Calibration : the Achilles heel of predictive analytics

Acknowledgements This work was developed as part of the international STRengthening Analytical Thinking for Observational Studies (STRATOS) initiative. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies (http://stratos-initiative.org/). Members of the STRATOS Topic Group ‘Evaluating diagnostic tests and prediction models’ are (alphabetically) Patrick Bossuyt, Gary S. Collins, Petra Macaskill, David J. McLernon, Karel G.M. Moons, Ewout W. Steyerberg, Ben Van Calster, Maarten van Smeden, and Andrew Vickers. Funding This work was funded by the Research Foundation – Flanders (FWO; grant G0B4716N) and Internal Funds KU Leuven (grant C24/15/037). The funders had no role in study design, data collection, data analysis, interpretation of results, or writing of the manuscript. Contributions All authors conceived of the study. BVC drafted the manuscript. All authors reviewed and edited the manuscript and approved the final version.Peer reviewedPublisher PD

Prediction of Large Events on a Dynamical Model of a Fault

We present results for long term and intermediate term prediction algorithms applied to a simple mechanical model of a fault. We use long term prediction methods based, for example, on the distribution of repeat times between large events to establish a benchmark for predictability in the model. In comparison, intermediate term prediction techniques, analogous to the pattern recognition algorithms CN and M8 introduced and studied by Keilis-Borok et al., are more effective at predicting coming large events. We consider the implications of several different quality functions Q which can be used to optimize the algorithms with respect to features such as space, time, and magnitude windows, and find that our results are not overly sensitive to variations in these algorithm parameters. We also study the intrinsic uncertainties associated with seismicity catalogs of restricted lengths.Comment: 33 pages, plain.tex with special macros include

Development and validation of a prognostic model to predict birth weight: individual participant data meta-analysis

OBJECTIVE: To predict birth weight at various potential gestational ages of delivery based on data routinely available at the first antenatal visit. DESIGN: Individual participant data meta-analysis. DATA SOURCES: Individual participant data of four cohorts (237 228 pregnancies) from the International Prediction of Pregnancy Complications (IPPIC) network dataset. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Studies in the IPPIC network were identified by searching major databases for studies reporting risk factors for adverse pregnancy outcomes, such as pre-eclampsia, fetal growth restriction, and stillbirth, from database inception to August 2019. Data of four IPPIC cohorts (237 228 pregnancies) from the US (National Institute of Child Health and Human Development, 2018; 233 483 pregnancies), UK (Allen et al, 2017; 1045 pregnancies), Norway (STORK Groruddalen research programme, 2010; 823 pregnancies), and Australia (Rumbold et al, 2006; 1877 pregnancies) were included in the development of the model. RESULTS: The IPPIC birth weight model was developed with random intercept regression models with backward elimination for variable selection. Internal-external cross validation was performed to assess the study specific and pooled performance of the model, reported as calibration slope, calibration-in-the-large, and observed versus expected average birth weight ratio. Meta-analysis showed that the apparent performance of the model had good calibration (calibration slope 0.99, 95% confidence interval (CI) 0.88 to 1.10; calibration-in-the-large 44.5 g, -18.4 to 107.3) with an observed versus expected average birth weight ratio of 1.02 (95% CI 0.97 to 1.07). The proportion of variation in birth weight explained by the model (R2) was 46.9% (range 32.7-56.1% in each cohort). On internal-external cross validation, the model showed good calibration and predictive performance when validated in three cohorts with a calibration slope of 0.90 (Allen cohort), 1.04 (STORK Groruddalen cohort), and 1.07 (Rumbold cohort), calibration-in-the-large of -22.3 g (Allen cohort), -33.42 (Rumbold cohort), and 86.4 g (STORK Groruddalen cohort), and observed versus expected ratio of 0.99 (Rumbold cohort), 1.00 (Allen cohort), and 1.03 (STORK Groruddalen cohort); respective pooled estimates were 1.00 (95% CI 0.78 to 1.23; calibration slope), 9.7 g (-154.3 to 173.8; calibration-in-the-large), and 1.00 (0.94 to 1.07; observed v expected ratio). The model predictions were more accurate (smaller mean square error) in the lower end of predicted birth weight, which is important in informing clinical decision making. CONCLUSIONS: The IPPIC birth weight model allowed birth weight predictions for a range of possible gestational ages. The model explained about 50% of individual variation in birth weights, was well calibrated (especially in babies at high risk of fetal growth restriction and its complications), and showed promising performance in four different populations included in the individual participant data meta-analysis. Further research to examine the generalisability of performance in other countries, settings, and subgroups is required. TRIAL REGISTRATION: PROSPERO CRD42019135045

