Prognostication and treatment predictions for estrogen receptor positive early-stage breast cancer: incorporating the 70-gene signature into the PREDICT prognostication model
The 70-gene signature (70-GS) has been shown to identify women at low-risk of distant recurrence who can safely forgo adjuvant chemotherapy. Incorporating this GS into the well-validated and widely used PREDICT breast cancer model could improve the model's ability to estimate breast cancer prog...
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| Published in: | Breast (Edinburgh) Vol. 83; p. 104542 |
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| Main Authors: | , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
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Netherlands
Elsevier Ltd
01.10.2025
Elsevier |
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| ISSN: | 0960-9776, 1532-3080, 1532-3080 |
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| Abstract | The 70-gene signature (70-GS) has been shown to identify women at low-risk of distant recurrence who can safely forgo adjuvant chemotherapy. Incorporating this GS into the well-validated and widely used PREDICT breast cancer model could improve the model's ability to estimate breast cancer prognosis, and thereby further reduce overtreatment and its long-term impact on patients' quality of life. We incorporated the 70-GS into PREDICT-v2.3 and assessed the new PREDICT-GS model's ability to predict 5-year risk of breast cancer death.
Data from the MINDACT trial (N = 5920) was used to estimate the 70-GS's prognostic effect (coefficient = 0.70), which was then incorporated into PREDICT-v2.3. Netherlands Cancer Registry (NCR) data (N = 3323) was used to assess PREDICT-GS's discrimination (area under curve (AUC)), calibration and clinical utility.
Compared to PREDICT-v2.3 (AUC: 0.71 (95 % CI: 0.63–0.79)), PREDICT-GS (AUC: 0.76 (95 % CI: 0.69–0.83)) had better discrimination. Both models tended to overestimate the 5-year risk of breast cancer death in the NCR cohort, but the absolute overestimation was smaller for PREDICT-GS. Regarding clinical utility, only at the 10 % decision threshold did we find modest improvement: four extra patients per 1000 tests were correctly classified as not needing chemotherapy by PREDICT-GS compared to PREDICT-v2.3.
Extending PREDICT-v2.3 with 70-GS led to modest improvement in its ability to predict 5-year risk of breast cancer death. Future research should focus on assessing the added value of the 70-GS for longer-term prediction of recurrence and death with the incorporation of quality of life in risk prediction tools.
•70-gene signature (GS) could improve PREDICT 5-year breast cancer death predictions.•PREDICT-GS (AUC:0.76) had slightly better discrimination than PREDICT (AUC:0.71).•Smaller overestimation of 5-year mortality by PREDICT-GS in population-based cohort.•Modest improvement in clinical utility of PREDICT-GS vs. PREDICT. |
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| AbstractList | Background: The 70-gene signature (70-GS) has been shown to identify women at low-risk of distant recurrence who can safely forgo adjuvant chemotherapy. Incorporating this GS into the well-validated and widely used PREDICT breast cancer model could improve the model's ability to estimate breast cancer prognosis, and thereby further reduce overtreatment and its long-term impact on patients' quality of life. We incorporated the 70-GS into PREDICT-v2.3 and assessed the new PREDICT-GS model's ability to predict 5-year risk of breast cancer death. Methods: Data from the MINDACT trial (N = 5920) was used to estimate the 70-GS's prognostic effect (coefficient = 0.70), which was then incorporated into PREDICT-v2.3. Netherlands Cancer Registry (NCR) data (N = 3323) was used to assess PREDICT-GS's discrimination (area under curve (AUC)), calibration and clinical utility. Results: Compared to PREDICT-v2.3 (AUC: 0.71 (95 % CI: 0.63–0.79)), PREDICT-GS (AUC: 0.76 (95 % CI: 0.69–0.83)) had better discrimination. Both models tended to overestimate the 5-year risk of breast cancer death in the NCR cohort, but the absolute overestimation was smaller for PREDICT-GS. Regarding clinical utility, only at the 10 % decision threshold did we find modest improvement: four extra patients per 1000 tests were correctly classified as not needing chemotherapy by PREDICT-GS compared to PREDICT-v2.3. Conclusion: Extending PREDICT-v2.3 with 70-GS led to modest improvement in its ability to predict 5-year risk of breast cancer death. Future research should focus on assessing the added value of the 70-GS for longer-term prediction of recurrence and death with the incorporation of quality of life in risk prediction tools. The 70-gene signature (70-GS) has been shown to identify women at low-risk of distant recurrence who can safely forgo adjuvant chemotherapy. Incorporating this GS into the well-validated and widely used PREDICT breast cancer model could improve the model's ability to estimate breast cancer prognosis, and thereby further reduce overtreatment and its long-term impact on patients' quality of life. We incorporated the 70-GS into PREDICT-v2.3 and assessed the new PREDICT-GS model's ability to predict 5-year risk of breast cancer death. Data from the MINDACT trial (N = 5920) was used to estimate the 70-GS's prognostic effect (coefficient = 0.70), which was then incorporated into PREDICT-v2.3. Netherlands Cancer Registry (NCR) data (N = 3323) was used to assess PREDICT-GS's discrimination (area under curve (AUC)), calibration and clinical utility. Compared to PREDICT-v2.3 (AUC: 0.71 (95 % CI: 0.63–0.79)), PREDICT-GS (AUC: 0.76 (95 % CI: 0.69–0.83)) had better discrimination. Both models tended to overestimate the 5-year risk of breast cancer death in the NCR cohort, but the absolute overestimation was smaller for PREDICT-GS. Regarding clinical utility, only at the 10 % decision threshold did we find modest improvement: four extra patients per 1000 tests were correctly classified as not needing chemotherapy by PREDICT-GS compared to PREDICT-v2.3. Extending PREDICT-v2.3 with 70-GS led to modest improvement in its ability to predict 5-year risk of breast cancer death. Future research should focus on assessing the added value of the 70-GS for longer-term prediction of recurrence and death with the incorporation of quality of life in risk prediction tools. •70-gene signature (GS) could improve PREDICT 5-year breast cancer death predictions.•PREDICT-GS (AUC:0.76) had slightly better discrimination than PREDICT (AUC:0.71).•Smaller overestimation of 5-year mortality by PREDICT-GS in population-based cohort.•Modest improvement in clinical utility of PREDICT-GS vs. PREDICT. •70-gene signature (GS) could improve PREDICT 5-year breast cancer death predictions.•PREDICT-GS (AUC:0.76) had slightly better discrimination than PREDICT (AUC:0.71).•Smaller overestimation of 5-year mortality by PREDICT-GS in population-based cohort.•Modest improvement in clinical utility of PREDICT-GS vs. PREDICT. The 70-gene signature (70-GS) has been shown to identify women at low-risk of distant recurrence who can safely forgo adjuvant chemotherapy. Incorporating this GS into the well-validated and widely used PREDICT breast cancer model could improve the model's ability to estimate breast cancer prognosis, and thereby further reduce overtreatment and its long-term impact on patients' quality of life. We incorporated the 70-GS into PREDICT-v2.3 and assessed the new PREDICT-GS model's ability to predict 5-year risk of breast cancer death.BACKGROUNDThe 70-gene signature (70-GS) has been shown to identify women at low-risk of distant recurrence who can safely forgo adjuvant chemotherapy. Incorporating this GS into the well-validated and widely used PREDICT breast cancer model could improve the model's ability to estimate breast cancer prognosis, and thereby further reduce overtreatment and its long-term impact on patients' quality of life. We incorporated the 70-GS into PREDICT-v2.3 and assessed the new PREDICT-GS model's ability to predict 5-year risk of breast cancer death.Data from the MINDACT trial (N = 5920) was used to estimate the 70-GS's prognostic effect (coefficient = 0.70), which was then incorporated into PREDICT-v2.3. Netherlands Cancer Registry (NCR) data (N = 3323) was used to assess PREDICT-GS's discrimination (area under curve (AUC)), calibration and clinical utility.METHODSData from the MINDACT trial (N = 5920) was used to estimate the 70-GS's prognostic effect (coefficient = 0.70), which was then incorporated into PREDICT-v2.3. Netherlands Cancer Registry (NCR) data (N = 3323) was used to assess PREDICT-GS's discrimination (area under curve (AUC)), calibration and clinical utility.Compared to PREDICT-v2.3 (AUC: 0.71 (95 % CI: 0.63-0.79)), PREDICT-GS (AUC: 0.76 (95 % CI: 