The effects of erythritol air-polishing powder on microbiologic and clinical outcomes during supportive periodontal therapy: Six-month results of a randomized controlled clinical trial.

OBJECTIVES To characterize the physical characteristics of a new low abrasive erythritol powder (EPAP) and to evaluate its influence on the clinical and microbiologic parameters over a period of 6 months in patients undergoing supportive periodontal therapy (SPT). METHOD AND MATERIALS Prior to the clinical application, the particle size and abrasion level of EPAP were compared to glycine air-polishing powder (GPAP) ex vivo. Subsequently, 40 chronic periodontitis patients previously enrolled in SPT were randomly assigned into two groups for the treatment with subgingival EPAP or repeated scaling and root planing (SRP). At baseline (BL), bleeding on probing positive (BOP+) sites with probing pocket depth (PPD) of ≥ 4 mm but no detectable calculus were defined as study sites. During SPT, these sites were either treated by EPAP or SRP at BL, 3, and 6 months (3M, 6M). When indicated, additional SRP was provided. Plaque Index, BOP, PPD, clinical attachment level (CAL), and subgingival plaque were evaluated at BL and 6M. RESULTS EPAP yielded lower abrasiveness and smaller particle sizes when compared to GPAP. In 38 patients completing the study, EPAP and SRP resulted in significant reductions of BOP% (EPAP, 40.45%; SRP, 42.53%), PPD (EPAP, -0.67; SRP, -0.68), and increase of CAL (EPAP, 0.48; SRP, 0.61) while at 6M no statistically significant between-group differences were observed (P > .05). Microbiologic evaluation revealed minor shifts in the composition of the subgingival biofilm without influence on periodontopathogenic bacteria. CONCLUSION The subgingival use of EPAP by means of an air-polishing device may be considered safe and may lead to comparable clinical and microbiologic outcomes to those obtained with SRP. CLINICAL RELEVANCE The subgingival use of EPAP appears to represent a promising modality for the removal of subgingival biofilm during SPT.

Clinical Validation of a Peritoneal Dialysis Prescription Model in the PatientOnLine Software

Peritoneal transport characteristics and residual renal function require regular control and subsequent adjustment of the peritoneal dialysis (PD) prescription. Prescription models shall facilitate the prediction of the outcome of such adaptations for a given patient. In the present study, the prescription model implemented in the PatientOnLine software was validated in patients requiring a prescription change. This multicenter, international prospective cohort study with the aim to validate a PD prescription model included patients treated with continuous ambulatory peritoneal dialysis. Patients were examined with the peritoneal function test (PFT) to determine the outcome of their current prescription and the necessity for a prescription change. For these patients, a new prescription was modeled using the PatientOnLine software (Fresenius Medical Care, Bad Homburg, Germany). Two to four weeks after implementation of the new PD regimen, a second PFT was performed. The validation of the prescription model included 54 patients. Predicted and measured peritoneal Kt/V were 1.52 ± 0.31 and 1.66 ± 0.35, and total (peritoneal + renal) Kt/V values were 1.96 ± 0.48 and 2.06 ± 0.44, respectively. Predicted and measured peritoneal creatinine clearances were 42.9 ± 8.6 and 43.0 ± 8.8 L/1.73 m2/week and total creatinine clearances were 65.3 ± 26.0 and 63.3 ± 21.8 L/1.73 m2/week, respectively. The analysis revealed a Pearson's correlation coefficient for peritoneal Kt/V of 0.911 and Lin's concordance coefficient of 0.829. The value of both coefficients was 0.853 for peritoneal creatinine clearance. Predicted and measured daily net ultrafiltration was 0.77 ± 0.49 and 1.16 ± 0.63 L/24 h, respectively. Pearson's correlation and Lin's concordance coefficient were 0.518 and 0.402, respectively. Predicted and measured peritoneal glucose absorption was 125.8 ± 38.8 and 79.9 ± 30.7 g/24 h, respectively, and Pearson's correlation and Lin's concordance coefficient were 0.914 and 0.477, respectively. With good predictability of peritoneal Kt/V and creatinine clearance, the present model provides support for individual dialysis prescription in clinical practice. Peritoneal glucose absorption and ultrafiltration are less predictable and are likely to be influenced by additional clinical factors to be taken into consideration.

