Literature DB >> 21194888

Trade-off between benefit and harm is crucial in health screening recommendations. Part II: evidence summaries.

Maria Asuncion A Silvestre1, Leonila F Dans, Antonio L Dans.   

Abstract

Evidence on the effectiveness of health screening strategies may be direct (i.e., studies on screening vs. no screening) or indirect (i.e., studies that separately evaluate the screening test[s], the confirmatory test, or the treatment). Critical trade-offs in the balance between harm and benefit for many screening strategies mandate that advocates of health screening adhere to the ethical precepts of nonmaleficence, autonomy, confidentiality, and equity. In our first article, we pointed out five prerequisites to justifying a health screening program: (1) the burden of illness should be high, (2) the screening and confirmatory tests should be accurate, (3) early treatment (or prevention) must be more effective than late treatment, (4) the tests and the treatment(s) must be safe, and (5) the cost of the screening strategy must be commensurate with the potential benefit. As can be gleaned from these criteria, recommendations on screening must be tailored to specific populations. Recommendations in one country, no matter how authoritative, cannot be generalized to apply to all other countries. Although accuracy, effectiveness, and safety data may be global (criteria 2-4), burden of illness and efficiency (criteria 1 and 5) will always vary from country to country. Rather than review various national guidelines, in this last article of our two-part series, we present evidence summaries to illustrate health screening. Our examples were selected to address special issues related to four situations-screening for cancer, risk factors for disease, genetic disorders, and infectious diseases. Copyright Â
© 2011 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 21194888     DOI: 10.1016/j.jclinepi.2010.09.008

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  1 in total

1.  An alternative method for Frailty Index cut-off points to define frailty categories.

Authors:  Roman Romero-Ortuno
Journal:  Eur Geriatr Med       Date:  2013-11-01       Impact factor: 1.710

  1 in total

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