Computational markers for personalized prediction of outcomes in non-small cell lung cancer patients with brain metastases.

Intracranial progression after curative treatment of early-stage non-small cell lung cancer (NSCLC) occurs from 10 to 50% and is difficult to manage, given the heterogeneity of clinical presentations and the variability of treatments available. The objective of this study was to develop a mechanistic model of intracranial progression to predict survival following a first brain metastasis (BM) event occurring at a time [Formula: see text]. Data included early-stage NSCLC patients treated with a curative intent who had a BM as the first and single relapse site (N = 31). We propose a mechanistic mathematical model able to derive computational markers from primary tumor and BM data at [Formula: see text] and estimate the amount and sizes of (visible and invisible) BMs, as well as their future behavior. These two key computational markers are [Formula: see text], the proliferation rate of a single tumor cell; and [Formula: see text], the per day, per cell, probability to metastasize. The predictive value of these individual computational biomarkers was evaluated. The model was able to correctly describe the number and size of metastases at [Formula: see text] for 20 patients. Parameters [Formula: see text] and [Formula: see text] were significantly associated with overall survival (OS) (HR 1.65 (1.07-2.53) p = 0.0029 and HR 1.95 (1.31-2.91) p = 0.0109, respectively). Adding the computational markers to the clinical ones significantly improved the predictive value of OS (c-index increased from 0.585 (95% CI 0.569-0.602) to 0.713 (95% CI 0.700-0.726), p < 0.0001). We demonstrated that our model was applicable to brain oligoprogressive patients in NSCLC and that the resulting computational markers had predictive potential. This may help lung cancer physicians to guide and personalize the management of NSCLC patients with intracranial oligoprogression.

Pulmonary adverse events of breast silicone implants and silicone injection.

The incidence of breast implants and silicone injections has continuously increased since their FDA approval for use in the 1960's. The prevalence of overall adverse events is approximately 20%. The actual incidence of pulmonary adverse events is unknown. This review focuses on the pulmonary adverse events of breast implants and silicone injections. Vascular complications are represented by acute and chronic embolisation syndromes with a clinico-radiological presentation of alveolar hemorrhage. Inflammatory complications are numerous, including siliconoma, which is a granulomatous reaction mimicking a mesothelioma. On the other hand, there are some reports arguing a link between the development of auto-immune diseases and breast implants, such as scleroderma, rheumatoid arthritis, Sjögren's syndrome, and dermatomyositis. Finally, for patients with asthma, breast implants may contribute to poor disease control. Cases of eosinophilic granulomatosis with polyangeitis have been described. Thus, it is of interest to decipherate mechanisms and incidence of these effects in prospective studies to better manage pulmonary diseases in patients wearing breast implants in order to understand their role as culprits or bystanders. In addition, characterization of subpopulations with increased risk of adverse events is needed as we highlighted that some subpopulations seem to be at greater risk of developing them, notably asthmatics.