Survival modelling in mathematical and medical statistics

An essential aspect of survival analysis is the estimation and prediction of survival probabilities for individuals. For this purpose, mathematical modelling of the hazard rate function is a fundamental issue. This thesis focuses on the novel estimation and application of hazard rate functions in mathematical and medical research. In mathematical research we focus on the development of a semiparametric kernel-based estimate of hazard rate function and a L$_1$ error optimal kernel hazard rate estimate. In medical research we concentrate on the development and validation of survival models using individual participant data from multiple studies. We also consider how to fit survival models that predict individual response to treatment effectiveness, given IPD from multiple trials

Trial of spesolimab for generalized pustular psoriasis.

BACKGROUND: Generalized pustular psoriasis (GPP) is a rare, life-threatening, inflammatory skin disease characterized by widespread eruption of sterile pustules. Interleukin-36 signaling is involved in the pathogenesis of this disorder. Spesolimab, a humanized anti–interleukin-36 receptor monoclonal antibody, is being studied for the treatment of GPP flares. METHODS: In a phase 2 trial, we randomly assigned patients with a GPP flare in a 2:1 ratio to receive a single 900-mg intravenous dose of spesolimab or placebo. Patients in both groups could receive an open-label dose of spesolimab on day 8, an open-label dose of spesolimab as a rescue medication after day 8, or both and were followed to week 12. The primary end point was a Generalized Pustular Psoriasis Physician Global Assessment (GPPGA) pustulation subscore of 0 (range, 0 [no visible pustules] to 4 [severe pustulation]) at the end of week 1. The key secondary end point was a GPPGA total score of 0 or 1 (clear or almost clear skin) at the end of week 1; scores range from 0 to 4, with higher scores indicating greater disease severity. RESULTS: A total of 53 patients were enrolled: 35 were assigned to receive spesolimab and 18 to receive placebo. At baseline, 46% of the patients in the spesolimab group and 39% of those in the placebo group had a GPPGA pustulation subscore of 3, and 37% and 33%, respectively, had a pustulation subscore of 4. At the end of week 1, a total of 19 of 35 patients (54%) in the spesolimab group had a pustulation subscore of 0, as compared with 1 of 18 patients (6%) in the placebo group (difference, 49 percentage points; 95% confidence interval [CI], 21 to 67; P<0.001). A total of 15 of 35 patients (43%) had a GPPGA total score of 0 or 1, as compared with 2 of 18 patients (11%) in the placebo group (difference, 32 percentage points; 95% CI, 2 to 53; P=0.02). Drug reactions were reported in 2 patients who received spesolimab, in 1 of them concurrently with a drug-induced hepatic injury. Among patients assigned to the spesolimab group, infections occurred in 6 of 35 (17%) through the first week; among patients who received spesolimab at any time in the trial, infections had occurred in 24 of 51 (47%) at week 12. Antidrug antibodies were detected in 23 of 50 patients (46%) who received at least one dose of spesolimab. CONCLUSIONS: In a phase 2 randomized trial involving patients with GPP, the interleukin-36 receptor inhibitor spesolimab resulted in a higher incidence of lesion clearance at 1 week than placebo but was associated with infections and systemic drug reactions. Longer and larger trials are warranted to determine the effect and risks of spesolimab in patients with pustular psoriasis. (Funded by Boehringer Ingelheim; Effisayil 1 ClinicalTrials.gov number, NCT03782792.

(K,Na)NbO3-based piezoelectric single crystals: Growth methods, properties, and applications

International audiencePiezoelectric single crystals based on the perovskite ferroelectric system (K,Na)NbO3 have been widely investigated over the past 20 years due to large piezoelectric coefficients, high transition temperatures, low density, and the nontoxic chemical composition. Various crystal growth methods were examined, including high-temperature solution growth, solid-state crystal growth, Bridgman–Stockbarger method, and the floating zone method. Increased understanding of the crystal growth process and post-growth treatments resulted in improved crystal quality and larger sizes. Recently, crystals with high piezoelectric and electromechanical coupling coefficients exceeding 1000 pC/N and 0.90, respectively, were reported. Moreover, their large potential for high-frequency ultrasonic medical imaging was demonstrated. This work provides a review of the development of piezoelectric (K,Na)NbO3-based single crystals, including their growth, defect chemistry, domain structures, electromechanical properties, and applications. Approaches for reducing growth defects, controlling point defects, and domain engineering are discussed. The remaining open issues are presented and an outlook on the future is provided

Effects of monochromatic lights on the growth performance, carcass characteristics, eyeball development, oxidation resistance, and cecal bacteria of Pekin ducks

