Statistical communications in infectious diseases最新文献

{"title":"Bayesian Design of Agricultural Disease Transmission Experiments for Individual Level Models","authors":"G. Kwong, R. Deardon, Scott Hunt, M. Guerin","doi":"10.1515/scid-2018-0005","DOIUrl":"https://doi.org/10.1515/scid-2018-0005","url":null,"abstract":"Abstract Here, we address the issue of experimental design for animal and crop disease transmission experiments, where the goal is to identify some characteristic of the underlying infectious disease system via a mechanistic disease transmission model. Design for such non-linear models is complicated by the fact that the optimal design depends upon the parameters of the model, so the problem is set in simulation-based, Bayesian framework using informative priors. This involves simulating the experiment over a given design repeatedly using parameter values drawn from the prior, calculating a Monte Carlo estimate of the utility function from those simulations for the given design, and then repeating this over the design space in order to find an optimal design or set of designs. Here we consider two agricultural scenarios. The first involves an experiment to characterize the effectiveness of a vaccine-based treatment on an animal disease in an in-barn setting. The design question of interest is on which days to make observations if we are limited to being able to observe the disease status of all animals on only two days. The second envisages a trial being carried out to estimate the spatio-temporal transmission dynamics of a crop disease. The design question considered here is how far apart to space the plants from each other to best capture those dynamics. In the in-barn animal experiment, we see that for the prior scenarios considered, observations taken very close to the beginning of the experiment tend to lead to designs with the highest values of our chosen utility functions. In the crop trial, we see that over the prior scenarios considered, spacing between plants is important for experimental performance, with plants being placed too close together being particularly deleterious to that performance.","PeriodicalId":74867,"journal":{"name":"Statistical communications in infectious diseases","volume":"435 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83629733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Designing the Next Generation of HIV Prevention Efficacy Trials: Synopsis of a 2018 Symposium","authors":"H. Janes, D. Donnell, M. Nason","doi":"10.1515/scid-2019-0004","DOIUrl":"https://doi.org/10.1515/scid-2019-0004","url":null,"abstract":"Abstract A one-day symposium was held in Seattle, Washington on November 5, 2018, including a broad array of stakeholders in the HIV prevention community. The topic of discussion was the challenge of designing future HIV prevention efficacy trials, given the multiplicity and speed of changes in the field in recent years, the development and rollout of effective prevention tools, and the resultant complexity in designing trials to evaluate new HIV prevention products. The goal was to identify potential statistical trial design approaches worthy of further investigation, as well as gaps in understanding and logical next steps. We overview the themes that emerged from the presentations, panels, and floor discussions, and outline initial next steps in further exploring design options.","PeriodicalId":74867,"journal":{"name":"Statistical communications in infectious diseases","volume":"65 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76281517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regulatory Perspectives for Streamlining HIV Prevention Trials","authors":"J. Murray","doi":"10.1515/scid-2019-0002","DOIUrl":"https://doi.org/10.1515/scid-2019-0002","url":null,"abstract":"Abstract Designing and conducting active-controlled trials of HIV pre-exposure prophylaxis (PrEP) therapeutics are becoming challenging due to inconsistency of adherence across trials and the need for increasingly larger trials to assess efficacy. In the United States (US), trials evaluating oral contraceptives (OC) use the Pearl Index to assess efficacy in single-arm trials. This article explores the possibility of using an index (“HIV Incidence Index”) analogous to the Pearl Index to assess preventive efficacy in active-controlled HIV prevention trials in sexually-acquired HIV. One proposal for constructing an HIV Incidence Index is to use the incidence of sexually transmitted infections (STIs) during a trial to serve as a marker for HIV risk behavior and to estimate what the HIV seroconversion rate would have been had the participants not been on efficacious PrEP. In addition, a consensus of expert opinion will be needed to define clinically acceptable HIV seroconversion rates for populations at risk of HIV-infection receiving active PrEP.","PeriodicalId":74867,"journal":{"name":"Statistical communications in infectious