1,660 research outputs found
Amy Carpenter Hay, BA, MS, Oral History Interview, June 02, 2015
Major Topics Covered: Business partnerships in the United States and abroad Financial challenges to MD Anderson and healthcare Visualizing business opportunity in healthcare Technology and business opportunity Women and leadership Shifts in MD Anderson research and culture to innovation and technologyhttps://openworks.mdanderson.org/mchv_interviewsessions/1203/thumbnail.jp
Amy Carpenter Hay, BA, MS, Oral History Interview, February 04, 2015
Major Topics Covered: Personal and educational background Evolution of the satellite/regional care system The development of the Proton Therapy Center The Center for Global Oncology The Office of Global Business Developmenthttps://openworks.mdanderson.org/mchv_interviewsessions/1202/thumbnail.jp
A Comparison of Initial Antiretroviral Therapy in the Swiss HIV Cohort Study and the Recommendations of the International AIDS Society-USA
BACKGROUND: In order to facilitate and improve the use of antiretroviral therapy (ART), international recommendations are released and updated regularly. We aimed to study if adherence to the recommendations is associated with better treatment outcomes in the Swiss HIV Cohort Study (SHCS). METHODS: Initial ART regimens prescribed to participants between 1998 and 2007 were classified according to IAS-USA recommendations. Baseline characteristics of patients who received regimens in violation with these recommendations (violation ART) were compared to other patients. Multivariable logistic and linear regression analyses were performed to identify associations between violation ART and (i) virological suppression and (ii) CD4 cell count increase, after one year. RESULTS: Between 1998 and 2007, 4189 SHCS participants started 241 different ART regimens. A violation ART was started in 5% of patients. Female patients (adjusted odds ratio aOR 1.83, 95%CI 1.28-2.62), those with a high education level (aOR 1.49, 95%CI 1.07-2.06) or a high CD4 count (aOR 1.53, 95%CI 1.02-2.30) were more likely to receive violation ART. The proportion of patients with an undetectable viral load (<400 copies/mL) after one year was significantly lower with violation ART than with recommended regimens (aOR 0.54, 95% CI 0.37-0.80) whereas CD4 count increase after one year of treatment was similar in both groups. CONCLUSIONS: Although more than 240 different initial regimens were prescribed, violations of the IAS-USA recommendations were uncommon. Patients receiving these regimens were less likely to have an undetectable viral load after one year, which strengthens the validity of these recommendations
Development and Validation of a Composite Programmatic Assessment Tool for HIV Therapy
Background
We developed and validated a new and simple metric, the Programmatic Compliance Score (PCS), based on the IAS-USA antiretroviral therapy management guidelines for HIV-infected adults, as a predictor of all-cause mortality, at a program-wide level. We hypothesized that non-compliance would be associated with the highest probability of mortality.
Methods and Findings
3543 antiretroviral-naive HIV-infected patients aged ≥19 years who initiated antiretroviral therapy between January 1, 2000 and August 31, 2009 in British Columbia (BC), Canada, were followed until August 31, 2010. The PCS is composed by six non-performance indicators based on the IAS-USA guidelines: (1) having <3 CD4 count tests in the first year after starting antiretroviral therapy; (2) having <3 plasma viral load tests in the first year after starting antiretroviral therapy; (3) not having drug resistance testing done prior to starting antiretroviral therapy; (4) starting on a non-recommended antiretroviral therapy regimen; (5) starting therapy with CD4 <200 cells/mm3; and (6) not achieving viral suppression within 6 months since antiretroviral therapy initiation. The sum of these six indicators was used to develop the PCS score - higher score indicates poorer performance. The main outcome was all-cause mortality. Each PCS component was independently associated with mortality. In the mortality analysis, the odds ratio (OR) for PCS ≥4 versus 0 was 22.37 (95% CI 10.46–47.84).
Conclusions
PCS was strongly associated with all-cause mortality. These results lend independent validation to the IAS-USA treatment guidelines for HIV-infected adults. Further efforts are warranted to enhance the PCS as a means to further improve clinical outcomes. These should be specifically evaluated and targeted at healthcare providers and patients
Investigating the missing data mechanism in quality of life outcomes: a comparison of approaches
Background: Missing data is classified as missing completely at random (MCAR), missing at
random (MAR) or missing not at random (MNAR). Knowing the mechanism is useful in identifying
the most appropriate analysis. The first aim was to compare different methods for identifying this
missing data mechanism to determine if they gave consistent conclusions. Secondly, to investigate
whether the reminder-response data can be utilised to help identify the missing data mechanism.
