Developing retinal biomarkers of neurological disease: An analytical perspective

Biomarkers in Medicine

Volumn 9, Issue 7, 2015, Pages 691-701

  Maccormick, Ian J C ^a,b,c   Czanner, Gabriela ^a   Faragher, Brian ^d  

^a UNIVERSITY OF LIVERPOOL   (United Kingdom)

^b MALAWI LIVERPOOL WELLCOME TRUST CLINICAL RESEARCH PROGRAMME   (Malawi)

^c UNIVERSITY OF EDINBURGH   (United Kingdom)

^d LIVERPOOL SCHOOL OF TROPICAL MEDICINE   (United Kingdom)

Author keywords

biomarker; brain; cerebral malaria; proxy marker; retina; surrogate end point

Indexed keywords

BIOLOGICAL MARKER;

ALZHEIMER DISEASE; BRAIN MALARIA; CEREBROVASCULAR ACCIDENT; COGNITIVE DEFECT; DISEASE MARKER; DISEASE SEVERITY; HUMAN; METHODOLOGY; MORTALITY; MULTIPLE SCLEROSIS; NEUROLOGIC DISEASE; NONHUMAN; PATHOGENESIS; PROGNOSIS; RETINA; RETINA CONE; RETINA DISEASE; RETINA ROD; REVIEW; SCHIZOPHRENIA; STATISTICAL ANALYSIS; STRUCTURAL EQUATION MODELING; BRAIN; BRAIN DISEASES; MALARIA, CEREBRAL; METABOLISM;

BIOMARKERS; BRAIN; BRAIN DISEASES; HUMANS; MALARIA, CEREBRAL; RETINA;

EID: 84946552428     PISSN: 17520363     EISSN: 17520371     Source Type: Journal    
DOI: 10.2217/bmm.15.17     Document Type: Review

References (41)

