Evidence map›Paper›PMID 31217346›Full record

Observational studyJCI insight2019

Predictive model of response to tafamidis in hereditary ATTR polyneuropathy.

Cecília Monteiro, Jaleh S Mesgazardeh, João Anselmo, Joana Fernandes, Marta Novais, Carla Rodrigues, Gabriel J Brighty, David L Powers, Evan T Powers, Teresa Coelho and 1 more

Abstract readObservational Study
In one paragraph

Observational study in JCI insight, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. Article
  8. Mass spectrometry footprinting reveals how kinetic stabilizers counteract transthyretin dynamics altered by pathogenic mutations.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  14. A Snapshot of the Most Recent Transthyretin Stabilizers.International journal of molecular sciences · 2024
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Cecília MonteiroDepartments of Chemistry and Molecular Medicine, The Scripps Research Institute, La Jolla, California, USA.
Jaleh S MesgazardehDepartments of Chemistry and Molecular Medicine, The Scripps Research Institute, La Jolla, California, USA.
João AnselmoUnidade Corino de Andrade, Centro Hospitalar do Porto, Porto, Portugal.
Joana FernandesUnidade Corino de Andrade, Centro Hospitalar do Porto, Porto, Portugal.
Marta NovaisUnidade Corino de Andrade, Centro Hospitalar do Porto, Porto, Portugal.
Carla RodriguesUnidade Corino de Andrade, Centro Hospitalar do Porto, Porto, Portugal.
Gabriel J BrightyDepartments of Chemistry and Molecular Medicine, The Scripps Research Institute, La Jolla, California, USA.
David L PowersDepartment of Mathematics, Clarkson University, Potsdam, New York, USA.
Evan T PowersDepartments of Chemistry and Molecular Medicine, The Scripps Research Institute, La Jolla, California, USA.
Teresa CoelhoUnidade Corino de Andrade, Centro Hospitalar do Porto, Porto, Portugal.
Jeffery W KellyDepartments of Chemistry and Molecular Medicine, The Scripps Research Institute, La Jolla, California, USA.

Funding

Probing the Biochemical Mechanisms of Amyloid DiseaseR01DK046335 · NIDDK · SCRIPPS RESEARCH INSTITUTE, THE · PI KELLY, JEFFERY W · 1998 to 2025
$8.8M
Probing the biochemical mechanism of amyloid diseaseR37DK046335 · NIDDK · SCRIPPS RESEARCH INSTITUTE, THE · PI KELLY, JEFFERY W · 2006 to 2015
$5.9M
NIDDK NIH HHS R01 DK046335NIDDK NIH HHS R37 DK046335
6 · The paper itself

Abstract

BACKGROUNDThe hereditary transthyretin (TTR) amyloidoses are a group of diseases for which several disease-modifying treatments are now available. Long-term effectiveness of these therapies is not yet fully known. Moreover, the existence of alternative therapies has resulted in an urgent need to identify patient characteristics that predict response to each therapy.METHODSWe carried out a retrospective cohort study of 210 patients with hereditary TTR amyloidosis treated with the kinetic stabilizer tafamidis (20 mg qd). These patients were followed for a period of 18-66 months, after which they were classified by an expert as responders, partial responders, or nonresponders. Correlations between baseline demographic and clinical characteristics, as well as plasma biomarkers and response to therapy, were investigated.RESULTS34% of patients exhibited an almost complete arrest of disease progression (classified by an expert as responders); 36% had a partial to complete arrest in progression of some but not all disease components (partial responders); whereas the remaining 30% continued progressing despite therapy (nonresponders). We determined that disease severity, sex, and native TTR concentration at the outset of treatment were the most relevant predictors of response to tafamidis. Plasma tafamidis concentration after 12 months of therapy was also a predictor of response for male patients. Using these variables, we built a model to predict responsiveness to tafamidis.CONCLUSIONOur study indicates long-term effectiveness for tafamidis, a kinetic stabilizer approved for the treatment of hereditary TTR amyloidosis. Moreover, we created a predictive model that can be potentially used in the clinical setting to inform patients and clinicians in their therapeutic decisions.

Indexed as

AdultAgedAged, 80 and overAmyloid Neuropathies, FamilialBenzoxazolesBiomarkersCohort StudiesDemographyFemaleHumansLongitudinal StudiesMaleMiddle AgedModels, BiologicalPrealbuminSex FactorsBenzoxazolesBiomarkersPrealbumintafamidisTTR protein, humanGenetic diseasesNeuromuscular diseaseNeuroscienceProtein misfoldingTherapeutics

Identifiers

PMID31217346
PMCPMC6629131

What OpenQuestion holds

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Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.