Efficacy of radiotherapy vs. The combination of radio- and immunotherapy: a systematic review and meta-analysis

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Introduction and objectives. The combination of radiotherapy and immune checkpoint inhibitors has demonstrated antitumor activity in numerous preclinical studies and is currently being investigated in the clinical setting. This study aims to compare the efficacy of radiotherapy alone (RT) vs. the combination of radio- and immunotherapy (IT-RT) and identify the treatment regimen associated with maximal efficacy by using a meta-analysis.

Materials and methods. A systematic literature search was performed using the PubMed database and materials of the key oncology congresses. Studies reporting 1-year overall survival (OS) of patients with brain metastases undergoing IT-RT treatment were included in the analysis. Information about 1-year OS, individual patients’ characteristics, and treatment regimens for both IT-RT and control RT arms was extracted. Identification of the optimal treatment regimen was performed using a mixed meta-regression modeling approach. Analysis was performed using the R statistical environment (metafoR package).

Results. In total, 30 studies were identified, of which 13 reported outcomes for the control RT groups. The analysis revealed that IT inclusion into RT is associated with a significant increase in 1-year OS; given simultaneously, IT and RT demonstrated the highest efficacy with a 1-year OS of 68% (95% confidence interval (CI): 60%–75%), followed by a sequential regimen: 1-year OS = 54% (95% CI: 47%–61%) and RT alone: 1-year OS = 32% (95% CI: 25–39%).

Conclusion. The current study demonstrates the superiority of combined IT-RT over RT alone; simultaneous IT and RT treatment is associated with the highest efficacy.

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Veronika M. Voronova

“I.M. Sechenov First Moscow State Medical University”; “M&S Decisions LLC”

Author for correspondence.
Email: Veronika.Voronova@msdecisions.ru

aspirant of the Institute of pharmacy; research scientist 

Russian Federation, Moscow

Svetlana A. Lebedeva

“I.M. Sechenov First Moscow State Medical University”

Email: Veronika.Voronova@msdecisions.ru

PhD, professor of the Institute of pharmacy 

Russian Federation, Moscow

Marina I. Sekacheva

“I.M. Sechenov First Moscow State Medical University”

Email: Veronika.Voronova@msdecisions.ru

PhD, professor, director of the Center of personalized oncology 

Russian Federation, Moscow

Gabriel Helmlinger


Email: Veronika.Voronova@msdecisions.ru

PhD, executive director of the quantitative clinical pharmacology group, department of clinical pharmacology

United States, MA02451, Boston

Kirill V. Peskov

“I.M. Sechenov First Moscow State Medical University”; “M&S Decisions” LLC

Email: Veronika.Voronova@msdecisions.ru

executive director of the “Computational oncology” group of the Center of personalized oncology; PhD, chief executive officer 

Russian Federation, Moscow


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Supplementary files

Supplementary Files
1. Fig. 1. Block diagram of data collection.

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2. Fig. 2. "Forest" is a diagram of group analysis of OOB. The squares correspond to the observations of individual CIs, the size of the squares reflects the number of patients in the cohort, error bars correspond to 95% CI for the corresponding observations; the magnitude of the generalized effect is shown by the vertical line, 95% CI by the gray area.

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3. Fig. 3. Funnel-shaped scattering diagram for the selected meta-regression model.

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СМИ зарегистрировано Федеральной службой по надзору в сфере связи, информационных технологий и массовых коммуникаций (Роскомнадзор).
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