Performance of gene-expression profiling test score variability to predict future clinical events in heart transplant recipients.

BACKGROUND A single non-invasive gene expression profiling (GEP) test (AlloMap®) is often used to discriminate if a heart transplant recipient is at a low risk of acute cellular rejection at time of testing. In a randomized trial, use of the test (a GEP score from 0-40) has been shown to be non-inferior to a routine endomyocardial biopsy for surveillance after heart transplantation in selected low-risk patients with respect to clinical outcomes. Recently, it was suggested that the within-patient variability of consecutive GEP scores may be used to independently predict future clinical events; however, future studies were recommended. Here we performed an analysis of an independent patient population to determine the prognostic utility of within-patient variability of GEP scores in predicting future clinical events. METHODS We defined the GEP score variability as the standard deviation of four GEP scores collected ≥315 days post-transplantation. Of the 737 patients from the Cardiac Allograft Rejection Gene Expression Observational (CARGO) II trial, 36 were assigned to the composite event group (death, re-transplantation or graft failure ≥315 days post-transplantation and within 3 years of the final GEP test) and 55 were assigned to the control group (non-event patients). In this case-controlled study, the performance of GEP score variability to predict future events was evaluated by the area under the receiver operator characteristics curve (AUC ROC). The negative predictive values (NPV) and positive predictive values (PPV) including 95 % confidence intervals (CI) of GEP score variability were calculated. RESULTS The estimated prevalence of events was 17 %. Events occurred at a median of 391 (inter-quartile range 376) days after the final GEP test. The GEP variability AUC ROC for the prediction of a composite event was 0.72 (95 % CI 0.6-0.8). The NPV for GEP score variability of 0.6 was 97 % (95 % CI 91.4-100.0); the PPV for GEP score variability of 1.5 was 35.4 % (95 % CI 13.5-75.8). CONCLUSION In heart transplant recipients, a GEP score variability may be used to predict the probability that a composite event will occur within 3 years after the last GEP score. TRIAL REGISTRATION Clinicaltrials.gov identifier NCT00761787.

Diffusion-weighted imaging in musculoskeletal radiology-clinical applications and future directions

Diffusion-weighted imaging (DWI) is an established diagnostic tool with regards to the central nervous system (CNS) and research into its application in the musculoskeletal system has been growing. It has been shown that DWI has utility in differentiating vertebral compression fractures from malignant ones, assessing partial and complete tears of the anterior cruciate ligament (ACL), monitoring tumor response to therapy, and characterization of soft-tissue and bone tumors. DWI is however less useful in differentiating malignant vs. infectious processes. As of yet, no definitive qualitative or quantitative properties have been established due to reasons ranging from variability in acquisition protocols to overlapping imaging characteristics. Even with these limitations, DWI can still provide clinically useful information, increasing diagnostic accuracy and improving patient management when magnetic resonance imaging (MRI) findings are inconclusive. The purpose of this article is to summarize recent research into DWI applications in the musculoskeletal system.

Anticoagulation Management Practices and Outcomes in Elderly Patients with Acute Venous Thromboembolism: A Clinical Research Study.

Whether anticoagulation management practices are associated with improved outcomes in elderly patients with acute venous thromboembolism (VTE) is uncertain. Thus, we aimed to examine whether practices recommended by the American College of Chest Physicians guidelines are associated with outcomes in elderly patients with VTE. We studied 991 patients aged ≥65 years with acute VTE in a Swiss prospective multicenter cohort study and assessed the adherence to four management practices: parenteral anticoagulation ≥5 days, INR ≥2.0 for ≥24 hours before stopping parenteral anticoagulation, early start with vitamin K antagonists (VKA) ≤24 hours of VTE diagnosis, and the use of low-molecular-weight heparin (LMWH) or fondaparinux. The outcomes were all-cause mortality, VTE recurrence, and major bleeding at 6 months, and the length of hospital stay (LOS). We used Cox regression and lognormal survival models, adjusting for patient characteristics. Overall, 9% of patients died, 3% had VTE recurrence, and 7% major bleeding. Early start with VKA was associated with a lower risk of major bleeding (adjusted hazard ratio 0.37, 95% CI 0.20-0.71). Early start with VKA (adjusted time ratio [TR] 0.77, 95% CI 0.69-0.86) and use of LMWH/fondaparinux (adjusted TR 0.87, 95% CI 0.78-0.97) were associated with a shorter LOS. An INR ≥2.0 for ≥24 hours before stopping parenteral anticoagulants was associated with a longer LOS (adjusted TR 1.2, 95% CI 1.08-1.33). In elderly patients with VTE, the adherence to recommended anticoagulation management practices showed mixed results. In conclusion, only early start with VKA and use of parenteral LMWH/fondaparinux were associated with better outcomes.

