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The purpose of this study was to examine changes in the functional impact of migraine following treatment with erenumab, as measured by the Migraine Functional Impact Questionnaire (MFIQ).The MFIQ, a novel patient-reported outcome (PRO) measuring the impact of migraine on four domains (physical function, social function, and emotional function [PF, SF, and EF]; usual activities [UAs]) and a single item assessing overall impact on UA, was included in phase III trials evaluating erenumab 70 and 140 mg monthly for migraine prevention among people with episodic migraine (EM).In the ARISE study, 577 patients with EM were randomized to erenumab 70 mg or placebo. In the STRIVE study, 955 patients with EM were randomized to erenumab, 70 mg or 140 mg or placebo. Pairwise comparisons of least-squares mean (LSM) change from baseline in MFIQ scores (with associated 95% confidence interval [CI]) were assessed for each active treatment versus placebo.In ARISE, greater reductions from baseline to month 3 were observed for 70 mg versus placebo for PF (LSM [95% CI]: -3.2 [-6.4 to -0.1]; p = 0.046) and EF (-4.0 [-7.3 to -0.7]; p = 0.019) domain scores. In STRIVE, between-group differences also reflected reductions from baseline to the average of months 4-6 that favored erenumab on all four MFIQ domain scores. Reductions in impact for 70 mg compared to placebo were -4.3 (95% CI: -6.8 to -1.7; p 0.001) for PF, -4.0 (-6.3 to -1.7; p 0.001) for UA, -3.7 (-6.1 to -1.2; p = 0.003) for SF, and -5.3 (-7.9 to -2.6; p 0.001) for EF domain scores. Improvements were also observed for 140 mg versus placebo with between-group differences of -5.7 (95% CI: -8.2 to -3.2; p 0.001) in PF, -5.1 (-7.5 to -2.8; p 0.001) in UA, -5.0 (-7.4 to -2.6; p 0.001) in SF, and -7.2 (-9.9 to -4.5; p 0.001) in EF domain scores. There were also greater improvements in the overall impact on UA score for 70 mg (LSM [95% CI]: -4.3 [-7.0 to -1.7]; p = 0.001) and 140 mg (-5.3 [-8.5 to -3.2]; p 0.001) versus placebo.The MFIQ measures the frequency of impacts and level of difficulty on multiple functional domains that provide a more complete picture of the effects of migraine. MFIQ scores showed that in comparison with placebo, patients treated with erenumab had greater reductions in the functional impact of migraine, providing insight into treatment benefits that extend beyond improvements in clinical status and health-related quality of life previously reported based on clinical end points and other PROs.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub ( https://covid19forecasthub.org/ ) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.

The Alzheimer's Disease Composite Score (ADCOMS) is a tool developed to detect clinical progression and measure treatment effect in patients in early stages of Alzheimer's disease (AD). The psychometric properties of the ADCOMS have been established; however, the threshold for clinical meaningfulness has yet to be identified.Anchor-based, distribution-based, and ROC curve analyses were used to estimate clinically meaningful thresholds for change in ADCOMS for patients with mild cognitive impairment (MCI) and AD dementia. This study included data from three sources: the Alzheimer's Disease Neuroimaging Initiative (ADNI), the National Alzheimer's Coordinating Center (NACC), and a legacy dataset that included data from four sources: the placebo group from three MCI trials and an earlier data cut from ADNI. Results were stratified by disease severity (MCI vs. dementia) and APOE ε4 carrier status.A total of 5355 participants were included in the analysis. The ADCOMS was able to detect change for MCI and dementia patients who experienced a meaningful decline in cognition (as defined by the Clinical Dementia Rating Scale Sum of Boxes [CDR-SOB]) between baseline and month 12. The following ADCOMS cut-offs were proposed: 0.05 for MCI and 0.10 for dementia.The ADCOMS was previously established as a valid and reliable tool for use in clinical trials for MCI due to AD and dementia populations. By defining thresholds for clinically meaningful change of ADCOMS, this work is an important step in interpreting clinical findings and estimates of treatment effects in early stage AD trials.

Pathogenic variants in the BRCA1 and BRCA2 (BRCA1/2) genes are associated with elevated cancer risks in men and women. Due to a founder effect, Ashkenazi Jewish individuals are at higher risk for carrying three specific BRCA1/2 pathogenic variants. There have been recent calls for population screening in this population because many carriers do not have family histories suggestive of hereditary cancer. One approach could be to integrate optional BRCA1/2 testing into routinely offered reproductive carrier screening for recessive and X-linked disorders. However, the differing goals of these types of testing (i.e., personal health risks versus family planning) raise questions about the implications for patient education and informed consent. To this end, we aimed to determine interest, attitudes, and preferences regarding integrating such testing by electronically surveying 331 Ashkenazi Jewish participants in JScreen - a national, not-for-profit, at-home carrier screening program focused on genetic risks in Jewish communities. We found that while 41% of participants had plans to pursue BRCA1/2 testing, 93% would have opted for such testing if offered as an add-on to reproductive carrier screening. This was particularly true of those with higher perceived cancer risk and more positive attitudes toward genetic testing. With respect to preferences about delivery of this service, more than 85% of participants preferred remote (telephone, print, or web-based) genetic education rather than traditional genetic counseling. These results suggest that offering optional BRCA1/2 testing within the context of reproductive carrier screening might provide opportunities for cancer prevention without overburdening scarce genetic counseling resources.

