Fuentes documentales y recursos docentes en Odontopediatría y Ortodoncia

214 p. : il. ; 24 c

A Bayesian Adaptive Design in Cancer Phase I Trials Using Dose Combinations with Ordinal Toxicity Grades

We propose a Bayesian adaptive design for early phase drug combination cancer trials incorporating ordinal grade of toxicities. Parametric models are used to describe the relationship between the dose combinations and the probabilities of the ordinal toxicities under the proportional odds assumption. Trial design proceeds by treating cohorts of two patients simultaneously receiving different dose combinations. Specifically, at each stage of the trial, we seek the dose of one agent by minimizing the Bayes risk with respect to a loss function given the current dose of the other agent. We consider two types of loss functions corresponding to the Continual Reassessment Method (CRM) and Escalation with Overdose Control (EWOC). At the end of the trial, we estimate the MTD curve as a function of Bayes estimates of the model parameters. We evaluate design operating characteristics in terms of safety of the trial and percent of dose recommendation at dose combination neighborhoods around the true MTD by comparing this design to the one that uses a binary indicator of DLT. The methodology is further adapted to the case of a pre-specified discrete set of dose combinations

Licitações e compras públicas de alimentos numa perspectiva da nova economia institucional

Este trabalho teve como objetivo analisar alguns aspectos da Lei nº 8.666/93, referente às licitações e compras de alimentos pela Prefeitura Municipal de Toledo – PR, a partir de pressupostos da Nova Economia Institucional (NEI) e dos Custos de Transação (CT). À guisa do referencial teórico supracitado, evidenciou-se diversos conceitos relativos a NEI e dos CT inseridos na abordagem da Lei 8.666/93, a qual se refere à aquisição de bens por parte de órgãos públicos e que rege a compra de merenda escolar de Toledo – PR. Constatou-se haver diversas associações entre o processo de licitação, compras públicas, NEI e CT, porquanto a existência de regras para estabelecerem condutas para a execução de transações faz com que ocorram características de assimetria de informações, incertezas, racionalidade limitada, especificidade de ativos, entre outro

Characterizing Dirichlet priors

The selection of prior distributions is a problem that has been heavily discussed since Bayes and Price published their article in 1763. Conjugate priors became popular, largely because of their mathematical convenience. In this study, we justify the use of the conjugate combination of a Dirichlet prior and a multinomial likelihood by imposing a fundamental principle that we call partition invariance, alongside other requirements that are well known in the literature

Visualizing adverse events in clinical trials using correspondence analysis with R-package visae

Abstract Background Graphical displays and data visualization are essential components of statistical analysis that can lead to improved understanding of clinical trial adverse event (AE) data. Correspondence analysis (CA) has been introduced decades ago as a multivariate technique that can communicate AE contingency tables using two-dimensional plots, while quantifying the loss of information as other dimension reduction techniques such as principal components and factor analysis. Methods We propose the application of stacked CA using contribution biplots as a tool to explore differences in AE data among treatments in clinical trials. We defined five levels of refinement for the analysis based on data derived from the Common Terminology Criteria for Adverse Events (CTCAE) grades, domains, terms and their combinations. In addition, we developed a Shiny app built in an R-package, visae, publicly available on Comprehensive R Archive Network (CRAN), to interactively investigate CA configurations based on the contribution to the explained variance and relative frequency of AEs. Data from two randomized controlled trials (RCT) were used to illustrate the proposed methods: NSABP R-04, a neoadjuvant rectal 2 × 2 factorial trial comparing radiation therapy with either capecitabine (Cape) or 5-fluorouracil (5-FU) alone with or without oxaliplatin (Oxa), and NSABP B-35, a double-blind RCT comparing tamoxifen to anastrozole in postmenopausal women with hormone-positive ductal carcinoma in situ. Results In the R04 trial (n = 1308), CA biplots displayed the discrepancies between single agent treatments and their combinations with Oxa at all levels of AE classes, such that these discrepancies were responsible for the largest portion of the explained variability among treatments. In addition, an interaction effect when adding Oxa to Cape/5-FU was identified when the distance between Cape+Oxa and 5-FU + Oxa was observed to be larger than the distance between 5-FU and Cape, with Cape+Oxa and 5-FU + Oxa in different quadrants of the CA biplots. In the B35 trial (n = 3009), CA biplots showed different patterns for non-adherent Anastrozole and Tamoxifen compared with their adherent counterparts. Conclusion CA with contribution biplot is an effective tool that can be used to summarize AE data in a two-dimensional display while minimizing the loss of information and interpretation.http://deepblue.lib.umich.edu/bitstream/2027.42/173584/1/12874_2021_Article_1368.pd

Simulation study comparing analytical methods for single-item longitudinal patient-reported outcomes data

PurposeEfficient analytical methods are necessary to make reproducible inferences on single-item longitudinal ordinal patient-reported outcome (PRO) data. A thorough simulation study was performed to compare the performance of the semiparametric probabilistic index models (PIM) with a longitudinal analysis using parametric cumulative logit mixed models (CLMM).MethodsIn the setting of a control and intervention arm, we compared the power of the PIM and CLMM to detect differences in PRO adverse event (AE) between these groups using several existing and novel summary scores of PROs. For each scenario, PRO data were simulated using copula multinomial models. Comparisons were also exemplified using clinical trial data.ResultsOn average, CLMM provided substantially greater power than the PIM to detect differences in PRO-AEs between the groups when the baseline-adjusted method was used, and a small advantage in power when using the baseline symptom as a covariate.ConclusionAlthough the CLMM showed the best performance among analytical methods, it relies on assumptions difficult to verify and that might not be fulfilled in the real world, therefore our recommendation is the use of PIM models with baseline symptom as a covariate