Early growth characteristics and the risk of reduced lung function and asthma: A meta-analysis of 25,000 children

BACKGROUND Children born preterm or with a small size for gestational age are at increased risk for childhood asthma. OBJECTIVE We sought to assess the hypothesis that these associations are explained by reduced airway patency. METHODS We used individual participant data of 24,938 children from 24 birth cohorts to examine and meta-analyze the associations of gestational age, size for gestational age, and infant weight gain with childhood lung function and asthma (age range, 3.9-19.1 years). Second, we explored whether these lung function outcomes mediated the associations of early growth characteristics with childhood asthma. RESULTS Children born with a younger gestational age had a lower FEV1, FEV1/forced vital capacity (FVC) ratio, and forced expiratory volume after exhaling 75% of vital capacity (FEF75), whereas those born with a smaller size for gestational age at birth had a lower FEV1 but higher FEV1/FVC ratio (P < .05). Greater infant weight gain was associated with higher FEV1 but lower FEV1/FVC ratio and FEF75 in childhood (P < .05). All associations were present across the full range and independent of other early-life growth characteristics. Preterm birth, low birth weight, and greater infant weight gain were associated with an increased risk of childhood asthma (pooled odds ratio, 1.34 [95% CI, 1.15-1.57], 1.32 [95% CI, 1.07-1.62], and 1.27 [95% CI, 1.21-1.34], respectively). Mediation analyses suggested that FEV1, FEV1/FVC ratio, and FEF75 might explain 7% (95% CI, 2% to 10%) to 45% (95% CI, 15% to 81%) of the associations between early growth characteristics and asthma. CONCLUSIONS Younger gestational age, smaller size for gestational age, and greater infant weight gain were across the full ranges associated with childhood lung function. These associations explain the risk of childhood asthma to a substantial extent.

Characteristics of Consecutive Esophageal Motility Diagnoses After a Decade of Change

BACKGROUND AND AIMS Combined multichannel intraluminal impedance and esophageal manometry (MII-EM) measures concomitantly bolus transit and pressure changes allowing determination of the functional impact of esophageal motility abnormalities. Ten years ago our laboratory reported MII-EM results in 350 consecutive patients. Since then high-resolution impedance manometry (HRIM) became available and the definitions of ineffective esophageal motility (IEM) and nutcracker esophagus were revised. The aim of this study was to assess the impact of these developments on esophageal function testing. METHODS From August 2012 through May 2013, HRIM was performed in 350 patients referred for esophageal function testing. Each patient received 10 liquid and 10 viscous swallows. While taking advantage of the new technology and revised criteria, HRIM findings were classified according to the conventional criteria to allow more appropriate comparison with our earlier analysis. RESULTS Compared with the study performed 10 years ago, the prevalence of normal manometry (36% vs. 35%), achalasia (7% vs. 8%), scleroderma (1% vs. 1%), hypertensive lower esophageal sphincter (LES) (7% vs. 7%), and hypotensive LES (1% vs. 2%) remained the same, whereas the prevalence of distal esophageal spasm (9% vs. 3%), nutcracker esophagus (9% vs. 3%), and poorly relaxing LES (10% vs. 3%) decreased and the prevalence of IEM increased (20% vs. 31%) significantly. Compared with the early study, normal liquid bolus transit was significantly different in patients with hypertensive LES (96% vs. 57%) and poorly relaxing LES (55% vs. 100%). CONCLUSIONS This study brings to light the increase in prevalence of IEM. In addition, it suggests that the hypertensive LES and poorly relaxing LES may each affect bolus transit in about half of these patients.

