BACKGROUND: The genetic and clinical heterogeneity of breast cancer makes the identification of effective therapies challenging. We designed I-SPY 2, a phase 2, multicenter, adaptively randomized trial to screen multiple experimental regimens in combination with standard neoadjuvant chemotherapy for breast cancer. The goal is to match experimental regimens with responding cancer subtypes. We report results for veliparib, a poly(ADP-ribose) polymerase (PARP) inhibitor, combined with carboplatin. METHODS: In this ongoing trial, women are eligible for participation if they have stage II or III breast cancer with a tumor 2.5 cm or larger in diameter; cancers are categorized into eight biomarker subtypes on the basis of status with regard to human epidermal growth factor receptor 2 (HER2), hormone receptors, and a 70-gene assay. Patients undergo adaptive randomization within each biomarker subtype to receive regimens that have better performance than the standard therapy. Regimens are evaluated within 10 biomarker signatures (i.e., prospectively defined combinations of biomarker subtypes). Veliparib-carboplatin plus standard therapy was considered for HER2-negative tumors and was therefore evaluated in 3 signatures. The primary end point is pathological complete response. Tumor volume changes measured by magnetic resonance imaging during treatment are used to predict whether a patient will have a pathological complete response. Regimens move on from phase 2 if and when they have a high Bayesian predictive probability of success in a subsequent phase 3 neoadjuvant trial within the biomarker signature in which they performed well. RESULTS: With regard to triple-negative breast cancer, veliparib-carboplatin had an 88% predicted probability of success in a phase 3 trial. A total of 72 patients were randomly assigned to receive veliparib-carboplatin, and 44 patients were concurrently assigned to receive control therapy; at the completion of chemotherapy, the estimated rates of pathological complete response in the triple-negative population were 51% (95% Bayesian probability interval [PI], 36 to 66%) in the veliparib-carboplatin group versus 26% (95% PI, 9 to 43%) in the control group. The toxicity of veliparib-carboplatin was greater than that of the control. CONCLUSIONS: The process used in our trial showed that veliparib-carboplatin added to standard therapy resulted in higher rates of pathological complete response than standard therapy alone specifically in triple-negative breast cancer. (Funded by the QuantumLeap Healthcare Collaborative and others; I-SPY 2 TRIAL ClinicalTrials.gov number, NCT01042379.).
RCT Entities:
BACKGROUND: The genetic and clinical heterogeneity of breast cancer makes the identification of effective therapies challenging. We designed I-SPY 2, a phase 2, multicenter, adaptively randomized trial to screen multiple experimental regimens in combination with standard neoadjuvant chemotherapy for breast cancer. The goal is to match experimental regimens with responding cancer subtypes. We report results for veliparib, a poly(ADP-ribose) polymerase (PARP) inhibitor, combined with carboplatin. METHODS: In this ongoing trial, women are eligible for participation if they have stage II or III breast cancer with a tumor 2.5 cm or larger in diameter; cancers are categorized into eight biomarker subtypes on the basis of status with regard to humanepidermal growth factor receptor 2 (HER2), hormone receptors, and a 70-gene assay. Patients undergo adaptive randomization within each biomarker subtype to receive regimens that have better performance than the standard therapy. Regimens are evaluated within 10 biomarker signatures (i.e., prospectively defined combinations of biomarker subtypes). Veliparib-carboplatin plus standard therapy was considered for HER2-negative tumors and was therefore evaluated in 3 signatures. The primary end point is pathological complete response. Tumor volume changes measured by magnetic resonance imaging during treatment are used to predict whether a patient will have a pathological complete response. Regimens move on from phase 2 if and when they have a high Bayesian predictive probability of success in a subsequent phase 3 neoadjuvant trial within the biomarker signature in which they performed well. RESULTS: With regard to triple-negative breast cancer, veliparib-carboplatin had an 88% predicted probability of success in a phase 3 trial. A total of 72 patients were randomly assigned to receive veliparib-carboplatin, and 44 patients were concurrently assigned to receive control therapy; at the completion of chemotherapy, the estimated rates of pathological complete response in the triple-negative population were 51% (95% Bayesian probability interval [PI], 36 to 66%) in the veliparib-carboplatin group versus 26% (95% PI, 9 to 43%) in the control group. The toxicity of veliparib-carboplatin was greater than that of the control. CONCLUSIONS: The process used in our trial showed that veliparib-carboplatin added to standard therapy resulted in higher rates of pathological complete response than standard therapy alone specifically in triple-negative breast cancer. (Funded by the QuantumLeap Healthcare Collaborative and others; I-SPY 2 TRIAL ClinicalTrials.gov number, NCT01042379.).
