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Priya Selvakumar, ; AJCC TNM COLLABORATIVE INTERNET STAGING VALIDATION FOR OPHTHALMIC TUMORS. Invest. Ophthalmol. Vis. Sci. 2013;54(15):5876.
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The current 7th edition of American Joint Committee on Cancer - International Union Against Cancer (AJCC-UICC) tumor, node, metastasis (TNM) staging for ophthalmic tumors is largely based on the consensus of 46 eye cancer specialists from 11 countries, since there is a paucity of evidence-based clinical trials in ocular oncology. In order to prepare for the 8th edition, we developed a collaborative internet survey evaluating the prognostic accuracy for the 7th edition.
Data fields were designed by multicenter clinical collaboration. Web-based algorithms were constructed to calculate cancer-specific TNM stage, based on ocular and systemic extent of disease. The accuracy of the algorithms was authenticated by the participating clinican-scientists through a demo online survey. Research features not yet established in treatment were included. Ongoing, after each participating center has obtained institutional ethics approval, they enter data anonymized data on all relevant patients treated in their institution over a 10 year period. Statistical analysis is applied to the collective multicenter data.
The algorithms include all data points required to calculate the TNM stage, including tumor site and dimensions at initial presentation, lymph node involvement, pathological grading, biomarkers, systemic metastasis, and research biomarkers and broad treatment categories and outcome at last follow-up. In the ongoing study of uveal melanoma, participating centres have entered more than 2529 uveal melanoma patients. The demo online surveys for retinoblastoma, conjunctival melanoma and conjunctival carcinoma are under construction.
The multicenter collaboration using the internet and TNM staging algorithms is collecting accurate data and outcomes with efficiency, ready for analysis. International collaboration provides large numbers of patients. The assessment of the 7th edition TNM staging to accurately predict outcomes will be used to improve the prognostic capability of the 8th edition.
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