Estimation of historical control rate for a single arm de-escalation study – Application to the POSITIVE trial
Zhuoxin Sun,
Samuel M. Niman,
Olivia Pagani,
Ann H. Partridge,
Hatem A. Azim, Jr.,
Fedro A. Peccatori,
Monica Ruggeri,
Angelo Di Leo,
Marco Colleoni,
Richard D. Gelber,
Meredith M. Regan
Affiliations
Zhuoxin Sun
International Breast Cancer Study Group Statistical Center, Department of Data Sciences, Division of Biostatistics, Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA, 02215, USA
Samuel M. Niman
International Breast Cancer Study Group Statistical Center, Department of Data Sciences, Division of Biostatistics, Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA, 02215, USA
Olivia Pagani
Institute of Oncology of Southern Switzerland, Geneva University Hospitals, Swiss Group for Clinical Cancer Research (SAKK), Lugano Viganello, Switzerland
Ann H. Partridge
Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02215, USA
Hatem A. Azim, Jr.
Breast Cancer Center, Hospital Zambrano Hellion, School of Medicine, Tecnologico de Monterrey, Av. Batallon de San Patricio 112, 66278, San Pedro Garza Garcia, Mexico
Fedro A. Peccatori
Fertility and Procreation Unit, Gynecologic Oncology Program, European Institute of Oncology IRCCS, Via Ripamonti 435, 20141, Milan, Italy
Monica Ruggeri
International Breast Cancer Study Group, Program for Young Patients, Coordinating Center, Effingerstrasse 40, 3008, Bern, Switzerland
Angelo Di Leo
“Sandro Pitigliani” Medical Oncology Department, Hospital of Prato, Via Suor Niccolina 20, Prato, 59100, Italy
Marco Colleoni
Division of Medical Senology, IEO, European Institute of Oncology, IRCCS, Milan, Italy
Richard D. Gelber
International Breast Cancer Study Group Statistical Center, Department of Data Sciences, Division of Biostatistics, Dana-Farber Cancer Institute, Harvard Medical School, Harvard TH Chan School of Public Health, And Frontier Science and Technology Research Foundation, 450 Brookline Ave, Boston, MA, 02215, USA
Meredith M. Regan
International Breast Cancer Study Group Statistical Center, Department of Data Sciences, Division of Biostatistics, Dana-Farber Cancer Institute, Harvard Medical School, 450 Brookline Ave, Boston, MA, 02215, USA; Corresponding author.
Background: Although randomized controlled clinical trials are optimal to evaluate the effect of an experimental therapy, single-arm trials are required whenever randomization is unethical or not feasible, such as de-escalation studies. We propose using prospectively identified historical controls to place results of single-arm, de-escalation trials into context. Methods: POSITIVE is a prospective, single-arm study in young women with hormone-receptor-positive early breast cancer to determine if temporarily interrupting adjuvant endocrine therapy in order to become pregnant increases the risk of a breast cancer event. After 272 women enrolled in POSITIVE, we identified a cohort of 1499 SOFT/TEXT patients potentially eligible to enroll in POSITIVE who did not interrupt endocrine therapy. Method I used the SOFT/TEXT cohort to calculate annualized hazard rates by a piecewise exponential model. Method II used the SOFT/TEXT cohort to group-match SOFT/TEXT patients to POSITIVE patients; sample sets of SOFT/TEXT patients were randomly drawn 5000 times to obtain sets having patient, disease, and treatment characteristics more balanced with POSITIVE participants. Results: Compared with SOFT/TEXT, POSITIVE participants were younger, less likely to be overweight/obese, had fewer positive nodes, and fewer received aromatase inhibitor or chemotherapy. The estimated 3-year breast cancer free interval event rates were 9.5% (95% CI: 7.9%,11.1%) for Method I and 9.4% (95% CI: 7.8%,10.9%) for Method II, compared with 5.8% initially assumed when POSITIVE was designed. Conclusion: External control datasets should be identified before launching single-arm, de-escalation trials and methods applied during their conduct to provide context for interim monitoring and interpretation of the final analysis.