Authors: Gunter von Minckwitz; Andreas Schneeweiss; Sibylle Loibl; Christoph Salat; Carsten Denkert; Mahdi Rezai; Jens U Blohmer; Christian Jackisch; Stefan Paepke; Bernd Gerber; Dirk M Zahm; Sherko Kümmel; Holger Eidtmann; Peter Klare; Jens Huober; Serban Costa; Hans Tesch; Claus Hanusch; Jörn Hilfrich; Fariba Khandan; Peter A Fasching; Bruno V Sinn; Knut Engels; Keyur Mehta; Valentina Nekljudova; Michael Untch Journal: Lancet Oncol Date: 2014-04-30 Impact factor: 41.316
Authors: Cherrie K Donawho; Yan Luo; Yanping Luo; Thomas D Penning; Joy L Bauch; Jennifer J Bouska; Velitchka D Bontcheva-Diaz; Bryan F Cox; Theodore L DeWeese; Larry E Dillehay; Debra C Ferguson; Nayereh S Ghoreishi-Haack; David R Grimm; Ran Guan; Edward K Han; Rhonda R Holley-Shanks; Boris Hristov; Kenneth B Idler; Ken Jarvis; Eric F Johnson; Lawrence R Kleinberg; Vered Klinghofer; Loren M Lasko; Xuesong Liu; Kennan C Marsh; Thomas P McGonigal; Jonathan A Meulbroek; Amanda M Olson; Joann P Palma; Luis E Rodriguez; Yan Shi; Jason A Stavropoulos; Alan C Tsurutani; Gui-Dong Zhu; Saul H Rosenberg; Vincent L Giranda; David J Frost Journal: Clin Cancer Res Date: 2007-05-01 Impact factor: 12.531
Authors: W Fraser Symmans; Florentia Peintinger; Christos Hatzis; Radhika Rajan; Henry Kuerer; Vicente Valero; Lina Assad; Anna Poniecka; Bryan Hennessy; Marjorie Green; Aman U Buzdar; S Eva Singletary; Gabriel N Hortobagyi; Lajos Pusztai Journal: J Clin Oncol Date: 2007-09-04 Impact factor: 44.544
Authors: Laura J Esserman; Donald A Berry; Maggie C U Cheang; Christina Yau; Charles M Perou; Lisa Carey; Angela DeMichele; Joe W Gray; Kathleen Conway-Dorsey; Marc E Lenburg; Meredith B Buxton; Sarah E Davis; Laura J van't Veer; Clifford Hudis; Koei Chin; Denise Wolf; Helen Krontiras; Leslie Montgomery; Debu Tripathy; Constance Lehman; Minetta C Liu; Olufunmilayo I Olopade; Hope S Rugo; John T Carpenter; Chad Livasy; Lynn Dressler; David Chhieng; Baljit Singh; Carolyn Mies; Joseph Rabban; Yunni-Yi Chen; Dilip Giri; Alfred Au; Nola Hylton Journal: Breast Cancer Res Treat Date: 2011-12-25 Impact factor: 4.872
Authors: Tessa G Steenbruggen; Mette S van Ramshorst; Marleen Kok; Sabine C Linn; Carolien H Smorenburg; Gabe S Sonke Journal: Drugs Date: 2017-08 Impact factor: 9.546
Authors: Jennifer K Litton; Marion E Scoggins; Kenneth R Hess; Beatriz E Adrada; Rashmi K Murthy; Senthil Damodaran; Sarah M DeSnyder; Abenaa M Brewster; Carlos H Barcenas; Vicente Valero; Gary J Whitman; Jill Schwartz-Gomez; Elizabeth A Mittendorf; Alastair M Thompson; Thorunn Helgason; Nuhad Ibrahim; Helen Piwnica-Worms; Stacy L Moulder; Banu K Arun Journal: J Clin Oncol Date: 2019-08-28 Impact factor: 44.544
Authors: Lillian L Siu; S Percy Ivy; Erica L Dixon; Amy E Gravell; Steven A Reeves; Gary L Rosner Journal: Clin Cancer Res Date: 2017-09-01 Impact factor: 12.531
Authors: Carolyn S Calfee; Kevin L Delucchi; Pratik Sinha; Michael A Matthay; Jonathan Hackett; Manu Shankar-Hari; Cliona McDowell; John G Laffey; Cecilia M O'Kane; Daniel F McAuley Journal: Lancet Respir Med Date: 2018-08-02 Impact factor: 30.700
Authors: Si-Si Wang; Maike Zimmermann; Hongyong Zhang; Tzu-Yin Lin; Michael Malfatti; Kurt Haack; Kenneth W Turteltaub; George D Cimino; Ralph de Vere White; Chong-Xian Pan; Paul T Henderson Journal: Int J Cancer Date: 2017-05-15 Impact factor: 7.396