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Methods Inf Med 2007; 46(04): 432-439
DOI: 10.1160/ME0328
 
Schattauer GmbH

Discovery of Factors Influencing the Growth of Geographic Atrophy in Patients with Age-related Macular Degeneration

J. Dreyhaupt
1   Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany
,
J. Dolar-Szczasny
2   First Eye Hospital of Medical University of Lublin, Lublin, Poland
,
A. Bindewald
3   Department of Ophthalmology, University of Bonn, Bonn, Germany
,
F. G. Holz
3   Department of Ophthalmology, University of Bonn, Bonn, Germany
,
U. Mansmann
4   Chair of Biometry and Bioinformatics, IBE, Medical School, LMU Munich, Munich, Germany
› Author Affiliations
Further Information

Publication History

Publication Date:
20 January 2018 (online)

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Summary

Objectives: Identifying factors influencing the growth of geographic atrophy (GA) in patients with age-related macular degeneration (AMD).

Methods: Data on the natural course and suspected modifying factors were collected as part of the multicenter, longitudinal, observational FAM-study in 178 eyes of 114 patients with atrophic AMD. The endpoint of interest – the size of GA – was measured in fundus autofluorescence images. The influence of different putative riskfactors on progression of GA is investigated with a forward selection procedure based on the likelihood ratio test. In orderto interpret non-significant results of the forward selection procedure, the power of the tests usedwas quantified bya parametric post-hoc bootstrap approach.

Results: A mean increase in GA of 175 mm2 per year was estimated for the given population (95% CI: [1.46; 2.02]). Patient and eye-specific random effects could be assessed. Neither patient-specific riskfactors nor ocular-specific risk factors show any significant influence on GA growth. The post-hoc bootstrap procedure shows that only very strong effects can be detected on the basis of the given data. For example, the hypercholesteremia which would result in an additional increase of GA by near 4mm2 per year can be detected with a power of 80%.

Conclusions: The use of linear mixed effects regression models offers a convenient way to explore sources of variation in the natural course of GA. Data from further follow-up examinations and data about other putative riskfactors than those investigated will be needed to further investigate of the GA growth process. The procedure described in this article is easily applicable to other putative risk factors as well as to other fields of application.

Keywords

Macular degeneration - regression analyses - likelihood ratio test - risk factors - natural history
 