Comparing Psychological Type and Explanatory Between Nursing Students and Clinical Faculty: A Pilot Study

Negotiation of complex collaboration and effective teamwork among health care providers is essential to patient safety and to quality of care. This study examined characteristics of nursing students and faculty influencing communication between them. Psychological type (Myers-Briggs Type Inventory (MBTI) (Myers, McCaulley, Quenk, & Hammer, 1998) and explanatory style (Attributional Style Questionnaire) (ASQ) (Peterson et al., 1982) were compared for participating first year baccalaureate nursing students (N=286), and clinical nursing faculty (N=59) from both two- and four-year nursing programs. Modal student psychological type was ESFJ; modal faculty psychological type was ISTJ. The two groups demonstrated significant differences in processing information, and making decisions and judgments. Students were slightly more optimistic than faculty. Psychological type and level of optimism did not appear to correlate. Data from this pilot study provide an initial framework on which to base further research that could enhance the quality of teamwork among healthcare providers.

Continuous safety screens for randomized controlled clinical trials with blinded treatment information

Standard methods for testing safety data are needed to ensure the safe conduct of clinical trials. In particular, objective rules for reliably identifying unsafe treatments need to be put into place to help protect patients from unnecessary harm. DMCs are uniquely qualified to evaluate accumulating unblinded data and make recommendations about the continuing safe conduct of a trial. However, it is the trial leadership who must make the tough ethical decision about stopping a trial, and they could benefit from objective statistical rules that help them judge the strength of evidence contained in the blinded data. We design early stopping rules for harm that act as continuous safety screens for randomized controlled clinical trials with blinded treatment information, which could be used by anyone, including trial investigators (and trial leadership). A Bayesian framework, with emphasis on the likelihood function, is used to allow for continuous monitoring without adjusting for multiple comparisons. Close collaboration between the statistician and the clinical investigators will be needed in order to design safety screens with good operating characteristics. Though the math underlying this procedure may be computationally intensive, implementation of the statistical rules will be easy and the continuous screening provided will give suitably early warning when real problems were to emerge. Trial investigators and trial leadership need these safety screens to help them to effectively monitor the ongoing safe conduct of clinical trials with blinded data.^

Clinical and economic outcomes of serious postoperative infections following resection of common respiratory and gastrointestinal solid tumors

Unlike infections occurring during periods of chemotherapy-induced neutropenia, postoperative infections in patients with solid malignancy remain largely understudied. The purpose of this population-based study was to evaluate the clinical and economic burden, as well as the relationship of hospital surgical volume and outcomes associated with serious postoperative infection (SPI) – i.e., bacteremia/sepsis, pneumonia, and wound infection – following resection of common solid tumors.^ From the Texas Discharge Data Research File, we identified all Texas residents who underwent resection of cancer of the lung, esophagus, stomach, pancreas, colon, or rectum between 2002 and 2006. From their billing records, we identified ICD-9 codes indicating SPI and also subsequent SPI-related readmissions occurring within 30 days of surgery. Random-effects logistic regression was used to calculate the impact of SPI on mortality, as well as the association between surgical volume and SPI, adjusting for case-mix, hospital characteristics, and clustering of multiple surgical admissions within the same patient and patients within the same hospital. Excess bed days and costs were calculated by subtracting values for patients without infections from those with infections computed using multilevel mixed-effects generalized linear model by fitting a gamma distribution to the data using log link.^ Serious postoperative infection occurred following 9.4% of the 37,582 eligible tumor resections and was independently associated with an 11-fold increase in the odds of in-hospital mortality (95% Confidence Interval [95% CI], 6.7-18.5, P < 0.001). Patients with SPI required 6.3 additional hospital days (95% CI, 6.1 - 6.5) at an incremental cost of $16,396 (95% CI, $15,927–$16,875). There was a significant trend toward lower overall rates of SPI with higher surgical volume (P=0.037). ^ Due to the substantial morbidity, mortality, and excess costs associated with SPI following solid tumor resections and given that, under current reimbursement practices, most of this heavy burden is borne by acute care providers, it is imperative for hospitals to identify more effective prophylactic measures, so that these potentially preventable infections and their associated expenditures can be averted. Additional volume-outcomes research is also needed to identify infection prevention processes that can be transferred from higher- to lower-volume providers.^

