nick Bansback
Keyword(s):  
Simulation Study ◽  
Treatment Effect ◽  
Mean Squared Error ◽  
Individual Patient Data ◽  
Meta Analysis ◽  
Model Performance ◽  
Patient Data ◽  
Meta Regression ◽  
Treatment Comparisons ◽  
The Impact

Abstract 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.

scholarly journals Lymphangiogenesis and Lesion Heterogeneity in Interstitial Lung Diseases

2015 ◽  
Vol 9s1 ◽  
pp. CCRPM.S33856 ◽  
Author(s):  
Masahiro Yamashita
Keyword(s):  
Lung Diseases ◽  
Interstitial Fluid ◽  
Usual Interstitial Pneumonia ◽  
Treatment Strategies ◽  
Interstitial Lung Diseases ◽  
Lymphatic Endothelial Cells ◽  
Different Types ◽  
New Treatment ◽  
Capillary Angiogenesis ◽  
Antigen Presenting

The lymphatic system has several physiological roles, including fluid homeostasis and the activation of adaptive immunity by fluid drainage and cell transport. Lymphangiogenesis occurs in adult tissues during various pathologic conditions. In addition, lymphangiogenesis is closely linked to capillary angiogenesis, and the balanced interrelationship between capillary angiogenesis and lymphangiogenesis is essential for maintaining homeostasis in tissues. Recently, an increasing body of information regarding the biology of lymphatic endothelial cells has allowed us to immunohistochemically characterize lymphangiogenesis in several lung diseases. Particular interest has been given to the interstitial lung diseases. Idiopathic interstitial pneumonias (IIPs) are characterized by heterogeneity in pathologic changes and lesions, as typified by idiopathic pulmonary fibrosis/usual interstitial pneumonia. In IIPs, lymphangiogenesis is likely to have different types of localized functions within each disorder, corresponding to the heterogeneity of lesions in terms of inflammation and fibrosis. These functions include inhibitory absorption of interstitial fluid and small molecules and maturation of fibrosis by excessive interstitial fluid drainage, caused by an unbalanced relationship between capillary angiogenesis and lymphangiogenesis and trafficking of antigen-presenting cells and induction of fibrogenesis via CCL21 and CCR7 signals. Better understanding for regional functions of lymphangiogenesis might provide new treatment strategies tailored to lesion heterogeneity in these complicated diseases.

Programming in Restrictive Housing: Considerations for Improving Outcome Evaluations

2018 ◽  
Vol 45 (8) ◽  
pp. 1174-1191 ◽  
Author(s):  
H. Daniel Butler ◽  
Starr Solomon ◽  
Ryan Spohn
Keyword(s):  
Treatment Effect ◽  
Successful Implementation ◽  
Inmate Misconduct ◽  
The Past ◽  
What Works ◽  
Different Types ◽  
Time Served ◽  
Using Data ◽  
Outcome Evaluations ◽  
Behavioral Programming

A number of studies have identified “what works” in regard to the successful implementation of correctional programming over the past several decades. Few studies, however, have examined the complexities associated with programming in restrictive housing. Using data from a Midwestern department of corrections, we examined whether the provision of programming in restrictive housing achieved desired outcomes (e.g., reductions in inmate misconduct). The findings revealed the amount of time served in restrictive housing and confinement in different types of restrictive housing may influence estimations of a treatment effect. As a growing number of states seek to reform the use of restrictive housing, the proper implementation of cognitive-behavioral programming may increase institutional security and safety.

Evaluating New Treatments and Diagnostic Technologies in Obstetrics: Practical Problems, Ethics, and Solutions

1989 ◽  
Vol 5 (3) ◽  
pp. 459-472 ◽  
Author(s):  
Richard J. Lilford
Keyword(s):  
Clinical Practice ◽  
Decision Theory ◽  
Treatment Effect ◽  
Conventional Therapy ◽  
Inexpensive Method ◽  
Less Invasive ◽  
New Treatment ◽  
New Treatments ◽  
Diagnostic Technologies ◽  
Clinical Experiments

This article develops arguments for the use of decision theory, rather than intuition, to determine the size of trials. It is wrong to expect doctors to ignore personal preferences in favor of clinical experiments unless the trial is capable of showing differences in treatment effect that would influence clinical practice substantially. It follows from our analysis that if delta (the treatment effect that the trial is designed to detect) is sufficient to alter clinical practice, then the alpha and beta errors of a trial should be equal. This applies even if a new treatment is to be compared with conventional therapy or if a treatment with high “costs” is compared with a less invasive or more inexpensive method.

scholarly journals Interval estimation of the overall treatment effect in random-effects meta-analyses: Recommendations from a simulation study comparing frequentist, Bayesian, and bootstrap methods

2020 ◽  
Author(s):  
Frank Weber ◽  
Guido Knapp ◽  
Anne Glass ◽  
Günther Kundt ◽  
Katja Ickstadt
Keyword(s):  
Literature Review ◽  
Random Effects ◽  
Simulation Study ◽  
Treatment Effect ◽  
Profile Likelihood ◽  
Meta Analysis ◽  
Artery Bypass ◽  
Interval Length ◽  
Interval Estimators ◽  
Meta Analyses