0.69-0.83)) had better discrimination. Both models tended to overestimate the 5-year risk of breast cancer death in the NCR cohort, but the absolute overestimation was smaller for PREDICT-GS. Regarding clinical utility, only at the 10 % decision threshold did we find modest improvement: four extra patients per 1000 tests were correctly classified as not needing chemotherapy by PREDICT-GS compared to PREDICT-v2.3.RESULTSCompared to PREDICT-v2.3 (AUC: 0.71 (95 % CI: 0.63-0.79)), PREDICT-GS (AUC: 0.76 (95 % CI: 0.69-0.83)) had better discrimination. Both models tended to overestimate the 5-year risk of breast cancer death in the NCR cohort, but the absolute overestimation was smaller for PREDICT-GS. Regarding clinical utility, only at the 10 % decision threshold did we find modest improvement: four extra patients per 1000 tests were correctly classified as not needing chemotherapy by PREDICT-GS compared to PREDICT-v2.3.Extending PREDICT-v2.3 with 70-GS led to modest improvement in its ability to predict 5-year risk of breast cancer death. Future research should focus on assessing the added value of the 70-GS for longer-term prediction of recurrence and death with the incorporation of quality of life in risk prediction tools.CONCLUSIONExtending PREDICT-v2.3 with 70-GS led to modest improvement in its ability to predict 5-year risk of breast cancer death. Future research should focus on assessing the added value of the 70-GS for longer-term prediction of recurrence and death with the incorporation of quality of life in risk prediction tools. The 70-gene signature (70-GS) has been shown to identify women at low-risk of distant recurrence who can safely forgo adjuvant chemotherapy. Incorporating this GS into the well-validated and widely used PREDICT breast cancer model could improve the model's ability to estimate breast cancer prognosis, and thereby further reduce overtreatment and its long-term impact on patients' quality of life. We incorporated the 70-GS into PREDICT-v2.3 and assessed the new PREDICT-GS model's ability to predict 5-year risk of breast cancer death. Data from the MINDACT trial (N = 5920) was used to estimate the 70-GS's prognostic effect (coefficient = 0.70), which was then incorporated into PREDICT-v2.3. Netherlands Cancer Registry (NCR) data (N = 3323) was used to assess PREDICT-GS's discrimination (area under curve (AUC)), calibration and clinical utility. Compared to PREDICT-v2.3 (AUC: 0.71 (95 % CI: 0.63-0.79)), PREDICT-GS (AUC: 0.76 (95 % CI: 0.69-0.83)) had better discrimination. Both models tended to overestimate the 5-year risk of breast cancer death in the NCR cohort, but the absolute overestimation was smaller for PREDICT-GS. Regarding clinical utility, only at the 10 % decision threshold did we find modest improvement: four extra patients per 1000 tests were correctly classified as not needing chemotherapy by PREDICT-GS compared to PREDICT-v2.3. Extending PREDICT-v2.3 with 70-GS led to modest improvement in its ability to predict 5-year risk of breast cancer death. Future research should focus on assessing the added value of the 70-GS for longer-term prediction of recurrence and death with the incorporation of quality of life in risk prediction tools. AbstractBackgroundThe 70-gene signature (70-GS) has been shown to identify women at low-risk of distant recurrence who can safely forgo adjuvant chemotherapy. Incorporating this GS into the well-validated and widely used PREDICT breast cancer model could improve the model's ability to estimate breast cancer prognosis, and thereby further reduce overtreatment and its long-term impact on patients' quality of life. We incorporated the 70-GS into PREDICT-v2.3 and assessed the new PREDICT-GS model's ability to predict 5-year risk of breast cancer death. MethodsData from the MINDACT trial (N = 5920) was used to estimate the 70-GS's prognostic effect (coefficient = 0.70), which was then incorporated into PREDICT-v2.3. Netherlands Cancer Registry (NCR) data (N = 3323) was used to assess PREDICT-GS's discrimination (area under curve (AUC)), calibration and clinical utility. ResultsCompared to PREDICT-v2.3 (AUC: 0.71 (95 % CI: 0.63–0.79)), PREDICT-GS (AUC: 0.76 (95 % CI: 0.69–0.83)) had better discrimination. Both models tended to overestimate the 5-year risk of breast cancer death in the NCR cohort, but the absolute overestimation was smaller for PREDICT-GS. Regarding clinical utility, only at the 10 % decision threshold did we find modest improvement: four extra patients per 1000 tests were correctly classified as not needing chemotherapy by PREDICT-GS compared to PREDICT-v2.3. ConclusionExtending PREDICT-v2.3 with 70-GS led to modest improvement in its ability to predict 5-year risk of breast cancer death. Future research should focus on assessing the added value of the 70-GS for longer-term prediction of recurrence and death with the incorporation of quality of life in risk prediction tools. |