diseases","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87214562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Modern Randomized Clinical Trial: Is it Time to Sharpen a Blunt Instrument?","authors":"J. Wittes","doi":"10.1515/scid-2019-0005","DOIUrl":"https://doi.org/10.1515/scid-2019-0005","url":null,"abstract":"Abstract In spite of the obvious differences in the diseases under study, designs of trials of prevention of HIV and cardiovascular disease share some common features. A trial of prevention should identify a population at risk for the disease; it should have a clearly defined, clinically important, outcome; it should be large enough to have sufficient power to detect an effect of public health importance; and participants should be followed long enough for the effect of the intervention to become manifest (but the trial should not take so long as to render the intervention no longer of interest). Many cardiovascular prevention studies have been large, simple, randomized trials leading to easily interpretable results. This paper urges that designers of trials of HIV prevention should consider mimicking the strategies used in cardiovascular disease prevention trials: focus on a clear inferential path to the question being asked while limiting unnecessary data collection, auditing, and complexity. Finally, showing benefit in a trial is only the first step in reducing the burden of disease: aggressive, effective efforts at educating the population at risk so they will implement the intervention is essential to improvement in public health.","PeriodicalId":74867,"journal":{"name":"Statistical communications in infectious diseases","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87119861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tomorrow’s HIV Prevention Trials of Vaccines and Antibodies","authors":"D. Follmann","doi":"10.1515/scid-2019-0007","DOIUrl":"https://doi.org/10.1515/scid-2019-0007","url":null,"abstract":"Abstract Effective HIV prevention has the potential to change the landscape of HIV prevention trials. Low infection rates will make superiority studies necessarily large while non-inferiority trials will need some evidence that a counterfactual placebo group had a meaningful HIV infection rate in order to provide evidence of effective interventions. This paper explores these challenges in the context of immune related interventions of mAbs and vaccines. We discuss the issue of effect modification in the presence of PrEP, where subjects on PrEP may have less of a benefit of a mAb or (vaccine) than subjects off PrEP. We also discuss different methods of placebo infection rate imputation. We estimate infection risk as a function of mAb level (or vaccine induced immune response) in the mAb (or vaccine) arm and then extrapolate this infection risk to zero mAbs as a proxy for the placebo infection rate. Important aspects are the use of triangulation or multiple methods to impute the placebo infection rate, concern about extrapolation if few mAbs are close to zero, and the use of currently available data with placebo groups to rigorously evaluate the accuracy of imputation methods. We also discuss use of historical controls and some generalizations of the idea of (DMurray, J. 2019. “Regulatory Perspectives for Streamlining HIV Prevention Trials.” Statistical Communications in Infectious Diseases.) to use rectal gonorrhea rates to impute HIV infection rate. Generalizations include regression adjustment to calibrate for potential differences in baseline covariates for ongoing vs historical studies and the use of the gonorrhea, HIV relationship in a contemporaneous observational study. Examples of recent and ongoing trials of malaria chemoprophylaxis and HPV vaccines, where extremely effect prevention methods are available, are provided.","PeriodicalId":74867,"journal":{"name":"Statistical communications in infectious diseases","volume":"107 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85334817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Crossover and Repeated Randomization in Event Driven Trials for HIV Prevention: Addressing the Impact of Heterogeneity in Risk in the Trial Design","authors":"C. D. Domínguez Islas, E. Brown","doi":"10.1515/scid-2019-0009","DOIUrl":"https://doi.org/10.1515/scid-2019-0009","url":null,"abstract":"Abstract The availability of effective Pre-Exposure Prophylaxis (PrEP) for HIV introduces new challenges for testing novel on-demand, user-controlled HIV prevention products, including lower placebo arm incidence and increased between-participant variability in HIV risk. In this paper, we discuss how low HIV incidence may result in longer trials in which the variability in participants' risk may impact the estimate of risk reduction. We introduce a measure of per-exposure efficacy that may be more relevant than the population level reduction in incidence for on demand products and explore alternatives to the parallel arm design that