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Improved Survival Prediction by Combining Radiological Imaging and S-100B Levels Into a Multivariate Model in Metastatic Melanoma Patients Treated With Immune Checkpoint Inhibition.
Burgermeister, Simon; Gabrys, Hubert S; Basler, Lucas; Hogan, Sabrina A; Pavic, Matea; Bogowicz, Marta; Martínez Gómez, Julia M; Vuong, Diem; Tanadini-Lang, Stephanie; Foerster, Robert; Huellner, Martin W; Dummer, Reinhard; Levesque, Mitchell P; Guckenberger, Matthias.
Afiliação
  • Burgermeister S; Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
  • Gabrys HS; Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
  • Basler L; Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
  • Hogan SA; Department of Dermatology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
  • Pavic M; Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
  • Bogowicz M; Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
  • Martínez Gómez JM; Department of Dermatology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
  • Vuong D; Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
  • Tanadini-Lang S; Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
  • Foerster R; Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
  • Huellner MW; Department of Nuclear Medicine, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
  • Dummer R; Department of Dermatology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
  • Levesque MP; Department of Dermatology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
  • Guckenberger M; Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
Front Oncol ; 12: 830627, 2022.
Article em En | MEDLINE | ID: mdl-35494048
ABSTRACT

Purpose:

We explored imaging and blood bio-markers for survival prediction in a cohort of patients with metastatic melanoma treated with immune checkpoint inhibition. Materials and

Methods:

94 consecutive metastatic melanoma patients treated with immune checkpoint inhibition were included into this study. PET/CT imaging was available at baseline (Tp0), 3 months (Tp1) and 6 months (Tp2) after start of immunotherapy. Radiological response at Tp2 was evaluated using iRECIST. Total tumor burden (TB) at each time-point was measured and relative change of TB compared to baseline was calculated. LDH, CRP and S-100B were also analyzed. Cox proportional hazards model and logistic regression were used for survival analysis.

Results:

iRECIST at Tp2 was significantly associated with overall survival (OS) with C-index=0.68. TB at baseline was not associated with OS, whereas TB at Tp1 and Tp2 provided similar predictive power with C-index of 0.67 and 0.71, respectively. Appearance of new metastatic lesions during follow-up was an independent prognostic factor (C-index=0.73). Elevated LDH and S-100B ratios at Tp2 were significantly associated with worse OS C-index=0.73 for LDH and 0.73 for S-100B. Correlation of LDH with TB was weak (r=0.34). A multivariate model including TB change, S-100B, and appearance of new lesions showed the best predictive performance with C-index=0.83.

Conclusion:

Our analysis shows only a weak correlation between LDH and TB. Additionally, baseline TB was not a prognostic factor in our cohort. A multivariate model combining early blood and imaging biomarkers achieved the best predictive power with regard to survival, outperforming iRECIST.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Oncol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Oncol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Suíça