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  1. Article ; Online: CUSUMIN: A cumulative sum interval design for cancer phase I dose finding studies.

    Hatayama, Tomoyoshi / Yasui, Seiichi

    Pharmaceutical statistics

    2022  Volume 21, Issue 6, Page(s) 1324–1341

    Abstract: Recently, model-assisted designs, including the Bayesian optimal interval (BOIN) design with optimal thresholds to determine the dose for the next cohort, have been proposed for cancer phase I studies. Model-assisted designs are useful because of their ... ...

    Abstract Recently, model-assisted designs, including the Bayesian optimal interval (BOIN) design with optimal thresholds to determine the dose for the next cohort, have been proposed for cancer phase I studies. Model-assisted designs are useful because of their good performance as model-based designs in addition to their algorithm-based simplicity. In BOIN, escalation and de-escalation based on boundaries can be understood as a type of change point detection based on a sequential test procedure. Notably, the sequential test procedure is used in a wide range of fields and is known for its application to control charts, statistical monitoring methods used for detecting abnormalities in manufacturing processes. In control charts, abnormalities are detected if the control chart statistics are observed to be outside of the optimal boundaries. The cumulative sum (CUSUM) statistic, which is developed for control chart applications, derives higher power under the same erroneous judgment rate. Hence, it is expected that a more efficient model-assisted design can be achieved by the application of CUSUM statistics. In this study, a model-assisted design based on the CUSUM statistic is proposed. In the proposed design, the dose for the next cohort is decided by CUSUM statistics calculated from the counts of the dose-limiting toxicity and pre-defined boundaries, based on the CUSUM control chart scheme. Intensive simulation shows that our proposed method performs better than BOIN, and other representative model-assisted designs, including modified toxicity probability interval (mTPI) and Keyboard, in terms of controlling over-dosing rates while maintaining similar performance in the determination of maximum tolerated dose.
    MeSH term(s) Humans ; Bayes Theorem ; Maximum Tolerated Dose ; Neoplasms/drug therapy ; Computer Simulation ; Algorithms
    Language English
    Publishing date 2022-07-14
    Publishing country England
    Document type Journal Article
    ZDB-ID 2083706-9
    ISSN 1539-1612 ; 1539-1604
    ISSN (online) 1539-1612
    ISSN 1539-1604
    DOI 10.1002/pst.2247
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  2. Article ; Online: Bayesian central statistical monitoring using finite mixture models in multicenter clinical trials.

    Hatayama, Tomoyoshi / Yasui, Seiichi

    Contemporary clinical trials communications

    2020  Volume 19, Page(s) 100566

    Abstract: Background: Central monitoring (CM), in which data across all clinical sites are monitored, has an important role in risk-based monitoring. Several statistical methods have been proposed to compare patient outcomes among the sites for detecting atypical ...

    Abstract Background: Central monitoring (CM), in which data across all clinical sites are monitored, has an important role in risk-based monitoring. Several statistical methods have been proposed to compare patient outcomes among the sites for detecting atypical sites that have different trends in observed data. These methods assume that the number of clinical sites is not small, e.g., 100 or more. In addition, the proportion of atypical sites is assumed to be relatively small. However, in actuality, the central statistical monitoring (CSM) has to be implemented in small or moderate sized clinical trials such as small phase II clinical trials. The number of sites is no longer large in such situations. Therefore, it is of concern that existing methods may not work efficiently in CM of small or moderate sized clinical trials. In the light of this problem, we propose a Bayesian CSM method to detect atypical sites as the robust method against the existence of atypical sites.
    Methods: We use Bayesian finite mixture models (FMM) to model patient outcome values of both atypical and typical sites. In the method, the distributions of outcome values in normal sites are determined by choosing the body distribution, which has the largest mixture parameter value of finite mixture models based on the assumption that normal sites are in the majority. Atypical sites are detected by the criterion based on the posterior predictive distribution of normal site's outcome values derived from only the chosen body distribution.
    Results: Proposed method is evaluated by cumulative detection probability and type I error averaged over sites every round of CSM under the various scenarios, being compared with the conventional type analysis. If the total number of patients enrolled is 48, the proposed method is superior at least 10% for any shift sizes at the 2nd and the 3rd rounds. If the total number of patients is 96, both methods show similar detection probability for only one atypical site and large shift size. However, the proposed method is superior for the other scenarios. It is observed that all the type I errors averaged over sites are little difference between the methods at all the scenarios.
    Conclusion: We propose a Bayesian CSM method which works efficiently in a practical use of CM. It is shown that our method detects atypical sites with high probability regardless of the proportion of the atypical sites under the small clinical trial settings which is the target of our proposed method.
    Language English
    Publishing date 2020-04-09
    Publishing country Netherlands
    Document type Journal Article
    ISSN 2451-8654
    ISSN (online) 2451-8654
    DOI 10.1016/j.conctc.2020.100566
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  3. Article ; Online: MN-166 (ibudilast) in amyotrophic lateral sclerosis in a Phase IIb/III study: COMBAT-ALS study design.

    Oskarsson, Björn / Maragakis, Nicholas / Bedlack, Richard S / Goyal, Namita / Meyer, Jenny A / Genge, Angela / Bodkin, Cynthia / Maiser, Samuel / Staff, Nathan / Zinman, Lorne / Olney, Nicholas / Turnbull, John / Brooks, Benjamin Rix / Klonowski, Emelia / Makhay, Malath / Yasui, Seiichi / Matsuda, Kazuko

    Neurodegenerative disease management

    2021  Volume 11, Issue 6, Page(s) 431–443

    Abstract: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with motor neuron loss as a defining feature. Despite significant effort, therapeutic breakthroughs have been modest. MN-166 (ibudilast) has demonstrated neuroprotective action by various ...

