Stanford Medicine student devises liver exchange, easing shortage of organs | News Center

Roth, known for his work in game theory and market design and for applying these concepts to real-world problems, was Chan’s longtime mentor. “The Liver Exchange idea actually came from a term paper in a first-year market design class at Stanford,” Chan says.

As he learned more about liver transplants, Chan realized there were important biological and ethical differences from kidney transplants. “It turns out it’s a very different problem,” he said. “Using kidney algorithms to match liver transplants would be like running a monorail train on two tracks.”

For both organs, the algorithm must consider blood type compatibility, but livers present an additional matching requirement, as organ size and the severity of the patient’s condition must be considered.

Although the liver has a remarkable ability to regenerate itself, older people require the donation of larger liver lobes. And while patients waiting for a kidney transplant can survive on dialysis, sometimes for years, patients with end-stage liver disease lack similar treatment and are likely to die within months without a transplant.

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Patients waiting for a liver are ranked according to their model for end-stage liver disease, or MELD, score, which estimates their short-term risk of death. Sicker patients with the highest risk of death are at the top of the waiting list.

“Instead of just looking for compatible swaps, we want to find swaps that prioritize the most urgent patients first to prevent the most deaths,” Chan said.

He designed his algorithm to incorporate liver size, medical urgency and donor risk in determining the optimal swap.

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“My being an economist in medical school, with access to physicians, was a huge advantage in helping to formulate the matching problem properly,” Chan said. “The algorithm follows institutional and ethical constraints for liver transplantation, so it is practically relevant.”

Fulfilling a need of Pakistan

The next challenge was putting the algorithm into practice. Chan and Salman reached out to several Asian countries and eventually connected with Faisal Saud Dar, MBBS, a renowned transplant surgeon at the Pakistan Kidney and Liver Institute and co-author of the paper.

To convince the institute’s liver transplant team, they ran the algorithm on the institute’s previous patients and found exchanges that could have saved many lives.

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“The surgery team was very important, not only in performing the surgery, but in helping us modify the algorithm by telling us what kind of clinical workup they used before doing the surgery,” Salman said.

With the transplant team on board, local authority approval, and patient and donor consent, the first algorithm-matched liver transplant went ahead. After one month, all patients were well.

Chan hopes the success of this transplant will encourage more hospitals to adopt the algorithm. “Liver exchange is not a weird, scary thing. It’s been done and it’s helped people,” he said. “If more people are willing to do it, we can increase access to liver transplants in general.”


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