There exists a variety of interval estimators for the overall treatment effect in a random-effects meta-analysis. A recent literature review summarizing existing methods suggested that in most situations, the Hartung-Knapp/Sidik-Jonkman (HKSJ) method was preferable. However, a quantitative comparison of those methods in a common simulation study is still lacking. Thus, we conduct such a simulation study for continuous and binary outcomes, focusing on the medical field for application.Based on the literature review and some new theoretical considerations, a practicable number of interval estimators is selected for this comparison: the classical normal-approximation interval using the DerSimonian-Laird heterogeneity estimator, the HKSJ interval using either the Paule-Mandel or the Sidik-Jonkman heterogeneity estimator, the Skovgaard higher-order profile likelihood interval, a parametric bootstrap interval, and a Bayesian interval using different priors. We evaluate the performance measures (coverage and interval length) at specific points in the parameter space, i.e. not averaging over a prior distribution. In this sense, our study is conducted from a frequentist point of view.We confirm the main finding of the literature review, the general recommendation of the HKSJ method (here with the Sidik-Jonkman heterogeneity estimator). For meta-analyses including only 2 studies, the high length of the HKSJ interval limits its practical usage. In this case, the Bayesian interval using a weakly informative prior for the heterogeneity may help. Our recommendations are illustrated using a real-world meta-analysis dealing with the efficacy of an intramyocardial bone marrow stem cell transplantation during coronary artery bypass grafting.

scholarly journals An Introduction to Economic Evaluation: What's in a Name?

2005 ◽  
Vol 50 (3) ◽  
pp. 159-166 ◽  
Author(s):  
Jeffrey S Hoch ◽  
Carolyn S Dewa
Keyword(s):  
Economic Evaluation ◽  
Evaluation Method ◽  
Cost Effective ◽  
Economic Evaluations ◽  
Economic Study ◽  
Value Judgment ◽  
A Value ◽  
Different Types ◽  
New Treatment ◽  
Evaluation Techniques

Objective: This paper describes the main types of economic evaluation techniques. Method: To examine the strengths and limitations of different types of economic evaluations, we used a hypothetical example to review the reasoning underlying each method and to illustrate when it is appropriate to use each method. Results: The choice of economic evaluation method reflects a decision about what should represent “success” and how success should be valued. Measures of benefit and cost must be considered systematically and simultaneously. Claiming that a new treatment is cost-effective requires making a value judgment based on the personal beliefs of the claimant. Even when cost and effect data are objective, a verdict of cost-effective is subjective. The conclusions of an economic study can change significantly, depending on which patient outcome is used to measure success. Conclusions: Clinicians must be sure that important patient outcomes are not excluded from economic evaluations. Economic evaluation is a process designed to produce an estimate rather than a decision. New treatment can be more costly and still be cost-effective (if the extra benefit is valued more than the extra cost to produce it). However, since economic evaluation does not explicitly consider a decision maker's available budget, a new treatment can be deemed cost-effective but too expensive to approve.

scholarly journals New therapeutic patents used for the treatment of leprosy: a review

2018 ◽  
Vol 146 (14) ◽  
pp. 1746-1749 ◽  
Author(s):  
Nayara Gomes Lima Santos ◽  
Karen Perez Pereira Ramos ◽  
Saravanan Shanmugam ◽  
Fernanda Oliveira de Carvalho ◽  
Luciana Garcez Barreto Teixeira ◽  
...  
Keyword(s):  
Peripheral Nerves ◽  
Peripheral Neuropathies ◽  
Loss Of Function ◽  
Cutaneous Lesions ◽  
Patent Classification ◽  
Human Needs ◽  
International Patent ◽  
Different Types ◽  
New Treatment

AbstractLeprosy is a granulomatous disease, infectious and transmissible, which affects the skin and peripheral nerves, havingMycobacterium lepraeas causative agent. The manifestation of this disease causes cutaneous lesions, peripheral neuropathies and, in more extreme cases, may generate deformities and disabilities in affected individuals. Patents were identified using the descriptor ‘leprosy’ and code A61K of the international patent classification, which indicates only products that meet human needs. The analysis was made using theWIPO,ESPACENETandUSPTOdatabases, until the month of September 2016. Through this review, we found a variety of in vitro, pre-clinical and clinical studies relating to the treatment of leprosy with different types of compounds and forms of administration. New treatment proposals should include pain reduction capabilities, prevention or limitation of the appearance of cutaneous lesions, as well as prevention of the progression of the disease to more severe stages that may lead to loss of function or potentiate the individual's immune response to theM. lepraebacillus in order to prevent bacterial spread. We concluded that any patents developed with natural products were not found in the treatment of leprosy. All the deposited products were synthetic origin, mostly tested in humans and of varied forms of administration.

Effect of Color Coding on Visually and Verbally Oriented Tests with Students of Different Field Dependence Levels

1992 ◽  
Vol 20 (4) ◽  
pp. 311-320 ◽  
Author(s):  
Francis M. Dwyer ◽  
David M. Moore
Keyword(s):  
Field Dependence ◽  
Information Acquisition ◽  
Color Coding ◽  
Treatment Groups ◽  
Black And White ◽  
Field Dependent ◽  
Different Types ◽  
Respective Treatment ◽  
The Impact ◽  
Instructional Variable

To assess the impact of instructional color coding on visually and verbally oriented tests and on field-dependent-independent subjects, undergraduate college students (119) were randomly assigned to two treatment groups (color—black and white). These subjects received their respective treatment and received four dependent measures measuring four different types of educational objectives. Results indicated that the subject's level of field dependence is an important instructional variable and that color coding is an effective variable for maximizing information acquisition levels for field dependent over oriented subjects.

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