Download Cardiovascular Clinical Trials: Putting the Evidence into by Marcus Flather, Deepak Bhatt, Tobias Geisler PDF

By Marcus Flather, Deepak Bhatt, Tobias Geisler

The velocity of healing advances within the remedy of cardiovascular ailments is swift, and new clinically-relevant details appears to be like with such frequency that it may be tremendous hard for clinicians to maintain up.

Still, wisdom and interpretation of significant medical trials is important for the variety of clinicians who deal with cardiovascular sufferers, in particular seeing that vital trial facts usually has to be carried out quickly after it really is published.

Confidently follow most fulfilling therapy for 10 of the main serious components of cardiology
Written by means of a world group of specialists, Cardiovascular medical Trials: placing the facts into Practice:

  • Provides a succinct review of contemporary significant medical trials - the most excellent for all scientific remedy - throughout all of the significant cardiovascular subspecialties, to make sure you’re up to date at the most important findings
  • Guides cardiology trainees and clinicians on how cardiovascular scientific trials are designed and performed, together with statistical method, so that you can behavior and/or appraise destiny trials yourself
  • Addresses technique in addition to medical effectiveness
  • Offers evidence-based exams at the most desirable remedies and authoritative medical details on administration of the stipulations so that you can optimistically follow what you learn

Physicians, surgeons, expert nurses – any clinician looking an obtainable source for designing and accomplishing cardiovascular trials after which translating their effects into perform will delight in this book’s transparent counsel and succinct and sensible approach.


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Additional info for Cardiovascular Clinical Trials: Putting the Evidence into Practice

Sample text

In general, it is of advantage to confirm the robustness of the principal trial results with respect to alternative subsets of patient populations. Any relevant differences deriving from the choice of patient population for analysis should be the subject of explicit discussion. , comparison of effects by age, gender, race, disease condition, or cardiovascular risk groups. These analyses are not intended to retrieve an otherwise negative study, but may reveal hypotheses worth examining in other trials or be helpful in refining labeling information, or patient or dose selection.

Methods such as generalized estimating equations and random-effects models can effectively deal with the problem of correlation within subjects and across time [48–50]. Missing data As mentioned above, numerous factors may influence drop-out rates: study duration, efficacy and toxicity of the study drug, disease nature, and other individual factors. , who did not complete the study for whatever reason) and only analyzing patients who completed the study can be misleading. A large number of drop-outs, however, even if included in the analysis, may cause bias, particularly if there are differences in the timing of drop-outs between the treatment groups or the reasons for dropping out are related to outcome.

All of them belong to the category of active-control RCTs. Among these trials, two different concepts are followed in the comparison with the active control. In the first group of trials, the aim was to show the preservation of a clinically meaningful efficacy and safety margin (equivalence or non-inferiority trials). Examples are CAPPP, INSIGHT, INVEST, LIFE and LIFE-ISH, STOP Hypertension 2 and NORDIL, and ONTARGET. In the second group of studies using an active control, the margin of clinically meaningful effect has been exceeded, as seen in superiority trials.

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