| ArticleNumber | 104542 |
| Author | Cardoso, Fatima Rutgers, Emiel J.T. Piccart, Martine Poncet, Coralie Schmidt, Marjanka K. Binuya, Mary Ann E. Pharoah, Paul D.P. Linn, Sabine C. van ‘t Veer, Laura J. Steyerberg, Ewout W. Engelhardt, Ellen G. |
| Author_xml | – sequence: 1 givenname: Ellen G. orcidid: 0000-0003-0016-4972 surname: Engelhardt fullname: Engelhardt, Ellen G. organization: Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands – sequence: 2 givenname: Mary Ann E. surname: Binuya fullname: Binuya, Mary Ann E. organization: Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands – sequence: 3 givenname: Paul D.P. surname: Pharoah fullname: Pharoah, Paul D.P. organization: Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA – sequence: 4 givenname: Coralie surname: Poncet fullname: Poncet, Coralie organization: European Organisation for Research and Treatment of Cancer Headquarters, Brussels, Belgium – sequence: 5 givenname: Emiel J.T. surname: Rutgers fullname: Rutgers, Emiel J.T. organization: Department of Surgical Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands – sequence: 6 givenname: Martine surname: Piccart fullname: Piccart, Martine organization: Oncology Department, Institut Jules Bordet and l'Université Libre de Bruxelles (U.L.B.), Hôpital Universitaire de Bruxelles (HUB), Brussels, Belgium – sequence: 7 givenname: Fatima surname: Cardoso fullname: Cardoso, Fatima organization: Breast Unit, Champalimaud Clinical Center, Champalimaud Foundation, Lisbon, Portugal – sequence: 8 givenname: Laura J. surname: van ‘t Veer fullname: van ‘t Veer, Laura J. organization: UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA – sequence: 9 givenname: Ewout W. surname: Steyerberg fullname: Steyerberg, Ewout W. organization: Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands – sequence: 10 givenname: Sabine C. surname: Linn fullname: Linn, Sabine C. organization: Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands – sequence: 11 givenname: Marjanka K. surname: Schmidt fullname: Schmidt, Marjanka K. email: mk.schmidt@nki.nl organization: Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands |
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| Keywords | Validation 70-Gene signature Prognostication Model extension PREDICT for breast cancer model |
| Language | English |
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| Snippet | The 70-gene signature (70-GS) has been shown to identify women at low-risk of distant recurrence who can safely forgo adjuvant chemotherapy. Incorporating this... AbstractBackgroundThe 70-gene signature (70-GS) has been shown to identify women at low-risk of distant recurrence who can safely forgo adjuvant chemotherapy.... •70-gene signature (GS) could improve PREDICT 5-year breast cancer death predictions.•PREDICT-GS (AUC:0.76) had slightly better discrimination than PREDICT... Background: The 70-gene signature (70-GS) has been shown to identify women at low-risk of distant recurrence who can safely forgo adjuvant chemotherapy.... |
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| SubjectTerms | 70-Gene signature Adult Aged Breast Neoplasms - drug therapy Breast Neoplasms - genetics Breast Neoplasms - mortality Breast Neoplasms - pathology Breast Neoplasms - therapy Chemotherapy, Adjuvant Female Gene Expression Profiling Hematology, Oncology, and Palliative Medicine Humans Middle Aged Model extension Neoplasm Recurrence, Local - genetics Neoplasm Staging Netherlands Original PREDICT for breast cancer model Predictive Value of Tests Prognosis Prognostication Receptors, Estrogen - metabolism Registries Risk Assessment - methods Transcriptome Validation |
| Title | Prognostication and treatment predictions for estrogen receptor positive early-stage breast cancer: incorporating the 70-gene signature into the PREDICT prognostication model |
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