Linear mixed-effects models for estimation of pulmonary metastasis growth rate: implications for CT surveillance in patients with sarcoma

Abstract

Objectives: Sarcoma patients often undergo surveillance chest CT for detection of pulmonary metastases. No data exist on the optimal surveillance interval for chest CT. The aim of this study was to estimate pulmonary metastasis growth rate in sarcoma patients. Methods: This was a retrospective review of 95 patients with pulmonary metastases (43 patients with histologically confirmed metastases and 52 with clinically diagnosed metastases) from sarcoma treated at an academic tertiary-care center between 01 January 2000 and 01 June 2019. Age, sex, primary tumor size, grade, subtype, size and volume of the pulmonary metastasis over successive chest CT scans were recorded. Two metastases per patient were chosen if possible. Multivariate linear mixed-effects models with random effects for each pulmonary metastasis and each patient were used to estimate pulmonary metastasis growth rate, evaluating the impact of patient age, tumor size, tumor grade, chemotherapy and tumor subtype. We estimated the pulmonary metastasis volume doubling time using these analyses. Results: Maximal primary tumor size at diagnosis (LRT statistic = 2.58, df = 2, p = 0.275), tumor grade (LRT statistic = 1.13, df = 2, p = 0.567), tumor type (LRT statistic = 7.59, df = 6, p = 0.269), and patient age at diagnosis (LRT statistic = 0.735, df = 2, p = 0.736) were not statistically significant predictors of pulmonary nodule growth from baseline values. Chemotherapy decreased the rate of pulmonary nodule growth from baseline (LRT statistic = 7.96, df = 2, p = 0.0187). 95% of untreated pulmonary metastases are expected to grow less than 6 mm in 6.4 months. There was significant intrapatient and interpatient variation in pulmonary metastasis growth rate. Pulmonary metastasis volume growth rate was best fit with an exponential model in time. The volume doubling time for pulmonary metastases assuming an exponential model in time was 143 days (95% CI (104, 231) days). Conclusions: Assuming a 2 mm nodule is the smallest reliably detectable nodule by CT, the data suggest that an untreated pulmonary metastasis is expected to grow to 8 mm in 8.4 months (95% CI (4.9, 10.2) months). Tumor size, grade and sarcoma subtype did not significantly alter pulmonary metastasis growth rate. However, chemotherapy slowed the pulmonary metastasis growth rate. Advances in knowledge: CT surveillance intervals for pulmonary metastases can be estimated based on metastasis growth rate. There was significant variation in the pulmonary metastasis growth rate between metastases within patient and between patients. Pulmonary nodule volume growth followed an exponential model, linear in time.