Combining Epidemiologic Information Across Space Agencies

Space flight is a very unique occupational exposure with potential hazards that are not fully understood. A limited number of individuals have experienced the exposures incurred during space flight, and epidemiologic research would benefit from shared information across space agencies. However, data sharing can be problematic due to agency protection policies for personally identifiable information as well as medical records. Compliance with these protocols in the astronaut population is particularly difficult given the small, high-profile population under study. Creativity in combining data is necessary in order to overcome these difficulties and improve statistical power in research. This study presents methods in meta-analysis that may be used to combine non-attributable data across space agencies so that meaningful conclusions may be drawn about study interests. Methods for combining epidemiologic data across space agencies are presented, and the processes are demonstrated using life-time mortality data in U.S. astronauts and Russian cosmonauts. This proof of concept was found to be an acceptable way of sharing data across agencies, and will be used in the future as more relevant research interests are identified

Combining Epidemiologic Information Across Space Agencies

We propose using meta-analytic methods to combine summary measures across space agencies: (1) Non-attributable data (2) Avoids problems with sharing health related data (3) Unpublished dat

The Integrated Medical Model - A Risk Assessment and Decision Support Tool for Human Space Flight Missions

The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission planners and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight

First-dose and steady-state pharmacokinetics of orally administered crizotinib in children with solid tumors: a report on ADVL0912 from the Children’s Oncology Group Phase 1/Pilot Consortium

Characterize the pharmacokinetics of oral crizotinib in children with cancer

Multicenter prevalence of anaphylaxis in clinic-based oral food challenges

Background Although previous single-center studies report the rate of anaphylaxis for oral food challenges (OFCs) as 9% to 11%, little is known regarding the epidemiology of clinical OFCs across multiple centers in the United States. Objective To examine the epidemiology, symptoms, and treatment of clinical low-risk OFCs in the nonresearch setting. Methods Data were obtained from 2008 to 2013 through a physician survey in 5 food allergy centers geographically distributed across the United States. Allergic reaction rates and the association of reaction rates with year, hospital, and demographics were determined using a linear mixed model. Meta-analysis was used to pool the proportion of reactions and anaphylaxis with inverse-variance weights using a random-effects model with exact confidence intervals (CIs). Results A total of 6,377 OFCs were performed, and the pooled estimate of anaphylaxis was 2% (95% CI, 1%-3%). The rate of allergic reactions was 14% (95% CI, 13%-16%) and was consistent during the study period (P = .40). Reaction rates ranged from 13% to 33%. Males reacted 16% more frequently than females (95% CI, 4%-37.5%; P = .04). Foods challenged in 2013 varied geographically, with peanut as the most challenged food in the Northeast, Midwest, and West and egg as the most challenged in the South. Conclusion As the largest national survey of allergic reactions of clinical open OFCs in a nonresearch setting in the United States, this study found that performing clinical nonresearch open low-risk OFCs results in few allergic reactions, with 86% of challenges resulting in no reactions and 98% without anaphylaxis

Design and Psychometrics for New Measures of Health-Related Quality of Life in Adults with Type 1 Diabetes: Type 1 Diabetes and Life (T1DAL)

AIMS: To use a three-phase process to develop and validate new self-report measures of diabetes-specific health-related quality of life (HRQOL) for adults with type 1 diabetes. We report on four versions of the Type 1 Diabetes and Life (T1DAL) measure for people age 18-25, 26-45, 46-60, and over 60 years. METHODS: We first conducted qualitative interviews to guide measure creation, then piloted the draft measures. We evaluated psychometric properties at six T1D Exchange Clinic Network sites via completion of T1DAL and validated measures of related constructs. Participants completed the T1DAL again in 4-6 weeks. We used psychometric data to reduce each measure to 23-27 items in length. Finally, we obtained participant feedback on the final measures. RESULTS: The T1DAL-Adult measures demonstrated good internal consistency (α=0.85-0.88) and test-retest reliability (r=0.77-0.87). Significant correlations with measures of general quality of life, generic and diabetes-specific HRQOL, diabetes burden, self-management, and glycemic control demonstrated validity. Factor analyses yielded 4-5 subscales per measure. Participants were satisfied with the final measures and reported they took 5-10 minutes to complete. CONCLUSIONS: The strong psychometric properties of the newly developed self-report T1DAL measures for adults with type 1 diabetes make them appropriate for use in clinical research and care

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Human Space Flight Missions

This slide presentation reviews the Integrated Medical Model (IMM) and its use as a risk assessment and decision support tool for human space flight missions. The IMM is an integrated, quantified, evidence-based decision support tool useful to NASA crew health and mission planners. It is intended to assist in optimizing crew health, safety and mission success within the constraints of the space flight environment for in-flight operations. It uses ISS data to assist in planning for the Exploration Program and it is not intended to assist in post flight research. The IMM was used to update Probability Risk Assessment (PRA) for the purpose of updating forecasts for the conditions requiring evacuation (EVAC) or Loss of Crew Life (LOC) for the ISS. The IMM validation approach includes comparison with actual events and involves both qualitative and quantitaive approaches. The results of these comparisons are reviewed. Another use of the IMM is to optimize the medical kits taking into consideration the specific mission and the crew profile. An example of the use of the IMM to optimize the medical kits is reviewed

Validation of the Integrated Medical Model Using Historical Space Flight Data

The Integrated Medical Model (IMM) utilizes Monte Carlo methodologies to predict the occurrence of medical events, utilization of resources, and clinical outcomes during space flight. Real-world data may be used to demonstrate the accuracy of the model. For this analysis, IMM predictions were compared to data from historical shuttle missions, not yet included as model source input. Initial goodness of fit test-ing on International Space Station data suggests that the IMM may overestimate the number of occurrences for three of the 83 medical conditions in the model. The IMM did not underestimate the occurrence of any medical condition. Initial comparisons with shuttle data demonstrate the importance of understanding crew preference (i.e., preferred analgesic) for accurately predicting the utilization of re-sources. The initial analysis demonstrates the validity of the IMM for its intended use and highlights areas for improvement

Search for supersymmetry with a dominant R-parity violating LQDbar couplings in e+e- collisions at centre-of-mass energies of 130GeV to 172 GeV

A search for pair-production of supersymmetric particles under the assumption that R-parity is violated via a dominant LQDbar coupling has been performed using the data collected by ALEPH at centre-of-mass energies of 130-172 GeV. The observed candidate events in the data are in agreement with the Standard Model expectation. This result is translated into lower limits on the masses of charginos, neutralinos, sleptons, sneutrinos and squarks. For instance, for m_0=500 GeV/c^2 and tan(beta)=sqrt(2) charginos with masses smaller than 81 GeV/c^2 and neutralinos with masses smaller than 29 GeV/c^2 are excluded at the 95% confidence level for any generation structure of the LQDbar coupling.Comment: 32 pages, 30 figure