This paper investigates the occurrence of severe oral mucositis and associated factors in blood and solid cancer pediatric patients subjected to cancer treatment, using a survival analysis. A longitudinal, descriptive, observational and inductive study of 142 pediatric patients aged from 0 to 19 years was conducted from 2013 to 2017. Data were collected using a form to record the sociodemographic characteristics and health-related aspects of patients and the modified Oral Assessment Guide (OAG). Survival analysis was performed using the Kaplan–Meier method and Cox semiparametric model. The median times to occurrence of severe oral mucositis were 35.3 and 77.1 days for patients with hematologic malignancies and solid tumors, respectively. The Cox model showed that white cell changes and platelet counts as well as the use of natural chemotherapeutic agents are risk factors for the occurrence of oral mucositis among patients with hematologic malignancies. Nonetheless, among patients with solid tumors, the occurrence of oral mucositis was associated with female sex, mixed ethnicity, the presence of metastasis, abnormal creatinine levels, a combination of chemotherapy, radiotherapy, and surgery, and the administration of chemotherapeutic agents included in the miscellaneous group. The time to occurrence of severe oral mucositis and its associated factors varied according to cancer type.

No abstract

This study aimed to investigate the contribution of motor changes to oral mucositis in children and adolescents with cancer undergoing antineoplastic treatment in a referral hospital. This was an observational, cross-sectional study with 70 patients aged 2 to 19 years, diagnosed with any type of cancer and treated in a pediatric hospital cancer ward from April to September 2017. A questionnaire related to the patients’ socioeconomic and clinical conditions was used, followed by the Oral Assessment Guide and selected domains of the activity and participation section of the International Classification of Functioning, Disability, and Health tool. The data were collected by previously calibrated examiners (kappa index > 0.75) and analyzed using descriptive statistics and logistic regression (α = 5%). Children and adolescents aged 7 to 10 years were more likely to develop oral mucositis (OR: 3.62). In addition, individuals who had severe difficulty in maintaining a body position (OR: 14.45) and walking (OR: 25.42), and those diagnosed with hematologic cancers (OR: 6.40) were more likely to develop oral mucositis during antineoplastic treatment. Within the limitations of this study, it is concluded that motor changes may contribute to the occurrence of oral mucositis in pediatric cancer patients.

This paper provides a general framework for controlling quality characteristics related to control variables and limited to the intervals (0, 1], [0, 1), or [0, 1]. The proposed control chart is based on the inflated beta regression model considering a reparametrization of the inflated beta distribution indexed by the response mean, which is useful for modeling fractions and proportions. The contribution of the paper is twofold. First, we extend the inflated beta regression model by allowing a regression structure for the precision parameter. We also present closed-form expressions for the score vector and Fisher’s information matrix. Second, based on the proposed regression model, we introduce a new model-based control chart. The control limits are obtained considering the estimates of the inflated beta regression model parameters. We conduct a Monte Carlo simulation study to evaluate the performance of the proposed regression model estimators, and the performance of the proposed control chart is evaluated in terms of run length distribution. Finally, we present and discuss an empirical application to show the applicability of the proposed regression control chart.

No abstract

In many practical situations, the quality characteristics of interest assume values in the range (0,1), like rates and proportions (but they are not results from Bernoulli experiments). Most control charts built for these quality characteristics rely on monitoring parameters of their probability distribution functions or on their averages after some reparameterization of their density probability function. However, for highly asymmetric distributions, the median is a more appropriate location parameter than the average. In this paper, we propose Shewhart-type control charts for monitoring the median of observations taken from quality characteristics double bounded after reparameterization of two probability density functions: Kumaraswamy and unit Weibull. The performance of the control charts is evaluated and compared in terms of run length (RL) analysis considering three estimators for the median. Finally, we also carry out two applications to demonstrate the applicability of these control charts.

This paper proposes a new Shewhart‐type control chart for circular or directional data. This type of data is found in several fields and applications, such as wind direction, the arrival time of a patient in a hospital, and the route of animals. The proposal is based on the Jones–Pewsey distribution, which is a very flexible three‐parameter distribution for modeling processes that can be represented as points on the circumference of the unit circle. We conduct an extensive Monte Carlo simulation study to evaluate and compare the performance of the proposed control chart with some competitors considering individual measurements and the mean direction (nonindividual observations). The results show that the Jones–Pewsey control chart outperforms the competitors in terms of run length distribution analysis. Finally, we present and discuss two applications based on actual datasets to show the applicability of the proposed control chart.

This paper proposes a control chart useful for detecting small shifts in the mean of a double‐bounded process, such as fractions and proportions, in the presence of control variables. For this purpose, we consider the cumulative sum (CUSUM) control chart applied to different residuals of the beta regression model. We conduct an extensive Monte Carlo simulation study to evaluate and compare the performance of the proposed control chart with two other control charts in the literature in terms of run length analysis. The numerical results show that the proposed control chart is more sensitive to detect changes in the process than its competitors and that the quantile residual is the most suitable residual to be used in our proposal. Finally, based on the quantile residual, we present and discuss applications to real and simulated data to show the applicability of the proposed control chart.