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A clinical calculator to predict disease outcomes in women with hormone receptor-positive advanced breast cancer treated with first-line endocrine therapy

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Abstract

Purpose

Endocrine therapy (ET) is an effective strategy to treat hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2−) advanced breast cancer (ABC) but nearly all patients eventually progress. Our goal was to develop and validate a web-based clinical calculator for predicting disease outcomes in women with HR+ABC who are candidates for receiving first-line single-agent ET.

Methods

The meta-database comprises 891 patient-level data from the control arms of five contemporary clinical trials where patients received first-line single-agent ET (either aromatase inhibitor or fulvestrant) for ABC. Risk models were constructed for predicting 24-months progression-free survival (PFS-24) and 24-months overall survival (OS-24). Final models were internally validated for calibration and discrimination using ten-fold cross-validation.

Results

Higher number of sites of metastases, measurable disease, younger age, lower body mass index, negative PR status, and prior endocrine therapy were associated with worse PFS. Final PFS and OS models were well-calibrated and associated with cross-validated time-dependent area under the curve (AUC) of 0.61 and 0.62, respectively.

Conclusions

The proposed ABC calculator is internally valid and can accurately predict disease outcomes. It may be used to predict patient prognosis, aid planning of first-line treatment strategies, and facilitate risk stratification for future clinical trials in patients with HR+ABC. Future validation of the proposed models in independent patient cohorts is warranted.

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Funding

Research reported in this article was supported by the National Cancer Institute of the National Institutes of Health under Award Number P50 CA116201 (Mayo Clinic Breast Cancer Specialized Program of Research Excellence) (MP, FC, and MPG).

Author information

Authors and Affiliations

  1. Department of Public Health Sciences, University of Chicago, Chicago, IL, USA

    Mei-Yin C. Polley

  2. Eli Lilly, Indianapolis, IN, USA

    Maura N. Dickler

  3. Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA

    Jason Sinnwell & Kathleen Tenner

  4. GEICAM, Madrid, Spain

    Juan de la Haba & Matthew P. Goetz

  5. German Breast Group (GBG), Neu-Isenburg, Germany

    Sibylle Loibl

  6. Department of Oncology, Mayo Clinic, Rochester, MN, USA

    Matthew P. Goetz

  7. Karolinska Institute, Stockholm, Sweden

    Jonas Bergh

  8. University of Nottingham, Nottingham, UK

    John Roberston

  9. Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA

    Fergus Couch

  10. Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA

    Matthew J. Ellis

  11. Gregorio Marañón University Hospital, Madrid, Spain

    Miguel Martin

Authors
  1. Mei-Yin C. Polley
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  2. Maura N. Dickler
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  3. Jason Sinnwell
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  4. Kathleen Tenner
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  8. Jonas Bergh
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  9. John Roberston
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  12. Miguel Martin
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Corresponding author

Correspondence to Mei-Yin C. Polley.

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Conflict of interest

Dr. Martin reports research Grants from Roche, PUMA and Novartis, consulting/advisory fees from AstraZeneca, Amgen, Taiho Oncology, Roche/Genentech, Novartis, PharmaMar, Eli Lilly, PUMA, Taiho Oncology, Daiichi Sankyo and Pfizer and speakers’ honoraria from AstraZeneca, Amgen, Roche/Genentech, Novartis, and Pfizer. Dr. Goetz reports personal fees from Genomic Health, consulting fees from Lilly, Biovica, Novartis, Sermonix, Context Pharm, Pfizer, Biotheranostics, and grants from Pfizer, Lilly, and Sermonix.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

The need for obtaining informed consent was waived by the institutional review board, given that this study was retrospective and non-interventional.

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Polley, MY.C., Dickler, M.N., Sinnwell, J. et al. A clinical calculator to predict disease outcomes in women with hormone receptor-positive advanced breast cancer treated with first-line endocrine therapy. Breast Cancer Res Treat 189, 15–23 (2021). https://doi.org/10.1007/s10549-021-06319-z

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