Cascade testing for hereditary breast/ovarian cancer is an important public health priority. Increasing attention has been paid to the relevance of testing for men within BRCA1/2-positive families given that such testing may provide important information about their cancer risks, particularly for prostate cancer, and risks to their offspring. However, men are much less likely to seek genetic counseling and testing than their at-risk female relatives. To facilitate access to pre-test information and testing, we developed a web-based intervention (WI) for men that we are evaluating in a pilot randomized controlled trial (RCT). This paper describes three phases of research in the development of the WI: (1) formative (qualitative) research among men from BRCA1/2 families to assess needs and preferences for education; (2) a detailed description of the organization, format, and content of the WI; and (3) usability testing. We discuss the aims and hypotheses of the pilot RCT in which the WI is being compared with an enhanced usual care condition among at-risk men. We expect that the WI described here will foster informed decisions and lead to increased use of BRCA1/2 counseling and testing, potentially yielding improved cancer control outcomes for this understudied group, and for their at-risk relatives.

SUMMARYWith the recent emergence of the B.1.617.2 (Delta) variant of SARS-CoV-2 in the U.S., many states are seeing rising cases and hospitalizations after a period of steady decline. As We used theCOVID-19 Simulator, an interactive online tool that utilizes a validated mathematical model, to simulate the trajectory of COVID-19 at the state level in the U.S. COVID-19 Simulator’s forecasts are updated weekly and included in the Centers for Disease Control and Prevention (CDC) ensemble model. We employed our model to analyze scenarios where the Delta variant becomes dominant in every state.The combination of high transmissibility of the Delta variant, low vaccination coverage in several regions, and more relaxed attitude towards social distancing is expected to result in as surge in COVID-19 deaths in at least 40 states. In several states – including Idaho, Maine, Montana, Nebraska, North Carolina, Oregon, Puerto Rico, Washington, and West Virginia – the projected daily deaths in 2021 could exceed the prior peak daily deaths under current social distancing behavior and vaccination rate. The number of COVID-19 deaths across the U.S. could exceed 1600 per day.Between August 1, 2021, and December 31, 2021, there could be additional 157,000 COVID-19 deaths across the U.S. Of note, our model projected approximately 20,700 COVID-19 deaths in Texas, 16,000 in California, 12,400 in Florida, 12,000 in North Carolina, and 9,300 in Georgia during this period. In contrast, the projected number of COVID-19 deaths would remain below 200 in New Jersey, Massachusetts, Connecticut, Vermont, and Rhode Island.We project COVID-19 deaths based on the current vaccination rates and social distancing behavior. Our hope is that the findings of this report serve a warning sign and people revert to wearing masks and maintain social distancing to reduce COVID-19 associated deaths in the U.S. Our projections are updated weekly by incorporating vaccination rates and social distancing measures in each state; the latest results can be found at theCOVID-19 Simulatorwebsite.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks. Significance Statement This paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the US. Results show high variation in accuracy between and within stand-alone models, and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public health action.

BACKGROUND AND OBJECTIVES Many newly diagnosed breast cancer patients do not receive genetic counseling and testing at the time of diagnosis. We examined predictors of genetic testing (GT) in this population. METHODS Within a randomized controlled trial of proactive rapid genetic counseling and testing vs usual care, patients completed a baseline survey within 6 weeks of breast cancer diagnosis but before a definitive survey. We conducted a multinomial logistic regression to identify predictors of GT timing/uptake. RESULTS Having discussed GT with a surgeon was a dominant predictor (χ2 (2, N = 320) = 70.13; P

PurposeTelegenetics has become the predominant mode of cancer genetic counseling during the COVID-19 pandemic. We sought to identify potential patient-level contraindicators for telegenetic genetic counseling.MethodsWe analyzed post-counseling (pre-result disclosure) follow-up data from a randomized noninferiority trial of a telephone genetic counseling versus usual care genetic counseling. Among 669 randomized participants, 600 completed pre-test counseling and 568 completed a 2-week follow-up assessment before receiving test results. In this analysis, we focused on genetic counseling outcomes (knowledge, decisional conflict, and distress). In multivariate models controlling for bivariate predictors of these outcomes, we tested our a priori hypotheses that pre-counseling numeracy, perceived stress, and race/ethnicity would moderate the outcomes of telephone genetic counseling versus usual care.ResultsOnly numeracy significantly moderated associations between mode of genetic counseling and outcomes. Higher numeracy was associated with higher post-counseling knowledge following telephone genetic counseling ( p 0.20).ConclusionAlthough high numeracy was associated with higher levels of knowledge following telegenetic counseling, we did not identify any clinically significant patient-level contraindicators for telegenetic counseling. These results lend further confidence to the broad use of telegenetics.

