Indiana University-Purdue University Indianapolis (IUPUI) / The “total-etch” or “etch-and-rinse” systems have been the gold standard of dental bonding for decades. However, these systems are very technique-sensitive and time-consuming compared to newer “self-etch” or “self-adhesive” systems and have been implicated in cases of postoperative sensitivity. The purpose of this study was to compare the effects of two surface treatment protocols (self-etch vs. selective-etch) on the clinical performance of a universal adhesive and resin composite in Class V non-carious cervical lesions (NCCLs). Thirty-three volunteer subjects (17 male; 16 female; age range = 20 to 75 years) having at least two NCCLs were selected from patients of record at Indiana University School of Dentistry. Each subject received one resin composite restoration (Tetric EvoCeram, Ivoclar Vivadent) utilizing a self-etch (SfE) universal adhesive (Adhese Universal, Ivoclar Vivadent) with no separate enamel etching and another restoration utilizing adhesive and selective enamel etching (SelE) with 37% phosphoric acid (H3PO4). Both the adhesive and composite were placed following the manufacturer’s instructions. The two techniques were compared for differences in sensitivity, retention, marginal discoloration, marginal adaptation, and clinical acceptability at baseline and 6 months using the Cochran-Mantel-Haenszel tests for stratified, ordered categorical outcomes. Seventy-four restorations (37 SfE, 37 SelE) in 30 volunteers were evaluated at 12 months. No significant differences were found between the SfE and SelE groups for any variable at the 12-month recall (p>0.21). Retention was 100% at 12 months for both groups. Marginal adaptation was significantly worse at 12 months than at baseline for SelE (p=0.0163), but there was no difference for SfE (p=0.08). Sensitivity improved significantly from baseline to 12 months for both SelE (p=0.0113) and SfE (p=0.0128). The results obtained from this study are comparable to results observed in similar studies. Like similar studies involving self-etch adhesives in non-carious cervical lesions, our study showed no restorations lost to caries and excellent retention. The deterioration of selective-etch dentin margins was a result that differed from similar studies. A likely explanation for this finding would be the difficulty of controlling precise placement of phosphoric acid gel, causing undesired etching of dentin; this could result in suboptimal bonding to dentin. This report on 12-month data for a two-year study indicates significantly reduced sensitivity for both the SelE and SfE groups, and deterioration of SelE marginal adaptation. No decreases in retention, marginal discoloration, or clinical acceptability were observed in either group.

Indiana University-Purdue University Indianapolis (IUPUI) / The marker strategy design (MSGD) has been proposed to assess and validate predictive markers for targeted therapies and immunotherapies. Under this design, patients are randomized into two strategies: the marker-based strategy, which treats patients based on their marker status, and the non-marker-based strategy, which randomizes patients into treatments independent of their marker status in the same way as in a standard randomized clinical trial. The strategy effect is then tested by comparing the response rate between the two strategies and this strategy effect is commonly used to evaluate the predictive capability of the markers. We show that this commonly used between-strategy test is flawed, which may cause investigators to miss the opportunity to discover important predictive markers or falsely claim an irrelevant marker as predictive. Then we propose new procedures to improve the power of the MSGD to detect the predictive marker effect. One is based on a binary response endpoint; the second is based on survival endpoints. We conduct simulation studies to compare the performance of the MSGD with the widely used marker stratified design (MSFD). Numerical studies show that the MSGD and MSFD has comparable performance. Hence, contrary to popular belief that the MSGD is an inferior design compared with the MSFD, we conclude that using the MSGD with the proposed tests is an efficient and ethical way to find predictive markers for targeted therapies.

No description available.

This study evaluated the efficacy of the From Survivor to Thriver program, an interactive, online therapist-facilitated cognitive-behavioral program for rape-related PTSD. Eighty-seven college women with rape-related PTSD were randomized to complete the interactive program (n = 46) or a psycho-educational self-help website (n = 41). Both programs led to large reductions in interview-assessed PTSD at post-treatment (interactive d = 2.22, psycho-educational d = 1.10), which were maintained at three month follow-up. Both also led to medium- to large-sized reductions in self-reported depressive and general anxiety symptoms. Follow-up analyses supported that the therapist-facilitated interactive program led to superior outcomes among those with higher pre-treatment PTSD whereas the psycho-educational self-help website led to superior outcomes for individuals with lower pre-treatment PTSD. Future research should examine the efficacy and effectiveness of online interventions for rape-related PTSD including whether treatment intensity matching could be utilized to maximize outcomes and therapist resource efficiency.

