Prediction of Bone Metastasis in Inflammatory Breast Cancer Using a Markov Chain Model

Author:

Fujii Takeo12,Mason Jeremy34,Chen Angela3,Kuhn Peter35674,Woodward Wendy A.28,Tripathy Debu1,Newton Paul K.957,Ueno Naoto T.12

Affiliation:

1. Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA

2. Morgan Welch Inflammatory Breast Cancer Research Program and Clinic, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA

3. Departments of Biological Sciences, Dornsife College of Letters, Arts, and Sciences, University of Southern California, Los Angeles, California, USA

4. USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA

5. Departments of Aerospace and Mechanical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA

6. Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA

7. Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California, USA

8. Department of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA

9. Mathematics, Dornsife College of Letters, Arts, and Sciences, University of Southern California, Los Angeles, California, USA

Abstract

Abstract Background Inflammatory breast cancer (IBC) is a rare yet aggressive variant of breast cancer with a high recurrence rate. We hypothesized that patterns of metastasis differ between IBC and non-IBC. We focused on the patterns of bone metastasis throughout disease progression to determine statistical differences that can lead to clinically relevant outcomes. Our primary outcome of this study is to quantify and describe this difference with a view to applying the findings to clinically relevant outcomes for patients. Subjects, Materials, and Methods We retrospectively collected data of patients with nonmetastatic IBC (n = 299) and non-IBC (n = 3,436). Probabilities of future site-specific metastases were calculated. Spread patterns were visualized to quantify the most probable metastatic pathways of progression and to categorize spread pattern based on their propensity to subsequent dissemination of cancer. Results In patients with IBC, the probabilities of developing bone metastasis after chest wall, lung, or liver metastasis as the first site of progression were high: 28%, 21%, and 21%, respectively. For patients with non-IBC, the probability of developing bone metastasis was fairly consistent regardless of initial metastasis site. Conclusion Metastatic patterns of spread differ between patients with IBC and non-IBC. Selection of patients with IBC with known liver, chest wall, and/or lung metastasis would create a population in whom to investigate effective methods for preventing future bone metastasis. Implications for Practice This study demonstrated that the patterns of metastasis leading to and following bone metastasis differ significantly between patients with inflammatory breast cancer (IBC) and those with non-IBC. Patients with IBC had a progression pattern that tended toward the development of bone metastasis if they had previously developed metastases in the liver, chest wall, and lung, rather than in other sites. Selection of patients with IBC with known liver, chest wall, and/or lung metastasis would create a population in whom to investigate effective methods for preventing future bone metastasis.

Funder

BCRF/JKTG

Morgan Welch Inflammatory Breast Cancer Research Program, a grant from the State of Texas Rare and Aggressive Breast Cancer Research Program

Novartis Pharmaceuticals Corporation

Seven Bridges

USC Institute of Urology, the USC Michelson Center for Convergent Biosciences, and the Carol Vassiliadis Fellowship

Publisher

Oxford University Press (OUP)

Subject

Cancer Research,Oncology

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