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Freddie Bray

Researcher at International Agency for Research on Cancer

Publications -  452
Citations -  345102

Freddie Bray is an academic researcher from International Agency for Research on Cancer. The author has contributed to research in topics: Cancer & Population. The author has an hindex of 111, co-authored 402 publications receiving 262938 citations. Previous affiliations of Freddie Bray include University of Oslo.

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Scaling Up the Surveillance of Childhood Cancer: A Global Roadmap

TL;DR: Based on their experience acquired at the International Agency for Research on Cancer in global cancer surveillance, this article reviewed crucial aspects to consider in the development of childhood cancer registration and presented their vision on how the Global Initiative for Cancer Registry Development can accelerate the measurement of the outcome of children with cancer.
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Cancer in Iran 2008 to 2025: Recent incidence trends and short-term predictions of the future burden.

Gholamreza Roshandel, +80 more
TL;DR: In this paper, the authors developed a method for approximating population-based incidence from the pathology-based data series available nationally for the years 2008 to 2013, and augmented this with data from the Iranian National Population-based Cancer Registry (INPCR), and fitted timelinear age-period models to the recent incidence trends to quantify the future cancer incidence burden to the year 2025, delineating the contribution of changes due to risk and those due to demographic change.
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Resource requirements for cancer registration in areas with limited resources: Analysis of cost data from four low- and middle-income countries.

TL;DR: The results suggest that cancer registration involve substantial fixed costs and labor, and that partnership with other institutions is critical for the operation and sustainability of cancer registries in limited resource settings.
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Measuring cancer in indigenous populations

TL;DR: This commentary describes key issues relating to cancer surveillance among indigenous populations including 1) suboptimal identification of indigenous populations, 2) numerator-denominator bias, 3) problems with data linkage in survival analysis, and 4) statistical analytic considerations.