Literature DB >> 3862352

Epidemiologic evaluation of screening for risk factors: application to genetic screening.

M J Khoury, C A Newill, G A Chase.   

Abstract

To assess the usefulness of screening for risk factors, we derived arithmetic relationships between screening parameters (sensitivity, specificity, and positive predictive value PPV) and risk factor frequency, disease frequency and relative risk. We evaluated these relationships in the special case of genetic markers and disease susceptibility. It can be shown that even in the face of very large relative risks, sensitivity and positive predictive value are affected by the relative magnitude of disease and genetic marker frequencies. When the genetic marker is less frequent than the disease, PPV increases with increasing relative risk but sensitivity remains low. When the genetic marker is more frequent than the disease, sensitivity increases with increasing relative risk but PPV remains low. When marker and disease frequencies are equal, both PPV and sensitivity increase with increasing relative risks, but very high relative risks (greater than 100) have to be obtained for rare diseases. Depending on the goals of the screening program, these relationships can be used to predict the relative magnitudes of false positives (low PPV) and false negatives (low sensitivity). This approach can be generalized to evaluate nongenetic risk factors in screening programs as well.

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Year:  1985        PMID: 3862352      PMCID: PMC1646387          DOI: 10.2105/ajph.75.10.1204

Source DB:  PubMed          Journal:  Am J Public Health        ISSN: 0090-0036            Impact factor:   9.308


  6 in total

Review 1.  Genetic screening.

Authors:  B Childs
Journal:  Annu Rev Genet       Date:  1975       Impact factor: 16.830

2.  Hypersusceptibility and genetic problems in occupational medicine--a consensus report.

Authors:  H E Stokinger; L D Scheel
Journal:  J Occup Med       Date:  1973-07

3.  Genetic screening: implications for preventive medicine.

Authors:  C H Scriver
Journal:  Am J Public Health       Date:  1983-03       Impact factor: 9.308

Review 4.  Predictive identification of hypersusceptible individuals.

Authors:  G S Omenn
Journal:  J Occup Med       Date:  1982-05

5.  Looking at genes in the workplace.

Authors:  C Holden
Journal:  Science       Date:  1982-07-23       Impact factor: 47.728

6.  Genetic screening for hypersusceptibles in industry.

Authors:  E J Calabrese
Journal:  Med Hypotheses       Date:  1981-03       Impact factor: 1.538

  6 in total
  14 in total

1.  Discriminative accuracy of genomic profiling comparing multiplicative and additive risk models.

Authors:  Ramal Moonesinghe; Muin J Khoury; Tiebin Liu; A Cecile J W Janssens
Journal:  Eur J Hum Genet       Date:  2010-11-17       Impact factor: 4.246

Review 2.  Reliability of statistical associations between genes and disease.

Authors:  Kenneth F Manly
Journal:  Immunogenetics       Date:  2005-09-29       Impact factor: 2.846

Review 3.  From genes to public health: the applications of genetic technology in disease prevention. Genetics Working Group.

Authors:  M J Khoury
Journal:  Am J Public Health       Date:  1996-12       Impact factor: 9.308

Review 4.  A testable prognostic model of nicotine dependence.

Authors:  Rachel Badovinac Ramoni; Nancy L Saccone; Dorothy K Hatsukami; Laura J Bierut; Marco F Ramoni
Journal:  J Neurogenet       Date:  2009-01-31       Impact factor: 1.250

5.  Usefulness of non-invasive diagnostic methods for early detection of neoplasms of the urinary tract and male genitals among workers of the Mazovian Refining and Petrochemical Plant in Płock.

Authors:  A Majek; E Miekoś
Journal:  Int Urol Nephrol       Date:  1992       Impact factor: 2.370

6.  Association of interferon-gamma and interleukin 10 genotypes and serum levels with partial clinical remission in type 1 diabetes.

Authors:  B Z Alizadeh; P Hanifi-Moghaddam; P Eerligh; A R van der Slik; H Kolb; A V Kharagjitsingh; A M Pereira Arias; M Ronkainen; M Knip; R Bonfanti; E Bonifacio; D Devendra; T Wilkin; M J Giphart; B P C Koeleman; R Nolsøe; T Mandrup Poulsen; N C Schloot; B O Roep
Journal:  Clin Exp Immunol       Date:  2006-09       Impact factor: 4.330

7.  Predictive genetic testing for the identification of high-risk groups: a simulation study on the impact of predictive ability.

Authors:  Raluca Mihaescu; Ramal Moonesinghe; Muin J Khoury; A Cecile Jw Janssens
Journal:  Genome Med       Date:  2011-07-28       Impact factor: 11.117

Review 8.  Genetic-based prediction of disease traits: prediction is very difficult, especially about the future.

Authors:  Steven J Schrodi; Shubhabrata Mukherjee; Ying Shan; Gerard Tromp; John J Sninsky; Amy P Callear; Tonia C Carter; Zhan Ye; Jonathan L Haines; Murray H Brilliant; Paul K Crane; Diane T Smelser; Robert C Elston; Daniel E Weeks
Journal:  Front Genet       Date:  2014-06-02       Impact factor: 4.599

9.  Applying measures of discriminatory accuracy to revisit traditional risk factors for being small for gestational age in Sweden: a national cross-sectional study.

Authors:  Sol Pía Juárez; Phillip Wagner; Juan Merlo
Journal:  BMJ Open       Date:  2014-07-30       Impact factor: 2.692

10.  Short Term Survival after Admission for Heart Failure in Sweden: Applying Multilevel Analyses of Discriminatory Accuracy to Evaluate Institutional Performance.

Authors:  Nermin Ghith; Philippe Wagner; Anne Frølich; Juan Merlo
Journal:  PLoS One       Date:  2016-02-03       Impact factor: 3.240

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