The University of California, San Francisco Documentation System for Retinoblastoma: Preparing to Improve Staging Methods for This Disease.

Prognosis Retinoblastoma Treatment

Journal

Ocular oncology and pathology
ISSN: 2296-4681
Titre abrégé: Ocul Oncol Pathol
Pays: Switzerland
ID NLM: 101656139

Informations de publication

Date de publication:
Jan 2019
Historique:
received: 13 02 2018
revised: 02 03 2018
entrez: 25 1 2019
pubmed: 25 1 2019
medline: 25 1 2019
Statut: ppublish

Résumé

Current retinoblastoma staging systems do not adequately describe the disease, especially in eyes with multiple tumors. The aims of this study were to develop methods for documenting individual tumors and to score disease burden over time. A coding system was devised to describe each tumor according to affected eye, meridian, anteroposterior location, activity, growth pattern, type of seed, and treatment. A scoring system for quantifying disease burden was developed, taking account of tumor number, size, spread, and secondary effects on the eye. Our coding system allowed contemporaneous tumor documentation, producing datasets that enabled generation of fundus diagrams, Kaplan-Meier curves, and tables summarizing disease progression in individual tumors and eyes. Our data showed disparities between ocular and tumor documentation, e.g., indicating earlier tumor development in the left eye but younger age at presentation if disease was worse in the right eye. Actuarial rates of local treatment failure were lower when individual tumors were analyzed than when data were reported in terms of whole eyes. Our methods for documenting individual retinoblastomas have facilitated the review of patients' progress in our routine practice and may provide data that could be used to refine retinoblastoma classifications in the future.

Sections du résumé

BACKGROUND/AIMS OBJECTIVE
Current retinoblastoma staging systems do not adequately describe the disease, especially in eyes with multiple tumors. The aims of this study were to develop methods for documenting individual tumors and to score disease burden over time.
METHODS METHODS
A coding system was devised to describe each tumor according to affected eye, meridian, anteroposterior location, activity, growth pattern, type of seed, and treatment. A scoring system for quantifying disease burden was developed, taking account of tumor number, size, spread, and secondary effects on the eye.
RESULTS RESULTS
Our coding system allowed contemporaneous tumor documentation, producing datasets that enabled generation of fundus diagrams, Kaplan-Meier curves, and tables summarizing disease progression in individual tumors and eyes. Our data showed disparities between ocular and tumor documentation, e.g., indicating earlier tumor development in the left eye but younger age at presentation if disease was worse in the right eye. Actuarial rates of local treatment failure were lower when individual tumors were analyzed than when data were reported in terms of whole eyes.
CONCLUSION CONCLUSIONS
Our methods for documenting individual retinoblastomas have facilitated the review of patients' progress in our routine practice and may provide data that could be used to refine retinoblastoma classifications in the future.

Identifiants

pubmed: 30675475
doi: 10.1159/000488147
pii: oop-0005-0036
pmc: PMC6341334
doi:

Types de publication

Journal Article

Langues

eng

Pagination

36-45

Subventions

Organisme : NEI NIH HHS
ID : P30 EY002162
Pays : United States

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Auteurs

Bertil Damato (B)

Department of Ophthalmology, University of California, San Francisco, San Francisco, California, USA.

Armin R Afshar (AR)

Department of Ophthalmology, University of California, San Francisco, San Francisco, California, USA.

Lesley Everett (L)

Department of Ophthalmology, University of California, San Francisco, San Francisco, California, USA.

Anuradha Banerjee (A)

Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA.

Steven W Hetts (SW)

Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA.

Classifications MeSH