Evidence map›Paper›PMID 31371934›Full record

ReviewInternational journal of chronic obstructive pulmonary disease2019

Personalized medicine for patients with COPD: where are we?

Frits Me Franssen, Peter Alter, Nadav Bar, Birke J Benedikter, Stella Iurato, Dieter Maier, Michael Maxheim, Fabienne K Roessler, Martijn A Spruit, Claus F Vogelmeier and 2 more

Abstract readReview
In one paragraph

Review in International journal of chronic obstructive pulmonary disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing 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

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

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  20. Applications of deep learning models in precision prediction of survival rates for heart failure patients.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024
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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

12 authors.

Frits Me FranssenDepartment of Research and Education, CIRO, Horn, The Netherlands.
Peter AlterDepartment of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps University of Marburg (UMR), Member of the German Center for Lung Research (DZL), Marburg, Germany.
Nadav BarDepartment of Chemical Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Birke J BenedikterInstitute for Lung Research, Universities of Giessen and Marburg Lung Centre, Philipps-University Marburg, Member of the German Center for Lung Research (DZL), Marburg, Germany.
Stella IuratoViscovery Software GmbH , Vienna, Austria.
Dieter MaierBiomax Informatics AG , Planegg, Germany.
Michael MaxheimDepartment of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps University of Marburg (UMR), Member of the German Center for Lung Research (DZL), Marburg, Germany.
Fabienne K RoesslerDepartment of Chemical Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Martijn A SpruitDepartment of Research and Education, CIRO, Horn, The Netherlands.
Claus F VogelmeierDepartment of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps University of Marburg (UMR), Member of the German Center for Lung Research (DZL), Marburg, Germany.
Emiel Fm WoutersDepartment of Research and Education, CIRO, Horn, The Netherlands.
Bernd SchmeckDepartment of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps University of Marburg (UMR), Member of the German Center for Lung Research (DZL), Marburg, Germany.

Funding

Austrian Science Fund FWF I 3736
6 · The paper itself

Abstract

Chronic airflow limitation is the common denominator of patients with chronic obstructive pulmonary disease (COPD). However, it is not possible to predict morbidity and mortality of individual patients based on the degree of lung function impairment, nor does the degree of airflow limitation allow guidance regarding therapies. Over the last decades, understanding of the factors contributing to the heterogeneity of disease trajectories, clinical presentation, and response to existing therapies has greatly advanced. Indeed, diagnostic assessment and treatment algorithms for COPD have become more personalized. In addition to the pulmonary abnormalities and inhaler therapies, extra-pulmonary features and comorbidities have been studied and are considered essential components of comprehensive disease management, including lifestyle interventions. Despite these advances, predicting and/or modifying the course of the disease remains currently impossible, and selection of patients with a beneficial response to specific interventions is unsatisfactory. Consequently, non-response to pharmacologic and non-pharmacologic treatments is common, and many patients have refractory symptoms. Thus, there is an ongoing urgency for a more targeted and holistic management of the disease, incorporating the basic principles of P4 medicine (predictive, preventive, personalized, and participatory). This review describes the current status and unmet needs regarding personalized medicine for patients with COPD. Also, it proposes a systems medicine approach, integrating genetic, environmental, (micro)biological, and clinical factors in experimental and computational models in order to decipher the multilevel complexity of COPD. Ultimately, the acquired insights will enable the development of clinical decision support systems and advance personalized medicine for patients with COPD.

Indexed as

Precision MedicineRisk Reduction BehaviorClinical Decision-MakingComorbidityDisease ProgressionGenetic Predisposition to DiseaseHealth StatusHumansMolecular Targeted TherapyPatient SelectionPhenotypePulmonary Disease, Chronic ObstructiveRespiratory System AgentsRisk AssessmentRisk FactorsTreatment OutcomeRespiratory System Agentschronic obstructive pulmonary diseasepersonalized medicinereviewsystems medicine

Identifiers

PMID31371934
PMCPMC6636434

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.