Mathematical prediction with pretreatment growth rate of metastatic cancer on outcomes: implications for the characterization of oligometastatic disease

Yerim Shin; Jee Suk Chang; Yeseul Kim; Sang Joon Shin; Jina Kim; Tae Hyung Kim; Mitchell Liu; Robert Olson; Jin Sung Kim; Wonmo Sung

doi:10.3389/fonc.2023.1061881

Mathematical prediction with pretreatment growth rate of metastatic cancer on outcomes: implications for the characterization of oligometastatic disease

Front Oncol. 2023 May 29:13:1061881. doi: 10.3389/fonc.2023.1061881. eCollection 2023.

Authors

Yerim Shin¹, Jee Suk Chang^{2

3}, Yeseul Kim¹, Sang Joon Shin⁴, Jina Kim², Tae Hyung Kim⁵, Mitchell Liu³, Robert Olson⁶, Jin Sung Kim⁷, Wonmo Sung¹

Affiliations

¹ Department of Biomedical Engineering and of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
² Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, Republic of Korea.
³ BC Cancer - Vancouver Centre, Vancouver, BC, Canada.
⁴ Division of Medical Oncology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
⁵ Department of Radiation Oncology, Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, Republic of Korea.
⁶ BC Cancer, Centre for the North, Prince George, BC, Canada.
⁷ Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.

Abstract

Background: Oligometastatic disease (OMD) represents an indolent cancer status characterized by slow tumor growth and limited metastatic potential. The use of local therapy in the management of the condition continues to rise. This study aimed to investigate the advantage of pretreatment tumor growth rate in addition to baseline disease burden in characterizing OMDs, generally defined by the presence of ≤ 5 metastatic lesions.

Methods: The study included patients with metastatic melanoma treated with pembrolizumab. Gross tumor volume of all metastases was contoured on imaging before (TP_-1) and at the initiation of pembrolizumab (TP₀). Pretreatment tumor growth rate was calculated by an exponential ordinary differential equation model using the sum of tumor volumes at TP_-1 and TP₀ and the time interval between TP_-1. and TP₀. Patients were divided into interquartile groups based on pretreatment growth rate. Overall survival, progression-free survival, and subsequent progression-free survival were the study outcomes.

Results: At baseline, median cumulative volume and number of metastases were 28.4 cc (range, 0.4-1194.8 cc) and 7 (range, 1-73), respectively. The median interval between TP_-1 and TP₀ was -90 days and pretreatment tumor growth rate (×10^-2 days^-1) was median 4.71 (range -0.62 to 44.1). The slow-paced group (pretreatment tumor growth rate ≤ 7.6 ×10^-2 days^-1, the upper quartile) had a significantly higher overall survival rate, progression-free survival, and subsequent progression-free survival compared to those of the fast-paced group (pretreatment tumor growth rate > 7.6 ×10^-2 days^-1). Notably, these differences were prominent in the subgroup with >5 metastases.

Conclusion: Pretreatment tumor growth rate is a novel prognostic metric associated with overall survival, progression-free survival, and subsequent progression-free survival among metastatic melanoma patients, especially patients with >5 metastases. Future prospective studies should validate the advantage of disease growth rate plus disease burden in better defining OMDs.

Keywords: immune checkpoint inhabitor; mathematical modeling; melanoma; oligometastasis; tumor growth rate.

Grants and funding

This study was supported by a grant from the National Research Foundation of Korea (NRF) funded by the Korean Government (MSIT) [NRF-2021R1C1C1005930 and NRF-2022R1F1A1074344].