| 1. |
- Bleeker, Gitta, et al.
(författare)
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MIBG scans in patients with stage 4 neuroblastoma reveal two metastatic patterns, one is associated with MYCN amplification and in MYCN-amplified tumours correlates with a better prognosis
- 2015
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Ingår i: European Journal of Nuclear Medicine and Molecular Imaging. - : Springer Science and Business Media LLC. - 1619-7070 .- 1619-7089. ; 42:2, s. 222-230
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Tidskriftsartikel (refereegranskat)abstract
- Purpose The aim of this study was to find clinically relevant MIBG-avid metastatic patterns in patients with newly diagnosed stage 4 neuroblastoma. Methods Diagnostic I-123-MIBG scans from 249 patients (123 from a European and 126 from the COG cohort) were assessed for metastatic spread in 14 body segments and the form of the lesions: "focal" (clear margins distinguishable from adjacent background) or "diffuse" (indistinct margins, dispersed throughout the body segment). The total numbers of diffuse and focal lesions were recorded. Patients were then categorized as having lesions exclusively focal, lesions more focal than diffuse, lesions more diffuse than focal, or lesions exclusively diffuse. Results Diffuse lesions affected a median of seven body segments and focal lesions a median of two body segments (P<0.001, both cohorts). Patients with a focal pattern had a median of 2 affected body segments and those with a diffuse pattern a median of 11 affected body segments (P<0.001, both cohorts). Thus, two MIBG-avid metastatic patterns emerged: "limited-focal" and "extensive-diffuse". The median numbers of affected body segments in MYCN-amplified (MNA) tumours were 5 (European cohort) and 4 (COG cohort) compared to 9 and 11, respectively, in single-copy MYCN (MYCNsc) tumours (P<0.001). Patients with exclusively focal metastases were more likely to have a MNA tumour (60 % and 70 %, respectively) than patients with the other types of metastases (23 % and 28 %, respectively; P<0.001). In a multivariate Cox regression analysis, focal metastases were associated with a better event-free and overall survival than the other types of metastases in patients with MNA tumours in the COG cohort (P<0.01). Conclusion Two metastatic patterns were found: a " limited and focal" pattern found mainly in patients with MNA neuroblastoma that correlated with prognosis, and an " extensive and diffuse" pattern found mainly in patients with MYCNsc neuroblastoma.
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| 2. |
- Lee, Jenny, et al.
(författare)
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Machine learning algorithm improves the detection of NASH (NAS-based) and at-risk NASH: A development and validation study
- 2023
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Ingår i: Hepatology. - : LIPPINCOTT WILLIAMS & WILKINS. - 0270-9139 .- 1527-3350. ; 78:1, s. 258-271
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Tidskriftsartikel (refereegranskat)abstract
- Background and Aims: Detecting NASH remains challenging, while at-risk NASH (steatohepatitis and F >= 2) tends to progress and is of interest for drug development and clinical application. We developed prediction models by supervised machine learning techniques, with clinical data and biomarkers to stage and grade patients with NAFLD. Approach and Results: Learning data were collected in the Liver Investigation: Testing Marker Utility in Steatohepatitis metacohort (966 biopsy-proven NAFLD adults), staged and graded according to NASH CRN. Conditions of interest were the clinical trial definition of NASH (NAS >= 4;53%), at-risk NASH (NASH with F >= 2;35%), significant (F >= 2;47%), and advanced fibrosis (F >= 3;28%). Thirty-five predictors were included. Missing data were handled by multiple imputations. Data were randomly split into training/validation (75/25) sets. A gradient boosting machine was applied to develop 2 models for each condition: clinical versus extended (clinical and biomarkers). Two variants of the NASH and at-risk NASH models were constructed: direct and composite models.Clinical gradient boosting machine models for steatosis/inflammation/ballooning had AUCs of 0.94/0.79/0.72. There were no improvements when biomarkers were included. The direct NASH model produced AUCs (clinical/extended) of 0.61/0.65. The composite NASH model performed significantly better (0.71) for both variants. The composite at-risk NASH model had an AUC of 0.83 (clinical and extended), an improvement over the direct model. Significant fibrosis models had AUCs (clinical/extended) of 0.76/0.78. The extended advanced fibrosis model (0.86) performed significantly better than the clinical version (0.82). Conclusions: Detection of NASH and at-risk NASH can be improved by constructing independent machine learning models for each component, using only clinical predictors. Adding biomarkers only improved the accuracy of fibrosis.
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| 3. |
- Vali, Yasaman, et al.
(författare)
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Enhanced liver fibrosis test for the non-invasive diagnosis of fibrosis in patients with NAFLD : A systematic review and meta-analysis
- 2020
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Ingår i: Journal of Hepatology. - : Elsevier. - 0168-8278 .- 1600-0641. ; 73:2, s. 252-262
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Forskningsöversikt (refereegranskat)abstract
- BACKGROUND AND AIMS: The Enhanced Liver Fibrosis (ELF) test is a non-invasive biomarker, suggested as an appropriate test for advanced liver fibrosis in non-alcoholic fatty liver disease (NAFLD). This systematic review aimed to provide summary estimates of the accuracy of this test against biopsy.METHODS: In this systematic review, we searched MEDLINE, Embase, Web of Science and the Cochrane Library, for studies included NAFLD patients and undertook both liver biopsy as the reference standard and the ELF test. Two authors independently screened the references, extracted the data and assessed the quality of included studies. Due to the variation in reported thresholds, we used a multiple thresholds random effects model for meta-analysis (diagmeta R-package).RESULTS: The meta-analysis of 11 studies reporting advanced fibrosis and five studies reporting significant fibrosis showed sensitivity of >0.90 of the ELF test for excluding fibrosis at threshold of 7.7. However, as a diagnostic test at high thresholds, the test showed specificity and positive predictive value >0.80, only in very high-prevalence settings (>50%). Desiring specificity of 0.90 for advanced and significant fibrosis resulted in thresholds of 10.18 (sensitivity: 0.57) and 9.86 (sensitivity: 0.55), respectively.CONCLUSION: The ELF test showed high sensitivity but limited specificity to exclude advanced and significant fibrosis at low cutoffs. The diagnostic performance of the test at higher thresholds was found to be more limited in low prevalence settings. We conclude that clinicians should carefully consider the likely disease prevalence in their practice setting and adopt suitable test thresholds to achieve the desired test performance.
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