Using quantitative computed tomography to predict mortality in patients with interstitial lung disease related to systemic sclerosis: implications for personalized medicine
A. Ariani, N. Sverzellati, Andrea Becciolni, G. Milanese, Mario Silva
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引用次数: 1
Abstract
ABSTRACT Introduction: Interstitial lung disease (ILD) is the main cause of mortality in systemic sclerosis (SSc). Methods stratifying the prognosis of SSc-ILD are lacking in clinical practice. The quantification of ILD provides a paramount contribution to establishing prognosis and may assist in tailored treatment. Areas covered: In this review, we provide an overview of the main quantitative methods implemented in SSc-ILD (semi-quantitative assessment, volumetric, parametric, and textural quantitative evaluation). Even if they are different one from another, all of them have a prognostic value as they predict mortality as well as radiological and functional worsening. Expert opinion: Semi-quantitative rating of CT images (sQCT) is now the gold standard for SSc-ILD patient assessment and stratification. Furthermore, there are many software available for quantification objective quantification, and classification of ILD. These tools are barely burdened by inter- intra-reader variability and they are suitable for both trial and clinical application. It is therefore expected that in the next few years a better stratification of patients will be achieved by these tools, allowing to recognize patients with the worst prognosis. This, together with the availability of different treatments for pulmonary fibrosis, makes it possible to develop precision medicine also in the field of SSc-ILD.
期刊介绍:
Expert Review of Precision Medicine and Drug Development publishes primarily review articles covering the development and clinical application of medicine to be used in a personalized therapy setting; in addition, the journal also publishes original research and commentary-style articles. In an era where medicine is recognizing that a one-size-fits-all approach is not always appropriate, it has become necessary to identify patients responsive to treatments and treat patient populations using a tailored approach. Areas covered include: Development and application of drugs targeted to specific genotypes and populations, as well as advanced diagnostic technologies and significant biomarkers that aid in this. Clinical trials and case studies within personalized therapy and drug development. Screening, prediction and prevention of disease, prediction of adverse events, treatment monitoring, effects of metabolomics and microbiomics on treatment. Secondary population research, genome-wide association studies, disease–gene association studies, personal genome technologies. Ethical and cost–benefit issues, the impact to healthcare and business infrastructure, and regulatory issues.