Literature DB >> 26286912

Relationship between Complete Pathologic Response to Neoadjuvant Chemotherapy and Survival in Triple-Negative Breast Cancer.

Christos Hatzis1, W Fraser Symmans2, Ya Zhang2, Rebekah E Gould2, Stacy L Moulder3, Kelly K Hunt4, Maysa Abu-Khalaf5, Erin W Hofstatter5, Donald Lannin6, Anees B Chagpar6, Lajos Pusztai1.   

Abstract

PURPOSE: Pathologic complete response (pCR) to neoadjuvant chemotherapy reflects the cytotoxic efficacy of a drug, but patient survival is influenced by many other factors. The purpose of this study was to assess the relationship between increased pCR rate and trial-level survival benefit in triple-negative breast cancer (TNBC). EXPERIMENTAL
DESIGN: We used bootstrap resampling from a neoadjuvant trial to simulate trials with different pCR rates. We used estimates from Adjuvant!Online to simulate trial populations with different baseline prognosis and estimated survival improvements associated with changes in pCR rate.
RESULTS: Assuming that survival is similar for patients with pCR regardless of treatment arm, a linear relationship exists between increasing pCR rate and increasing recurrence-free survival (RFS). The slope is equal to the difference in survival between those with pCR and residual disease, which in turn is influenced by (i) the baseline prognosis of the trial population, (ii) interactions between prognostic variables and pCR, and (iii) the efficacy of the postneoadjuvant therapies. For example, if the pCR rates are 30% and 60% (OR = 3.5) and the 10-year RFS of the control arm is 0.74, the trial would require 3,550 patients per arm, whereas if the RFS is 0.54, the trial would require only 425 patients per arm to detect significant survival benefit.
CONCLUSIONS: We provide a framework for understanding the relationship between pCR and overall survival benefit that can help inform the design of neoadjuvant trials aiming to demonstrate improved survival from a regimen that results in higher pCR rate. ©2015 American Association for Cancer Research.

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Year:  2015        PMID: 26286912     DOI: 10.1158/1078-0432.CCR-14-3304

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  20 in total

1.  Triple-negative breast cancer cell line sensitivity to englerin A identifies a new, targetable subtype.

Authors:  Corena V Grant; Chase M Carver; Shayne D Hastings; Karthik Ramachandran; Madesh Muniswamy; April L Risinger; John A Beutler; Susan L Mooberry
Journal:  Breast Cancer Res Treat       Date:  2019-06-22       Impact factor: 4.872

2.  Right-Sizing Adjuvant and Neoadjuvant Clinical Trials in Breast Cancer.

Authors:  Donald A Berry
Journal:  Clin Cancer Res       Date:  2015-10-28       Impact factor: 12.531

3.  Long-Term Prognostic Risk After Neoadjuvant Chemotherapy Associated With Residual Cancer Burden and Breast Cancer Subtype.

Authors:  W Fraser Symmans; Caimiao Wei; Rebekah Gould; Xian Yu; Ya Zhang; Mei Liu; Andrew Walls; Alex Bousamra; Maheshwari Ramineni; Bruno Sinn; Kelly Hunt; Thomas A Buchholz; Vicente Valero; Aman U Buzdar; Wei Yang; Abenaa M Brewster; Stacy Moulder; Lajos Pusztai; Christos Hatzis; Gabriel N Hortobagyi
Journal:  J Clin Oncol       Date:  2017-01-30       Impact factor: 44.544

4.  Mid-treatment Ultrasound Descriptors as Qualitative Imaging Biomarkers of Pathologic Complete Response in Patients with Triple-Negative Breast Cancer.

Authors:  Rosalind P Candelaria; Beatriz E Adrada; Deanna L Lane; Gaiane M Rauch; Stacy L Moulder; Alastair M Thompson; Roland L Bassett; Elsa M Arribas; Huong T Le-Petross; Jessica W T Leung; David A Spak; Elizabeth E Ravenberg; Jason B White; Vicente Valero; Wei T Yang
Journal:  Ultrasound Med Biol       Date:  2022-03-14       Impact factor: 2.998

5.  Kinetic information from dynamic contrast-enhanced MRI enables prediction of residual cancer burden and prognosis in triple-negative breast cancer: a retrospective study.

Authors:  Ayane Yamaguchi; Maya Honda; Hiroshi Ishiguro; Masako Kataoka; Tatsuki R Kataoka; Hanako Shimizu; Masae Torii; Yukiko Mori; Nobuko Kawaguchi-Sakita; Kentaro Ueno; Masahiro Kawashima; Masahiro Takada; Eiji Suzuki; Yuji Nakamoto; Kosuke Kawaguchi; Masakazu Toi
Journal:  Sci Rep       Date:  2021-05-12       Impact factor: 4.379

6.  Design of phase III trials with long-term survival outcomes based on short-term binary results.

Authors:  Marta Bofill Roig; Yu Shen; Guadalupe Gómez Melis
Journal:  Stat Med       Date:  2021-05-03       Impact factor: 2.497

7.  I-SPY 2: optimising cancer drug development in the 21st century.

Authors:  Rupert Bartsch; Evandro de Azambuja
Journal:  ESMO Open       Date:  2016-11-15

8.  Ki-67 as a controversial predictive and prognostic marker in breast cancer patients treated with neoadjuvant chemotherapy.

Authors:  Balázs Ács; Veronika Zámbó; Laura Vízkeleti; A Marcell Szász; Lilla Madaras; Gyöngyvér Szentmártoni; Tímea Tőkés; Béla Á Molnár; István Artúr Molnár; Stefan Vári-Kakas; Janina Kulka; Anna-Mária Tőkés
Journal:  Diagn Pathol       Date:  2017-02-21       Impact factor: 2.644

9.  Predictors of Chemosensitivity in Triple Negative Breast Cancer: An Integrated Genomic Analysis.

Authors:  Tingting Jiang; Weiwei Shi; Vikram B Wali; Lőrinc S Pongor; Charles Li; Rosanna Lau; Balázs Győrffy; Richard P Lifton; William F Symmans; Lajos Pusztai; Christos Hatzis
Journal:  PLoS Med       Date:  2016-12-13       Impact factor: 11.069

Review 10.  My burning issues in the neoadjuvant treatment for breast cancer.

Authors:  Elisabeth S Bergen; Rupert Bartsch
Journal:  Memo       Date:  2017-12-22
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