Evaluation of Predict, a prognostic risk tool, after diagnosis of a second breast cancer

Abstract

Background: The UK National Health Service's Predict is a clinical tool widely used to estimate the prognosis of early-stage breast cancer. The performance of Predict for a second primary breast cancer is unknown.

Methods: Women 18 years of age or older diagnosed with a first or second invasive breast cancer between 2000 and 2013 and followed for at least 5 years were identified from the US Surveillance, Epidemiology, and End Results (SEER) database. Model calibration of Predict was evaluated by comparing predicted and observed 5-year breast cancer-specific mortality separately by estrogen receptor status for first vs second breast cancer. Receiver operating characteristic curves and areas under the curve were used to assess model discrimination. Model performance was also evaluated for various races and ethnicities.

Results: The study population included 6729 women diagnosed with a second breast cancer and 357 204 women with a first breast cancer. Overall, Predict demonstrated good discrimination for first and second breast cancers (areas under the curve ranging from 0.73 to 0.82). Predict statistically significantly underestimated 5-year breast cancer mortality for second estrogen receptor-positive breast cancers (predicted-observed = ‒6.24%, 95% CI = ‒6.96% to ‒5.49%). Among women with a first estrogen receptor-positive cancer, model calibration was good (predicted-observed = ‒0.22%, 95% CI = ‒0.29% to ‒0.15%), except in non-Hispanic Black women (predicted-observed = ‒2.33%, 95% CI = ‒2.65% to ‒2.01%) and women 80 years of age or older (predicted-observed = ‒3.75%, 95% CI = ‒4.12% to ‒3.41%). Predict performed well for second estrogen receptor-negative cancers overall (predicted-observed = ‒1.69%, 95% CI = ‒3.99% to 0.16%) but underestimated mortality among those who had previously received chemotherapy or had a first cancer with more aggressive tumor characteristics. In contrast, Predict overestimated mortality for first estrogen receptor-negative cancers (predicted-observed = 4.54%, 95% CI = 4.27% to 4.86%).

Conclusion: The Predict tool underestimated 5-year mortality after a second estrogen receptor-positive breast cancer and in certain subgroups of women with a second estrogen receptor-negative breast cancer.

Figure 1.

Calibration plot (A1 and B1) and receiver operating characteristic curve (A2 and B2) for estrogen receptor–positive breast cancer. A1 and A2 are for first breast cancers. B1 and B2 are for second breast cancers. The dotted line in A1 and B1 indicates perfect agreement between predicted and observed mortality. The black dots and bars in A1 and B1 represent the observed mortality with 95% confidence interval against deciles of the predicted mortality. AUC = area under the curve.

Figure 2.

Calibration plot (A1 and B1) and receiver operating characteristic curve (A2 and B2) for estrogen receptor–negative breast cancer. A1 and A2 are for first breast cancers. B1 and B2 are for second breast cancers. The dotted line in A1 and B1 indicates perfect agreement between predicted and observed mortality. The black dots and bars in A1 and B1 represent the observed mortality with 95% confidence interval against deciles of the predicted mortality. AUC = area under the curve.