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Ridge regression is a widely used method to mitigate the multicollinearly problem often arising in multiple linear regression. It is well known that the ridge regression estimator can be derived from the Bayesian framework by the posterior mode under a multivariate normal prior. However, the ridge regression model with a copula-based multivariate prior model has not been employed in the Bayesian framework. Motivated by the multicollinearly problem due to an interaction term, we adopt a vine copula to construct the copula-based joint prior distribution. For selected copulas and hyperparameters, we propose Bayesian ridge estimators and credible intervals for regression coefficients. A simulation study is carried out to compare the performance of four different priors (the Clayton, Gumbel, and Gaussian copula priors, and the tri-variate normal prior) on the regression coefficients. Our simulation studies demonstrate that the Archimedean (Clayton and Gumbel) copula priors give more accurate estimates in the presence of multicollinearity compared with the other priors. Finally, a real dataset is analyzed, where the Bayesian ridge estimators and some frequentist estimators are compared.

Survival and reliability analyses deal with incomplete failure time data, such as censored and truncated data. Recently, the classical left-truncation scheme was generalized to analyze “field data”, defined as samples collected within a fixed period. However, existing competing risks models dealing with left-truncated field data are not flexible enough. We propose copula-based competing risks models for latent failure times, permitting a flexible parametric form. We formulate maximum likelihood estimation methods under the Weibull, lognormal, and gamma distributions for the latent failure times. We conduct simulations to check the performance of the proposed methods. We finally give a real data example. We provide the R code to reproduce the simulations and data analysis results.

The primary analysis of the JGOG 3016 trial showed that a dose-dense paclitaxel and carboplatin regimen significantly improves progression-free and overall survival compared with the conventional regimen as first-line chemotherapy for patients with epithelial ovarian, fallopian tube, or primary peritoneal cancer. We report the long-term follow-up results for survival. This randomised controlled trial was done at 85 centres in Japan. Patients with stage II–IV ovarian cancer were randomly assigned to receive conventional treatment (carboplatin area under the curve [AUC] 6 mg/mL per min and paclitaxel 180 mg/m2 on day 1) or dose-dense treatment (carboplatin AUC 6 mg/mL per min on day 1 and paclitaxel 80 mg/m2 on days 1, 8, and 15). The treatments were repeated every 3 weeks for six cycles; responding patients had three additional cycles. The randomisation was done centrally by telephone or fax, stratified by residual disease, stage, and histological type. The primary endpoint was progression-free survival; overall survival was a secondary endpoint. Long-term information on adverse events was not collected. Efficacy analyses were by intention to treat. This study is registered with ClinicalTrials.gov, number NCT00226915. 637 patients were enrolled, of whom 631 were analysed (312 assigned to the dose-dense regimen, 319 to the conventional regimen). Median follow-up was 76·8 months (IQR 68·9–85·6). Median progression-free survival was significantly longer in the dose-dense treatment group than in the conventional treatment group (28·2 months [95% CI 22·3–33·8] vs 17·5 months [15·7–21·7]; hazard ratio [HR] 0·76, 95% CI 0·62–0·91; p=0·0037). Median overall survival was 100·5 months (95% CI 65·2–∞) in the dose-dense treatment group and 62·2 months (52·1–82·6) in the conventional treatment group (HR 0·79, 95% CI 0·63–0·99; p=0·039). Dose-dense treatment offers better survival than conventional treatment and is a potential new standard of care for first-line chemotherapy for patients with advanced epithelial ovarian cancer. Japanese Gynecologic Oncology Group, Bristol-Myers Squibb.

