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Dosimetric predictors of treatment-related lymphopenia induced by palliative radiotherapy: predictive ability of dose-volume parameters based on body surface contour

Open Access
|Oct 2016

Abstract

Background

Radiation-related lymphopenia has been associated with poor patient outcome. Our aim was to identify predictors of lymphopenia after palliative radiotherapy, with a focus on dose-volume parameters.

Patients and methods

To retrospectively assess patients with various cancers who had undergone palliative radiotherapy, we delineated three organs at risk: the volume enclosed by the body surface contour (body A), the volume left after excluding air, pleural effusion, ascites, bile, urine, and intestinal content (body B), and the volume of the bone marrow (BM). We then noted the absolute volume of the three organs at risk that had received 5-30 Gy, and assessed the predictive value for post-treatment lymphopenia of grade 3 or higher (LP3+).

Results

Of 54 patients, 23 (43%) developed LP3+. Univariate logistic regression analysis showed that body A V5, body A V10, body B V5, body B V10, the number of fractions, and splenic irradiation were significant predictors of LP3+ (p < 0.05). By multivariate analysis, body A V5, body A V10, body B V5, body B V10, and the number of fractions retained significance (p < 0.05). BM dose-volume parameters did not predict lymphopenia.

Conclusions

Higher body A and body B dose-volume parameters and a larger number of fractions may be predictors of severe lymphopenia after palliative radiotherapy.

DOI: https://doi.org/10.1515/raon-2016-0050 | Journal eISSN: 1581-3207 | Journal ISSN: 1318-2099
Language: English
Page range: 228 - 234
Submitted on: Jul 18, 2016
Accepted on: Aug 30, 2016
Published on: Oct 13, 2016
Published by: Association of Radiology and Oncology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2016 Tetsuo Saito, Ryo Toya, Tomohiko Matsuyama, Akiko Semba, Natsuo Oya, published by Association of Radiology and Oncology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.