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Journal of Neuro-Oncology

, Volume 135, Issue 2, pp 403–411 | Cite as

Prediction of new brain metastases after radiosurgery: validation and analysis of performance of a multi-institutional nomogram

  • Diandra N. Ayala-PeacockEmail author
  • Albert Attia
  • Steve E. Braunstein
  • Manmeet S. Ahluwalia
  • Jaroslaw Hepel
  • Caroline Chung
  • Joseph Contessa
  • Emory McTyre
  • Ann M. Peiffer
  • John T. LucasJr
  • Scott Isom
  • Nicholas M. Pajewski
  • Rupesh Kotecha
  • Mark J. Stavas
  • Brandi R. Page
  • Lawrence Kleinberg
  • Colette Shen
  • Robert B. Taylor
  • Nasarachi E. Onyeuku
  • Andrew T. Hyde
  • Daniel Gorovets
  • Samuel T. Chao
  • Christopher Corso
  • Jimmy Ruiz
  • Kounosuke Watabe
  • Stephen B. Tatter
  • Gelareh Zadeh
  • Veronica L. S. Chiang
  • John B. Fiveash
  • Michael D. Chan
Clinical Study

Abstract

Stereotactic radiosurgery (SRS) without whole brain radiotherapy (WBRT) for brain metastases can avoid WBRT toxicities, but with risk of subsequent distant brain failure (DBF). Sole use of number of metastases to triage patients may be an unrefined method. Data on 1354 patients treated with SRS monotherapy from 2000 to 2013 for new brain metastases was collected across eight academic centers. The cohort was divided into training and validation datasets and a prognostic model was developed for time to DBF. We then evaluated the discrimination and calibration of the model within the validation dataset, and confirmed its performance with an independent contemporary cohort. Number of metastases (≥8, HR 3.53 p = 0.0001), minimum margin dose (HR 1.07 p = 0.0033), and melanoma histology (HR 1.45, p = 0.0187) were associated with DBF. A prognostic index derived from the training dataset exhibited ability to discriminate patients’ DBF risk within the validation dataset (c-index = 0.631) and Heller’s explained relative risk (HERR) = 0.173 (SE = 0.048). Absolute number of metastases was evaluated for its ability to predict DBF in the derivation and validation datasets, and was inferior to the nomogram. A nomogram high-risk threshold yielding a 2.1-fold increased need for early WBRT was identified. Nomogram values also correlated to number of brain metastases at time of failure (r = 0.38, p < 0.0001). We present a multi-institutionally validated prognostic model and nomogram to predict risk of DBF and guide risk-stratification of patients who are appropriate candidates for radiosurgery versus upfront WBRT.

Keywords

Brain metastases Distant brain failure Stereotactic radiosurgery Multi-Institutional nomogram 

Notes

Funding

S. Isom and N. Pajewski funding via Wake Forest Comprehensive Cancer Center Grant (P30 CA012197-40). Otherwise no additional funding sources.

Compliance with ethical standards

Conflict of interest

None.

Ethical approval

This data is a retrospective review. Data collection was in accordance with all the individual institution’s IRB standards.

Research involving human and animal participants

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

11060_2017_2588_MOESM1_ESM.docx (17 kb)
Supplementary material 1 (DOCX 17 KB)

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Diandra N. Ayala-Peacock
    • 1
    • 2
    Email author
  • Albert Attia
    • 2
  • Steve E. Braunstein
    • 3
  • Manmeet S. Ahluwalia
    • 4
  • Jaroslaw Hepel
    • 5
  • Caroline Chung
    • 6
    • 16
  • Joseph Contessa
    • 7
  • Emory McTyre
    • 1
  • Ann M. Peiffer
    • 1
  • John T. LucasJr
    • 1
  • Scott Isom
    • 8
  • Nicholas M. Pajewski
    • 8
  • Rupesh Kotecha
    • 4
  • Mark J. Stavas
    • 2
  • Brandi R. Page
    • 9
  • Lawrence Kleinberg
    • 9
  • Colette Shen
    • 9
  • Robert B. Taylor
    • 10
  • Nasarachi E. Onyeuku
    • 1
  • Andrew T. Hyde
    • 10
  • Daniel Gorovets
    • 5
  • Samuel T. Chao
    • 4
  • Christopher Corso
    • 7
  • Jimmy Ruiz
    • 11
  • Kounosuke Watabe
    • 12
  • Stephen B. Tatter
    • 13
  • Gelareh Zadeh
    • 14
  • Veronica L. S. Chiang
    • 7
    • 15
  • John B. Fiveash
    • 10
  • Michael D. Chan
    • 1
  1. 1.Department of Radiation OncologyWake Forest School of MedicineWinston-SalemUSA
  2. 2.Department of Radiation OncologyVanderbilt University School of MedicineNashvilleUSA
  3. 3.Department of Radiation OncologyUniversity of California San FranciscoSan FranciscoUSA
  4. 4.Brain Tumor and Neuro-Oncology Center, Neurological InstituteCleveland Clinic FoundationClevelandUSA
  5. 5.Department of Radiation OncologyBrown University Alpert Medical SchoolProvidenceUSA
  6. 6.Department of Radiation OncologyPrincess Margaret Cancer CenterTorontoCanada
  7. 7.Department of Therapeutic Radiology/Radiation OncologyYale University School of MedicineNew HavenUSA
  8. 8.Department of Biostatistical Sciences, Division of Public Health SciencesWake Forest School of MedicineWinston-SalemUSA
  9. 9.Department of Radiation OncologyJohns Hopkins UniversityBaltimoreUSA
  10. 10.Department of Radiation OncologyUniversity of Alabama-BirminghamBirminghamUSA
  11. 11.Department of MedicineWake Forest School of MedicineWinston-SalemUSA
  12. 12.Department of Cancer BiologyWake Forest School of MedicineWinston-SalemUSA
  13. 13.Department of NeurosurgeryWake Forest School of MedicineWinston-SalemUSA
  14. 14.Division of NeurosurgeryUniversity of TorontoTorontoCanada
  15. 15.Department of NeurosurgeryYale University School of MedicineNew HavenUSA
  16. 16.Department of Radiation OncologyMD Anderson Cancer CenterHoustonUSA

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