Climate Change and Human Development in Africa: Assessing the Risks and Vulnerability of Climate Change in Kenya, Malawi and Ethiopia

human development, climate change

22 years of predictive testing for Huntington's disease: the experience of the UK Huntington's Prediction Consortium

Huntington’s disease (HD) is a progressive neurodegenerative condition. At-risk individuals have accessed predictive testing via direct mutation testing since 1993. The UK Huntington’s Prediction Consortium has collected anonymised data on UK predictive tests, annually, from 1993 to 2014: 9407 predictive tests were performed across 23 UK centres. Where gender was recorded, 4077 participants were male (44.3%) and 5122 were female (55.7%). The median age of participants was 37 years. The most common reason for predictive testing was to reduce uncertainty (70.5%). Of the 8441 predictive tests on individuals at 50% prior risk, 4629 (54.8%) were reported as mutation negative and 3790 (44.9%) were mutation positive, with 22 (0.3%) in the database being uninterpretable. Using a prevalence figure of 12.3 × 10−5, the cumulative uptake of predictive testing in the 50% at-risk UK population from 1994 to 2014 was estimated at 17.4% (95% CI: 16.9–18.0%). We present the largest study conducted on predictive testing in HD. Our findings indicate that the vast majority of individuals at risk of HD (>80%) have not undergone predictive testing. Future therapies in HD will likely target presymptomatic individuals; therefore, identifying the at-risk population whose gene status is unknown is of significant public health value

Box Traps for Feral Swine Capture: A Comparison of Gate Styles in Texas

Many different types of traps have been developed to increase feral swine (Sus scrofa) capture efficiency. Though not previously compared, gate styles may influence capture success. Our objectives were to report feral swine capture data from 31 trapping campaigns conducted in 17 counties from 2005 to 2011 in Texas, USA, compare capture rates by demographic category between side-swing and rooter gates, and evaluate influences of moisture, using the Palmer Drought Severity Index (PDSI), on juvenile capture rates. We trapped feral swine during all months of the year. Our trap configurations were identical with the exception of gate style. Traps had either side-swing or rooter gates. We captured 1,310 feral swine during 2,424 trap-nights. We found no differences in capture rates between gate styles for adults, adult males, or adult females. However, we found juvenile capture rates and total capture rates to differ between gate styles. Box traps with rooter gates captured more juveniles, resulting in more total captures than in box traps with side-swing gates. Partitioned rooter gates are constructed to allow for continual entry after the gate has been tripped; whereas with single-panel side-swine gates, continual entry may be more challenging for juvenile animals that lack the size and strength to push through the spring tension. Rooter gates should be considered over side-swing gates in management programs aimed at overall damage reduction. However, in management or research programs that seek to capture adult feral swine, side-swing gates may be more appropriate because fewer non-target juvenile feral swine are captured

Institutional Linkages, South-South Partnerships and Capacity Building Hands-on Workshop on Objective Climate Forecasts for the Agriculture and Food Security Sector in Eastern and Southern Africa

