May 2005
Volume 46, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2005
Risk Assessment of Recurrence in Sporadic Retinoblastoma (Rb) Using a Novel Molecular–Based Algorithm
Author Affiliations & Notes
  • H.V. Tran
    Jules Gonin Eye Hospital, University of Lausanne, Switzerland
  • A. Balmer
    Jules Gonin Eye Hospital, University of Lausanne, Switzerland
  • D.F. Schorderet
    Jules Gonin Eye Hospital, University of Lausanne, Switzerland
    Institute of Research in Ophthalmology, Sion, Switzerland
  • F.L. Munier
    Jules Gonin Eye Hospital, University of Lausanne, Switzerland
    Institute of Research in Ophthalmology, Sion, Switzerland
  • Footnotes
    Commercial Relationships  H.V. Tran, None; A. Balmer, None; D.F. Schorderet, None; F.L. Munier, None.
  • Footnotes
    Support  None.
Investigative Ophthalmology & Visual Science May 2005, Vol.46, 3211. doi:
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      H.V. Tran, A. Balmer, D.F. Schorderet, F.L. Munier; Risk Assessment of Recurrence in Sporadic Retinoblastoma (Rb) Using a Novel Molecular–Based Algorithm . Invest. Ophthalmol. Vis. Sci. 2005;46(13):3211.

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Abstract

Abstract: : Purpose: Identification of sporadic Rb recurrence is not cost effective and because in despite of all mutational screening efforts, 90% of unilateral and 20% of bilateral sporadic Rb have undetected mutation, we designed and evaluated a new algorithm based on linkage analysis. Methods: All consecutive patients with sporadic Rb referred to the Jules Gonin Eye Hospital between January 1994 and July 2003 were enrolled. The designed algorithm is based on 3 observations: a) RB1 loss of heterozygosity in 2/3 of the tumors; b) preferential paternal origin of new germline mutations; and c) a priori risk derived from empirical data by Vogel (1979). Linkage study, using intragenic RB1 polymorphic markers was performed on each proband, siblings, living 1st– and 2nd–degree relatives, and on tumor material, when accessible. Modification of the a priori risk was computed using the algorithm, adjusted to the age of the patient. The calculated risks were then cumulated and compared with the observed occurrence of Rb until all at–risk patients were older than 48 months of age. The siblings, offsprings and 2nd degree relatives of affected patients were classified into 3 categories: low–risk (<1%), medium–risk (<1%–12%), and high–risk (≥90%), our algorithm allowing us to sort patients between 12 and 90% in medium or high risk. Results: 104 (53 with unifocal and 51 with multifocal Rb) out of 206 index patients had a total of 125 siblings, 20 offsprings, and 12 2nd degree relatives; of which 70 siblings, 15 offsprings and all 2nd degree relatives were younger than 48 months of age by the time of the linkage analysis and older than 48 months of age by December 2004. Fifty–two of these siblings were classified as low–risk and 18 were considered as medium–risk. Eight of 15 offsprings were at low–risk, 7 were at medium–risk. All 2nd degree relatives were at low risk. Applying our algorithm to this cohort of patients, we expected 1.56 new cases of Rb (0.88 for the siblings group, 0.67 for the offsprings group and 0.01 for the 2nd degree relatives) during the pre–defined follow up period. After a mean follow up of 62.6 +/– 20.4 months, 1 new case of Rb was diagnosed among the 2nd degree relatives from a low–risk patient (0.2%). All the patients older than 4 years old were followed carefully and none of them developed Rb. Conclusions: The present algorithm proved to be cost–effective, rapid and reliable, especially when mutational screening is not available or failed to identify the disease–causing mutation. Its clinical implementation should help to provide accurate genetic counseling.

Keywords: retinoblastoma • genetics • clinical (human) or epidemiologic studies: biostatistics/epidemiology methodology 
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