Clinical risk prediction formulas for cancer patients can be improved by dynamically updating the formulas by intermediate events, such as tumor progression. The increased accessibility of individual patient data (IPD) from multiple studies has motivated the development of dynamic prediction formulas accounting for between-study heterogeneity. A joint frailty-copula model for overall survival and time to tumor progression has the potential to develop a dynamic prediction formula of death from heterogenous studies. However, the process of developing, validating, and publishing the prediction formula is complex, which has not been sufficiently described in the literature. In this article, we provide a tutorial in order to build a web-based application for dynamic risk prediction for cancer patients on the basis of the R packages joint.Cox and Shiny. We demonstrate the proposed methods using a dataset of breast cancer patients from multiple clinical studies. Following this tutorial, we demonstrate how one can publish web applications available online, which can be manipulated by any user through a smartphone or personal computer. After learning this tutorial, developers acquire the ability to build an online web application using their own datasets.

Statistical packages such as edgeR and DESeq are intended to detect genes that are relevant to phenotypic traits and diseases. A few studies have also modeled the relationships between gene expressions and traits. In the presence of multicollinearity and outliers, which are unavoidable in genetic data, the robust ridge regression estimator can be applied with the trait value as the response variable and the gene expressions as explanatory variables. In some simulation scenarios, the robust ridge estimator is resistant to outliers and less susceptible to multicollinearity than the ordinary least-squares (OLS) estimator. This study investigated the reliability of the robust ridge estimator, in a scenario where the explanatory variables have tail-dependence and negative binomial distributions, by comparing its performance to that of OLS using vine copula to model the tail-dependence among gene expressions. The robust ridge estimator and OLS were both applied to an ecological dataset. First, statistical analysis was used to compare RNA sequencing data between two treatments; then, 15 differentially expressed genes were selected. Next, the regression parameter estimates of robust ridge and OLS for the effects of the 15 contigs (explanatory variables) on trait values (response variables) were compared. Robust ridge regression was found to detect fewer positive and negative slopes than OLS regression. These results indicate that robust ridge regression can be successfully applied for RNA sequencing analysis to estimate the effect of trait-associated genes using real data, and holds great promise as a tool for modeling the association between RNA expression and phenotypic traits.

Meta-analysis is an indispensable tool for synthesizing statistical results obtained from individual studies. Recently, non-Bayesian estimators for individual means were proposed by applying three methods: the James–Stein (JS) shrinkage estimator, isotonic regression estimator, and pretest (PT) estimator. In order to make these methods available to users, we develop a new R package meta.shrinkage. Our package can compute seven estimators (named JS, JS+, RML, RJS, RJS+, PT, and GPT). We introduce this R package along with the usage of the R functions and the “average-min-max” steps for the pool-adjacent violators algorithm. We conduct Monte Carlo simulations to validate the proposed R package to ensure that the package can work properly in a variety of scenarios. We also analyze a data example to show the ability of the R package.

BackgroundEndometrial carcinoma, the most common gynecologic carcinoma, has an excellent prognosis post-surgery when diagnosed early. The role of postoperative adjuvant chemotherapy in stages I–II endometrial carcinoma remains controversial. This study assesses the efficacy of adjuvant chemotherapy in improving prognosis for these patients.MethodsA retrospective analysis was conducted on 1223 stage I–II endometrial carcinoma patients who underwent surgical treatment including total hysterectomy, bilateral salpingo-oophorectomy, and lymph-node biopsy or dissection across four Jikei University School of Medicine-affiliated facilities between 2001 and 2018. Patients were divided into low intermediate risk (LIR) and high intermediate risk (HIR) groups based on recurrence risk. Propensity score matching adjusted for various covariates was used to compare progression-free survival (PFS) and overall survival (OS) between patients who received adjuvant chemotherapy and those who did not.ResultsThe study included 443 eligible patients, with 288 in the LIR group and 155 in the HIR group. Post propensity score matching, no significant difference in PFS or OS was observed between the observation and adjuvant chemotherapy groups within both risk categories. Notably, the 5-year OS for LIR was 97.6% in the observation group and 96.7% in the chemotherapy group; for HIR, the 5-year OS was similarly high with no significant difference.ConclusionsThe findings suggest that postoperative adjuvant chemotherapy does not significantly contribute to the improvement of recurrence or prognosis in patients with stage I–II endometrial carcinoma who are categorized outside the low-risk group and have no lymph-node metastasis.