Objectives: Dynamic and fast actions are needed to suppress the coronavirus disease 2019 (COVID-19) pandemic, which has affected every sector of human life Our objective was to develop an open-access, interactive tool for policy makers to inform timely decisions and evaluate the impact of different non-pharmaceutical interventions (of varied intensity and timing) on reducing the spread of COVID-19 in the Methods: We developed a compartmental model, the COVID-19 Simulator, to simulate the trajectory of COVID-19 in 50 states, DC, and Puerto Rico The model is defined using Susceptible, Exposed, Infectious, and Recovered compartments (SEIR model) with continuous time progression Input data included reported state-specific daily cases, hospitalizations, and deaths;disease epidemiology parameters estimated by clinical studies, state-specific effective reproduction numbers, testing rates, and changes in mobility as reported by GPS location data Unobserved parameters were calibrated using generalized simulated annealing to match the daily reported cases and deaths We projected future cases of COVID-19, active cases of COVID-19, deaths, hospitalizations, and intensive care unit admissions under different levels of social-distancing measures (minimal restrictions, current intervention, stay-at-home orders, and lockdown) Results: The COVID-19 Simulator can help users to understand the implications, including deaths and hospital beds needed, of removing or adding restrictions at different time points Under current intervention levels, new cases per day are projected to surpass 100,000 by September in the US;implementing stay at home orders again in many states is necessary to create a downward trajectory in incidence High prevalence states may see a dramatic increase in deaths by Fall if policies do not change Conclusions: The COVID-19 Simulator provides an interactive platform to inform policy decisions on controlling the spread of COVID-19 The simulator is updated on a regular basis as new data become available and will be extended to inform new policy-relevant questions

Risk-reducing mastectomy (RRM) and salpingo-oophorectomy (RRSO) are increasingly used to reduce breast and ovarian cancer risk following BRCA1/BRCA2 testing. However, little is known about how genetic counseling influences decisions about these surgeries. Although previous studies have examined intentions prior to counseling, few have examined RRM and RRSO intentions in the critical window between genetic counseling and test result disclosure. Previous research has indicated that intentions at this time point predict subsequent uptake of surgery, suggesting that much decision-making has taken place prior to result disclosure. This period may be a critical time to better understand the drivers of prophylactic surgery intentions. The aim of this study was to examine predictors of RRM and RRSO intentions. We hypothesized that variables from the Health Belief Model would predict intentions, and we also examined the role of affective factors. Participants were 187 women, age 21–75, who received genetic counseling for hereditary breast and ovarian cancer. We utilized multiple logistic regression to identify independent predictors of intentions. 49.2% and 61.3% of participants reported intentions for RRM and RRSO, respectively. Variables associated with RRM intentions include: newly diagnosed with breast cancer (OR = 3.63, 95% CI = 1.20–11.04), perceived breast cancer risk (OR = 1.46, 95% CI = 1.17–1.81), perceived pros (OR = 1.79, 95% CI = 1.38–2.32) and cons of RRM (OR = 0.81, 95% CI = 0.65–0.996), and decision conflict (OR = 0.80, 95% CI = 0.66–0.98). Variables associated with RRSO intentions include: proband status (OR = 0.28, 95% CI = 0.09–0.89), perceived pros (OR = 1.35, 95% CI = 1.11–1.63) and cons of RRSO (OR = 0.72, 95% CI = 0.59–0.89), and ambiguity aversion (OR = 0.79, 95% CI = 0.65–0.95). These data provide support for the role of genetic counseling in fostering informed decisions about risk management, and suggest that the role of uncertainty should be explored further.

The Western Division of Dow Chemical, USA, started a program in the late 1970's to review early stage research projects prior to operation. The name Pre-op (Pre-operational Review) was given to describe the series of steps or process of reviewing projects for safety concerns. In recent years, the process has been examined and improved by a committee of research chemists and engineers. Some of the changes have been dictated by regulatory considerations, but primarily the focus of the continuous improvement effort has been directed at the customers: the users of the system and the research management who are ultimately responsible for the safety of their area. Pre-op reviews are a thorough review of the safety aspects of a new project along with the information necessary to meet current OSHA, EPA, Safety and Loss Prevention Principles, industrial hygiene, and other environmental regulatory concerns. The end result of the Pre-op review process is a document that contains the information needed to understand and review the proposed project. The document is reviewed at a meeting with two to eight reviewers that are not directly involved with the project. The review committee is appointed by a Pre-op Coordinator, a person who administers the system.more » The committee should include research management, research safety management, a site reactive chemicals committee representative, the pilot plant supervisor, operators, an unaffiliated chemist and engineer, and the project supervisor. The committee reviews the document package and then conducts a field inspection of the facility so that a list of recommendations can be generated. The committee recommendations must be completed by the person responsible for the project prior to start-up.« less