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Abstract
Objective: This study aimed to develop and validate post- and preoperative models for predicting recurrence after curative-intent surgery using an FDG PET-CT metabolic parameter to improve the prognosis of patients with synchronous colorectal cancer liver metastasis (SCLM).

Methods: In this retrospective multicenter study, consecutive patients with resectable SCLM underwent upfront surgery between 2006 and 2015 (development cohort) and between 2006 and 2017 (validation cohort). In the development cohort, we developed and internally validated the post- and preoperative models using multivariable Cox regression with an FDG metabolic parameter (metastasis-to-primary-tumor uptake ratio [M/P ratio]) and clinicopathological variables as predictors. In the validation cohort, the models were externally validated for discrimination, calibration, and clinical usefulness. Model performance was compared with that of Fong's clinical risk score (FCRS).

Results: A total of 374 patients (59.1 ± 10.5 years, 254 men) belonged in the development cohort and 151 (60.3 ± 12.0 years, 94 men) in the validation cohort. The M/P ratio and nine clinicopathological predictors were included in the models. Both postoperative and preoperative models showed significantly higher discrimination than FCRS (p < .05) in the external validation (time-dependent AUC = 0.76 [95% CI 0.68-0.84] and 0.76 [0.68-0.84] vs. 0.65 [0.57-0.74], respectively). Calibration plots and decision curve analysis demonstrated that both models were well calibrated and clinically useful. The developed models are presented as a web-based calculator ( https://cpmodel.shinyapps.io/SCLM/ ) and nomograms.

Conclusions: FDG metabolic parameter-based prognostic models are well-calibrated recurrence prediction models with good discriminative power. They can be used for accurate risk stratification in patients with SCLM.

Key points: • In this multicenter study, we developed and validated prediction models for recurrence in patients with resectable synchronous colorectal cancer liver metastasis using a metabolic parameter from FDG PET-CT. • The developed models showed good predictive performance on external validation, significantly exceeding that of a pre-existing model. • The models may be utilized for accurate patient risk stratification, thereby aiding in therapeutic decision-making.

Affiliations

Hyo Sang Lee 1, Hyun Woo Kwon 2, Seok-Byung Lim 3, Jin Cheon Kim 3, Chang Sik Yu 3, Yong Sang Hong 4, Tae Won Kim 4, Minyoung Oh 5, Sangwon Han 5, Jae Hwan Oh 6, Sohyun Park 7, Tae-Sung Kim 7, Seok-Ki Kim 7, Hyun Joo Kim 2, Jae Young Kwak 8, Ho-Suk Oh 9, Sungeun Kim 2, Jung-Myun Kwak 10, Ji Sung Lee 11, Jae Seung Kim 5
1Department of Nuclear Medicine, GangNeung Asan Hospital, University of Ulsan College of Medicine, 38 Bangdong-gil, Sacheon-myeon, Gangneung-si, Gangwon-do, 25440, Republic of Korea. leehs75@gnah.co.kr.
2Department of Nuclear Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
3Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
4Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
5Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
6Center for Colorectal Cancer, Research Institute and Hospital, National Cancer Center, Goyang, Republic of Korea.
7Department of Nuclear Medicine, Research Institute and Hospital, National Cancer Center, Goyang, Republic of Korea.
8Department of Surgery, GangNeung Asan Hospital, University of Ulsan College of Medicine, Gangneung, Republic of Korea.
9Division of Hemato-oncology in the Department of Internal Medicine, GangNeung Asan Hospital, University of Ulsan College of Medicine, Gangneung, Republic of Korea.
10Department of Surgery, Korea University College of Medicine, Seoul, Republic of Korea.
11Clinical Research Center in the Asan Institute for Life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.