We investigated the effect of increased pH induced by acid suppressants on the viability of non –Helicobacter pylori helicobacters (NHPHs) within parietal cell intracellular canaliculi and fundic glandular lumina by immunohistochemistry, electron microscopy, quantitative PCR, urea breath tests, and using a bilayer culture system. Three months before the experiment, mice were infected with the NHPH H. suis and then treated with famotidine (2 mg/kg body weight [BW], once daily), lansoprazole (30 mg/kg BW, once daily), or vonoprazan (20 mg/kg BW, once daily) for 3 days. Immunohistochemical studies using the TUNEL method, quantitative PCR analysis, and urea breath tests were performed. PCR analysis showed a decrease in the NHPH quantity after vonoprazan treatment. Urea breath tests revealed a significant decrease in the NHPH urease activity after vonoprazan, lansoprazole, and famotidine treatments for 3 days; however, 4 days after the treatment, urease activity reversed to the pretreatment level for each treatment group. Electron microscopy revealed an increase in the damaged NHPH after vonoprazan treatment. The TUNEL method revealed apoptotic NHPH within parietal cells after vonoprazan treatment. The bilayer culture results demonstrated that NHPH moved more quickly at a pH of 4.0 than at a pH of 3.0, 5.0, and 6.5, and electron microscopy revealed a change from the spiral form to the coccoid form under near-neutral pH conditions. We thus proposed that acid suppressants, especially vonoprazan, induce NHPH damage by altering pH.

The Hokkaido salamander (Hynobius retardatus) is endemic to Hokkaido Island, Japan, and shows intriguing flexible phenotypic plasticity and regional morphological diversity. However, to date, allozymes and partial mitochondria DNA sequences have provided only an outline of its demographic histories and the pattern of its genetic diversification. To understand the finer details of the population structure of this species and its evolution since speciation, we genotyped five regional populations by using 12 recently developed microsatellite polymorphic markers. We found a clear population structure with low gene flow among the five populations, but a close genetic relationship between the Teshio and Kitami populations. Our demographic analysis suggested that Teshio and Erimo had the largest effective population sizes among the five populations. These findings regarding the population structure and demography of H. retardatus improve our understanding of the faunal phylogeography on Hokkaido Island and also provide fundamental genetic information that will be useful for future studies.

Summary In most animal species, the hatchling stage is a highly vulnerable life‐history stage. In many fish and amphibian species, hatchling abundance varies substantially among sites and years, with the result that selection strength in conspecific interactions such as cannibalism is also variable. The variability of selection leads species to evolve phenotypic plasticity, and adaptive trait changes in hatchlings that depend on the density of conspecifics can therefore be expected. However, plasticity strategies in response to cannibalistic interactions in this vulnerable life‐history stage have received little attention. Because cannibalism success is dependent on the size balance between predator capturing organ and prey body, and also on the prey‐capturing ability of the cannibal and the escape ability of its prey, we hypothesize that hatchlings will exhibit faster growth and development in response to conspecific interactions. We performed a series of experiments to test this hypothesis, using pre‐feeding larvae of a cannibalistic salamander (Hynobius retardatus). Many traits of the hatchlings reared with conspecifics were larger than the same traits in those reared alone, because the former hatchlings grew faster and were more advanced developmentally. The time to the beginning of feeding was shorter, and swimming speed as an indicator of escape performance was faster, for hatchlings reared with conspecifics. Hatchlings reared with conspecifics more successfully cannibalized small hatchlings and were also highly resistant to being cannibalized by large conspecifics, compared with hatchlings reared alone. These differences in cannibalism success and avoidance of cannibalization were well explained by differences in gape and head size, respectively, between the interacting hatchlings. Therefore, acceleration of growth and development of hatchlings in the proximate presence of conspecifics may confer significant fitness advantages on hatchlings in a high‐density cannibalistic situation. Developmental and growth plasticity may thus be a powerful adaptive mechanism that allows individuals to respond to the dynamic character of salamander populations in nature. Lay Summary