    Abstract Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with motor neuron loss as a defining feature. Despite significant effort, therapeutic breakthroughs have been modest. MN-166 (ibudilast) has demonstrated neuroprotective action by various mechanisms: inhibition of proinflammatory cytokines and macrophage migration inhibitory factor, phosphodiesterase inhibition, and attenuation of glial cell activation in models of ALS. Early-phase studies suggest that MN-166 may improve survival outcomes and slow disease progression in patients with ALS. This article describes the rationale and design of COMBAT-ALS, an ongoing randomized, double-blind, placebo-controlled, multicenter Phase IIb/III study in ALS. This study is designed to evaluate the pharmacokinetics, safety and tolerability and assess the efficacy of MN-166 on function, muscle strength, quality of life and survival in ALS.
    MeSH term(s) Amyotrophic Lateral Sclerosis/drug therapy ; Double-Blind Method ; Humans ; Neurodegenerative Diseases ; Pyridines ; Quality of Life
    Chemical Substances Pyridines ; ibudilast (M0TTH61XC5)
    Language English
    Publishing date 2021-11-24
    Publishing country England
    Document type Journal Article ; Multicenter Study ; Randomized Controlled Trial ; Research Support, Non-U.S. Gov't
    ZDB-ID 2608846-0
    ISSN 1758-2032 ; 1758-2024
    ISSN (online) 1758-2032
    ISSN 1758-2024
    DOI 10.2217/nmt-2021-0042
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  4. Article ; Online: Valorizing waste iron powder in biogas production: Hydrogen sulfide control and process performances.

    Andriamanohiarisoamanana, Fetra J / Shirai, Tomoya / Yamashiro, Takaki / Yasui, Seiichi / Iwasaki, Masahiro / Ihara, Ikko / Nishida, Takehiro / Tangtaweewipat, Suchon / Umetsu, Kazutaka

    Journal of environmental management

    2017  Volume 208, Page(s) 134–141

    Abstract: Biogas is composed of different gases including hydrogen sulfide ( ... ...

    Abstract Biogas is composed of different gases including hydrogen sulfide (H
    MeSH term(s) Anaerobiosis ; Biofuels ; Bioreactors ; Hydrogen Sulfide ; Iron ; Manure ; Methane
    Chemical Substances Biofuels ; Manure ; Iron (E1UOL152H7) ; Methane (OP0UW79H66) ; Hydrogen Sulfide (YY9FVM7NSN)
    Language English
    Publishing date 2017-12-16
    Publishing country England
    Document type Journal Article
    ZDB-ID 184882-3
    ISSN 1095-8630 ; 0301-4797
    ISSN (online) 1095-8630
    ISSN 0301-4797
    DOI 10.1016/j.jenvman.2017.12.012
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  5. Article ; Online: Effects of handling parameters on hydrogen sulfide emission from stored dairy manure.

    Andriamanohiarisoamanana, Fetra J / Sakamoto, Yushi / Yamashiro, Takaki / Yasui, Seiichi / Iwasaki, Masahiro / Ihara, Ikko / Tsuji, Osamu / Umetsu, Kazutaka

    Journal of environmental management

    2015  Volume 154, Page(s) 110–116

    Abstract: Hydrogen sulfide (H2S) emission from liquid manure in the process preceding field application is an important issue in fertigation systems. Given that H2S poses a significant health risk, it is important to determine the effects of different handling ... ...

    Abstract Hydrogen sulfide (H2S) emission from liquid manure in the process preceding field application is an important issue in fertigation systems. Given that H2S poses a significant health risk, it is important to determine the effects of different handling parameters on H2S emissions to prevent health risks to farmers. In this study, the effects of total solids (TS; 3, 5, 7, 9, and 11%) and mixing speed (100, 200, 300, and 400 rpm), duration (5, 15, 30, and 60 min), and frequency (one, two, three, and four times a day) on H2S emissions from two different dairy manures were investigated. The results indicate that the quantity of sulfur-containing substrate intake determines the potential of dairy manure to emit H2S because manure from cows fed with concentrate-based feed generates higher amounts of H2S than manure from cows fed with forage-based feed. The H2S concentration increased with TS concentration and reached a maximum of 1133 ppm at a TS of 9%; thereafter, it decreased with further increases in TS concentration. H2S emission increased with mixing speed with a peak concentration of 3996 ppm at 400 rpm. A similar trend was observed for mixing duration. However, there were no significant differences between the amounts H2S emitted at different frequencies of mixing (P > 0.05). The results indicate that mixing speed, duration, and TS are the major determinants of the quantity of H2S emitted from dairy manure. Therefore, to prevent health risks associated with H2S emission from dairy manure, it is recommended that the mixing speed and duration should be kept as low as possible, while a TS concentration of above 9% should be applied during the fertigation of dairy manure.
    MeSH term(s) Air Pollutants, Occupational/chemistry ; Animal Feed ; Animals ; Cattle ; Dairying ; Environmental Monitoring ; Female ; Hydrogen Sulfide/chemistry ; Manure/analysis ; Waste Management
    Chemical Substances Air Pollutants, Occupational ; Manure ; Hydrogen Sulfide (YY9FVM7NSN)
    Language English
    Publishing date 2015-05-01
    Publishing country England
    Document type Journal Article
    ZDB-ID 184882-3
    ISSN 1095-8630 ; 0301-4797
    ISSN (online) 1095-8630
    ISSN 0301-4797
    DOI 10.1016/j.jenvman.2015.02.003
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    In stock of ZB MED Bonn / Germany

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