4.6 Article

A nomogram for individualized estimation of survival among patients with brain metastasis

Journal

NEURO-ONCOLOGY
Volume 14, Issue 7, Pages 910-918

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/neuonc/nos087

Keywords

brain metastases; nomogram; prediction; prognosis; survival

Funding

  1. Radiation Therapy Oncology Group [U10 CA21661]
  2. Case Comprehensive Cancer Center Core [NCI P30-CA043703]
  3. CCOP from the National Cancer Institute [U10 CA37422]

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Purpose: An estimated 2445 of patients with cancer develop brain metastases. Individualized estimation of survival for patients with brain metastasis could be useful for counseling patients on clinical outcomes and prognosis. Methods: De-identified data for 2367 patients with brain metastasis from 7 Radiation Therapy Oncology Group randomized trials were used to develop and internally validate a prognostic nomogram for estimation of survival among patients with brain metastasis. The prognostic accuracy for survival from 3 statistical approaches (Cox proportional hazards regression, recursive partitioning analysis [RPA], and random survival forests) was calculated using the concordance index. A nomogram for 12-month, 6-month, and median survival was generated using the most parsimonious model. Results: The majority of patients had lung cancer, controlled primary disease, no surgery, Karnofsky performance score (KPS) epsilon 70, and multiple brain metastases and were in RPA class II or had a Diagnosis-Specific Graded Prognostic Assessment (DS-GPA) score of 1.252.5. The overall median survival was 136 days (95 confidence interval, 126144 days). We built the nomogram using the model that included primary site and histology, status of primary disease, metastatic spread, age, KPS, and number of brain lesions. The potential use of individualized survival estimation is demonstrated by showing the heterogeneous distribution of the individual 12-month survival in each RPA class or DS-GPA score group. Conclusion: Our nomogram provides individualized estimates of survival, compared with current RPA and DS-GPA group estimates. This tool could be useful for counseling patients with respect to clinical outcomes and prognosis.

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