Objective: Light is a significant component of housing environment in commercial poultry industry. This study was conducted to investigate whether Pekin ducks perform better under monochromatic lights than under white light with respect to their growth performance, carcass quality, eyeball development, oxidation resistance, and cecal bacterial communities. Methods: A total of 320 one-day-old male Pekin ducklings were randomly distributed into five rooms with different light treatments, white, red, yellow, green, and blue light. Each room consisted of 4 replicated pens with 16 ducklings per pen. Results: Blue light significantly decreased fat deposition by decreasing abdominal fat. Long wavelength light, such as red, green, and yellow light, considerably increased the back-to-front eyeball diameter and the red light potentially enlarged the side-to-side eyeball diameter. Besides, the blue light had adverse effects on the oxidation resistance status in terms of increasing the product malonaldehyde of lipid oxidation and decreasing the plasma concentration of total superoxide dismutase. The phyla of Firmicutes had the greatest abundance in the green and blue treatments, while Bacteroidetes in blue treatment was the least. The genus of Faecalibacterium was significantly lower under the red light. Conclusion: The high risk of cecal health status and decreased anti-oxidation activity were observed under blue light. Red, yellow, and green light might increase the risk of oversized eyeball and cecal illness. Therefore, monochromatic lights compared to white light did not show advantages on the performance of housing ducks, it turns out that the white light is the best light condition for grow-out ducks.</p

One-stage individual participant data meta-analysis models: estimation of treatment-covariate interactions must avoid ecological bias by separating out within-trial and across-trial information

Stratified medicine utilizes individual-level covariates that are associated with a differential treatment effect, also known as treatment-covariate interactions. When multiple trials are available, meta-analysis is used to help detect true treatment-covariate interactions by combining their data. Meta-regression of trial-level information is prone to low power and ecological bias, and therefore, individual participant data (IPD) meta-analyses are preferable to examine interactions utilizing individual-level information. However, one-stage IPD models are often wrongly specified, such that interactions are based on amalgamating within-and across-trial information. We compare, through simulations and an applied example, fixed-effect and random-effects models for a one-stage IPD meta-analysis of time-to-event data where the goal is to estimate a treatment-covariate interaction. We show that it is crucial to centre patient-level covariates by their mean value in each trial, in order to separate out within-trial and across-trial information. Otherwise, bias and coverage of interaction estimates may be adversely affected, leading to potentially erroneous conclusions driven by ecological bias. We revisit an IPD meta-analysis of five epilepsy trials and examine age as a treatment effect modifier. The interaction is À0.011 (95% CI: À0.019 to À0.003; p = 0.004), and thus highly significant, when amalgamating within-trial and across-trial information. However, when separating within-trial from across-trial information, the interaction is À0.007 (95% CI: À0.019 to 0.005; p = 0.22), and thus its magnitude and statistical significance are greatly reduced. We recommend that meta-analysts should only use within-trial information to examine individual predictors of treatment effect and that one-stage IPD models should separate within-trial from across-trial information to avoid ecological bias

Finite Element Analysis of Large Plastic Deformation Process of Pure Molybdenum Plate during Hot Rolling

The rare molybdenum resources are being increasingly used in heavy industries. In this study, the common unidirectional and cross hot rolling operations, for pure molybdenum plates, were numerically simulated by using MSC. Marc software. An elastic–plastic finite element model was employed, together with the updated Lagrange method, to predict stress and strain fields in the workpiece. The results showed that there was a typical three-dimensional additional compressive stress (σy> σz > σx) in the deformation zone, while strain could be divided into uniaxial compressive strain and biaxial tensile strain (εy > εx > εz). Tensile stress σx increased with the accumulation of reduction and the decrease in friction coefficient at the edge of the width spread. More importantly, the interlaced deformation caused by cross-commutations, which were helpful in repairing the severe anisotropy created by unidirectional hot rolling. The evolution of the temperature field of pure molybdenum plate was investigated. The surface quenching depth of the pure molybdenum plate was about 1/6 H under different initial temperatures and reductions. In addition, the fundamental reason for the nonuniform distribution of stress and strain fields was the joint influence of rolling stress, contact friction, and external resistance. By comparing the theoretical simulation value of the model with the experimental verification data, we found that the model was aligning well with the actual engineering

One-stage individual participant data meta-analysis models: estimation of treatment-covariate interactions must avoid ecological bias by separating out within-trial and across-trial information

Stratified medicine utilizes individual-level covariates that are associated with a differential treatment effect, also known as treatment-covariate interactions. When multiple trials are available, meta-analysis is used to help detect true treatment-covariate interactions by combining their data. Meta-regression of trial-level information is prone to low power and ecological bias, and therefore, individual participant data (IPD) meta-analyses are preferable to examine interactions utilizing individual-level information. However, one-stage IPD models are often wrongly specified, such that interactions are based on amalgamating within- and across-trial information. We compare, through simulations and an applied example, fixed-effect and random-effects models for a one-stage IPD meta-analysis of time-to-event data where the goal is to estimate a treatment-covariate interaction. We show that it is crucial to centre patient-level covariates by their mean value in each trial, in order to separate out within-trial and across-trial information. Otherwise, bias and coverage of interaction estimates may be adversely affected, leading to potentially erroneous conclusions driven by ecological bias. We revisit an IPD meta-analysis of five epilepsy trials and examine age as a treatment effect modifier. The interaction is -0.011 (95% CI: -0.019 to -0.003; p = 0.004), and thus highly significant, when amalgamating within-trial and across-trial information. However, when separating within-trial from across-trial information, the interaction is -0.007 (95% CI: -0.019 to 0.005; p = 0.22), and thus its magnitude and statistical significance are greatly reduced. We recommend that meta-analysts should only use within-trial information to examine individual predictors of treatment effect and that one-stage IPD models should separate within-trial from across-trial information to avoid ecological bias. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd