Potti retraction tally grows to six with a withdrawal in PLoS ONE, and will likely end up near a dozen

Anil Potti and his former Duke colleagues have retracted a sixth paper, this one in PLoS ONE.

According to the retraction notice for “An Integrated Approach to the Prediction of Chemotherapeutic Response in Patients with Breast Cancer,” the withdrawal was prompted by the retraction of a Nature Medicine paper that formed the basis of the PLoS ONE study’s approach:

The chemotherapy sensitivity predictions as reported in this PLoS One article were based on an approach as described by Potti et al. in Nature Medicine (1). Reexamination of the validation datasets used for the Nature Medicine study has revealed the presence of errors in the labeling of clinical response in some datasets (2). Re-analysis of the predictive accuracy with correctly labeled data has shown that in two instances the reported signatures do not predict the response of the validation samples to chemotherapy (2). The authors of the Nature Medicine paper have therefore decided to retract that paper (2). Since the PLoS One article is based on the approach reported in the Nature Medicine article, we have decided to retract the PLoS One article. We apologize to readers for any inconvenience caused by the publication of our article in PLoS One.

The PLoS ONE paper has been cited 29 times, according to Thomson Scientific’s Web of Knowledge. As we reported in January when the Nature Medicine paper was retracted, that paper was cited more than 250 times.

The PLoS ONE retraction means we are likely halfway through all of the paper withdrawals, according to a report in The Cancer Letter of an August 22,  2011 Institute of Medicine meeting:

Robert Califf, director of the Duke Translational Medicine Institute and vice chancellor for clinical research, said that the university has nearly completed an internal investigation of Potti’s published research.

“There were about 40 [manuscripts] that had original data that were generated at Duke,” Califf said. “We had an institutional need to understand the veracity of the manuscripts that had the institution’s name on it.”

“About a third of the manuscripts are being fully retracted,” Califf said. “About a third are having a portion retracted with other components remaining intact, and about a third seem to be ok.”

“In those retractions and partial retractions, there is a clear correlation between the need to withdraw the data and the extent to which the data originated from Dr. Potti,” Califf said. “It looks like they’re fundamentally not reproducible.”

No timeframe was given for these retractions.

There’s plenty more in The Cancer Letter’s current issue, including details on the lawsuits filed against Duke, Potti, and his colleagues by a number of former clinical trial participants. The Economist also covers the Potti story this week, and Darrel Ince has a piece on it in the journal Significance.

8 thoughts on “Potti retraction tally grows to six with a withdrawal in PLoS ONE, and will likely end up near a dozen”

    1. I wrote to the NYT a whle back, since they had a story on this guy. The author passed the info on. I hope they’ll pick it up again.

  1. All that remains is for someone to point out to Google that Potti is manipulating their Page ranking system… I’ve heard that they have the “death penalty” for this sort of behavior, meaning that his sites will simply disappear from Google searches.
    They’ll put him down eventually.
    Shouldn’t he have been publishing in the Journal of Irreproducible Results?

  2. Why would anything he did be allowed to stay in the literature. He clearly makes up everything. Has anything he’s ever done been verified by another scientist or statistician?

  3. It is so shame that the corespondent author,their lab and even Potti didn’t get any punishment. Just retract papers and pretend not things happen for their lab, for Duke university and for all science community. As a young post-doc, I would say, our life is much easier: if these totally fake data still can bring funding and paper without any risk, why we need do experiments and repeat again and again. we can make all we need data in minutes.

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