The Experts below are selected from a list of 24276 Experts worldwide ranked by ideXlab platform
Keith Tan - One of the best experts on this subject based on the ideXlab platform.
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Implementation of a Bayesian adaptive design in a proof of concept study.
Pharmaceutical statistics, 2006Co-Authors: Mike K. Smith, Ieuan Jones, Mark Morris, Andrew P. Grieve, Keith TanAbstract:With increased costs of drug development the need for efficient studies has become critical. A Key Decision Point on the development pathway has become the proof of concept study. These studies must provide clear information to the project teams to enable Decision making about further developing a drug candidate but also to gain evidence that any effect size is sufficient to warrant this development given the current market environment. Our case study outlines one such proof of concept trial where a new candidate therapy for neuropathic pain was investigated to assess dose-response and to evaluate the magnitude of its effect compared to placebo. A Normal Dynamic Linear Model was used to estimate the dose-response--enforcing some smoothness in the dose-response, but allowing for the fact that the dose-response may be non-monotonic. A pragmatic, parallel group study design was used with interim analyses scheduled to allow the sponsor to drop ineffective doses or to stop the study. Simulations were performed to assess the operating characteristics of the study design. The study results are presented. Significant cost savings were made when it transpired that the new candidate drug did not show superior efficacy when compared placebo and the study was stopped.
Marcos Montagnini - One of the best experts on this subject based on the ideXlab platform.
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Geriatric failure to thrive.
American family physician, 2004Co-Authors: Russell G. Robertson, Marcos MontagniniAbstract:In elderly patients, failure to thrive describes a state of decline that is multifactorial and may be caused by chronic concurrent diseases and functional impairments. Manifestations of this condition include weight loss, decreased appetite, poor nutrition, and inactivity. Four syndromes are prevalent and predictive of adverse outcomes in patients with failure to thrive: impaired physical function, malnutrition, depression, and cognitive impairment. Initial assessments should include information on physical and psychologic health, functional ability, socioenvironmental factors, and nutrition. Laboratory and radiologic evaluations initially are limited to a complete blood count, chemistry panel, thyroid-stimulating hormone level, urinalysis, and other studies that are appropriate for an individual patient. A medication review should ensure that side effects or drug interactions are not a contributing factor to failure to thrive. The impact of existing chronic diseases should be assessed. Interventions should be directed toward easily treatable causes of failure to thrive, with the goal of maintaining or improving overall functional status. Physicians should recognize the diagnosis of failure to thrive as a Key Decision Point in the care of an elderly person. The diagnosis should prompt discussion of end-of-life care options to prevent needless interventions that may prolong suffering.
Mike K. Smith - One of the best experts on this subject based on the ideXlab platform.
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Implementation of a Bayesian adaptive design in a proof of concept study.
Pharmaceutical statistics, 2006Co-Authors: Mike K. Smith, Ieuan Jones, Mark Morris, Andrew P. Grieve, Keith TanAbstract:With increased costs of drug development the need for efficient studies has become critical. A Key Decision Point on the development pathway has become the proof of concept study. These studies must provide clear information to the project teams to enable Decision making about further developing a drug candidate but also to gain evidence that any effect size is sufficient to warrant this development given the current market environment. Our case study outlines one such proof of concept trial where a new candidate therapy for neuropathic pain was investigated to assess dose-response and to evaluate the magnitude of its effect compared to placebo. A Normal Dynamic Linear Model was used to estimate the dose-response--enforcing some smoothness in the dose-response, but allowing for the fact that the dose-response may be non-monotonic. A pragmatic, parallel group study design was used with interim analyses scheduled to allow the sponsor to drop ineffective doses or to stop the study. Simulations were performed to assess the operating characteristics of the study design. The study results are presented. Significant cost savings were made when it transpired that the new candidate drug did not show superior efficacy when compared placebo and the study was stopped.
R. Sean Morrison - One of the best experts on this subject based on the ideXlab platform.
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The Palliative Care Model for Emergency Department Patients with Advanced Illness
Journal of palliative medicine, 2011Co-Authors: Corita R. Grudzen, Susan Stone, R. Sean MorrisonAbstract:Abstract Background: Large gaps in the delivery of palliative care services exist in the outpatient setting, where there is a failure to address goals of care and to plan for and treat predictable crises. While not originally considered an ideal environment to deliver palliative care services, the emergency department presents a Key Decision Point at which providers set the course for a patient's subsequent trajectory and goals of care. Many patients with serious and life-threatening illness present to emergency departments because symptoms, such as pain or nausea and vomiting, cannot be controlled at home, in an assisted living facility, or in a provider's office. Even for patients in whom goals of care are clear, families often need support for their loved one's physical as well as mental distress. The emergency department is often the only place that can provide needed interventions (e.g., intravenous fluids or pain medications) as well as immediate access to advanced diagnostic tests (e.g. computed to...
Josef S. Smolen - One of the best experts on this subject based on the ideXlab platform.
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Optimisation of a treat-to-target approach in rheumatoid arthritis: strategies for the 3-month time Point
Annals of the rheumatic diseases, 2015Co-Authors: Daniel Aletaha, F. Alasti, Josef S. SmolenAbstract:Background Treat-to-target (T2T) is a widely accepted management strategy for rheumatoid arthritis (RA) with a Key Decision Point at 3 months after treatment initiation. At this time Point, it remains unclear which patients will benefit from treatment adaptation or from continuation of existing treatment. Methods We performed a pooled analysis of patient-level clinical trial data of patients with RA. We used a diagnostic testing methodology and a probabilistic approach employing logistic regression to investigate which levels of response at 3 months can inform treatment Decisions in regard to achieving the target at 6 months. Results To be at least 80% sensitive for achieving the low disease activity (LDA) target at 6 months, a change at 3 months in Simplified Disease Activity Index/Clinical Disease Activity Index (SDAI or CDAI) of 58% needs to be observed at 3 months. Higher changes are needed to sensitively predict remission (REM). Not reaching the (minor) SDAI 50% response level is afflicted with very low negative likelihood ratios (LRs) (0.28 for LDA and 0.07 for REM at 6 months). Experiencing (major) SDAI 85% response has substantial positive LRs of 9.2 for reaching LDA and 6.2 for reaching REM at 6 months. In logistic regression, the change at 3 months is significantly associated with reaching of the target at 6 months. Conclusions The 3-month time Point is a critical Decision Point. Not achieving minor responses at 3 months makes reaching of the treatment target at 6 months highly unlikely, while reaching major responses is highly predictive of reaching the treatment target.
