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Validation and optimization of a web-based nomogram for predicting survival of patients with newly diagnosed glioblastoma

  • Nalee Kim
  • Jee Suk Chang
  • Chan Woo Wee
  • In Ah Kim
  • Jong Hee Chang
  • Hye Sun Lee
  • Se Hoon Kim
  • Seok-Gu Kang
  • Eui Hyun Kim
  • Hong In Yoon
  • Jun Won Kim
  • Chang-Ki Hong
  • Jaeho Cho
  • Eunji Kim
  • Tae Min Kim
  • Yu Jung Kim
  • Chul-Kee Park
  • Jin Wook Kim
  • Chae-Yong Kim
  • Seung Hong Choi
  • Jae Hyoung Kim
  • Sung-Hye Park
  • Gheeyoung Choe
  • Soon-Tae Lee
  • Il Han KimEmail author
  • Chang-Ok SuhEmail author
Original Article
  • 155 Downloads

Abstract

Purpose

To optimize and validate a current (NRG [a newly constituted National Clinical Trials Network group through National Surgical Adjuvant Breast and Bowel Project [NSABP], the Radiation Therapy Oncology Group [RTOG] and the Gynecologic Oncology Group (GOG)]) nomogram for glioblastoma patients as part of continuous validation.

Methods

We identified patients newly diagnosed with glioblastoma who were treated with temozolomide-based chemoradiotherapy between 2006 and 2016 at three large-volume hospitals. The extent of resection was determined via postoperative MRI. The discrimination and calibration abilities of the prediction algorithm were assessed; if additional factors were identified as independent prognostic factors, updated models were developed using the data from two hospitals and were externally validated using the third hospital. Models were internally validated using cross-validation and bootstrapping.

Results

A total of 837 patients met the eligibility criteria. The median overall survival (OS) was 20.0 (95% CI 18.5–21.5) months. The original nomogram was able to estimate the 6‑, 12-, and 24-month OS probabilities, but it slightly underestimated the OS values. In multivariable Cox regression analysis, MRI-defined total resection had a greater impact on OS than that shown by the original nomogram, and two additional factors—IDH1 mutation and tumor contacting subventricular zone—were newly identified as independent prognostic values. An updated nomogram incorporating these new variables outperformed the original nomogram (C-index at 6, 12, 24, and 36 months: 0.728, 0.688, 0.688, and 0.685, respectively) and was well calibrated. External validation using an independent cohort showed C‑indices of 0.787, 0.751, 0.719, and 0.702 at 6, 12, 24, and 36 months, respectively, and was well calibrated.

Conclusion

An updated and validated nomogram incorporating the contemporary parameters can estimate individual survival outcomes in patients with glioblastoma with better accuracy.

Keywords

Model Validation Subventricular zone IDH1 mutation Extent of resection 

Validierung und Optimierung eines webbasierten Nomogramms zur Vorhersage des Überlebens von Patienten mit neu diagnostiziertem Glioblastom

Zusammenfassung

Ziel der Arbeit

Ziel der vorliegenden Arbeit war die Optimierung und Validierung eines aktuellen NRG-Nomogramms für Glioblastompatienten im Rahmen einer kontinuierlichen Validierung.

Methoden

Die Autoren identifizierten Patienten mit neu diagnostiziertem Glioblastom, die zwischen 2006 und 2016 in 3 großen Krankenhäusern mit einer temozolomidbasierten Radiochemotherapie behandelt wurden. Das Ausmaß der Resektion wurde mittels postoperativer Magnetresonanztomographie (MRT) bestimmt. Die Diskriminierung- und Kalibrierungsfähigkeit des Prognosealgorithmus wurden bewertet. Unter Einbeziehung zusätzlicher Faktoren, die als unabhängige prognostische Faktoren identifiziert wurden, entwickelten die Autoren aktualisierte Modelle unter Verwendung der Daten von 2 Zentren. Diese wurden mit Daten aus dem dritten Zentrum extern validiert. Die Modelle wurden mithilfe der Kreuzvalidierung und Bootstrapping intern bestätigt.

Ergebnisse

Insgesamt 837 Patienten erfüllten die Einschlusskriterien. Das mediane Gesamtüberleben (OS) betrug 20,0 (95%-Konfidenzintervall, 95%-KI: 18,5–21,5) Monate. Mit dem ursprünglichen Nomogramm konnten die OS-Wahrscheinlichkeiten für 6, 12 und 24 Monate geschätzt werden, die OS-Werte wurden jedoch geringfügig unterschätzt. In der multivariablen Cox-Regressionsanalyse wirkte sich das MRT-definierte Ausmaß der Resektion stärker auf das OS als im ursprünglichen Nomogramm aus. Es wurden 2 zusätzliche Faktoren, eine IDH1-Mutation und der Kontakt des Tumors zur subventrikulären Zone, neu als unabhängige prognostische Werte definiert. Ein aktualisiertes Nomogramm, das diese neuen Variablen enthält, ist gut kalibriert und war dem ursprünglichen Nomogramm (C-Index bei 6, 12, 24 und 36 Monaten: 0,728; 0,688; 0,688 und 0,685) überlegen. Die externe Validierung mit einer unabhängigen Kohorte ist gut kalibriert und ergab C‑Indizes von 0,787; 0,751; 0,719 und 0,702 bei jeweils 6, 12, 24 und 36 Monaten.

