2012
DOI: 10.7326/0003-4819-156-10-201205150-00004
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A Multidimensional Index and Staging System for Idiopathic Pulmonary Fibrosis

Abstract: The GAP models use commonly measured clinical and physiologic variables to predict mortality in patients with IPF.

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Cited by 1,051 publications
(1,026 citation statements)
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References 25 publications
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“…Future studies should also consider whether sLOXL2, along with other promising prognostic IPF biomarkers (e.g. matrix metalloproteinase (MMP)1, MMP7, KL-6, periostin, surfactant protein-A and D, CC chemokine ligand 18, vascular endothelial growth factor and YKL-40) [19][20][21][22][23][24][25][26][27][28][29], as well as prognostic scores [30,31] and radiological modalities [32], might have prognostic value for helping physicians and patients anticipate the patient's IPF disease progression. This might include evaluation of serially collected sLOXL2 levels and their relationship to IPF acute exacerbations, which represent a terminal event for many IPF patients [33].…”
Section: Discussionmentioning
confidence: 99%
“…Future studies should also consider whether sLOXL2, along with other promising prognostic IPF biomarkers (e.g. matrix metalloproteinase (MMP)1, MMP7, KL-6, periostin, surfactant protein-A and D, CC chemokine ligand 18, vascular endothelial growth factor and YKL-40) [19][20][21][22][23][24][25][26][27][28][29], as well as prognostic scores [30,31] and radiological modalities [32], might have prognostic value for helping physicians and patients anticipate the patient's IPF disease progression. This might include evaluation of serially collected sLOXL2 levels and their relationship to IPF acute exacerbations, which represent a terminal event for many IPF patients [33].…”
Section: Discussionmentioning
confidence: 99%
“…Ley and colleagues found that GAP index correlated well with 1-year mortality among patients with IPF [29,30]. …”
Section: Methodsmentioning
confidence: 99%
“…More recently, LEY et al [22] developed a multidimensional risk prediction model and staging system using data from three large, geographically distinct cohorts of IPF patients in California (USA), Minnesota (USA) and Northern Italy. This GAP model consists of four baseline variables: gender (G), age (A) and two lung physiology variables (P) (FVC and DLCO).…”
Section: Novel Ipf Staging Systemsmentioning
confidence: 99%