New Web-Based App May Help Doctors Predict Risk of Breast Cancer Recurrence
BALTIMORE, Md -- October 11, 2016 -- Researchers have developed a free web-based app that could take some of the guesswork out of decisions to order an additional and costly molecular test for assessing risk for recurrence in women with early-stage breast cancer.
The app, described in the October 10 online edition of the Journal of Clinical Oncology, uses routine data provided by a pathologist’s analysis of a patient’s breast tumour biopsy to predict the recurrence risk category generated by commercially available molecular tests.
One such test, OncotypeDX (Genomic Health), detects alterations in genes linked to aggressive breast cancers that are more likely to recur and costs approximately $4,200 in the United State.
Antonio Wolf, MD, Johns Hopkins Kimmel Cancer Center, Baltimore, Maryland, and colleagues said that determining a patient’s risk for recurrence is a major factor in determining the need for chemotherapy and anti-hormone medications after surgery to remove an early-stage tumour.
“While such tests can be informative, clinicians ideally should use them when there is a gray zone in which high-quality pathology measures alone do not give doctors all the information they need,” he said. “Molecular tests should complement, not duplicate information that is already available.”
The researchers developed their app, called the Breast Cancer Recurrence Score Estimator, based on information extracted from the medical records of 1,113 patients treated at 5 hospitals in the United States for stage 1 or 2 breast cancer that was oestrogen receptor-positive and had the OncotypeDX test done.
The team used data from 472 additional patients from 3 of the hospitals to test the estimator and identified the risk category predicted by the OncotypeDX test for 248 of the patients (53%), with an accuracy of 97%.
In the remaining 224 patients, the app was not able to predict OncotypeDX’s risk score with certainty.
The app may not change the total number of molecular tests ordered at any particular hospital, but it may shift ordering of the tests to cases where pathology measures are more ambiguous, the authors reported.
The researchers also looked at what would happen if doctors at Johns Hopkins used this app, rather than their own intuition, to decide when to request the molecular test. They said that their analysis in 939 patients suggested that by using the app, they would have ordered 297 tests, instead of the 299 tests actually ordered. This is essentially the same total number of tests but now includes a very different group of patients for whom the molecular test would add the most information, according to Leslie Cope, PhD, Johns Hopkins University School of Medicine.
To use the app, doctors enter information from pathologists’ examination of a tumour, including levels of Ki67, the cancer’s grade, the tumour cells’ ability to bind to oestrogen and progesterone, and increased expression of the human epidermal growth factor receptor 2 (HER2) gene.
The app provides doctors with an overall estimate of the OncotypeDX risk category --high or low -- which aims to predict whether a patient’s cancer will recur by the end of 10 years and if additional therapy might reduce the recurrence risk in a meaningful way, explained Dr. Wolf.
“Before doctors begin using this app routinely, we ask them to test it on a group of their own patients,” noted Christopher Umbricht, MD, Johns Hopkins University School of Medicine.
The app’s website includes information on testing additional patient populations, and the investigators said they hope that other scientists will join them in efforts to improve the app.
A similar app has been developed by the University of Pittsburgh, Pittsburgh, Pennsylvania, using different pathology data.
SOURCE: Johns Hopkins Kimmel Cancer Center
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