Schlussfolgerungen

Mit einem aktualisierten und validierten Nomogramm, welches aktualisierte Parameter berücksichtigt, ist es möglich, die individuelle Überlebensfähigkeit von Patienten mit einem Glioblastom mit größerer Genauigkeit abzuschätzen.

Schlüsselwörter

Modell Validerung Subventrikulare Zone IDH1-Mutation Ausmaß der Resektion 

Notes

Acknowledgements

The authors would like to thank Franziska Walter (LMU University Hospital, 81377, Munich, Germany) for her help with the German abstract of this manuscript.

Author Contribution

N.K., J.S.C, C.W.W, and I.A.K analyzed the data. J.H.C, S.H.K., S.K., E.H.K., H.I.Y., J.W.K., C.H., J.C., E.K., T.M.K., Y.J.K., C.P., J.W.K., C.K., S.H.C, J.H.K., S.P., G.C, and S.L. provided clinical samples, reviewed and provided insight to the manuscript. H.S.L provided the statistical analysis N.K., J.S.C., I.H.K., and C.O.S designed the study and supervised the overall project. N.K. and J.S.C. wrote the manuscript.

Compliance with ethical guidelines

Conflict of interest

N. Kim, J.S. Chang, C.W. Wee, I.A. Kim, J.H. Chang, H.S. Lee, S.H. Kim, S.-G. Kang, E.H. Kim, H.I. Yoon, J.W. Kim, C.-K. Hong, J. Cho, E. Kim, T.M. Kim, Y.J. Kim, C.-K. Park, J.W. Kim, C.-Y. Kim, S.H. Choi, J.H. Kim, S.-H. Park, G. Choe, S.-T. Lee, I.H. Kim, and C.-O. Suh declare that they have no competing interests.

Ethical standards

All procedures performed in studies involving human participants or on human tissue were in accordance with the ethical standards of the institutional and/or national research committee and with the 1975 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was waived due to the retrospective nature of this study.

Supplementary material

66_2019_1512_MOESM1_ESM.tif (515 kb)
Online Resource 1: Kaplan–Meier survival curves for the development set (N = 739) and validation set (N = 98).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Nalee Kim
    • 1
  • Jee Suk Chang
    • 1
  • Chan Woo Wee
    • 2
  • In Ah Kim
    • 2
  • Jong Hee Chang
    • 3
  • Hye Sun Lee
    • 4
  • Se Hoon Kim
    • 5
  • Seok-Gu Kang
    • 3
  • Eui Hyun Kim
    • 3
  • Hong In Yoon
    • 1
  • Jun Won Kim
    • 6
  • Chang-Ki Hong
    • 7
  • Jaeho Cho
    • 1
  • Eunji Kim
    • 2
  • Tae Min Kim
    • 8
  • Yu Jung Kim
    • 8
  • Chul-Kee Park
    • 9
  • Jin Wook Kim
    • 9
  • Chae-Yong Kim
    • 9
  • Seung Hong Choi
    • 10
  • Jae Hyoung Kim
    • 10
  • Sung-Hye Park
    • 10
  • Gheeyoung Choe
    • 10
  • Soon-Tae Lee
    • 10
  • Il Han Kim
    • 2
    Email author
  • Chang-Ok Suh
    • 1
    • 11
    Email author
  1. 1.Department of Radiation Oncology, Yonsei Cancer CenterYonsei University College of MedicineSeoulKorea (Republic of)
  2. 2.Department of Radiation Oncology, Cancer Research Institute, Institute of Radiation MedicineSeoul National University College of MedicineSeoulKorea (Republic of)
  3. 3.Department of Neurosurgery, Severance HospitalYonsei University College of MedicineSeoulKorea (Republic of)
  4. 4.Department of BiostatisticsYonsei University College of MedicineSeoulKorea (Republic of)
  5. 5.Department of Pathology, Severance HospitalYonsei University College of MedicineSeoulKorea (Republic of)
  6. 6.Department of Radiation Oncology, Gangnam Severance HospitalYonsei University College of MedicineSeoulKorea (Republic of)
  7. 7.Department of Neurosurgery, Gangnam Severance HospitalYonsei University College of MedicineSeoulKorea (Republic of)
  8. 8.Department of Internal MedicineSeoul National University College of MedicineSeoulKorea (Republic of)
  9. 9.Department of NeurosurgerySeoul National University College of MedicineSeoulKorea (Republic of)
  10. 10.Department of RadiologySeoul National University College of MedicineSeoulKorea (Republic of)
  11. 11.Department of Radiation Oncology, CHA Bundang Medical CenterCHA UniversitySeongnam-siKorea (Republic of)

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