The institutional linkages, south-south partnerships, and capacity building hands-on workshop on "Objective Climate Forecasts for Agriculture, and Food Security Sector in Eastern and Southern Africa" was conducted between August 31- September 4, 2021, in Victoria Falls, Zimbabwe. The workshop brought together more than 50 experts from National Meteorological and Hydrological Services (NMHS), Regional Climate Centers, Research Institutions, Agricultural and Food Security institutions, and actors from 15 Southern, Eastern, and Horn of Africa nations. Mr. Munesu Munodawafa, the Permanent Secretary of Zimbabwe's Ministry of Environment, Climate Change, Tourism and Hospitality Industry (MECCTHI), officially opened the event. The main objectives of the training workshop were to build the capacities of national and regional experts in objective seasonal forecasting, enhance the co-production of reliable and improved climate information and services in the agriculture and food security sector, and establish multi-institutional and multi-stakeholder dialogue and knowledge sharing platform to strengthen institutional linkages and south-south partnerships. The UN Economic Commission for Africa's Climate Research for Development (CR4D) initiative convened the workshop, which is funded by the Government of the United Kingdom of Great Britain and Northern Ireland through the Foreign Commonwealth Development Office (FCDO) within the Weather and Climate Information SERvice (WISER) Programme, the IGAD Climate Prediction and Applications Centre (ICPAC), and the CGIAR Research Program on Climate Change, Agriculture and Food Security East Africa (CCAFS-EA). ICPAC is a World Meteorological Organizations Regional Climate Center and a specialized institution of the Inter-Governmental Authority on Development (IGAD), while CCAFS is a program of the Consultative Group on International Agricultural Research (CGIAR). Both ICPAC and CCAFS, which have long-standing records of public service accomplishments on climate change in Africa, are members of the Institutional Collaboration Platform (ICP) – one of the three governing arms of the CR4D. Complementing ICP in the governing of the CR4D are the Oversight Board (OB) and the Scientific Advisory Committee (SAC). The CR4D secretariat is domiciled at the lead continental climate think-tank, the Africa Climate Policy Centre (ACPC) of the United Nations Economic Commission for Africa (UNECA). The workshop participants had the opportunity to practice the procedures developing the ICPAC objective seasonal forecasts. They practiced using Python-based Climate Predictability Tool (PyCPT) and ensemble regression method, which empowered them to generate the national seasonal forecast. Additionally, the co-production session enabled the participants to learn the theory and implications of co-production for generating reliable climate information and services for development and planning in the agricultural sector. To practice the idea of co-production, the participants were divided into five groups. They were provided questions where users, climate experts, agriculture experts, multi-institutional, and multi-stakeholders mixed to dialogue and share knowledge. Group representatives had a chance to present the result, highlighted the importance of such a rich discussion for co-producing climate services, and summarised the main points raised. Besides, they have emphasized the approaches were effective and provided recommendations. Furthermore, the workshop proved highly successful, demonstrating a keen appetite for closer collaboration and further consideration of future activities in similar contexts and content

Exome Sequencing Reveals Common and Rare Variants in F5 Associated With ACE Inhibitor and Angiotensin Receptor Blocker–Induced Angioedema

Angioedema occurring in the head and neck region is a rare and sometimes life‐threatening adverse reaction to angiotensin‐converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs). Few studies have investigated the association of common variants with this extreme reaction, but none have explored the combined influence of rare variants yet. Adjudicated cases of ACEI‐induced angioedema (ACEI‐AE) or ARB‐induced angioedema (ARB‐AE) and controls were recruited at five different centers. Sequencing of 1,066 samples (408 ACEI‐AE, ARB‐AE, and 658 controls) was performed using exome‐enriched sequence data. A common variant of the F5 gene that causes an increase in blood clotting (rs6025, p.Arg506Gln, also called factor V Leiden), was significantly associated with both ACEI‐AE and ARB‐AE (odds ratio: 2.85, 95% confidence interval (CI), 1.89–4.25). A burden test analysis of five rare missense variants in F5 was also found to be associated with ACEI‐AE or ARB‐AE, P = 2.09 × 10−3. A combined gene risk score of these variants, and the common variants rs6025 and rs6020, showed that individuals carrying at least one variant had 2.21 (95% CI, 1.49–3.27, P = 6.30 × 10−9) times the odds of having ACEI‐AE or ARB‐AE. The increased risk due to the common Leiden allele was confirmed in a genome‐wide association study from the United States. A high risk of angioedema was also observed for the rs6020 variant that is the main coagulation defect‐causing variant in black African and Asian populations. We found that deleterious missense variants in F5 are associated with an increased risk of ACEI‐AE or ARB‐AE

Impact of large-scale climatic oscillations on snowfall-related climate parameters in the world's major downhill ski areas: a review

Skiers are passionate about finding the best snow conditions. Snow conditions in thousands of ski resorts around the world depend mainly on natural snowfall, particularly in the case of backcountry skiing. In various mountain ranges popular among skiers, snowfall is strongly linked to large-scale climatic oscillations. This paper reviews existing information on the impacts of several of these phenomena, such as the El Niño-Southern Oscillation, North Atlantic Oscillation, and North Pacific Index, on snowfall-related climate parameters in the world's major ski areas. We found that in each of the studied areas, one or more large-scale climatic oscillations affected snowfall-related climate parameters. Understanding the predictability of such oscillations is high on the climate research agenda. If this research leads to improved predictability in the coming years, this could be combined with the knowledge summarized in our paper on the relationships between climatic oscillations and snow-related parameters to provide useful information for winter sports and other snow-related fields. © 2012 International Mountain Society