1. London A, Benhar I, Schwartz M. The retina as a window to the brain-from eye research to CNS disorders. Nat. Rev. Neurol. 9(1), 44-53 (2013
2. Dowling JE. The Retina: An Approachable Part Of The Brain (2nd Edition). Belknap Press, London, UK (1992
3. Cheung CY-L, Ong Y-T, Ikram MK, Chen C, Wong TY. Retinal microvasculature in Alzheimer's disease. J. Alzheimers Dis. 42, S339-S352 (2014
4. Chu EM-Y, Kolappan M, Barnes TRE, Joyce EM, Ron MA. A window into the brain: an in vivo study of the retina in schizophrenia using optical coherence tomography. Psychiatry Res. 203(1), 89-94 (2012
5. Ong Y-T, De Silva DA, Cheung CY, et al. Microvascular structure and network in the retina of patients with ischemic stroke. Stroke. 44(8), 2121-2127 (2013
6. MacCormick IJC, Beare NA V, Taylor TE, et al. Cerebral malaria in children: using the retina to study the brain. Brain 137, 2119-2142 (2014
7. Patton N, Aslam T, Macgillivray T, Pattie A, Deary IJ, Dhillon B. Retinal vascular image analysis as a potential screening tool for cerebrovascular disease: a rationale based on homology between cerebral and retinal microvasculatures. J. Anat. 206(4), 319-348 (2005
8. MacGillivray TJ, Trucco E, Cameron JR, Dhillon B, Houston JG, van Beek EJR. Retinal imaging as a source of biomarkers for diagnosis, characterization and prognosis of chronic illness or long-Term conditions. Br. J. Radiol. 87(1040), 20130832 (2014
9. Doubal FN, Hokke PE, Wardlaw JM. Retinal microvascular abnormalities and stroke: a systematic review. J. Neurol. Neurosurg. Psychiatry. 80(2), 158-165 (2009
10. Ong Y-T, Hilal S, Cheung CY-L, et al. Retinal vascular fractals and cognitive impairment. Dement. Geriatr. Cogn. Dis. Extra. 4(2), 305-313 (2014
11. Green AJ, McQuaid S, Hauser SL, Allen I V, Lyness R. Ocular pathology in multiple sclerosis: retinal atrophy and inflammation irrespective of disease duration. Brain. 133(Pt 6), 1591-1601 (2010
12. Walker AS, Eyre DW, Wyllie DH, et al. Relationship between bacterial strain type, host biomarkers, and mortality in clostridium difficile infection. Clin. Infect. Dis. 56(11), 1589-1600 (2013
13. Beran TN, Violato C. Structural equation modeling in medical research: a primer. BMC Res. Notes 3, 267 (2010
14. Kline RB. Principles and Practice of Structural Equation Modeling (3rd Edition). Guilford Press, London, UK (2011
15. Joffe MM, Greene T. Related causal frameworks for surrogate outcomes. Biometrics. 65(2), 530-538 (2009
16. VanderWeele TJ. Surrogate measures and consistent surrogates. Biometrics. 69(3), 561-565 (2013
17. Burzykowski T, Molenberghs G, Buyse M. The Evaluation of Surrogate End Points (1st Edition). Springer, NY, USA (1998
18. Biomarkers Definitions Working Group. Biomarkers and surrogate end points: preferred definitions and conceptual framework. Clin. Pharmacol. Ther. 69(3), 89-95 (2001
19. Fleming TR, DeMets DL. Surrogate end points in clinical trials: are we being misled Ann. Intern. Med. 125(7), 605-613 (1996
20. Weir CJ, Walley RJ. Statistical evaluation of biomarkers as surrogate end points: a literature review. Stat. Med. 25(2), 183-203 (2006
21. Lassere MN. The Biomarker-Surrogacy Evaluation Schema: a review of the biomarker-surrogate literature and a proposal for a criterion-based, quantitative, multidimensional hierarchical levels of evidence schema for evaluating the status of biomarkers as surrogate end points. Stat. Methods Med. Res. 17(3), 303-340 (2007
22. Prentice RL. Surrogate end points in clinical trials: definition and operational criteria. Stat. Med. 8(4), 431-440 (1989
23. Freedman LS, Graubard BI, Schatzkin A. Statistical validation of intermediate end points for chronic diseases. Stat. Med. 11(2), 167-178 (1992
24. Buyse M, Molenberghs G. Criteria for the validation of surrogate end points in randomized experiments. Biometrics. 54(3), 1014-1029 (1998
25. Qu Y, Case M. Quantifying the effect of the surrogate marker by information gain. Biometrics. 63(3), 958-962; author reply 962-963 (2007
26. Alonso A, Molenberghs G, Burzykowski T, et al. Prentice's approach and the meta-Analytic paradigm: a reflection on the role of statistics in the evaluation of surrogate end points. Biometrics. 60(3), 724-728 (2004
27. Molenberghs G, Geys H, Buyse M. Evaluation of surrogate end points in randomized experiments with mixed discrete and continuous outcomes. Stat. Med. 20(20), 3023-3038 (2001
28. Bartha P. Analogy and analogical reasoning. Stanford Encycl. Philos. (2013). http://plato.stanford.edu/entries/reasoning-Analogy/
29. Buyse M, Sargent DJ, Grothey A, Matheson A, de Gramont A. Biomarkers and surrogate end points - The challenge of statistical validation. Nat. Rev. Clin. Oncol. 7(6), 309-317 (2010
30. Wu Z, He P, Geng Z. Sufficient conditions for concluding surrogacy based on observed data. Stat. Med. 30(19), 2422-2434 (2011
31. Vandenbroucke JP, von Elm E, Altman DG, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. PLoS Med. 4(10), e297 (2007
32. World Health Organisation. Severe malaria. Trop. Med. Int. Health. 19(Suppl. 1), 7-131 (2014
33. WHO. World Malaria Report (2014). http://apps.who.int
34. White NJ, Turner GDH, Day NPJ, Dondorp AM. Lethal malaria: marchiafava and bignami were right. J. Infect. Dis. 208(2), 192-198 (2013
35. Dondorp AM, Desakorn V, Pongtavornpinyo W, et al. Estimation of the total parasite biomass in acute falciparum malaria from plasma PfHRP2. PLoS Med. 2(8), e204 (2005
36. Fox LL, Taylor TE, Pensulo P, et al. Histidine-rich protein 2 plasma levels predict progression to cerebral malaria in Malawian children with Plasmodium falciparum infection. J. Infect. Dis. 208(3), 500-503 (2013
37. Seydel KB, Fox LL, Glover SJ, et al. Plasma concentrations of parasite histidine-rich protein 2 distinguish between retinopathy-positive and retinopathy-negative cerebral malaria in Malawian children. J. Infect. Dis. 206, 309-318 (2012
38. Taylor TE, Fu WJ, Carr RA, et al. Differentiating the pathologies of cerebral malaria by postmortem parasite counts. Nat. Med. 10(2), 143-145 (2004
39. White VA, Lewallen S, Beare N, Kayira K, Carr RA, Taylor TE. Correlation of retinal haemorrhages with brain haemorrhages in children dying of cerebral malaria in Malawi. Trans. R Soc. Trop. Med. Hyg. 95(6), 618-621 (2001
40. Barrera V, Hiscott PS, Craig AG, et al. Severity of retinopathy parallels the degree of parasite sequestration in eye and brain in Malawian children with fatal cerebral malaria. J. Infect. Dis. pii: jiu592 (2014) (Epub ahead of print
41. Greenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research. Epidemiology. 10(1), 37-48 (1999