Clinical and Psychosocial Impact of Communication about Oral Potentially Malignant Disorders: A Scoping Review

Delivering bad news has been widely studied in cancer, thus, this scoping review aims to identify the available evidence concerning the communication of oral potentially malignant disorders (OPMDs) and their clinical and psychosocial impacts. A search was performed using electronic databases (Medline/PubMed, Scopus, Embase, and Web of Science) and one grey literature database (Google Scholar). Studies focused on communicating the diagnosis of OPMDs and the patients’ perceptions were included. Study selection and data extraction were performed by two authors in a two-phase process. Five publications were included in the qualitative analysis. Differences regarding the study design, population, OPMDs assessed, and outcomes of professional–patient communication were found in each study. Protocols for OPMD communication have not yet been reported and there is a need to standardize strategies as communication skills may provide better clinical outcomes for patients diagnosed with potentially malignant disorders. Although future studies are needed, a brief list recommending the aspects that must be communicated is proposed

Evaluating Treatment Tolerability in Cancer Clinical Trials Using the Toxicity Index.

BackgroundThe National Cancer Institute Moonshot research initiative calls for improvements in the analysis and reporting of treatment toxicity to advise key stakeholders on treatment tolerability and inform regulatory and clinical decision making. This study illustrates alternative approaches to toxicity evaluation using the National Surgical Adjuvant Breast and Bowel Project R-04 clinical trial as an example.MethodsNational Surgical Adjuvant Breast and Bowel Project R-04 was a neoadjuvant chemoradiation trial in stage II-III rectal cancer patients. A 2 x 2 factorial design was used to evaluate whether the addition of oxaliplatin (Oxa) to 5-fluorouracil (5FU) or capecitabine (Cape) with radiation therapy improved local-regional tumor control. The toxicity index (TI), which accounts for the frequency and severity of toxicities, was compared across treatments using multivariable probabilistic index models, where Pr A < B indicates the probability that higher values of TI were observed for A when compared with B. Baseline age, sex, performance status, body mass index, surgery type, and stage were evaluated as independent risk factors.ResultsA total of 4560 toxicities from 1558 patients were analyzed. Results from adjusted probabilistic index models indicate that oxaliplatin-containing regimens had statistically significant (P < .001) probability (Pr) for higher TI compared with regimens without oxaliplatin (Pr 5FU < 5FU + Oxa = 0.619, 95% confidence interval [CI] = 0.560 to 0.674; Pr 5FU < Cape + Oxa = 0.627, 95% CI = 0.568 to 0.682; Pr Cape < 5FU + Oxa = 0.587, 95% 0.527 to 0.644; and Pr Cape < Cape + Oxa = 0.596, 95% 0.536 to 0.653). When compared with other existing toxicity analysis methods, TI provided greater power to detect differences between treatments.ConclusionsThis article uses standard data collected in a cancer clinical trial to introduce descriptive and analytic methods that account for the additional burden of multiple toxicities. These methods may provide a more accurate description of a patient's treatment experience that could lead to individualized dosing for better toxicity control. Future research will evaluate the generalizability of these findings in trials with similar drugs

Dynamic Risk Prediction of Treatment Discontinuation Using Patient-Reported Outcomes Data in the Phase III NSABP B-35 Trial.

Predicting an individual's risk of treatment discontinuation is critical for the implementation of precision chemoprevention. We developed partly conditional survival models to predict discontinuation of tamoxifen or anastrozole using patient-reported outcome (PRO) data from postmenopausal women with ductal carcinoma in situ (DCIS) enrolled in the NSABP B-35 clinical trial. In a secondary analysis of the NSABP B-35 clinical trial PRO data, we proposed two models for treatment discontinuation within each treatment arm (anastrozole or tamoxifen treated patients) using partly conditional Cox-type models with time-dependent covariates. A 70/30 split of the sample was used for the training and validation datasets. The predictive performance of the models was evaluated using calibration and discrimination measures based on the Brier score and area under the curve (AUC) from time-dependent receiver operating characteristics curves. The predictive models stratified high-risk versus low-risk early discontinuation at a 6-month horizon. For anastrozole-treated patients, predictive factors included baseline body mass index (BMI) and longitudinal patient-reported symptoms such as insomnia, joint pain, hot flashes, headaches, gynecologic symptoms, and vaginal discharge, all collected up to 12 months (Brier score 0.039, AUC 0.76, 95%CI 0.57-0.95). As for tamoxifen-treated patients, predictive factors included baseline BMI, and time-dependent covariates: cognitive problems, feelings of happiness, calmness, weight problems, and pain (Brier score 0.032, AUC 0.78, 95%CI 0.65-0.91). A real-time calculator based on these models was developed in Shiny to create a web-based application with a future goal to aid healthcare professionals in decision-making