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There Is Nothing Personal—Reply

There Is Nothing Personal—Reply In reply I agree with Chiolero that the terms personal and personalized have been misinterpreted, fueling unrealistic expectations of predictive accuracy.1,2 Chiolero suggests that the term stratified should be used instead because it captures more appropriately the effort to create relatively accurate predictions for discrete strata rather than individuals. The term stratified (eg, stratified medicine) has gained some traction recently. I agree that it is technically sound and to the point in most cases where some predictive tool is applied. However, the term stratified also has some disadvantages. First, it is probably too technical, and most people in the general public would not understand what “strata” and “stratified” mean. Second, it does not capture the fact that the new wave of “omics” and related information is indeed making an effort to move beyond what we could achieve with classic stratification variables available for many decades. Third, it is not very useful in those cases where prediction can indeed be personalized. There are some select situations where prediction is perfect. For example, there are several mutations with practically perfect penetrance or chromosomal abnormalities that confer practically 100% risk of developing a specific phenotype or disease. Even on the side of nongenetic exposures, there are some exposures that also carry practically 100% risk of specific outcomes, eg, exposure at doses of toxins, pollutants, or radiation that is way above the lethal dose threshold, or certain modes of suicide attempts. For most phenotypes and diseases in which the etiology is very complex and multifactorial, we do not know exactly how far we can reach with deterministic prediction tools and how much will remain entirely in the domain of random events. Some events that now seem random may have some hidden determinism that will be possible to decipher with very intensive capture of biological and other information at the level of single patients.3 Even though we may be very far from the perfect prediction of most diseases, I see no major problem in using the term personal, provided that it is widely understood that we are not there yet and that we may never reach the goal in its entirety. In fact, I would argue that the term personal is also pretty good at conveying the sense that some events are totally random, and thus their occurrence would pertain only to the specific individual, ie, they are highly “personal” and not to be shared with anyone else in the future. Back to top Article Information Correspondence: Dr Ioannidis, Stanford Prevention Research Center, Stanford University School of Medicine, University Campus, Stanford, CA 94305 (jioannid@stanford.edu). Conflict of Interest Disclosures: None reported. References 1. Ioannidis JPA. Genetic prediction for common diseases: will personal genomics ever work? Arch Intern Med. 2012;172:744-74622782208PubMedGoogle ScholarCrossref 2. Ioannidis JPA. Limits to forecasting in personalized medicine: an overview. Int J Forecast. 2009;25(4):773-783Google ScholarCrossref 3. Chen R, Mias GI, Li-Pook-Than J, et al. Personal omics profiling reveals dynamic molecular and medical phenotypes. Cell. 2012;148(6):1293-130722424236PubMedGoogle ScholarCrossref http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Archives of Internal Medicine American Medical Association

There Is Nothing Personal—Reply

Archives of Internal Medicine , Volume 172 (21) – Nov 26, 2012

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Publisher
American Medical Association
Copyright
Copyright © 2012 American Medical Association. All Rights Reserved.
ISSN
0003-9926
eISSN
1538-3679
DOI
10.1001/2013.jamainternmed.13
Publisher site
See Article on Publisher Site

Abstract

In reply I agree with Chiolero that the terms personal and personalized have been misinterpreted, fueling unrealistic expectations of predictive accuracy.1,2 Chiolero suggests that the term stratified should be used instead because it captures more appropriately the effort to create relatively accurate predictions for discrete strata rather than individuals. The term stratified (eg, stratified medicine) has gained some traction recently. I agree that it is technically sound and to the point in most cases where some predictive tool is applied. However, the term stratified also has some disadvantages. First, it is probably too technical, and most people in the general public would not understand what “strata” and “stratified” mean. Second, it does not capture the fact that the new wave of “omics” and related information is indeed making an effort to move beyond what we could achieve with classic stratification variables available for many decades. Third, it is not very useful in those cases where prediction can indeed be personalized. There are some select situations where prediction is perfect. For example, there are several mutations with practically perfect penetrance or chromosomal abnormalities that confer practically 100% risk of developing a specific phenotype or disease. Even on the side of nongenetic exposures, there are some exposures that also carry practically 100% risk of specific outcomes, eg, exposure at doses of toxins, pollutants, or radiation that is way above the lethal dose threshold, or certain modes of suicide attempts. For most phenotypes and diseases in which the etiology is very complex and multifactorial, we do not know exactly how far we can reach with deterministic prediction tools and how much will remain entirely in the domain of random events. Some events that now seem random may have some hidden determinism that will be possible to decipher with very intensive capture of biological and other information at the level of single patients.3 Even though we may be very far from the perfect prediction of most diseases, I see no major problem in using the term personal, provided that it is widely understood that we are not there yet and that we may never reach the goal in its entirety. In fact, I would argue that the term personal is also pretty good at conveying the sense that some events are totally random, and thus their occurrence would pertain only to the specific individual, ie, they are highly “personal” and not to be shared with anyone else in the future. Back to top Article Information Correspondence: Dr Ioannidis, Stanford Prevention Research Center, Stanford University School of Medicine, University Campus, Stanford, CA 94305 (jioannid@stanford.edu). Conflict of Interest Disclosures: None reported. References 1. Ioannidis JPA. Genetic prediction for common diseases: will personal genomics ever work? Arch Intern Med. 2012;172:744-74622782208PubMedGoogle ScholarCrossref 2. Ioannidis JPA. Limits to forecasting in personalized medicine: an overview. Int J Forecast. 2009;25(4):773-783Google ScholarCrossref 3. Chen R, Mias GI, Li-Pook-Than J, et al. Personal omics profiling reveals dynamic molecular and medical phenotypes. Cell. 2012;148(6):1293-130722424236PubMedGoogle ScholarCrossref

Journal

Archives of Internal MedicineAmerican Medical Association

Published: Nov 26, 2012

Keywords: phenotype,chromosome abnormality,mutation,penetrance, genetic,sound,toxins,traction,lethal dose

References