Literature DB >> 18056680

Combined use of clinical and pathologic staging variables to define outcomes for breast cancer patients treated with neoadjuvant therapy.

Jacqueline S Jeruss1, Elizabeth A Mittendorf, Susan L Tucker, Ana M Gonzalez-Angulo, Thomas A Buchholz, Aysegul A Sahin, Janice N Cormier, Aman U Buzdar, Gabriel N Hortobagyi, Kelly K Hunt.   

Abstract

PURPOSE: Neoadjuvant chemotherapy is being used with increasing frequency for operable breast cancer. We hypothesized that by using clinical and pathologic staging parameters, in conjunction with biologic tumor markers, a novel means of determining prognosis for patients treated with neoadjuvant chemotherapy could be facilitated. PATIENTS AND METHODS: A prospective database of patients treated with neoadjuvant chemotherapy from 1997 to 2003 was reviewed, and 932 patients meeting inclusion criteria were identified. Clinical and pathologic tumor characteristics, treatment regimens, and patient outcomes were recorded. Cox proportional hazards models were used to create two prognostic scoring systems. American Joint Committee on Cancer (AJCC) clinical and pathologic staging parameters and biologic tumor markers were investigated to devise the scoring systems.
RESULTS: Median follow-up time was 5 years (range, 0.4 to 9.4 years). Five-year disease-specific survival rate was 96% for patients who experienced a pathologic complete response (pCR; n = 130) compared with 87% for patients who did not have a pCR (n = 802; P = .001). Two scoring systems, based on summing binary indicators for clinical substages >/= IIB and >/= IIIB, pathologic substages >/= ypIIA and >/= ypIIIC, negative estrogen receptor status, and grade 3 pathology, were devised to predict 5-year patient outcomes. These scoring systems facilitated separation of the study population into more refined subgroups by outcome than the current AJCC staging system.
CONCLUSION: The scoring systems derived in this work provide a novel means for evaluating prognosis after neoadjuvant therapy. Future work will focus on prospective validation of these scoring systems and refinement of the scoring systems through addition of new biologic markers.

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Year:  2007        PMID: 18056680     DOI: 10.1200/JCO.2007.11.5352

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  49 in total

1.  [Importance of mammography, sonography and MRI for surveillance of neoadjuvant chemotherapy for locally advanced breast cancer].

Authors:  T Schlossbauer; M Reiser; K Hellerhoff
Journal:  Radiologe       Date:  2010-11       Impact factor: 0.635

2.  Locoregional risk assessment after neoadjuvant chemotherapy in patients with primary breast cancer: clinical utility of the CPS + EG score.

Authors:  Laura L Michel; Laura Sommer; Rosa González Silos; Justo Lorenzo Bermejo; Alexandra von Au; Julia Seitz; André Hennigs; Katharina Smetanay; Michael Golatta; Jörg Heil; Florian Schütz; Christof Sohn; Andreas Schneeweiss; Frederik Marmé
Journal:  Breast Cancer Res Treat       Date:  2019-06-24       Impact factor: 4.872

3.  ER, PgR, HER-2, Ki-67, topoisomerase IIα, and nm23-H1 proteins expression as predictors of pathological complete response to neoadjuvant chemotherapy for locally advanced breast cancer.

Authors:  Xi-ru Li; Mei Liu; Yan-jun Zhang; Jian-dong Wang; Yi-qiong Zheng; Jie Li; Bing Ma; Xin Song
Journal:  Med Oncol       Date:  2010-09-25       Impact factor: 3.064

Review 4.  Neoadjuvant chemotherapy for breast cancer-background for the indication of locoregional treatment.

Authors:  David Krug; René Baumann; Wilfried Budach; Jürgen Dunst; Petra Feyer; Rainer Fietkau; Wulf Haase; Wolfgang Harms; Thomas Hehr; Marc D Piroth; Felix Sedlmayer; Rainer Souchon; Frederik Wenz; Rolf Sauer
Journal:  Strahlenther Onkol       Date:  2018-07-04       Impact factor: 3.621

5.  Machine learning for predicting the response of breast cancer to neoadjuvant chemotherapy.

Authors:  Subramani Mani; Yukun Chen; Xia Li; Lori Arlinghaus; A Bapsi Chakravarthy; Vandana Abramson; Sandeep R Bhave; Mia A Levy; Hua Xu; Thomas E Yankeelov
Journal:  J Am Med Inform Assoc       Date:  2013-04-24       Impact factor: 4.497

6.  [Therapy monitoring of neoadjuvant therapy with MRI. RECIST and functional imaging].

Authors:  S Grandl; M Ingrisch; K Hellerhoff
Journal:  Radiologe       Date:  2014-03       Impact factor: 0.635

7.  Neo-Bioscore in Guiding Post-surgical Therapy in Patients With Triple-negative Breast Cancer Who Received Neoadjuvant Chemotherapy.

Authors:  Yoriko Hasegawa; Nobuaki Matsubara; Takahiro Kogawa; Yoichi Naito; Kenichi Harano; Ako Hosono; Tatsuya Onishi; Takashi Hojo; Mototsugu Shimokawa; Toru Mukohara
Journal:  In Vivo       Date:  2021 Mar-Apr       Impact factor: 2.155

8.  Evaluation of the stage IB designation of the American Joint Committee on Cancer staging system in breast cancer.

Authors:  Elizabeth A Mittendorf; Karla V Ballman; Linda M McCall; Min Yi; Aysegul A Sahin; Isabelle Bedrosian; Nora Hansen; Sheryl Gabram; Thelma Hurd; Armando E Giuliano; Kelly K Hunt
Journal:  J Clin Oncol       Date:  2014-12-08       Impact factor: 44.544

9.  Quality of pathologic response and surgery correlate with survival for patients with completely resected bladder cancer after neoadjuvant chemotherapy.

Authors:  Guru Sonpavde; Bryan H Goldman; V O Speights; Seth P Lerner; David P Wood; Nicholas J Vogelzang; Donald L Trump; Ronald B Natale; H Barton Grossman; E David Crawford
Journal:  Cancer       Date:  2009-09-15       Impact factor: 6.860

10.  Predicting pathologic response to neoadjuvant chemotherapy in breast cancer by using MR imaging and quantitative 1H MR spectroscopy.

Authors:  Hyeon-Man Baek; Jeon-Hor Chen; Ke Nie; Hon J Yu; Shadfar Bahri; Rita S Mehta; Orhan Nalcioglu; Min-Ying Su
Journal:  Radiology       Date:  2009-03-10       Impact factor: 11.105

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