Evidence map›Paper›PMID 31239737›Full record

ArticleClinicoEconomics and outcomes research : CEOR2019

Abatacept: from a budget impact model to cost-effectiveness analysis - data from RCT and real life.

Maurizio Benucci, Arianna Damiani, Mariangela Manfredi, Maria Infantino, Valentina Grossi, Francesca Li Gobbi

Open access · goldAbstract read
In one paragraph

Article in ClinicoEconomics and outcomes research : CEOR, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 55% of its field
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 2 institutions in 1 country.

Maurizio BenucciRheumatology Unit, S.Giovanni di Dio Hospital, Florence, Italy.
Arianna DamianiRheumatology Unit, S.Giovanni di Dio Hospital, Florence, Italy.
Mariangela ManfrediImmunology and Allergology Laboratory Unit, S.Giovanni di Dio Hospital, Azienda USL-Toscana Centro, Florence, Italy.
Maria InfantinoImmunology and Allergology Laboratory Unit, S.Giovanni di Dio Hospital, Azienda USL-Toscana Centro, Florence, Italy.
Valentina GrossiImmunology and Allergology Laboratory Unit, S.Giovanni di Dio Hospital, Azienda USL-Toscana Centro, Florence, Italy.
Francesca Li GobbiRheumatology Unit, S.Giovanni di Dio Hospital, Florence, Italy.
Azienda Usl Toscana Centro · ITNuovo Ospedale San Giovanni di Dio · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rheumatoid arthritis (RA) is a chronic inflammatory disorder that affects joints with swelling and progressive joint destruction. The pathology leads to a progressive disability with an impact on the quality of life of the patients. Strategies to reduce in-patient care costs could have a considerable impact on lowering the direct medical costs of RA in Italy. Abatacept, a selective T-cell costimulation modulator, is a valuable treatment option for patients with moderate-to-severe RA. A search using the keywords "cost-effectiveness analysis", "budget impact model", "abatacept", and "rheumatoid arthritis" was carried out on PubMed. Abatacept in the first- and second-treatment lines has been evaluated in our research. We evaluated patients with inadequate MTX response, inadequate anti-TNF agents response, switch studies and real-world data. Furthermore, in our research, we evaluated the main head-to-head studies published.

Indexed as

abataceptbudget impact modelcost-effectiveness analysisrheumatoid arthritis

Identifiers

PMID31239737
PMCPMC6560192
OpenAlexW2948251549

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.