Danish scientists recently teamed up with
This approach maps out surprising correlations: a disease like gout - a form of arthritis - is strongly linked to cardiovascular disease, for example. In the future, this could enable physicians to make diagnoses sooner using simple tests in combination with known disease progression patterns.
The research is outlined in a study, "Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients," published in
"This is a leap into a fairly large data base," Moseley says. "This method is able to recognize patterns in data that not only include diagnostic patterns, but includes the element of time and is able to build networks from that."
"Every diagnosis on every Dane from every hospitalization and outpatient clinic visit is entered into the national health registry for the last 14 years," he says. "You're able to take these mass of data and look at it over time and begin to draw associations."
The team boiled down the massive trove of data to 1,171 so-called thoroughfares with central information on the course of diabetes, chronic obstructive pulmonary disease (COPD), cancer, arthritis and cardiovascular disease.
"Instead of looking at each disease in isolation, you can talk about a complex system with many different interacting factors," says Jensen, a post-doctoral fellow at the
Oprea points out an additional advantage of the data-mining method. "The disease trajectories in this study follow causal relationships that were identified by a medically agnostic software," he says. "This illustrates the power of data mining as a means to uncover novel disease relationships and its ability to inform the health care sector about new avenues in patient management."
The data analysis showed, for example, that a diagnosis of anemia is typically followed months later by the discovery of colon cancer, Oprea says, "which suggests that cancer lesions were present and occult bleeding occurred, but remained undiagnosed."
Meanwhile, in addition to identifying gout as a step on the path toward cardiovascular disease, the team made surprising findings about COPD.
"In just looking at these codes that were based on age and gender and where the code was done, we were able to say that COPD is diagnosed late," Moseley says. "It's therefore under-diagnosed and probably because of that undertreated. All we have is this diagnostic code, but our analysis of the pattern said that."
That finding received unexpected support last February when another team published a paper on a large epidemiological study of 6,000 Danish COPD patients, each of whom was interviewed and subjected to extensive examination, laboratory review and testing.
"Their conclusion is COPD is diagnosed late, under-diagnosed and undertreated," Moseley says. "We were able to come to the same conclusions without ever having gone the other way. We essentially did the experiment with a computer out of a health registry."
The research could yield tangible health benefits as we move beyond one-size-fits-all medicine, says Prof.
"The perspective is that your genetic profile or the total network of associated proteins in your body, your proteome, can be mapped in a few years' time, enabling you to suddenly learn things about yourself which can be used to forecast the progress of diseases over an entire lifetime," he says.
Moseley describes the partnership with the Danes as "a really very nice marriage . . . it's a strong informatics and systems biology collaboration." Going forward, he hopes to access the data for even larger populations.
Keywords for this news article include: Information Technology, Information and Data Mining,
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