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Estimating the prevalence of hematological malignancies and precursor conditions using data from Haematological Malignancy Research Network (HMRN)

Overview of attention for article published in Cancer Causes & Control, June 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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1 policy source
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Citations

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127 Mendeley
Title
Estimating the prevalence of hematological malignancies and precursor conditions using data from Haematological Malignancy Research Network (HMRN)
Published in
Cancer Causes & Control, June 2016
DOI 10.1007/s10552-016-0780-z
Pubmed ID
Authors

Jinlei Li, Alex Smith, Simon Crouch, Steven Oliver, Eve Roman

Abstract

Well-established cancer registries that routinely link to death registrations can estimate prevalence directly by counting patients alive at a particular point in time (observed prevalence). Such direct methods can only provide prevalence for the years over which the registry has been operational. Time-defined estimates, including 5- and 10-year prevalence, may however underestimate the total cancer burden, and compared with other cancers, there is a lack of accurate information on the total prevalence of hematological malignancy subtypes. Accordingly, we aimed to estimate prevalence (observed and total prevalence) of hematological malignancies and precursor conditions by clinically meaningful subtypes using data from the UK's specialist population-based register, the Haematological Malignancy Research Network ( www.hmrn.org ). Observed and total prevalences were estimated from 15,810 new diagnoses of hematological malignancies from 2004 to 2011 and followed up to the 31 August 2011 (index data). Observed prevalence was calculated by the counting method, and a method based on modelling incidence and survival was used to estimate total prevalence. Estimates were made according to current disease classification for the HMRN region and for the UK. The overall observed and total prevalence rates were 281.9 and 548.8 per 100,000, respectively; the total number of observed and total prevalent cases in the UK was estimated as 165,841 and 327,818 cases, as expected variation existed by disease subtype reflecting the heterogeneity in underlying disease incidence, survival and age distribution of hematological cancers. This study demonstrates the importance of estimating 'total' prevalence rather than 'observed' prevalence by current disease classification (ICD-O-3), particularly for subtypes that have a more indolent nature and for those that are curable. Importantly, these analyses demonstrate that relying on observed prevalence alone would result in a significant underestimation of the relative burden of some subtypes. While many of these cases may be considered cured and no longer being actively treated, people in this survivorship phase may have long-term medical needs and accordingly, it is important to provide accurate counts to allow for healthcare planning.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 127 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 19 15%
Other 15 12%
Researcher 14 11%
Student > Master 14 11%
Student > Ph. D. Student 13 10%
Other 22 17%
Unknown 30 24%
Readers by discipline Count As %
Medicine and Dentistry 43 34%
Biochemistry, Genetics and Molecular Biology 10 8%
Nursing and Health Professions 9 7%
Agricultural and Biological Sciences 6 5%
Immunology and Microbiology 5 4%
Other 19 15%
Unknown 35 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 May 2018.
All research outputs
#7,660,617
of 23,854,458 outputs
Outputs from Cancer Causes & Control
#904
of 2,187 outputs
Outputs of similar age
#122,253
of 356,407 outputs
Outputs of similar age from Cancer Causes & Control
#7
of 27 outputs
Altmetric has tracked 23,854,458 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 2,187 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has gotten more attention than average, scoring higher than 57% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 356,407 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.