Methods: Five clinical trial datasets that employed a reminder system at follow-up were used.
Some quality of life questionnaires were initially missing, but later recovered through reminders.
Four methods of determining the missing data mechanism were applied. Two response data
scenarios were considered. Firstly, immediate data only; secondly, all observed responses
(including reminder-response).
Results: In three of five trials the hypothesis tests found evidence against the MCAR assumption.
Logistic regression suggested MAR, but was able to use the reminder-collected data to highlight
potential MNAR data in two trials.
Conclusion: The four methods were consistent in determining the missingness mechanism. One
hypothesis test was preferred as it is applicable with intermittent missingness. Some inconsistencies between the two data scenarios were found. Ignoring the reminder data could potentially give a distorted view of the missingness mechanism. Utilising reminder data allowed the possibility of MNAR to be considered.The Chief Scientist Office of the Scottish Government Health Directorate.
Research Training Fellowship (CZF/1/31
The changing nature of risk and risk management: the challenge of borders, uncertainty and resilience
No abstract available
Axion Protection from Flavor
The QCD axion fails to solve the strong CP problem unless all explicit PQ
violating, Planck-suppressed, dimension n<10 operators are forbidden or have
exponentially small coefficients. We show that all theories with a QCD axion
contain an irreducible source of explicit PQ violation which is proportional to
the determinant of the Yukawa interaction matrix of colored fermions.
Generically, this contribution is of low operator dimension and will
drastically destabilize the axion potential, so its suppression is a necessary
condition for solving the strong CP problem. We propose a mechanism whereby the
PQ symmetry is kept exact up to n=12 with the help of the very same flavor
symmetries which generate the hierarchical quark masses and mixings of the SM.
This "axion flavor protection" is straightforwardly realized in theories which
employ radiative fermion mass generation and grand unification. A universal
feature of this construction is that the heavy quark Yukawa couplings are
generated at the PQ breaking scale.Comment: 16 pages, 2 figure
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Multiple imputation approaches for epoch-level accelerometer data in trials.
Clinical trials that investigate physical activity interventions often use accelerometers to measure step count at a very granular level, for example in 5-second epochs. Participants typically wear the accelerometer for a week-long period at baseline, and for one or more week-long follow-up periods after the intervention. The data is aggregated to provide daily or weekly step counts for the primary analysis. Missing data are common as participants may not wear the device as per protocol. Approaches to handling missing data in the literature have defined missingness on the day level using a threshold on daily weartime, which leads to loss of information on the time of day when data are missing. We propose an approach to identifying and classifying missingness at the finer epoch-level and present two approaches to handling missingness using multiple imputation. Firstly, we present a parametric approach which accounts for the number of missing epochs per day. Secondly, we describe a non-parametric approach where missing periods during the day are replaced by donor data from the same person where possible, or data from a different person who is matched on demographic and physical activity-related variables. Our simulation studies show that the non-parametric approach leads to estimates of the effect of treatment that are least biased while maintaining small standard errors. We illustrate the application of these different multiple imputation strategies to the analysis of the 2017 PACE-UP trial. The proposed framework is likely to be applicable to other digital health outcomes and to other wearable devices
A framework for handling missing accelerometer outcome data in trials.
Accelerometers and other wearable devices are increasingly being used in clinical trials to provide an objective measure of the impact of an intervention on physical activity. Missing data are ubiquitous in this setting, typically for one of two reasons: patients may not wear the device as per protocol, and/or the device may fail to collect data (e.g. flat battery, water damage). However, it is not always possible to distinguish whether the participant stopped wearing the device, or if the participant is wearing the device but staying still. Further, a lack of consensus in the literature on how to aggregate the data before analysis (hourly, daily, weekly) leads to a lack of consensus in how to define a "missing" outcome. Different trials have adopted different definitions (ranging from having insufficient step counts in a day, through to missing a certain number of days in a week). We propose an analysis framework that uses wear time to define missingness on the epoch and day level, and propose a multiple imputation approach, at the day level, which treats partially observed daily step counts as right censored. This flexible approach allows the inclusion of auxiliary variables, and is consistent with almost all the primary analysis models described in the literature, and readily allows sensitivity analysis (to the missing at random assumption) to be performed. Having presented our framework, we illustrate its application to the analysis of the 2019 MOVE-IT trial of motivational interviewing to increase exercise
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