  • References

  • 1 Grehn F. Augenheilkunde. Berlin, Heidelberg, New York: Springer; 2003.
  • 2 Sunness JS, Gonzalez-Baron J, Applegate CA, Bressler NM, Tian Y, Hawkins B. et al. Enlargement of atrophy and visual acuity loss in the geographic atrophy form of age-related macular degeneration. Ophthalmology 1999; 106: 1768-79.
    CrossrefPubMedGoogle Scholar
  • 3 Sunness JS. The natural history of geographic atrophy, the advanced atrophic form of age-related macular degeneration. Molecular vision (electronic resource) 1999; 03: 5-25.
    PubMedGoogle Scholar
  • 4 Schmitz-Valckenberg S, Jorzik J, Unnebrink K, Holz FG. Analysis of digital scanning laser oph-thalmoscopy fundus autofluorescence images of geographic atrophy in advanced age-related macular degeneration. Graefes Arch Clin Exp Ophthalmol 2002; 240: 73-8.
    CrossrefPubMedGoogle Scholar
  • 5 Gouras P, Flood MT, Kjedbye H, Bilek MK, Eggers H. Transplantation of cultured human retinal epithelium to Bruch’s membrane of the owl monkey’s eye. Curr Eye Res 1985; 04: 253-65.
    CrossrefPubMedGoogle Scholar
  • 6 Bindewald A, Schutt F, Specht H, Holz FG. Preclinical Study for Intraocular Microablation of Choroidal Tissue Using a 308 nm UV Excimer Laser for RPE-Sheet Translocation. ARVO2003 Abstracts.
    PubMedGoogle Scholar
  • 7 A randomized, placebo-controlled, clinical trial of high-dose supplementation with vitamins C and Ε and beta carotene for age-related cataract and vision loss: AREDS reportno. 9. Arch Ophthalmol 2001; 119: 1439-52.
    CrossrefPubMedGoogle Scholar
  • 8 A randomized, placebo-controlled, clinical trial of high-dose supplementation with vitamins C and E, beta carotene, and zinc for age-related macular degeneration and vision loss: AREDS reportno. 8. Arch Ophthalmol 2001; 119: 1417-36.
    CrossrefPubMedGoogle Scholar
  • 9 Evans JR, Henshaw K. Antioxidant vitamin and mineral supplementation for preventing age-related macular degeneration. Cochrane Database Syst Rev. 2000: CD000253.
    PubMedGoogle Scholar
  • 10 van Leeuwen R, Vingerling JR, de Jong PT. Risk of macular degeneration with statin use should be interpreted with caution. BMJ 2001; 323: 1308.
    PubMedGoogle Scholar
  • 11 van Leeuwen R, Klaver CC, Vingerling JR, Hof-man A, Van Duijn CM, Stricker BH. et al. Cholesterol and age-related macular degeneration: is there a link?. Am J Ophthalmol 2004; 137: 750-2.
    PubMedGoogle Scholar
  • 12 Dreyhaupt J, Mansmann U, Pritsch M, Dolar-Szczasny J, Bindewald A, Holz FG. Modelling the natural history of geographic atrophy in patients with age-related macular degeneration. Ophthalmic epidemiology 2005; 12: 353-62.
    CrossrefPubMedGoogle Scholar
  • 13 Pinheiro JC, Bates DM. Mixed-effects models in S and S-plus. Berlin, Heidelberg, New York: Springer; 2000.
  • 14 Pearson JD, Morrell CH, Landis PK, Carter HB, Brant LJ. Mixed-effects regression models for studying the natural history of prostate disease. Stat Med 1994; 13: 587-601.
    CrossrefPubMedGoogle Scholar
  • 15 Baeten S, Bouckaert A, Thomas K, Loumaye E. The prognosis of in vitro fertilization (IVF): a regression approach. Methods Inf Med 1988; 27: 135-6.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 16 Coles LS, Brown BW, Engelhard C, Halpern J, Fries JF. Determining the most valuable clinical variables: a stepwise multiple logistic regression program. Methods Inf Med 1980; 19: 42-9.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 17 Sauerbrei W, Madjar H, Prompeler HJ. Differentiation of benign and malignant breast tumors by logistic regression and a classification tree using Dopplerflowsignals. Methods Inf Med 1998; 37: 226-34.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 18 Jorzik JJ, Deckert A, Schmitz-Valckenberg S, Bindewald A, Mansmann U, Holz FG. FAM Study Group. Computer-assisted Automated Analysis of Digital cSLO Fundus Autofluorescence Images in Advanced Atrophic AMD. ARVO2004 Abstracts.
    PubMedGoogle Scholar
  • 19 Roth F, Bindewald A, Dolar-Szczasny J, Spital G, Mackiewicz J, Pauleikhoff D, Holz FG. Fundus Autofluorescence Imaging of Pigment Epithelial Detachments. ARVO2004 Abstracts.
    PubMedGoogle Scholar
  • 20 Bindewald A, Dolar-Szczasny J, Sieber H, Schmitz-Valckenberg S, Jorzik JJ, Keilhauer C, Pauleikhoff D, Wolf S, Mansmann U, Holz FG. Fundus Autofluorescence Patterns in the Junctional Zone as Prognostic Determinants for Spread of Geographic Atrophy in Age-related Macular Degeneration (AMD). ARVO2004 Abstracts.
    PubMedGoogle Scholar
  • 21 Deckert A, Schmitz-Valckenberg S, Jorzik J, Bindewald A, Holz FG, Mansmann U. Automated analysis of digital fundus autofluorescence images of geographic atrophy in advanced age-related macular degeneration using confocal scanning laser ophthalmoscopy (cSLO). BMC Ophthalmology (electronic resource) 2005; 05: 8 10.1186/1471-2415-5-8
    CrossrefPubMedGoogle Scholar
  • 22 Verbeke G, Molenberghs G. Linear mixed models for longitudinal data. New York, Berlin, Heidelberg: Springer; 2000.
  • 23 Pinheiro JC, Bates DM. lme and nlme: Mixed-effects Methods and Classes for S and S-Plus. Version 3.0. June 1999.
    PubMedGoogle Scholar
  • 24 Beran R. Simulated Power Functions. The Annals of Statistics 1986; 14: 151-73.
    CrossrefPubMedGoogle Scholar
  • 25 Seuchter SA, Eisenacher M, Riesbeck M, Gaebel W, Kopcke W. Methods for predictor analysis of repeated measurements: application to psychiatric data. Methods Inf Med 2004; 43: 184-91.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 26 Bahnsen U. Lichtblick im Alter. Die Zeit. 2006: 39-44.
    PubMedGoogle Scholar