scholarly journals RESPONSE: Re: Assessing the Probability That a Positive Report is False: An Approach for Molecular Epidemiology Studies

2004 ◽  
Vol 96 (22) ◽  
pp. 1722-1723 ◽  
Author(s):  
S. Wacholder ◽  
S. Chanock ◽  
M. Garcia-Closas ◽  
H. A. Katki ◽  
L. El ghormli ◽  
...  
2004 ◽  
Vol 96 (6) ◽  
pp. 434-442 ◽  
Author(s):  
Sholom Wacholder ◽  
Stephen Chanock ◽  
Montserrat Garcia-Closas ◽  
Laure El ghormli ◽  
Nathaniel Rothman

Abstract Too many reports of associations between genetic variants and common cancer sites and other complex diseases are false positives. A major reason for this unfortunate situation is the strategy of declaring statistical significance based on a P value alone, particularly, any P value below .05. The false positive report probability (FPRP), the probability of no true association between a genetic variant and disease given a statistically significant finding, depends not only on the observed P value but also on both the prior probability that the association between the genetic variant and the disease is real and the statistical power of the test. In this commentary, we show how to assess the FPRP and how to use it to decide whether a finding is deserving of attention or “noteworthy.” We show how this approach can lead to improvements in the design, analysis, and interpretation of molecular epidemiology studies. Our proposal can help investigators, editors, and readers of research articles to protect themselves from overinterpreting statistically significant findings that are not likely to signify a true association. An FPRP-based criterion for deciding whether to call a finding noteworthy formalizes the process already used informally by investigators—that is, tempering enthusiasm for remarkable study findings with considerations of plausibility.


Mutagenesis ◽  
2007 ◽  
Vol 22 (6) ◽  
pp. 381-385 ◽  
Author(s):  
A. Munnia ◽  
F. Saletta ◽  
A. Allione ◽  
S. Piro ◽  
M. Confortini ◽  
...  

2014 ◽  
Vol 95 (1) ◽  
pp. 66-70 ◽  
Author(s):  
Victoria C. Edwards ◽  
C. Patrick McClure ◽  
Richard J. P. Brown ◽  
Emma Thompson ◽  
William L. Irving ◽  
...  

Sequence analysis is used to define the molecular epidemiology and evolution of the hepatitis C virus. Whilst most studies have shown that individual patients harbour viruses that are derived from a limited number of highly related strains, some recent reports have shown that some patients can be co-infected with very distinct variants whose frequency can fluctuate greatly. Whilst co-infection with highly divergent strains is possible, an alternative explanation is that such data represent contamination or sample mix-up. In this study, we have shown that DNA fingerprinting techniques can accurately assess sample provenance and differentiate between samples that are truly exhibiting mixed infection from those that harbour distinct virus populations due to sample mix-up. We have argued that this approach should be adopted routinely in virus sequence analyses to validate sample provenance.


2017 ◽  
Vol 6 (3) ◽  
Author(s):  
Cynthia Schairer ◽  
Sanjay R. Mehta ◽  
Staal A. Vinterbo ◽  
Martin Hoenigl ◽  
Michael Kalichman ◽  
...  

Background: Advances in viral sequence analysis make it possible to track the spread of infectious pathogens, such as HIV, within a population. When used to study HIV, these analyses (i.e., molecular epidemiology) potentially allow inference of the identity of individual research subjects. Current privacy standards are likely insufficient for this type of public health research. To address this challenge, it will be important to understand how stakeholders feel about the benefits and risks of such research. Design and Methods: To better understand perceived benefits and risks of these research methods, in-depth qualitative interviews were conducted with HIV-infected individuals, individuals at high-risk for contracting HIV, and professionals in HIV care and prevention. To gather additional perspectives, attendees to a public lecture on molecular epidemiology were asked to complete an informal questionnaire. Results: Among those interviewed and polled, there was near unanimous support for using molecular epidemiology to study HIV. Questionnaires showed strong agreement about benefits of molecular epidemiology, but diverse attitudes regarding risks. Interviewees acknowledged several risks, including privacy breaches and provocation of anti-gay sentiment. The interviews also demonstrated a possibility that misunderstandings about molecular epidemiology may affect how risks and benefits are evaluated. Conclusions: While nearly all study participants agree that the benefits of HIV molecular epidemiology outweigh the risks, concerns about privacy must be addressed to ensure continued trust in research institutions and willingness to participate in research.


2013 ◽  
Vol 54 (7) ◽  
pp. 500-517 ◽  
Author(s):  
Cliona M. McHale ◽  
Luoping Zhang ◽  
Reuben Thomas ◽  
Martyn T. Smith

Sign in / Sign up

Export Citation Format

Share Document