Variable selection under multiple imputation using the bootstrap in a prognostic study

Background: Missing data is a challenging problem in many prognostic studies. Multiple imputation (MI) accounts for imputation uncertainty that allows for adequate statistical testing. We developed and tested a methodology combining MI with bootstrapping techniques for studying prognostic variable selection. Method: In our prospective cohort study we merged data from three different randomized controlled trials (RCTs) to assess prognostic variables for chronicity of low back pain. Among the outcome and prognostic variables data were missing in the range of 0 and 48.1%. We used four methods to investigate the influence of respectively sampling and imputation variation: MI only, bootstrap only, and two methods that combine MI and bootstrapping. Variables were selected based on the inclusion frequency of each prognostic variable, i.e. the proportion of times that the variable appeared in the model. The discriminative and calibrative abilities of prognostic models developed by the four methods were assessed at different inclusion levels. Results: We found that the effect of imputation variation on the inclusion frequency was larger than the effect of sampling variation. When MI and bootstrapping were combined at the range of 0% (full model) to 90% of variable selection, bootstrap corrected c-index values of 0.70 to 0.71 and slope values of 0.64 to 0.86 were found. Conclusion: We recommend to account for both imputation and sampling variation in sets of missing data. The new procedure of combining MI with bootstrapping for variable selection, results in multivariable prognostic models with good performance and is therefore attractive to apply on data sets with missing values

NIOX VERO: Individualized Asthma Management in Clinical Practice

As we move toward an era of precision medicine, novel biomarkers of disease will enable the identification and personalized treatment of new endotypes. In asthma, fractional exhaled nitric oxide (FeNO) serves as a surrogate marker of airway inflammation that often correlates with the presence of sputum eosinophils. The increase in FeNO is driven by an upregulation of inducible nitric oxide synthase (iNOS) by cytokines, which are released as a result of type-2 airway inflammation. Scientific evidence supports using FeNO in routine clinical practice. In steroid-naive patients and in patients with mild asthma, FeNO levels decrease within days after corticosteroid treatment in a dose-dependent fashion and increase after steroid withdrawal. In difficult asthma, FeNO testing correlates with anti-inflammatory therapy compliance. Assessing adherence by FeNO testing can remove the confrontational aspect of questioning a patient about compliance and change the conversation to one of goal setting and ways to improve disease management. However, the most important aspect of incorporating FeNO in asthma management is the reduction in the risk of exacerbations. In a recent primary care study, reduction of exacerbation rates and improved symptom control without increasing overall inhaled corticosteroid (ICS) use were demonstrated when a FeNO-guided anti-inflammatory treatment algorithm was assessed and compared to the standard care. A truly personalized asthma management approach—showing reduction of exacerbation rates, overall use of ICS and neonatal hospitalizations—was demonstrated when FeNO testing was applied as part of the treatment algorithm that managed asthma during pregnancy. The aim of this article is to describe how FeNO and the NIOX VERO® analyzer can help to optimize diagnosis and treatment choices and to aid in the monitoring and improvement of clinical asthma outcomes in children and adults

Dopaminergic drugs and the risk of hip or femur fracture: a population-based case–control study

SUMMARY: The effect of dopaminergic medication on the risk of hip/femur fractures is not clear. Our results showed a nearly twofold increased risk of hip/femur fractures in current dopaminergic drug users. Concomitant use of antidepressants further increased this risk. Fracture risk assessment may be warranted in elderly users of dopaminergic drugs. INTRODUCTION: Dopaminergic drugs, often used in the treatment of Parkinson's disease, have several pharmacological effects that may increase or decrease the risk of falling and fractures. Thus, the effect of dopaminergic medication on the risk of hip/femur fractures is not clear. The objective of the study was to examine the effect of dopaminergic medication and concomitant use of psychotropics on the risk of hip/femur fractures taking into account the timing of dopaminergic drug use. METHODS: A population-based case-control study in the PHARMO database was conducted for the period 1991 to 2002. Cases were patients aged 18 years and older with a first hip or femur fracture and matched to four control patients by year of birth, sex and geographical region. RESULTS: The study population included 6,763 cases and 26,341 controls. Current use of dopaminergic drugs (1-30 days before the index date) was associated with an increased risk of hip/femur fractures compared to never use (OR(adj) 1.76, 95% CI = 1.39-2.22), but this excess risk rapidly dropped to baseline levels when treatment had been discontinued >1 year ago. Concomitant use of antidepressants among current dopaminergic drug users further increased the risk of hip/femur fractures (OR(adj) 3.51, 95% CI = 2.10-5.87) while there was no additional risk with concomitant use of other psychotropics. CONCLUSIONS: Although the observed association between dopaminergic drugs and fracture risk may not be entirely causal, due to absence of information on the (severity of the) underlying disease, fracture risk assessment may be warranted in elderly users of dopaminergic drugs

Beached bachelors: An extensive study on the largest recorded sperm whale Physeter macrocephalus mortality event in the North Sea

