An update on statistical boosting in biomedicine

Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine-learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates. They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables) can be combined with any kind of loss function (target function to be optimized, defining the type of regression setting). In this review article, we highlight the most recent methodological developments on statistical boosting regarding variable selection, functional regression and advanced time-to-event modelling. Additionally, we provide a short overview on relevant applications of statistical boosting in biomedicine

Comparing the harmful effects of nontuberculous mycobacteria and Gram negative bacteria on lung function in patients with cystic fibrosis

BACKGROUND: To better understand the relative effects of infection with nontuberculous mycobacteria and Gram negative bacteria on lung function decline in cystic fibrosis, we assessed the impact of each infection in a Danish setting. METHODS: Longitudinal registry study of 432 patients with cystic fibrosis contributing 53,771 lung function measures between 1974 and 2014. We used a mixed effects model with longitudinally structured correlation, while adjusting for clinically important covariates. RESULTS: Infections with a significant impact on rate of decline in %FEV1 were Mycobacterium abscessus complex with -2.22% points per year (95% CI -3.21 to -1.23), Burkholderia cepacia complex -1.95% (95% CI -2.51 to -1.39), Achromobacterxylosoxidans -1.55% (95% CI -2.21 to -0.90), and Pseudomonas aeruginosa -0.95% (95% CI -1.24 to -0.66). Clearing M. abscessus complex was associated with a change to a slower decline, similar in magnitude to the pre-infection slope. CONCLUSIONS: In a national population we have demonstrated the impact on lung function of each chronic CF pathogen. M. abscessus complex was associated with the worst impact on lung function. Eradication of M. abscessus complex may significantly improve lung function

Quantile regression: A short story on how and why

Quantile regression quantifies the association of explanatory variables with a conditional quantile of a dependent variable without assuming any specific conditional distribution. It hence models the quantiles, instead of the mean as done in standard regression. In cases where either the requirements for mean regression, such as homoscedasticity, are violated or interest lies in the outer regions of the conditional distribution, quantile regression can explain dependencies more accurately than classical methods. However, many quantile regression papers are rather theoretical so the method has still not become a standard tool in applications. In this article, we explain quantile regression from an applied perspective. In particular, we illustrate the concept, advantages and disadvantages of quantile regression using two datasets as examples

A Key Role for TGF-beta Signaling to T Cells in the Long-Term Acceptance of Allografts

TGF-β is a key immunoregulatory cytokine which supports self-tolerance by signaling to T cells. In this report, we show a crucial role for TGF-β signaling to T cells in enabling the long-term acceptance of allografts, whether natural or induced therape

Ovarian Follicular Response to Oestrous Synchronisation and Induction of Ovulation in Norwegian Red Cattle

Oestrous synchronisation of cattle has been widely applied to accomplish simultaneous ovulation in animals and facilitate timed artificial insemination. The main aim of this study was to investigate the ovarian follicular growth and ovulatory response to oestrus and ovulation synchronisation in Norwegian Red heifers and cows. Oestrous cycles in 34 heifers and 10 cows from 4 herds were synchronised with two PGF2α analogue treatments 11 days apart, followed by GnRH analogue treatment for induction of ovulation. Thereafter, the ovaries were examined by ultrasonography at 3 h intervals until ovulation. Results The luteolytic effect of the PGF2α analogue was verified in 9 of 10 cows by progesterone contents in milk. Maximum physical activity of the cows occurred on average 69 h after PGF2α analogue treatment. An ovulatory response was recorded in 95.5% (42/44) of the animals. A significant difference in follicle size at ovulation was found between 2 of the herds. Animals with medium sized and large follicles and heifers aged > 16 months ovulated earlier than other animals. Conclusions The applied sequence of treatments in the study was shown to be effective in synchronizing and inducing ovulation within a relatively narrow time interval in the Norwegian Red heifers and cows, consistent with findings in other cattle breeds.publishedVersio