Lab mix-up results in mastectomy


When she heard the diagnosis of invasive lobular carcinoma, Darrie Eason had but one thought: Please don’t let me die.

Four months and a double mastectomy later, doctors told Eason that her tissue sample had been mislabeled, and that she never had cancer.

“I didn’t know what to believe,” said Eason, a 35-year-old single mother from Long Beach, N.Y. “They told me I had cancer, and now they’re telling me I didn’t. I didn’t know if the next day they were going to call me and say, ‘Sorry, we made a mistake, you really do have cancer.’ ”


According to her attorney and a New York state health department report, Eason is the victim of a mix-up at the CBLPath medical lab in Rye Brook.

Eason sued CBLPath in state supreme court in Mineola last month, seeking an undisclosed sum of money.

The 1 1/2 -page state report, issued in August 2006 to CBLPath, refers to a company report that blamed the mix-up on a technician who admitted cutting corners while labeling tissue specimens.

CBLPath Chief Executive William Curtis said he was familiar with Eason’s case but could not speak about any of his company’s patients because of federal privacy laws. He said the CBLPath doctor who signed off on Eason’s diagnosis, Dr. Beiyun Chen, no longer works for the company but said her departure had “nothing to do with this case.”

Chen could not be reached for comment.

While the state report found “no systemic problems” at CBLPath, Eason’s attorney, Steven E. Pegalis, said the lab must be held accountable.

“You kind of assume that if a lab diagnoses you as having cancer, you’ve got it,” he said. “How do you have faith and trust in systems that are supposed to be infallible?”


Pegalis said they chose not to sue Eason’s doctors because they were working with flawed information provided to them by CBLPath.

Medical experts say mistakes of this magnitude are rare.

Jim Conway, a senior fellow at the Institute for Health Care Improvement, a not-for-profit health research organization in Cambridge, Mass., said labs must create systems that prevent human errors from going unchecked.

“We have to put in place systems that mitigate chances of a human being making a mistake,” he said.