Between the 8th January and the 25th February 2016, the largest sperm whale Physeter macrocephalus mortality event ever recorded in the North Sea occurred with 30 sperm whales stranding in five countries within six weeks. All sperm whales were immature males. Groups were stratified by size, with the smaller animals stranding in the Netherlands, and the largest in England. The majority (n = 27) of the stranded animals were necropsied and/or sampled, allowing for an international and comprehensive investigation into this mortality event. The animals were in fair to good nutritional condition and, aside from the pathologies caused by stranding, did not exhibit significant evidence of disease or trauma. Infectious agents were found, including various parasite species, several bacterial and fungal pathogens and a novel alphaherpesvirus. In nine of the sperm whales a variety of marine litter was found. However, none of these findings were considered to have been the primary cause of the stranding event. Potential anthropogenic and environmental factors that may have caused the sperm whales to enter the North Sea were assessed. Once sperm whales enter the North Sea and head south, the water becomes progressively shallower (<40 m), making this region a global hotspot for sperm whale strandings. We conclude that the reasons for sperm whales to enter the southern North Sea are the result of complex interactions of extrinsic environmental factors. As such, these large mortality events seldom have a single ultimate cause and it is only through multidisciplinary, collaborative approaches that potentially multifactorial large-scale stranding events can be effectively investigated

Beached bachelors: An extensive study on the largest recorded sperm whale Physeter macrocephalus mortality event in the North Sea

Between the 8th January and the 25th February 2016, the largest sperm whale Physeter macrocephalus mortality event ever recorded in the North Sea occurred with 30 sperm whales stranding in five countries within six weeks. All sperm whales were immature males. Groups were stratified by size, with the smaller animals stranding in the Netherlands, and the largest in England. The majority (n = 27) of the stranded animals were necropsied and/or sampled, allowing for an international and comprehensive investigation into this mortality event. The animals were in fair to good nutritional condition and, aside from the pathologies caused by stranding, did not exhibit significant evidence of disease or trauma. Infectious agents were found, including various parasite species, several bacterial and fungal pathogens and a novel alphaherpesvirus. In nine of the sperm whales a variety of marine litter was found. However, none of these findings were considered to have been the primary cause of the stranding event. Potential anthropogenic and environmental factors that may have caused the sperm whales to enter the North Sea were assessed. Once sperm whales enter the North Sea and head south, the water becomes progressively shallower (<40 m), making this region a global hotspot for sperm whale strandings. We conclude that the reasons for sperm whales to enter the southern North Sea are the result of complex interactions of extrinsic environmental factors. As such, these large mortality events seldom have a single ultimate cause and it is only through multidisciplinary, collaborative approaches that potentially multifactorial large-scale stranding events can be effectively investigated

Calibration of FRAX ® 3.1 to the Dutch population with data on the epidemiology of hip fractures

SummaryThe FRAX tool has been calibrated to the entire Dutch population, using nationwide (hip) fracture incidence rates and mortality statistics from the Netherlands. Data used for the Dutch model are described in this paper.IntroductionRisk communication and decision making about whether or not to treat with anti-osteoporotic drugs with the use of T-scores are often unclear for patients. The recently developed FRAX models use easily obtainable clinical risk factors to estimate an individual's 10-year probability of a major osteoporotic fracture and hip fracture that is useful for risk communication and subsequent decision making in clinical practice. As of July 1, 2010, the tool has been calibrated to the total Dutch population. This paper describes the data used to develop the current Dutch FRAX model and illustrates its features compared to other countries.MethodsAge- and sex-stratified hip fracture incidence rates (LMR database) and mortality rates (Dutch national mortality statistics) for 2004 and 2005 were extracted from Dutch nationwide databases (patients aged 50+ years). For other major fractures, Dutch incidence rates were imputed, using Swedish ratios for hip to osteoporotic fracture (upper arm, wrist, hip, and clinically symptomatic vertebral) probabilities (age- and gender-stratified). The FRAX tool takes into account age, sex, body mass index (BMI), presence of clinical risk factors, and bone mineral density (BMD).ResultsFracture incidence rates increased with increasing age: for hip fracture, incidence rates were lowest among Dutch patients aged 50–54 years (per 10,000 inhabitants: 2.3 for men, 2.1 for women) and highest among the oldest subjects (95–99 years; 169 of 10,000 for men, 267 of 10,000 for women). Ten-year probability of hip or major osteoporotic fracture was increased in patients with a clinical risk factor, lower BMI, female gender, a higher age, and a decreased BMD T-score. Parental hip fracture accounted for the greatest increase in 10-year fracture probability.ConclusionThe Dutch FRAX tool is the first fracture prediction model that has been calibrated to the total Dutch population, using nationwide incidence rates for hip fracture and mortality rates. It is based on the original FRAX methodology, which has been externally validated in several independent cohorts. Despite some limitations, the strengths make the Dutch FRAX tool a good candidate for implementation into clinical practice

PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS

Background: The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study.Methods: We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T&gt;G and c.3113G&gt;A, CHEK2c.349A&gt;G, c.538C&gt;T, c.715G&gt;A, c.1036C&gt;T, c.1312G&gt;T, and c.1343T&gt;G and ATM c.7271T&gt;G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant.Results: For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10−5), PALB2 c.3113G&gt;A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10−8) and ATM c.7271T&gt;G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A&gt;G OR 2.26 (95% CI 1.29 to 3.95), c.1036C&gt;T OR 5.06 (95% CI 1.09 to 23.5) and c.538C&gt;T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T&gt;G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G&gt;T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants.Conclusions: This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.</p