The continual reassessment method (CRM) is an adaptive design for Phase I trials whose operating characteristics, including appropriate sample size, probability of correctly identifying the maximum ...tolerated dose, and the expected proportion of participants assigned to each dose, can only be determined via simulation. The actual time to determine a final “best” design can take several hours or days, depending on the number of scenarios that are examined. The computational cost increases as the kernel of the one‐parameter CRM design is expanded to other settings, including additional parameters, monitoring of both toxicity and efficacy, and studies of combinations of two agents. For a given vector of true DLT probabilities, we have developed an approach that replaces a simulation study of thousands of hypothetical trials with a single simulation. Our approach, which is founded on the consistency of the CRM, very accurately reflects the results produced by the simulation study, but does so in a fraction of time required by the simulation study. Relative to traditional simulations, we extensively examine how our method is able to assess the operating characteristics of a CRM design for a hypothetical trial whose characteristics are based upon a previously published Phase I trial. We also provide a metric of nonconsistency and demonstrate that although nonconsistency can impact the operating characteristics of our method, the degree of over‐ or under‐estimation is unpredictable. As a solution, we provide an algorithm for maintaining the consistency of a chosen CRM design so that our method is applicable for any trial.
In contrast with typical Phase III clinical trials, there is little existing methodology for determining the appropriate numbers of patients to enroll in adaptive Phase I trials. And, as stated by ...Dennis Lindley in a more general context, u the simple practical question of 'What size of sample should I take' is often posed to a statistician, and it is a question that is embarrassingly difficult to answer." Historically, simulation has been the primary option for determining sample sizes for adaptive Phase I trials, and although useful, can be problematic and time-consuming when a sample size is needed relatively quickly. We propose a computationally fast and simple approach that uses Beta distributions to approximate the posterior distributions of DLT rates of each dose and determines an appropriate sample size through posterior coverage rates. We provide sample sizes produced by our methods for a vast number of realistic Phase I trial settings and demonstrate that our sample sizes are generally larger than those produced by a competing approach that is based upon the nonparametric optimal design.
The Continual Reassessment Method (CRM) was developed for Phase I trials to identify a maximum‐tolerated dose of an agent using a design in which each participant is treated with a single ...administration of the agent. We propose an extension of the CRM in which participants receive multiple administrations of an agent using a so‐called step‐up dosing procedure in which participants receive one or more administrations of lower doses of the agent before they receive their penultimate dose. We use methods developed for the CRM to model the probability of DLT for each administration, which leads to the use of conditional probability models to model the joint probability of DLT across multiple administrations. We compare our approach to two existing methods that use time‐to‐event modeling methods for modeling the probability of DLT. We demonstrate through simulations that our approach has operating characteristics similar to existing methods, but due to its foundations in the CRM, ours is simpler to implement than existing approaches and is therefore more likely to be adopted in practice.
Machine learning techniques are widely used nowadays in the healthcare domain for the diagnosis, prognosis, and treatment of diseases. These techniques have applications in the field of hematopoietic ...cell transplantation (HCT), which is a potentially curative therapy for hematological malignancies. Herein, a systematic review of the application of machine learning (ML) techniques in the HCT setting was conducted. We examined the type of data streams included, specific ML techniques used, and type of clinical outcomes measured. A systematic review of English articles using PubMed, Scopus, Web of Science, and IEEE Xplore databases was performed. Search terms included "hematopoietic cell transplantation (HCT)," "autologous HCT," "allogeneic HCT," "machine learning," and "artificial intelligence." Only full-text studies reported between January 2015 and July 2020 were included. Data were extracted by two authors using predefined data fields. Following PRISMA guidelines, a total of 242 studies were identified, of which 27 studies met the inclusion criteria. These studies were sub-categorized into three broad topics and the type of ML techniques used included ensemble learning (63%), regression (44%), Bayesian learning (30%), and support vector machine (30%). The majority of studies examined models to predict HCT outcomes (e.g., survival, relapse, graft-versus-host disease). Clinical and genetic data were the most commonly used predictors in the modeling process. Overall, this review provided a systematic review of ML techniques applied in the context of HCT. The evidence is not sufficiently robust to determine the optimal ML technique to use in the HCT setting and/or what minimal data variables are required.