Background and objectives: Prediction models are useful tools in clinical practise by providing predictive estimates of outcome probabilities to aid in decision making. As biomedical research advances, concerns have been raised regarding combined effectiveness (benefit) and safety (harm) outcomes in a prediction model, while typically different prediction models only focus on predictions of separate outcomes. A second issue is that, evidence also reveals poor predictive accuracy in different populations and settings for some prediction models, requiring model calibration or redevelopment. A third issue in data analyses is whether the treatment effect estimates could be influenced by competing risk bias. If other events preclude the outcomes of interest, these events would compete with the outcomes and thus fundamentally change the probability of the outcomes of interest. Failure to recognize the existence of competing risk or to account for it may result in misleading conclusions in health research. Therefore in this thesis, we explored three methodological issues in prediction models and data analyses by: (1) developing and externally validating a prediction model for patients’ individual combined benefit and harm outcomes (stroke with no major bleeding, major bleeding with no stroke, neither event, or both stroke and major bleeding) with and without warfarin therapy for atrial fibrillation; (2) constructing a prediction model for hospital mortality in medical-surgical critically ill patients; and (3) performing a competing risk analysis to assess the efficacy of the low molecular weight heparin dalteparin versus unfractionated heparin in venous thromboembolism in medical-surgical critically ill patients. Methods: Project 1: Using the Kaiser Permanente Colorado (KPCO) anticoagulation management cohort in the Denver-Boulder metropolitan area of Colorado in the United States to include patients with AF who were and were not prescribed warfarin therapy, we used a new approach to build a prediction model of individual combined benefit and harm outcomes related to warfarin therapy (stroke with no major bleeding, major bleeding with no stroke, neither event, or both stroke and major bleeding) in patients with AF. We utilized a polytomous logistic regression (PLR) model to identify risk factors and then construct the new prediction model. Model performances and validation were evaluated systematically in the study. Project 2: We used data from a multicenter randomized controlled trial named Prophylaxis for Thromboembolism in Critical Care Trial (PROTECT) to develop a new prediction model for hospital mortality in critically ill medical-surgical patients receiving heparin thromboprophylaxis. We first identified risk factors independent of APACHE (Acute Physiology and Chronic Health Evaluation) II score for hospital mortality, and then combined the identified risk factors and APACHE II score to build the new prediction model. Model performances were compared between the new prediction model and the APACHE II score. Project 3: We re-analyzed the data from PROTECT to perform a sensitivity analysis based on a competing risk analysis to investigate the efficacy of dalteparin versus unfractionated heparin in preventing venous thromboembolism in medical-surgical critically ill patients, taking all-cause death as a competing risk for venous thromboembolism. Results from the competing risk analysis were compared with findings from the cause-specific analysis. Results and Conclusions: Project 1: The PLR model could simultaneously predict risk of individual combined benefit and harm outcomes in patients with and without warfarin therapy for AF. The prediction model was a good fit, had acceptable discrimination and calibration, and was internally and externally validated. Should this approach be validated in other patient populations, it has potential advantages over existing risk stratification approaches. Project 2: The new model combining other risk factors and APACHE II score was a good fit, well calibrated and internally validated. However, the discriminative ability of the prediction model was not satisfactory. Compared with the APACHE II score alone, the new prediction model increased data collection, was more complex but did not substantially improve discriminative ability. Project 3: The competing risk analysis yielded no significant effect of dalteparin compared with unfractionated heparin on proximal leg deep vein thromboses, but a lower risk of pulmonary embolism in critically ill medical-surgical patients. Findings from the competing risk analysis were similar to results from the cause-specific analysis. / Thesis / Doctor of Philosophy (PhD)

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No description available.

No description available.

The analgesic effect of 600 mg and 1500 mg of a pain killing drug to metastatic bone pain, and associated side effects, were assessed. The experimental design was a double-blind cross over clinical trial involving 44 patients known to suffer from metastatic bone pain. Each patient received the active drug in one of two dosages and the placebo in a random order, each lasting about 14 consecutive days. The data consisted of daily measurements of several pain and side effect variables. A few covariates were available. It was found that the patient and the investigator achieved a high degree of agreement on the blinded preference of the active drug to the placebo. A multivariate analysis of variance (MANOVA) on three different summary scores (mean, median, trmean) calculated on the daily measurements for which the patient received the active drug and on those for which the patient received the placebo was conducted. It was found that for the group of pain variables the order of application and the treatment do not have a significant effect marginally, but that they interact significantly. Variation between subjects was also significant. For the group of side effect variables, however, only significant variation between subjects was found. This suggests that the drug does not have noticeable overall side effects. To account for correlations among the response measurements within each patient, the methodology of generalized estimating equations was used to assess the significance of the effects of the predictors. Although the results are less reliable as they depend on the asymptotic behaviour of statistics, it was found that regardless of the level of correlation within patient response measurements, only the interaction of order of application with treatment has a significant effect on each of the pain variables. All the statistical analyses were carried out using Minitab, SAS, Matlab and Splus. / Thesis / Master of Science (MS)

In active controlled clinical trials a possible objective is to test a non-inferiority hypothesis that the experimental treatment is therapeutically not inferior to the active control within a pre-defined margin. At the design stage, the misspecification of any design parameters (e.g., the variance or treatment difference for continuous endpoints, control event rate or non-inferiority margin for binary endpoints) can lead to study power below the desired level. Sample size re-estimation (SSR) procedures protect study power by allowing sample size re-estimation based on an interim analysis using revised estimates of the design parameters. For continuous endpoints, current approaches to SSR for non-inferiority trials focus on updating the sample size based solely on the estimated variance (blinded or unblinded) at the interim. The SSR using both sample variance and the observed treatment difference at interim in conditional power calculations is used in superiority trials. We have extended the methodology to non-inferiority trials, quantified the effect on the type I error rate, and proposed controlling it by modifying the critical value and/or stopping the trial at the interim for futility. For binary endpoints, current approaches to SSR for non-inferiority trials focus on estimating the event rates (blinded or unblinded) at the interim and update the sample size solely on the estimated event rates at the interim without updating the non-inferiority margin. A procedure that adapts both the absolute non-inferiority margin, and sample size based on the underlying interim observed pooled (blinded) event rate, and updates non-inferiority margin again at the final analysis based on the observed estimate of the event rate in control group at the end of the study is proposed. Our simulation results show the proposed adaptive procedures for extending a study by adding sample size, if necessary, preserve the overall type I error rate and maintain desired power. Combining sample size re-estimation methods with early stopping rules for continuous endpoints and adapting non-inferiority margins for binary endpoints could increase study flexibility, scope, and efficiency of non-inferiority trials. The proposed methodologies can be used for designing efficient two-stage non-inferiority trials with sample size re-estimation in active controlled non-inferiority clinical trials.