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A clinical-molecular prognostic model to predict survival in patients with post polycythemia vera and post essential thrombocythemia myelofibrosis

Overview of attention for article published in Leukemia (08876924), May 2017
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2 tweeters
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Citations

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88 Mendeley
Title
A clinical-molecular prognostic model to predict survival in patients with post polycythemia vera and post essential thrombocythemia myelofibrosis
Published in
Leukemia (08876924), May 2017
DOI 10.1038/leu.2017.169
Pubmed ID
Authors

F Passamonti, T Giorgino, B Mora, P Guglielmelli, E Rumi, M Maffioli, A Rambaldi, M Caramella, R Komrokji, J Gotlib, J J Kiladjian, F Cervantes, T Devos, F Palandri, V De Stefano, M Ruggeri, R T Silver, G Benevolo, F Albano, D Caramazza, M Merli, D Pietra, R Casalone, G Rotunno, T Barbui, M Cazzola, A M Vannucchi

Abstract

Polycythemia vera (PV) and essential thrombocythemia (ET) are myeloproliferative neoplasms with variable risk of evolution into post-PV and post-ET myelofibrosis, from now on referred to as secondary myelofibrosis (SMF). No specific tools have been defined for risk stratification in SMF. To develop a prognostic model for predicting survival, we studied 685 JAK2, CALR, and MPL annotated patients with SMF. Median survival of the whole cohort was 9.3 years (95% CI: 8-not reached-NR-). Through penalized Cox regressions we identified negative predictors of survival and according to beta risk coefficients we assigned 2 points to hemoglobin level <11 g/dl, to circulating blasts ⩾3%, and to CALR-unmutated genotype, 1 point to platelet count <150 × 10(9)/l and to constitutional symptoms, and 0.15 points to any year of age. MYSEC-PM (Myelofibrosis Secondary to PV and ET-Prognostic Model) allocated SMF patients into four risk categories with different survival (P<0.0001): low (median survival NR; 133 patients), intermediate-1 (9.3 years, 95% CI: 8.1-NR; 245 patients), intermediate-2 (4.4 years, 95% CI: 3.2-7.9; 126 patients), and high risk (2 years, 95% CI: 1.7-3.9; 75 patients). Finally, we found that the MYSEC-PM represents the most appropriate tool for SMF decision-making to be used in clinical and trial settings.Leukemia accepted article preview online, 31 May 2017. doi:10.1038/leu.2017.169.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 88 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 13%
Other 11 13%
Student > Ph. D. Student 11 13%
Professor 10 11%
Student > Bachelor 9 10%
Other 17 19%
Unknown 19 22%
Readers by discipline Count As %
Medicine and Dentistry 46 52%
Biochemistry, Genetics and Molecular Biology 8 9%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Engineering 2 2%
Agricultural and Biological Sciences 2 2%
Other 5 6%
Unknown 23 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 07 September 2017.
All research outputs
#7,303,823
of 11,727,438 outputs
Outputs from Leukemia (08876924)
#2,448
of 3,160 outputs
Outputs of similar age
#152,582
of 271,237 outputs
Outputs of similar age from Leukemia (08876924)
#62
of 87 outputs
Altmetric has tracked 11,727,438 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,160 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
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 271,237 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 87 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.