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Accuracy of the online prognostication tools PREDICT and Adjuvant! for early-stage breast cancer patients younger than 50 years

Published:April 14, 2017DOI:https://doi.org/10.1016/j.ejca.2017.03.015

      Highlights

      • PREDICT all-cause mortality estimates are suboptimal for patients ≤40 years and those with <20 or >40% mortality probability.
      • PREDICT overestimates breast cancer–specific survival across multiple patient subgroups.
      • Adjuvant! discriminatory accuracy and calibration are in line with PREDICT's.
      • Although these tools' estimates of all-cause mortality are reasonably sound, oncologists must interpret them with caution.

      Abstract

      Importance

      Online prognostication tools such as PREDICT and Adjuvant! are increasingly used in clinical practice by oncologists to inform patients and guide treatment decisions about adjuvant systemic therapy. However, their validity for young breast cancer patients is debated.

      Objective

      To assess first, the prognostic accuracy of PREDICT's and Adjuvant! 10-year all-cause mortality, and second, its breast cancer–specific mortality estimates, in a large cohort of breast cancer patients diagnosed <50 years.

      Design

      Hospital-based cohort.

      Setting

      General and cancer hospitals.

      Participants

      A consecutive series of 2710 patients without a prior history of cancer, diagnosed between 1990 and 2000 with unilateral stage I–III breast cancer aged <50 years.

      Main outcome measures

      Calibration and discriminatory accuracy, measured with C-statistics, of estimated 10-year all-cause and breast cancer–specific mortality.

      Results

      Overall, PREDICT's calibration for all-cause mortality was good (predicted versus observed) meandifference: −1.1% (95%CI: −3.2%–0.9%; P = 0.28). PREDICT tended to underestimate all-cause mortality in good prognosis subgroups (range meandifference: −2.9% to −4.8%), overestimated all-cause mortality in poor prognosis subgroups (range meandifference: 2.6%–9.4%) and underestimated survival in patients < 35 by −6.6%. Overall, PREDICT overestimated breast cancer–specific mortality by 3.2% (95%CI: 0.8%–5.6%; P = 0.007); and also overestimated it seemingly indiscriminately in numerous subgroups (range meandifference: 3.2%–14.1%). Calibration was poor in the cohort of patients with the lowest and those with the highest mortality probabilities. Discriminatory accuracy was moderate-to-good for all-cause mortality in PREDICT (0.71 [95%CI: 0.68 to 0.73]), and the results were similar for breast cancer–specific mortality. Adjuvant!'s calibration and discriminatory accuracy for both all-cause and breast cancer–specific mortality were in line with PREDICT's findings.

      Conclusions

      Although imprecise at the extremes, PREDICT's estimates of 10-year all-cause mortality seem reasonably sound for breast cancer patients <50 years; Adjuvant! findings were similar. Prognostication tools should be used with caution due to the intrinsic variability of their estimates, and because the threshold to discuss adjuvant systemic treatment is low. Thus, seemingly insignificant mortality overestimations or underestimations of a few percentages can significantly impact treatment decision-making.

      Keywords

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