Biological-effect modeling of radioimmunotherapy for non-hodgkins lymphoma: determination of model parameters

Beyond Dose: Using Pretherapy Biomarkers to Improve Dose Prediction of Outcomes for Radioimmunotherapy of Non-Hodgkin Lymphoma

INTRODUCTION

Non-Hodgkin Lymphoma patients respond differently to therapy according to inherent biological variations. Pretherapy biomarkers may improve dose-response prediction.

MATERIALS AND METHODS

Hybrid single-photon emission computed tomography (SPECT)/computed tomography (CT) three-dimensional imaging at multiple time points plus follow-up positron emission tomography (PET)/CT or CT at 2 and 6 months post therapy were used to fit tumor response to combined biological effect and cell clearance models from which three biological effect response parameters (radiosensitivity, cold effect sensitivity, and proliferation potential) were determined per patient. A correlation of biological effect parameters and pretherapy biomarker data (ki67, p53, and phospho-histone H3) allowed a dose-based equivalent biological effect (EBE) to be calculated for each patient.

RESULTS

Significant correlations were found between biological effect parameters and pretherapy biomarkers. Optimum correlations were found by splitting the patient data according to p53 status. Response correlation of progression free survival (PFS) and EBE were significantly improved compared with PFS and absorbed dose alone.

CONCLUSIONS

It is possible and desirable to use pretherapy biomarkers to enhance the predictive potential of dose calculations for patient-specific treatment planning.

Cellular Response to Exponentially Increasing and Decreasing Dose Rates: Implications for Treatment Planning in Targeted Radionuclide Therapy

The treatment of cancer using targeted radionuclide therapy is of interest to nuclear medicine and radiation oncology because of its potential for killing tumor cells while minimizing dose-limiting toxicities to normal tissue. The ionizing radiations emitted by radiopharmaceuticals deliver radiation absorbed doses over protracted periods of time with continuously varying dose rates. As targeted radionuclide therapy becomes a more prominent part of cancer therapy, accurate models for estimating the biologically effective dose (BED) or equieffective dose (EQD2α/β) will become essential for treatment planning. This study examines the radiobiological impact of the dose rate increase half-time during the uptake phase of the radiopharmaceutical. MDA-MB-231 human breast cancer cells and V79 Chinese hamster lung fibroblasts were irradiated chronically with 662 keV γ rays delivered with time-varying dose rates that are clinically relevant. The temporal dose-rate patterns were: 1. acute, 2. exponential decrease with a half-time of 64 h (Td = 64 h), 3. initial exponential increase to a maximum (half time Ti = 2, 8 or 24 h) followed by exponential decrease (Td = 64 h). Cell survival assays were conducted and surviving fractions were determined. There was a marked reduction in biological effect when Ti was increased. Cell survival data were tested against existing dose-response models to assess their capacity to predict response. Currently accepted models that are used in radiation oncology overestimated BED and EQD2α/β at low-dose rates and underestimated them at high-dose rates. This appears to be caused by an adaptive response arising as a consequence of the initial low-dose-rate phase of exposure. An adaptive response function was derived that yields more accurate BED and EQD2α/β values over the spectrum of dose rates and absorbed doses delivered. Our experimental data demonstrate a marked increase in cell survival when the dose-rate-increase half-time is increased, thereby suggesting an adaptive response arising as a consequence of this phase of exposure. We have modified conventional radiobiological models used in the clinic for brachytherapy and external beams of radiation to account for this phenomenon and facilitate their use for treatment planning in targeted radionuclide therapy.