Richard D Gelber1, Xin V Wang2, Bernard F Cole3, David Cameron4, Fatima Cardoso5, Vivianne Tjan-Heijnen6, Ian Krop7, Sherene Loi8, Roberto Salgado9, Astrid Kiermaier10, Elizabeth Frank11, Debora Fumagalli12, Carmela Caballero13, Evandro de Azambuja14, Marion Procter15, Emma Clark16, Eleonora Restuccia17, Sarah Heeson18, Jose Bines19, Sibylle Loibl20, Martine Piccart-Gebhart21. 1. Dana-Farber Cancer Institute, Harvard Medical School, Harvard TH Chan School of Public Health, Frontier Science Foundation, Boston, MA, USA. Electronic address: gelber@jimmy.harvard.edu. 2. Dana-Farber Cancer Institute, Harvard TH Chan School of Public Health, Boston, MA, USA. Electronic address: vwang@jimmy.harvard.edu. 3. Department of Mathematics and Statistics, University of Vermont, Burlington, VT, USA. Electronic address: bfcole@uvm.edu. 4. Edinburgh University Cancer Research Centre, IGC, Western General Hospital, Edinburgh & Breast International Group, Brussels, Belgium. Electronic address: D.Cameron@ed.ac.uk. 5. Breast Unit, Champalimaud Clinical Center/Champalimaud Foundation, Lisbon, Portugal. Electronic address: fatimacardoso@fundacaochampalimaud.pt. 6. Department of Medical Oncology, Maastricht University Medical Centre, GROW, Maastricht, the Netherlands. Electronic address: vcg.tjan.heijnen@mumc.nl. 7. Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA. Electronic address: Ian_Krop@dfci.harvard.edu. 8. Division of Research, Peter MacCallum Cancer Centre, Melbourne, Australia; The Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Australia. Electronic address: sherene.loi@petermac.org. 9. Department of Pathology, GZA-ZNA Hospitals, Antwerp, Belgium; Division of Research, Peter MacCallum Cancer Centre, Melbourne, Australia; Roche Pharma Research and Early Development (pRED), Roche Innovation Center Basel, Basel, Switzerland. Electronic address: roberto@salgado.be. 10. Roche Pharma Research and Early Development (pRED), Roche Innovation Center Basel, Basel, Switzerland. Electronic address: astrid.kiermaier@roche.com. 11. Dana-Farber Cancer Institute, Boston, MA, USA. Electronic address: efrank2@partners.org. 12. Breast International Group (BIG), Brussels, Belgium. Electronic address: debora.fumagalli@gmail.com. 13. Breast International Group (BIG), Brussels, Belgium. Electronic address: Carmela.Caballero@bigagainstbc.org. 14. Institut Jules Bordet and L'Université Libre de Bruxelles (U.L.B), Brussels, Belgium. Electronic address: evandro.azambuja@bordet.be. 15. Frontier Science Scotland Ltd., Kincraig, Kingussie, UK. Electronic address: marion.procter@frontier-science.co.uk. 16. Roche Products Limited, Welwyn Garden City, UK. Electronic address: emma.clark@roche.com. 17. Hoffmann-La Roche Ltd., Basel, Switzerland. Electronic address: eleonora.restuccia@roche.com. 18. Roche Products Limited, Welwyn Garden City, UK. Electronic address: sarah.heeson@roche.com. 19. Instituto Nacional de Câncer, Rio de Janeiro, Brazil. Electronic address: jose_bines@yahoo.com. 20. German Breast Group, Neu-Isenburg, Germany; Centre for Haematology and Oncology Bethanien, Frankfurt, Germany. Electronic address: Sibylle.Loibl@germanbreastgroup.de. 21. Institut Jules Bordet and L'Université Libre de Bruxelles (U.L.B), Brussels, Belgium. Electronic address: martine.piccart@bordet.be.
