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Incidence and survival of uveal melanoma in Northern Ireland: how incomplete data can skew results in rare cancers

  • Hibba Quhill
  • , Joanna M Jefferis
  • , Ian G Rennie
  • , Sachin M Salvi
  • , Anna Gavin
  • , Deirdre Fitzpatrick
  • , Gerard Savage
  • , David Curragh
  • , Paul Rundle

Research output: Contribution to journalArticlepeer-review

Abstract

Background
The majority of Northern Irish uveal melanoma (UM) patients are diagnosed in Sheffield. This study aims to present incidence and survival outcomes for UM patients from Northern Ireland (NI).

Methods
Collaborative retrospective study between Sheffield and Northern Ireland Cancer Registry (NICR). For UM cases not on both databases, outcomes and survival rates (via Kaplan-Meier analysis) were compared. Anonymised NICR data were used to calculate whole-population incidence of UM for NI.

Results
In total, 161 patients from NI were diagnosed in Sheffield, 90 of which were not registered with NICR at the start of this study. Data-omissions were not consistent across patient groups, leading to significant differences between those patients registered and those not. Registered patients had an all-cause 5-year survival rate of only 68.9% compared to 92.5% of those not registered (p < 0.01) and were >17x more likely to have systemic metastases than those not registered (p < 0·001). Following rectification of data-omissions, the European age-standardised incidence rate of UM for NI was 8·6 per million.

Conclusions
This study illustrates the impact of incomplete population-wide data, serving as a real-world lesson in case-identification bias. Rare cancers are at higher risk of omission due to systemic failures as the small numbers involved are not detected by system-wide validation procedures. Following this study, data-transfer agreements between England and NI were actioned, preventing future data-omissions. We present survival and incidence data for UM in NI for the first time, showing the incidence is amongst the highest in Europe, with good survival rates.
Original languageEnglish
Pages (from-to)2454–2460
Number of pages7
JournalEye
Volume37
Early online date09 Dec 2022
DOIs
Publication statusPublished - 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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