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Misleading Clinical Data

Clinical data are, at present, inevitably open to doubt, and any list of suspected drugs must become obsolete and misleading very quickly. This topic must, therefore, be followed in the periodical press and manufacturers up-to-date information. [Pg.149]

Misleading clinical data relates to information which is available to the clinician but its nature or presentation is such that it fails to convey the meaning intended by its original author. Data can be misleading by nature of its ... [Pg.88]

Whilst the underlying clinical data in an application may be representative of the author s intention it is quite possible for the system to fail at the final hurdle by presenting that data to the user in a manner which misleads a user. [Pg.91]

Clinical data can give rise to hazards when either it is not available to a clinician or if it is misleading in some way. [Pg.100]

Clinical data can be absent because all or part of the system is unavailable or slow, access to it is denied, its presence it not noticed or it fails to be delivered. Clinical data can be misleading because of how it is presented, contextualised, identified or entered. Additionally information can become corrupted, fail to be communicated or the system provide inaccurate advice such that decision making is compromised. [Pg.100]

Comparative claims The FDA requires that any comparative claim made by a company for its pharmaceutical product be substantiated with scientific evidence. Examples of comparative claims are drug of choice, unsurpassed, or more effective. The supporting studies must be head-to-head —that is, they must be designed prospectively to compare the two products directly. The FDA prohibits a claim of superiority based solely on data derived from two or more studies that are compared, even when those studies have similar protocols. Further, the FDA requires that any comparative claim be clinically relevant to patients. And, if a comparative claim is made, it cannot be false or misleading and cannot leave out other measurements by which the company s product is inferior to its competitor. [Pg.61]

It is important to ensure that the graphics used in the presentation of the results of the pharmacometric analysis of clinical trial data do not lie or mislead. The way to do this is to avoid visual distortion. That is, the pharmacometrician has to ensure that the visual representation of the data is consistent with the numerical representation. This is in terms of volume, area, and so on. [Pg.932]

Firstly one is required to examine the extended effeets of incorrect data in the clinical record. For example, suppose that data erroneously gives the impression that a patient s diabetes was well-controlled when, in fact, this was not the case. Potentially the patient could change the manner in which they approach their condition, become lax in managing their diet or reduce their compliance with medication instructions. A record can be misleading if the underlying data is incorrect but also, and perhaps more likely, when the manner in which it is presented to the consumer is suboptimal. Patients are unlikely to be expert users of the system and translating the entire medical record into a form that facilitates safe patient interpretation is no easy task. [Pg.145]

The scenario becomes far more complex when one is faced with information which is both misleading and undetectable. Here there are no cues for the clinician to mistrust the data, no reason to consult other sources or investigate the issue further. The so-called credibly incorrect scenario is often associated with the greatest degree of clinical risk as the human factor controls of professional judgement are effectively bypassed. [Pg.210]

In the design phase of the product lifecycle, it is useful to identify those data items which have the potential to significantly impact care should a credibly incorrect error occur. Assessors should ask thanselves whether a data item is available elsewhere in the system to be cross-checked in the event that there is suspicion of inaccuracy. Similarly, are there single data items which, if misleading, could have a catastrophic clinical impact (e.g. a drug dosage or a positive indication of no... [Pg.210]

Another term used to characterize the transport properties of dialysis membranes is the so-called mass transfer area coefficient (MTAC), which is the product of the mass transfer coefficient (Ko) times the membrane surface area (A), or KoA. Usually, the terms MTAC and KoA reported are those for urea. While Ko should equal the maximum clearance obtained at high blood and dialysate flow rates, reports in the dialysis Hterature (Leypoldt et al., 1997) discuss the variation of KoA with dialysate flow rate. Such reports reflect the manufacturers or others inappropriate extrapolation of KoA from data obtained at typically clinically relevant flow rates, which arc not high enough to minimize boundary layer resistance. While the measurement of in vivo rather than in vitro characteristics of dialyzers is meant to provide more accurate or realistic information, it can be misleading in this context. [Pg.522]


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See also in sourсe #XX -- [ Pg.88 , Pg.89 , Pg.90 , Pg.91 , Pg.92 , Pg.93 , Pg.94 , Pg.95 , Pg.96 , Pg.97 , Pg.98 , Pg.99 ]




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