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Importance: Clarifying the relationship between kindergarteners' characteristics and their future handwriting performance is beneficial for the early detection of children at risk of handwriting difficulties. Objective: To determine which visual–perceptual and motor skills and behavioral traits significantly predict kindergartners' Chinese handwriting legibility and speed in the first grade. Design: One-year longitudinal, observational design. Setting: Kindergarten and elementary schools. Participants: One hundred six kindergarten children (53 boys and 53 girls; ages 5 or 6 yr) were recruited. Outcomes and Measures: The participants completed two subtests of the Bruininks–Oseretsky Test of Motor Proficiency–Second Edition, Test of Visual Perceptual Skills–Third Edition, Beery–Buktenica Developmental Test of Visual–Motor Integration (Beery™ VMI), and the Attention-Deficit/Hyperactivity Disorder Test–Chinese Version in kindergarten. Their handwriting legibility (character accuracy and construction) and speed were assessed by investigator-developed Chinese handwriting tests in the first grade. Results: Multivariate regression analyses indicated the independent predictive power of spatial relationships (p =.042) and inattention (p =.004) for character accuracy. Visual–motor integration (VMI; p =.008) and inattention (p =.002) were the key predictors of character construction. Manual dexterity (p =.001) was the only significant predictor of writing speed. Conclusions and Relevance: Kindergarteners who perform poorly in spatial relationships, VMI, manual dexterity, and attention are likely to have less legible Chinese handwriting and slow writing speed in first grade. Plain-Language Summary: Children's visual–perceptual and motor skills and behavioral traits in kindergarten can predict their Chinese handwriting legibility and speed in first grade. This study found that kindergarteners who performed poorly in spatial relationships, VMI, manual dexterity, and attention were likely to have less legible Chinese handwriting and slow writing speed in the first grade. This study found that kindergarteners who performed poorly in spatial relationships, visual–motor Integration, manual dexterity, and attention were likely to have less legible Chinese handwriting and slow writing speed in the first grade. [ABSTRACT FROM AUTHOR]

Background: Limited efficacy has been observed when using opioids to treat neuropathic pain. Lidocaine patches reduce neuropathic pain in postherpetic neuralgia, but their benefits for cancer-related neuropathic pain remain unclear. This study aimed to investigate a treatment for cancer-related neuropathic pain. Methods: We conducted a prospective, open-label, single-arm study to assess the efficacy and safety of lidocaine transdermal patches in patients experiencing localized, superficial, neuropathic cancer pain. Terminal cancer patients already receiving opioid treatment participated in the 3-day study. The primary endpoint was pain intensity evaluated by the numerical rating scale (NRS). The secondary endpoints were the pain relief score and the quality of analgesic treatment. Results: The results showed a significant difference in the median NRS over 3 days (Kruskal–Wallis test, p < 0.0001). The median NRS pain intensity from Day 1 to Day 3 was 4.0 with 95% C.I. (3.3, 5.0), 3.0 (2.5, 3.5), and 2.6 (2.0, 3.0), respectively. The difference between the median NRS pain intensities of any 2 days was significant (Wilcoxon signed-rank test, p < 0.0001). The generalized estimating equation (GEE) estimation model showed significant differences between the NRS pain intensities on any 2 days. There was no significant difference in the pain relief score or the quality of analgesic treatment. Conclusions: In this study, the 5% lidocaine transdermal patch reduced the NRS pain intensity in neuropathic cancer patients already receiving opioid treatment. Treatment of localized and superficial neuropathic pain caused by cancer was well tolerated and effective. [ABSTRACT FROM AUTHOR]

In long‐term clinical studies, recurrent event data are sometimes collected and used to contrast the efficacies of two different treatments. The event reoccurrence rates can be compared using the popular negative binomial model, which incorporates information related to patient heterogeneity into a data analysis. For treatment allocation, a balanced approach in which equal sample sizes are obtained for both treatments is predominately adopted. However, if one treatment is superior, then it may be desirable to allocate fewer subjects to the less‐effective treatment. To accommodate this objective, a sequential response‐adaptive treatment allocation procedure is derived based on the doubly adaptive biased coin design. Our proposed treatment allocation schemes have been shown to be capable of reducing the number of subjects receiving the inferior treatment while simultaneously retaining a test power level that is comparable to that of a balanced design. The redesign of a clinical study illustrates the advantages of using our procedure. [ABSTRACT FROM AUTHOR]

Determination of an adequate sample size is critical to the design of research ventures. For clustered right-censored data, Manatunga and Chen [Sample size estimation for survival outcomes in cluster-randomized studies with small cluster sizes. Biometrics. 2000;56(2):616–621] proposed a sample size calculation based on considering the bivariate marginal distribution as Clayton copula model. In addition to the Clayton copula, other important family of copulas, such as Gumbel and Frank copulas are also well established in multivariate survival analysis. However, sample size calculation based on these assumptions has not been fully investigated yet. To broaden the scope of Manatunga and Chen [Sample size estimation for survival outcomes in cluster-randomized studies with small cluster sizes. Biometrics. 2000;56(2):616–621]'s research and achieve a more flexible sample size calculation for clustered right-censored data, we extended the work by assuming the marginal distribution as bivariate Gumbel and Frank copulas. We evaluate the performance of the proposed method and investigate the impacts of the accrual times, follow-up times and the within-clustered correlation effect of the study. The proposed method is applied to two real-world studies, and the R code is made available to users. [ABSTRACT FROM PUBLISHER]

The Shewhart-type control chart is traditionally developed under the normality assumption. In practice, however, this assumption may not hold. Because the skew normal distribution represents a broad distribution class and is more flexible than is the normal distribution, we propose two new control charts to monitor process mean and spread for skew normal distributed data. Moreover, to facilitate practical implementation, tables of charting constants are provided. We conducted simulation studies to compare the false alarm rates, and the results show that new proposed charts perform better than others as skewness increases. Finally, an illustrative example is provided. [ABSTRACT FROM PUBLISHER]