Epidemiology in wonderland: Big Data and precision medicine
R Saracci - European journal of epidemiology, 2018 - Springer
R Saracci
European journal of epidemiology, 2018•SpringerBig Data and precision medicine, two major contemporary challenges for epidemiology, are
critically examined from two different angles. In Part 1 Big Data collected for research
purposes (Big research Data) and Big Data used for research although collected for other
primary purposes (Big secondary Data) are discussed in the light of the fundamental
common requirement of data validity, prevailing over “bigness”. Precision medicine is
treated developing the key point that high relative risks are as a rule required to make a …
critically examined from two different angles. In Part 1 Big Data collected for research
purposes (Big research Data) and Big Data used for research although collected for other
primary purposes (Big secondary Data) are discussed in the light of the fundamental
common requirement of data validity, prevailing over “bigness”. Precision medicine is
treated developing the key point that high relative risks are as a rule required to make a …
Abstract
Big Data and precision medicine, two major contemporary challenges for epidemiology, are critically examined from two different angles. In Part 1 Big Data collected for research purposes (Big research Data) and Big Data used for research although collected for other primary purposes (Big secondary Data) are discussed in the light of the fundamental common requirement of data validity, prevailing over “bigness”. Precision medicine is treated developing the key point that high relative risks are as a rule required to make a variable or combination of variables suitable for prediction of disease occurrence, outcome or response to treatment; the commercial proliferation of allegedly predictive tests of unknown or poor validity is commented. Part 2 proposes a “wise epidemiology” approach to: (a) choosing in a context imprinted by Big Data and precision medicine—epidemiological research projects actually relevant to population health, (b) training epidemiologists, (c) investigating the impact on clinical practices and doctor-patient relation of the influx of Big Data and computerized medicine and (d) clarifying whether today "health" may be redefined—as some maintain in purely technological terms.
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