ArticleThe British journal of radiology2020
Linear mixed-effects models for estimation of pulmonary metastasis growth rate: implications for CT surveillance in patients with sarcoma.
Article in The British journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 1 citations in OpenAlex.
- Prospective exploratory pilot study of 18 F-FMISO PET/CT for assessing tumor hypoxia in soft tissue sarcomas.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Trial
- Linear mixed-effects models for predicting sarcoma local recurrence growth rates: Implications for optimal surveillance imaging frequency.European journal of radiology · 2020Article
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3 authors at 2 institutions in 1 country.
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Abstract
objectivesSarcoma 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.
methodsThis 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.
resultsMaximal primary tumor size at diagnosis (LRT statistic = 2.58, df = 2,
conclusionsAssuming 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.
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