Graft-versus-host disease (GVHD) is the major cause of non-relapse mortality after allogeneic haemopoietic stem-cell transplantation (SCT). The severity of symptoms at the onset of GVHD does not ...accurately define risk, and thus most patients are treated alike with high dose systemic corticosteroids. We aimed to define clinically meaningful risk strata for patients with newly diagnosed acute GVHD using plasma biomarkers.
Between April 13, 2000, and May 7, 2013, we prospectively collected plasma from 492 SCT patients with newly diagnosed acute GVHD and randomly assigned (2:1) using a random number generator, conditional on the final two datasets having the same median day of onset, into training (n=328) and test (n=164) sets. We used the concentrations of three recently validated biomarkers (TNFR1, ST2, and Reg3α) to create an algorithm that computed the probability of non-relapse mortality 6 months after GVHD onset for individual patients in the training set alone. We rank ordered the probabilities and identified thresholds that created three distinct non-relapse mortality scores. We evaluated the algorithm in the test set, and again in an independent validation set of an additional 300 patients who underwent stem cell transplant and were enrolled on multicentre clinical trials of primary therapy for acute GVHD.
In all three datasets (training, test, and validation), the cumulative incidence of 6-month non-relapse mortality significantly increased as the Ann Arbor GVHD score increased. In the multicentre validation set, scores were 8% (95% CI 3-16) for score 1, 27% (20-34) for score 2, and 46% (33-58) for score 3 (p<0·0001). Conversely, the response to primary GVHD treatment within 28 days decreased as the GVHD score increased 86% for score 1, 67% for score 2, and 46% for score 3 in the multicentre validation set, p<0·0001).
Biomarker-based scores can be used to guide risk-adapted therapy at the onset of acute GVHD. High risk patients with a score of 3 are candidates for intensive primary therapy, while low risk patients with a score of 1 are candidates for rapid tapers of systemic steroid therapy.
The National Cancer Institute, the National Heart, Lung, and Blood Institute, the National Institute of Allergy and Infectious Diseases, the Doris Duke Charitable Fund, the American Cancer Society, and the Judith Devries Fund.
Serum levels of an interleukin-1 receptor family member called suppressor of tumorigenicity 2 (ST2) predict response to therapy for graft-versus-host disease (GVHD) and improve on clinical grading in ...assessing the risk of death without relapse after allogeneic transplantation.
Although mortality related to graft-versus-host disease (GVHD) after allogeneic hematopoietic stem-cell transplantation has been reduced,
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acute GVHD remains a major complication of allogeneic transplantation, occurring in approximately half the transplant recipients.
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High-dose systemic glucocorticoids remain the first-line therapy for GVHD,
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although just half of patients have complete resolution of GVHD by day 28 after therapy initiation.
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Patients who do not have a response to GVHD therapy are at high risk for death without relapse of the primary disease for which the transplantation was performed within 6 months after therapy initiation.
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We previously reported that a model . . .
N,N-Substituted ditetrazolylalkanes are widely used molecules in the field of coordination chemistry and are known with different alkyl chain lengths. The missing fragment within this row is ...presented by the elementary methylene-bridged ditetrazoles. The three different isomers (di(tetrazol-1-yl)methane (1,1-dtm, 1), (tetrazol-1-yl)(tetrazol-2-yl)methane (1,2-dtm, 2), and di(tetrazol-2-yl)methane (2,2-dtm, 3)) were synthesized in a convenient one-step reaction. All of them were successfully incorporated as neutral ligands in 15 new energetic coordination compounds (ECC) based on Cu2+ and Ag+ as well as different anions (nitrate, picrate (PA), styphnate (TNR), trinitrophloroglucinate (TNPG), and perchlorate) revealing an extraordinary coordination behavior of the ligands compared to other 5H-ditetrazolylalkanes. All compounds were extensively characterized using single-crystal X-ray diffraction experiments, infrared spectroscopy (IR), elemental analysis (EA), and differential thermal analysis (DTA). Furthermore, the sensitivities were determined using standard techniques, and Hirshfeld surface calculations of the ligands were applied to explain their significant divergences to external stimuli. The ECC possess very good exothermic decomposition temperatures up to 242 °C. The ignition of all colored complexes was tested in laser experiments, and two copper(II) perchlorate compounds showed promising results in classic initiation capability tests using pentaerythritol tetranitrate (PETN).