Procedure for the identification of population characteristics for targeting intervention services on the basis of outcome-goal priorities: Case management services for the chronic mentally ill

Although the processes involved in rational patient targeting may be obvious for certain services, for others, both the appropriate sub-populations to receive services and the procedures to be used for their identification may be unclear. This project was designed to address several research questions which arise in the attempt to deliver appropriate services to specific populations. The related difficulties are particularly evident for those interventions about which findings regarding effectiveness are conflicting. When an intervention clearly is not beneficial (or is dangerous) to a large, diverse population, consensus regarding withholding the intervention from dissemination can easily be reached. When findings are ambiguous, however, conclusions may be impossible.^ When characteristics of patients likely to benefit from an intervention are not obvious, and when the intervention is not significantly invasive or dangerous, the strategy proposed herein may be used to identify specific characteristics of sub-populations which may benefit from the intervention. The identification of these populations may be used both in further informing decisions regarding distribution of the intervention and for purposes of planning implementation of the intervention by identifying specific target populations for service delivery.^ This project explores a method for identifying such sub-populations through the use of related datasets generated from clinical trials conducted to test the effectiveness of an intervention. The method is specified in detail and tested using the example intervention of case management for outpatient treatment of populations with chronic mental illness. These analyses were applied in order to identify any characteristics which distinguish specific sub-populations who are more likely to benefit from case management service, despite conflicting findings regarding its effectiveness for the aggregate population, as reported in the body of related research. However, in addition to a limited set of characteristics associated with benefit, the findings generated, a larger set of characteristics of patients likely to experience greater improvement without intervention. ^

Bayesian adaptive designs for drug combinations in early phase clinical trials

Treating patients with combined agents is a growing trend in cancer clinical trials. Evaluating the synergism of multiple drugs is often the primary motivation for such drug-combination studies. Focusing on the drug combination study in the early phase clinical trials, our research is composed of three parts: (1) We conduct a comprehensive comparison of four dose-finding designs in the two-dimensional toxicity probability space and propose using the Bayesian model averaging method to overcome the arbitrariness of the model specification and enhance the robustness of the design; (2) Motivated by a recent drug-combination trial at MD Anderson Cancer Center with a continuous-dose standard of care agent and a discrete-dose investigational agent, we propose a two-stage Bayesian adaptive dose-finding design based on an extended continual reassessment method; (3) By combining phase I and phase II clinical trials, we propose an extension of a single agent dose-finding design. We model the time-to-event toxicity and efficacy to direct dose finding in two-dimensional drug-combination studies. We conduct extensive simulation studies to examine the operating characteristics of the aforementioned designs and demonstrate the designs' good performances in various practical scenarios.^

