↓ Skip to main content

Treatment of idiopathic pulmonary fibrosis: a network meta-analysis

Overview of attention for article published in BMC Medicine, February 2016
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

5 tweeters


32 Dimensions

Readers on

93 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Treatment of idiopathic pulmonary fibrosis: a network meta-analysis
Published in
BMC Medicine, February 2016
DOI 10.1186/s12916-016-0558-x
Pubmed ID

Bram Rochwerg, Binod Neupane, Yuan Zhang, Carlos Cuello Garcia, Ganesh Raghu, Luca Richeldi, Jan Brozek, Joseph Beyene, Holger Schünemann


Idiopathic pulmonary fibrosis (IPF) is an interstitial lung disease associated with high morbidity and mortality. Effective treatments for IPF are limited. Several recent studies have investigated novel therapeutic agents for IPF, but very few have addressed their comparative benefits and harms. We performed a Bayesian network meta-analysis (NMA) to assess the effects of different treatments for IPF on mortality and serious adverse events (SAEs). We searched MEDLINE and EMBASE for randomized controlled trials (RCTs) up to August 2015. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach served to assess the certainty in the evidence of direct and indirect estimates. We calculated the surface under the cumulative ranking curve (SUCRA) for each treatment. We included parallel group RCTs, including factorial designs, but excluded quasi-randomized and cross-over trials. Studies were only included if they involved adult (≥18 years of age) patients with IPF as defined by the 2011 criteria and examined one of the 10 interventions of interest (ambrisentan, bosentan, imatinib, macitentan, N-acetylcysteine, nintedanib, pirfenidone, sildenafil, prednisone/azathioprine/N-acetylcysteine triple therapy, and vitamin K antagonist). A total of 19 RCTs (5,694 patients) comparing 10 different interventions with placebo and an average follow-up period of 1 year fulfilled the inclusion criteria. SUCRA analysis suggests nintedanib, pirfenidone, and sildenafil are the three treatments with the highest probability of reducing mortality in IPF. Indirect comparison showed no significant difference in mortality between pirfenidone and nintedanib (NMA OR, 1.05; 95 % CrI, 0.45-2.78, moderate certainty of evidence), pirenidone and sildenafil (NMA OR, 2.26; 95 % CrI, 0.44-13.17, low certainty of evidence), or nintedanib and sildenafil (NMA OR 2.40; 95 % CrI, 0.47-14.66, low certainty of evidence). Sildenafil, pirfenidone, and nintedanib were ranked second, fourth, and sixth out of 10 for SAEs. In the absence of direct comparisons between treatment interventions, this NMA suggests that treatment with nintedanib, pirfenidone, and sildenafil extends survival in patients with IPF. The SAEs of these agents are similar to the other interventions and include mostly dermatologic and gastrointestinal manifestations. Head-to-head comparisons need to confirm these findings.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 1%
Canada 1 1%
Brazil 1 1%
Unknown 90 97%

Demographic breakdown

Readers by professional status Count As %
Other 15 16%
Student > Bachelor 14 15%
Researcher 14 15%
Student > Master 9 10%
Student > Ph. D. Student 9 10%
Other 19 20%
Unknown 13 14%
Readers by discipline Count As %
Medicine and Dentistry 49 53%
Pharmacology, Toxicology and Pharmaceutical Science 7 8%
Agricultural and Biological Sciences 5 5%
Biochemistry, Genetics and Molecular Biology 3 3%
Nursing and Health Professions 3 3%
Other 8 9%
Unknown 18 19%

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 24 August 2016.
All research outputs
of 11,342,938 outputs
Outputs from BMC Medicine
of 1,810 outputs
Outputs of similar age
of 345,120 outputs
Outputs of similar age from BMC Medicine
of 42 outputs
Altmetric has tracked 11,342,938 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,810 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 32.7. This one is in the 23rd percentile – i.e., 23% 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 345,120 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 69% of its contemporaries.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.