could target better this parameter of interest: the crossover and the re-randomization designs. We propose three different ways in which crossover and re-randomization of intervention assignments could be implemented in event-driven trials. We evaluate the performance of these designs through a simulation study, finding that they allow for better estimation and higher power than the traditional event-driven parallel arm design. We conclude by discussing future work, practical challenges and ethical considerations that need to be addressed to take these designs closer to implementation.","PeriodicalId":74867,"journal":{"name":"Statistical communications in infectious diseases","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83015331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current and Future Challenges in Trial Design for Pre-Exposure Prophylaxis in HIV Prevention","authors":"D. Donnell","doi":"10.1515/scid-2019-0008","DOIUrl":"https://doi.org/10.1515/scid-2019-0008","url":null,"abstract":"Abstract Success in establishing efficacy of antiretroviral drugs to prevent acquisition of HIV infection has fundamentally changed the trial design considerations for future experimental drugs. Current trials of potential new antiretroviral agents for pre-exposure prophylaxis are using active control designs – where all trial participants receive an active antiretroviral drug. Current trials of other experimental approaches, such as vaccines and monoclonal antibodies, permit use of the proven prevention agent FTC/TDF for all trial participants. In the future, if even more effective prevention methods are approved, active control designs would anticipate very few infection events and not provide statistically robust evidence. A potential alternative is to conduct placebo randomized trials limited to participants for whom current prevention tools are not acceptable.","PeriodicalId":74867,"journal":{"name":"Statistical communications in infectious diseases","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87193756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of Power Law Network Models of Epidemic Surveillance Data for Better Evaluation of Outbreak Detection Alarms","authors":"R. Romanescu, R. Deardon","doi":"10.1515/scid-2018-0004","DOIUrl":"https://doi.org/10.1515/scid-2018-0004","url":null,"abstract":"Abstract Properties of statistical alarms have been well studied for simple disease surveillance models, such as normally distributed incidence rates with a sudden or gradual shift in mean at the start of an outbreak. It is known, however, that outbreak dynamics in human populations depend significantly on the heterogeneity of the underlying contact network. The rate of change in incidence for a disease such as influenza peaks early on during the outbreak, when the most highly connected individuals get infected, and declines as the average number of connections in the remaining susceptible population drops. Alarm systems currently in use for detecting the start of influenza seasons generally ignore this mechanism of disease spread, and, as a result, will miss out on some early warning signals. We investigate the performance of various alarms on epidemics simulated from an undirected network model with a power law degree distribution for a pathogen with a relatively short infectious period. We propose simple custom alarms for the disease system considered, and show that they can detect a change in the process sooner than some traditional alarms. Finally, we test our methods on observed rates of influenza-like illness from two sentinel providers (one French, one Spanish) to illustrate their use in the early detection of the flu season.","PeriodicalId":74867,"journal":{"name":"Statistical communications in infectious diseases","volume":"53 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91273764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ongoing Vaccine and Monoclonal Antibody HIV Prevention Efficacy Trials and Considerations for Sequel Efficacy Trial Designs.","authors":"Peter B Gilbert","doi":"10.1515/scid-2019-0003","DOIUrl":"https://doi.org/10.1515/scid-2019-0003","url":null,"abstract":"<p><p>Four randomized placebo-controlled efficacy trials of a candidate vaccine or passively infused monoclonal antibody for prevention of HIV-1 infection are underway (HVTN 702 in South African men and women; HVTN 705 in sub-Saharan African women; HVTN 703/HPTN 081 in sub-Saharan African women; HVTN 704/HPTN 085 in U.S., Peruvian, Brazilian, and Swiss men or transgender persons who have sex with men). Several challenges are posed to the optimal design of the sequel efficacy trials, including: (1) how to account for the evolving mosaic of effective prevention interventions that may be part of the trial design or standard of prevention; (2) how to define viable and optimal sequel trial designs depending on the primary efficacy results and secondary \"correlates of protection\" results