Aim
Assess the ability of a panel of gingival crevicular fluid (GCF) biomarkers as predictors of periodontal disease progression (PDP).
Materials and methods
In this study, 100 individuals ...participated in a 12‐month longitudinal investigation and were categorized into four groups according to their periodontal status. GCF, clinical parameters and saliva were collected bi‐monthly. Subgingival plaque and serum were collected bi‐annually. For 6 months, no periodontal treatment was provided. At 6 months, patients received periodontal therapy and continued participation from 6 to 12 months. GCF samples were analysed by ELISA for MMP‐8, MMP‐9, Osteoprotegerin, C‐reactive Protein and IL‐1β. Differences in median levels of GCF biomarkers were compared between stable and progressing participants using Wilcoxon Rank Sum test (p = 0.05). Clustering algorithm was used to evaluate the ability of oral biomarkers to classify patients as either stable or progressing.
Results
Eighty‐three individuals completed the 6‐month monitoring phase. With the exception of GCF C‐reactive protein, all biomarkers were significantly higher in the PDP group compared to stable patients. Clustering analysis showed highest sensitivity levels when biofilm pathogens and GCF biomarkers were combined with clinical measures, 74% (95% CI = 61, 86).
Conclusions
Signature of GCF fluid‐derived biomarkers combined with pathogens and clinical measures provides a sensitive measure for discrimination of PDP (ClinicalTrials.gov NCT00277745).
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For the first time, the highly sensitive 1-(nitratomethyl)-5H-tetrazole (1-NAMT) was synthesized, representing the shortest possible 1-(nitratoalkyl)-5H-tetrazole with a combined nitrogen and oxygen ...content of 81.4%. Compared to its related ethyl derivative, 1-(nitratoethyl)-5H-tetrazole, it exhibits improved oxygen balance, resulting in higher detonation parameters. 1-NAMT was thoroughly analyzed by single-crystal diffraction experiments accompanied by elemental analysis, IR spectroscopy, and multinuclear (1H, 13C, and 14N) NMR measurements. The thermal behavior of 1-NAMT was analyzed by differential thermal analysis supported by thermogravimetric analysis. Furthermore, energetic coordination compounds (ECCs) of Cu with different inorganic (e.g., nitrate, chlorate, and perchlorate) and nitroaromatic anions (e.g., picrate and styphnate) were synthesized and thoroughly analyzed. It is shown that the formation of ECCs with nitroaromatic anions (T dec ∼ 180 °C) is a suitable strategy to improve the rather low thermal stability of 1-NAMT (125 °C).
•Reduced absenteeism among community hospital emergency room personnel after implementation of an automated hand hygiene compliance system.•Use of automated hand hygiene compliance systems may ...decrease health care personnel sick call outs and the number of overtime hours worked by substitute staff.•Decreased health care personnel absenteeism and decreased overtime hours paid represent significant returns on the investment of implementing an automated hand hygiene compliance system.
Few studies have examined the use of hand hygiene interventions among health care personnel and employee absenteeism. To improve the hand hygiene practices of emergency room nurses and technicians, we implemented mandatory use of an automated hand hygiene compliance system. After implementation, we found reductions in employee absenteeism and the number of overtime hours worked by substitute staff. These unanticipated results demonstrate a return on investment that benefits the health of employees.
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