US 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 uses routine data provided by a pathologist’s analysis of a patient’s breast tumour to predict the recurrence risk category otherwise generated by commercially available molecular tests. One such test, OncotypeDX, detects alterations in genes linked to aggressive breast cancers that are more likely to recur and costs approximately $4,200 in the US. 

To use the app, doctors enter information from pathologists’ examination of a tumour. The app provides doctors with an overall estimate of the OncotypeDX risk category – high or low – that 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. 

The Johns Hopkins Kimmel Cancer Center scientists developed their app – the Breast Cancer Recurrence Score Estimator – based on information extracted from the medical records of 1,113 patients treated at five US hospitals 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 three 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 scientists reported recently in the Journal of Clinical Oncology.