of each of the ongoing trials; and (3) how to define the primary objective of sequel efficacy trials if HIV-1 incidence is expected to be very low in all study arms such that a standard trial design has a steep opportunity cost. After summarizing the ongoing trials, I discuss statistical science considerations for sequel efficacy trial designs, both generally and specifically to each trial listed above. One conclusion is that the results of \"correlates of protection\" analyses, which ascertain how different host immunological markers and HIV-1 viral features impact HIV-1 risk and prevention efficacy, have an important influence on sequel trial design. This influence is especially relevant for the monoclonal antibody trials because of the focused pre-trial hypothesis that potency and coverage of serum neutralization constitutes a surrogate endpoint for HIV-1 infection. Another conclusion is that while assessing prevention efficacy against a counterfactual placebo group is fraught with risks for bias, such analysis is nonetheless important and study designs coupled with analysis methods should be developed to optimize such inferences. I draw a parallel with non-inferiority designs, which are fraught with risks given the necessity of making unverifiable assumptions for interpreting results, but nevertheless have been accepted when a superiority design is not possible and a rigorous/conservative non-inferiority margin is used. In a similar way, counterfactual placebo group efficacy analysis should use rigorous/conservative inference techniques that formally build in a rigorous/conservative margin to potential biases that could occur due to departures from unverifiable assumptions. Because reliability of this approach would require new techniques for verifying that the study cohort experienced substantial exposure to HIV-1, currently it may be appropriate as a secondary objective but not as a primary objective.</p>","PeriodicalId":74867,"journal":{"name":"Statistical communications in infectious diseases","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/scid-2019-0003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38708111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Designing & Conducting Trials To Reliably Evaluate HIV Prevention Interventions.","authors":"Thomas R Fleming,&nbsp;Victor DeGruttola,&nbsp;Deborah Donnell","doi":"10.1515/scid-2019-0001","DOIUrl":"https://doi.org/10.1515/scid-2019-0001","url":null,"abstract":"<p><p>While much has been achieved, much remains to be accomplished in the science of preventing the spread of HIV infection. Clinical trials that are properly designed, conducted and analyzed are of integral importance in the pursuit of reliable insights about HIV prevention. As we build on previous scientific breakthroughs, there will be an increasing need for clinical trials to be designed to efficiently achieve insights without compromising their reliability and generalizability. Key design features should continue to include: 1) the use of randomization and evidence-based controls, 2) specifying the use of intention-to-treat analyses to preserve the integrity of randomization and to increase interpretability of results, 3) obtaining direct assessments of effects on clinical endpoints such as the risk of HIV infection, 4) using either superiority designs or non-inferiority designs with rigorous non-inferiority margins, and 5) enhancing generalizability through the choice of a relative risk rather than risk difference metric. When interventions have complementary and potentially synergistic effects, factorial designs should be considered to increase efficiency as well as to obtain clinically important insights about interaction and the contribution of component interventions to the efficacy and safety of combination regimens. Key trial conduct issues include timely enrollment of participants at high HIV risk recruited from populations with high viral burden, obtaining 'best real-world achievable' levels of adherence to the interventions being assessed and ensuring high levels of retention. High quality of trial conduct occurs through active rather than passive monitoring, using pre-specified targeted levels of performance with defined methods to achieve those targets. During trial conduct, active monitoring of the performance standards not only holds the trial leaders accountable but also can assist in the development and implementation of creative alternative approaches to increase the quality of trial conduct. Designing, conducting and analyzing HIV prevention trials with the quality needed to obtain reliable insights is an ethical as well as scientific imperative.</p>","PeriodicalId":74867,"journal":{"name":"Statistical communications in infectious diseases","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/scid-2019-0001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25525068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}