Browsing by Author "Arana, Estanislao"

Purpose: To assess variability in the use of Tomita and modified Bauer scores in spine metastases. Materials and methods: Clinical data and imaging from 90 patients with biopsy-proven spinal metastases, were provided to 83 specialists from 44 hospitals. Spinal levels involved and the Tomita and modified Bauer scores for each case were determined twice by each clinician, with a minimum of 6-week interval. Clinicians were blinded to every evaluation. Kappa statistic was used to assess intra and inter-observer agreement. Subgroup analyses were performed according to clinicians' specialty (medical oncology, neurosurgery, radiology, orthopedic surgery and radiation oncology), years of experience (⩽7, 8-13, ⩾14), and type of hospital (four levels). Results: For metastases identification, intra-observer agreement was "substantial" (0.600.80) at the other levels. Inter-observer agreement was "almost perfect" at lumbar spine, and "substantial" at the other levels. Intra-observer agreement for the Tomita and Bauer scores was almost perfect. Inter-observer agreement was almost perfect for the Tomita score and substantial for the Bauer one. Results were similar across specialties, years of experience and type of hospital. Conclusion: Agreement in the assessment of metastatic spine disease is high. These scoring systems can improve communication among clinicians involved in oncology care.

Brain metastases (BMs) are cancer cells that spread to the brain from primary tumors in other organs. Up to 35% of adult cancer patients develop BMs. The treatment of BM patients who have well-controlled extracranial disease and a small number of lesions consists of localized doses of radiation (stereotactic radio surgery (SRS)). Estimating prognosis among BM patients may allow treatments to be chosen that balance durability of intracranial tumor control with quality of life and the side effects of treatment. No mathematical model-based quantitative biomarkers have been determined for estimating prognosis. As a first step toward that goal, we describe a mathematical model of growth and response of brain metastasis to stereotactic radio surgery. The mathematical model incorporates some biological mechanisms involved in BM growth and response to SRS and allows the observed dynamics to be accurately described.

Most physical and other natural systems are complex entities composed of a large number of interacting individual elements. It is a surprising fact that they often obey the so-called scaling laws relating an observable quantity with a measure of the size of the system. Here we describe the discovery of universal superlinear metabolic scaling laws in human cancers. This dependence underpins increasing tumour aggressiveness, due to evolutionary dynamics, which leads to an explosive growth as the disease progresses. We validated this dynamic using longitudinal volumetric data of different histologies from large cohorts of cancer patients. To explain our observations we put forward increasingly-complex biologically-inspired mathematical models that captured the key processes governing tumor growth. Our models predicted that the emergence of superlinear allometric scaling laws is an inherently three-dimensional phenomenon. Moreover, the scaling laws thereby identified allowed us to define a set of metabolic metrics with prognostic value, thus providing added clinical utility to the base findings.