Even with large amounts of data, the association between the drug combination and the prolonged QT interval does not prove the drugs caused this problem. To get more information, researchers then applied more traditional analyses and laboratory experiments to validate the predictions.

In this study, people taking ceftriaxone (a cephalosporin antibiotic) and lansoprazole (a proton pump inhibitor) were 40 percent more likely to have a QT interval above 500 ms, which is the current FDA-stated threshold of clinical concern. Among men taking both of these drugs, QT intervals were 12ms longer than men who took either drug alone. This trend was then validated by cellular data from the electrophysiology experiment, which found that together these drugs block one of the cardiac ion channel responsible for controlling heart rhythm. White women and men appear to be more sensitive to this interaction.


Interestingly, the interaction identified in the data analysis was specific to lansoprazole and ceftriaxone, and not other cephalosporin antibiotics. Even though they share similar chemical structure and mode of action, Tatonetti said, "our algorithm was able to distinguish between one that would cause this interaction (ceftriaxone) and another that would not (cefuroxime). We tested both in the lab and the algorithm was correct in both cases."

This research comes at a time when an increasing number of Americans are taking multiple prescriptions and over-the-counter medications. All told, nearly 70 percent take at least one prescription drug, and more than half take two, according to a 2013 study published in the Mayo Clinic Proceedings. Among the most commonly prescribed drugs are antibiotics. Twenty percent of patients are on five or more prescription medications. Finding ways to identify potentially harmful interactions is critical.

In an accompanying editorial, Dan M. Roden, M.D., and colleagues wrote that the findings of this study are not robust enough to advise clinicians to avoid this combination in all patients, but it shows that it is important to examine the effects of these drugs individually and in combination in patients.

The editorial said that with an aging population, it is becoming more common for patients to be on multiple medications, making it more important than ever to find a faster data-driven approach to identifying potential interactions among a vast number of possible drug pairs patients could be taking.

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