Bayesian Adaptive Designs for Early Phase Clinical Trials

My dissertation focuses mainly on Bayesian adaptive designs for phase I and phase II clinical trials. It includes three specific topics: (1) proposing a novel two-dimensional dose-finding algorithm for biological agents, (2) developing Bayesian adaptive screening designs to provide more efficient and ethical clinical trials, and (3) incorporating missing late-onset responses to make an early stopping decision. Treating patients with novel biological agents is becoming a leading trend in oncology. Unlike cytotoxic agents, for which toxicity and efficacy monotonically increase with dose, biological agents may exhibit non-monotonic patterns in their dose-response relationships. Using a trial with two biological agents as an example, we propose a phase I/II trial design to identify the biologically optimal dose combination (BODC), which is defined as the dose combination of the two agents with the highest efficacy and tolerable toxicity. A change-point model is used to reflect the fact that the dose-toxicity surface of the combinational agents may plateau at higher dose levels, and a flexible logistic model is proposed to accommodate the possible non-monotonic pattern for the dose-efficacy relationship. During the trial, we continuously update the posterior estimates of toxicity and efficacy and assign patients to the most appropriate dose combination. We propose a novel dose-finding algorithm to encourage sufficient exploration of untried dose combinations in the two-dimensional space. Extensive simulation studies show that the proposed design has desirable operating characteristics in identifying the BODC under various patterns of dose-toxicity and dose-efficacy relationships. Trials of combination therapies for the treatment of cancer are playing an increasingly important role in the battle against this disease. To more efficiently handle the large number of combination therapies that must be tested, we propose a novel Bayesian phase II adaptive screening design to simultaneously select among possible treatment combinations involving multiple agents. Our design is based on formulating the selection procedure as a Bayesian hypothesis testing problem in which the superiority of each treatment combination is equated to a single hypothesis. During the trial conduct, we use the current values of the posterior probabilities of all hypotheses to adaptively allocate patients to treatment combinations. Simulation studies show that the proposed design substantially outperforms the conventional multi-arm balanced factorial trial design. The proposed design yields a significantly higher probability for selecting the best treatment while at the same time allocating substantially more patients to efficacious treatments. The proposed design is most appropriate for the trials combining multiple agents and screening out the efficacious combination to be further investigated. The proposed Bayesian adaptive phase II screening design substantially outperformed the conventional complete factorial design. Our design allocates more patients to better treatments while at the same time providing higher power to identify the best treatment at the end of the trial. Phase II trial studies usually are single-arm trials which are conducted to test the efficacy of experimental agents and decide whether agents are promising to be sent to phase III trials. Interim monitoring is employed to stop the trial early for futility to avoid assigning unacceptable number of patients to inferior treatments. We propose a Bayesian single-arm phase II design with continuous monitoring for estimating the response rate of the experimental drug. To address the issue of late-onset responses, we use a piece-wise exponential model to estimate the hazard function of time to response data and handle the missing responses using the multiple imputation approach. We evaluate the operating characteristics of the proposed method through extensive simulation studies. We show that the proposed method reduces the total length of the trial duration and yields desirable operating characteristics for different physician-specified lower bounds of response rate with different true response rates.

Association of ALLHAT investigator characteristics with participant recruitment

Clinical trials are often not successful because of the inability to recruit a sufficient number of patients. The Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT), the largest antihypertensive trial ever conducted, provided highly generalized results and successful recruitment of over 42,000 participants. The overall purpose of this study was to examine the association of investigator characteristics with anti-hypertensive (AHT) participant recruitment in ALLHAT. This secondary data analyses collected data from the ALLHAT investigator profile survey and related investigator characteristics to recruitment success. The sample size was 502 investigators, with recruitment data from 37,947AHT participants. Recruitment was dichotomized by categorizing all sites with recruitment numbers at or above the overall median recruitment number of 46 as "Successful Recruitment". Frequency distributions and univariate and multivariate logistic regression were conducted. When adjusting for all other factors, Hispanic ethnicity, suburban setting, Department of Veterans Affairs Medical Centers (VAMC) site type, number of clinical site staff working on the trial, study coordinator hours per week, medical conference sessions attended, the investigator's primary goal and the likelihood that a physician will convince a patient to continue on randomized treatment, have significant impacts on the recruitment success of ALLHAT investigators. Most of the ALLHAT investigators described their primary commitment as being towards their patients and not to scientific knowledge alone. However, investigators that distinguished themselves as leaders in research had greater recruitment success than investigators who were leaders in clinical practice. ALLHAT was a highly successful trial that proved that community based cardiovascular trials can be implemented on a large scale. Exploring characteristics of ALLHAT investigators provides data that can be generalized to sponsors, sites, and others interested in maximizing clinical trial recruitment numbers. Future studies should further evaluate investigator and study coordinator factors that impact cardiovascular clinical trial recruitment success.^

Bayesian adaptive designs in early phase clinical trials

There are two practical challenges in the phase I clinical trial conduct: lack of transparency to physicians, and the late onset toxicity. In my dissertation, Bayesian approaches are used to address these two problems in clinical trial designs. The proposed simple optimal designs cast the dose finding problem as a decision making process for dose escalation and deescalation. The proposed designs minimize the incorrect decision error rate to find the maximum tolerated dose (MTD). For the late onset toxicity problem, a Bayesian adaptive dose-finding design for drug combination is proposed. The dose-toxicity relationship is modeled using the Finney model. The unobserved delayed toxicity outcomes are treated as missing data and Bayesian data augment is employed to handle the resulting missing data. Extensive simulation studies have been conducted to examine the operating characteristics of the proposed designs and demonstrated the designs' good performances in various practical scenarios.^