TY - JOUR
T1 - External validation and clinical utility assessment of PREDICT breast cancer prognostic model in young, systemic treatment-naïve women with node-negative breast cancer
AU - Wang, Yuwei
AU - Broeks, Annegien
AU - Giardiello, Daniele
AU - Hauptmann, Michael
AU - Józwiak, Katarzyna
AU - Koop, Esther A.
AU - Opdam, Mark
AU - Siesling, Sabine
AU - Sonke, Gabe S.
AU - Stathonikos, Nikolas
AU - ter Hoeve, Natalie D.
AU - van der Wall, Elsken
AU - van Deurzen, Carolien H.M.
AU - van Diest, Paul J.
AU - Voogd, Adri C.
AU - Vreuls, Willem
AU - Linn, Sabine C.
AU - Dackus, Gwen M.H.E.
AU - Schmidt, Marjanka K.
N1 - Funding Information:
The Netherlands Cancer Institute was supported by an institutional grant of the Dutch Cancer Society and of the Dutch Ministry of Health, Welfare and Sport . This study was supported by grants from the Dutch Cancer Society (KWF, grant number 11655/2018-1 to Marjanka K. Schmidt), the Netherlands Organization for Health Research and Development (project number 836021019 , to Sabine C. Linn), A Sister's Hope (to Sabine C. Linn), and De Vrienden van UMC Utrecht (to Sabine C. Linn). The funders of this study had no role in the design and conduct of the study; collection, analysis, and interpretation of the data; writing of the manuscript; and the decision to submit the manuscript for publication.
Publisher Copyright:
© 2023 The Authors
PY - 2023/12/1
Y1 - 2023/12/1
N2 - Background: The validity of the PREDICT breast cancer prognostic model is unclear for young patients without adjuvant systemic treatment. This study aimed to validate PREDICT and assess its clinical utility in young women with node-negative breast cancer who did not receive systemic treatment. Methods: We selected all women from the Netherlands Cancer Registry who were diagnosed with node-negative breast cancer under age 40 between 1989 and 2000, a period when adjuvant systemic treatment was not standard practice for women with node-negative disease. We evaluated the calibration and discrimination of PREDICT using the observed/expected (O/E) mortality ratio, and the area under the receiver operating characteristic curve (AUC), respectively. Additionally, we compared the potential clinical utility of PREDICT for selectively administering chemotherapy to the chemotherapy-to-all strategy using decision curve analysis at predefined thresholds. Results: A total of 2264 women with a median age at diagnosis of 36 years were included. Of them, 71.2% had estrogen receptor (ER)-positive tumors and 44.0% had grade 3 tumors. Median tumor size was 16 mm. PREDICT v2.2 underestimated 10-year all-cause mortality by 33% in all women (O/E ratio:1.33, 95%CI:1.22–1.43). Model discrimination was moderate overall (AUC10-year:0.65, 95%CI:0.62–0.68), and poor for women with ER-negative tumors (AUC10-year:0.56, 95%CI:0.51–0.62). Compared to the chemotherapy-to-all strategy, PREDICT only showed a slightly higher net benefit in women with ER-positive tumors, but not in women with ER-negative tumors. Conclusions: PREDICT yields unreliable predictions for young women with node-negative breast cancer. Further model updates are needed before PREDICT can be routinely used in this patient subset.
AB - Background: The validity of the PREDICT breast cancer prognostic model is unclear for young patients without adjuvant systemic treatment. This study aimed to validate PREDICT and assess its clinical utility in young women with node-negative breast cancer who did not receive systemic treatment. Methods: We selected all women from the Netherlands Cancer Registry who were diagnosed with node-negative breast cancer under age 40 between 1989 and 2000, a period when adjuvant systemic treatment was not standard practice for women with node-negative disease. We evaluated the calibration and discrimination of PREDICT using the observed/expected (O/E) mortality ratio, and the area under the receiver operating characteristic curve (AUC), respectively. Additionally, we compared the potential clinical utility of PREDICT for selectively administering chemotherapy to the chemotherapy-to-all strategy using decision curve analysis at predefined thresholds. Results: A total of 2264 women with a median age at diagnosis of 36 years were included. Of them, 71.2% had estrogen receptor (ER)-positive tumors and 44.0% had grade 3 tumors. Median tumor size was 16 mm. PREDICT v2.2 underestimated 10-year all-cause mortality by 33% in all women (O/E ratio:1.33, 95%CI:1.22–1.43). Model discrimination was moderate overall (AUC10-year:0.65, 95%CI:0.62–0.68), and poor for women with ER-negative tumors (AUC10-year:0.56, 95%CI:0.51–0.62). Compared to the chemotherapy-to-all strategy, PREDICT only showed a slightly higher net benefit in women with ER-positive tumors, but not in women with ER-negative tumors. Conclusions: PREDICT yields unreliable predictions for young women with node-negative breast cancer. Further model updates are needed before PREDICT can be routinely used in this patient subset.
KW - Breast cancer
KW - Clinical utility
KW - External validation
KW - PREDICT Breast
KW - Prognosis prediction
U2 - 10.1016/j.ejca.2023.113401
DO - 10.1016/j.ejca.2023.113401
M3 - Article
SN - 0959-8049
VL - 195
JO - European Journal of Cancer
JF - European Journal of Cancer
IS - 1
M1 - 113401
ER -