Abstract
AIM: The APHINITY trial showed that adding adjuvant pertuzumab (P) to trastuzumab and chemotherapy, compared with adding placebo (Pla), significantly improved invasive disease-free survival (IDFS) for patients with HER2+ early breast cancer both overall and for the node-positive (N+) cohort. We explored whether adding P could benefit some N- subpopulations and whether to consider de-escalation for some N+ subpopulations. METHODS: Subpopulation Treatment Effect Pattern Plot (STEPP) is an exploratory, graphical method that plots estimates of treatment effect for overlapping patient subpopulations defined by a covariate of interest. We used STEPP to estimate Kaplan-Meier differences in 6-year IDFS percentages (P minus Pla: Δ ± standard error [SE]), both overall and by nodal status, for overlapping subpopulations defined by (1) a clinical composite risk score, (2) tumour infiltrating lymphocytes (TILs) percentage, and (3) human epidermal growth factor receptor 2 (HER2) FISH copy number. Because of multiplicity, a Δ of at least three SE is required to warrant attention. RESULTS: The average absolute gains in 6-year IDFS percentages were 2.8 ± 0.9 overall; 4.5 ± 1.2 for N+ and 0.1 ± 1.1 for N-. Largest gains were for patients with intermediate clinical composite risk (5.3 ± 1.9 overall; 6.9 ± 2.3 N+; 4.0 ± 3.0 N-), highest TILs percentage (6.3 ± 1.7 overall; 7.4 ± 2.4 N+; 3.2 ± 1.7 N-), and intermediate HER2 copy number (2.8 ± 1.9 overall; 7.4 ± 2.5 N+; -1.3 ± 1.9 N-), but clear evidence indicating a pattern of differential subpopulation treatment effects was lacking. CONCLUSIONS: STEPP plots for N- did not identify subpopulations clearly benefiting from adding P, and those for N+ did not identify subpopulations warranting de-escalation. TILs percentage appeared to be more predictive of P treatment effect than clinical composite risk score. TRIAL REGISTRATION: clinicaltrials.gov Identifier NCT01358877.
AIM: The APHINITY trial showed that adding adjuvant pertuzumab (P) to trastuzumab and chemotherapy, compared with adding placebo (Pla), significantly improved invasive disease-free survival (IDFS) for patients with HER2+ early breast cancer both overall and for the node-positive (N+) cohort. We explored whether adding P could benefit some N- subpopulations and whether to consider de-escalation for some N+ subpopulations. METHODS: Subpopulation Treatment Effect Pattern Plot (STEPP) is an exploratory, graphical method that plots estimates of treatment effect for overlapping patient subpopulations defined by a covariate of interest. We used STEPP to estimate Kaplan-Meier differences in 6-year IDFS percentages (P minus Pla: Δ ± standard error [SE]), both overall and by nodal status, for overlapping subpopulations defined by (1) a clinical composite risk score, (2) tumour infiltrating lymphocytes (TILs) percentage, and (3) human epidermal growth factor receptor 2 (HER2) FISH copy number. Because of multiplicity, a Δ of at least three SE is required to warrant attention. RESULTS: The average absolute gains in 6-year IDFS percentages were 2.8 ± 0.9 overall; 4.5 ± 1.2 for N+ and 0.1 ± 1.1 for N-. Largest gains were for patients with intermediate clinical composite risk (5.3 ± 1.9 overall; 6.9 ± 2.3 N+; 4.0 ± 3.0 N-), highest TILs percentage (6.3 ± 1.7 overall; 7.4 ± 2.4 N+; 3.2 ± 1.7 N-), and intermediate HER2 copy number (2.8 ± 1.9 overall; 7.4 ± 2.5 N+; -1.3 ± 1.9 N-), but clear evidence indicating a pattern of differential subpopulation treatment effects was lacking. CONCLUSIONS: STEPP plots for N- did not identify subpopulations clearly benefiting from adding P, and those for N+ did not identify subpopulations warranting de-escalation. TILs percentage appeared to be more predictive of P treatment effect than clinical composite risk score. TRIAL REGISTRATION: clinicaltrials.gov Identifier NCT01358877.
Authors: Davide Massa; Anna Tosi; Antonio Rosato; Valentina Guarneri; Maria Vittoria Dieci Journal: Cancers (Basel) Date: 2022-10-06 Impact factor: 6.575