Evidence map›Paper›PMID 30390240›Full record

ArticlePharmacoEconomics - open2019

Economics of Acromegaly Treatment in Brazil: A Budget Impact Analysis of Pituitary Surgery Compared with Long-Term Octreotide LAR.

Lara Benigno Porto, Ivan Ricardo Zimmermann, Luciana Ansaneli Naves

Abstract read
In one paragraph

Article in PharmacoEconomics - open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Lara Benigno PortoFaculty of Health Sciences, University of Brasilia, Brasília, Brazil. larabporto@yahoo.com.br.ORCID http://orcid.org/0000-0002-1993-6584
Ivan Ricardo ZimmermannDepartment of Pharmaceutical Assistance and Strategic Inputs, Ministry of Health, Brasília, Brazil.ORCID http://orcid.org/0000-0001-7757-7519
Luciana Ansaneli NavesFaculty of Health Sciences, University of Brasilia, Brasília, Brazil.ORCID http://orcid.org/0000-0002-3363-3803

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcromegaly is a rare, chronic and debilitating disease whose treatment places a high burden on health systems. In the reality of the Brazilian public health network, many patients are kept on drug treatment because of barriers to access to surgery.

objectiveThe aim of this study was to estimate the costs and budget impact of routine transsphenoidal endoscopic surgery in relation to those of long-term drug treatment with octreotide long-acting release (LAR) from a cohort of patients followed at the referral medical centre for acromegaly treatment in the Federal District, Brazil.

methodsBased on micro-costing data collected using mixed methods from a local perspective of the public health system, we performed a budget impact analysis (BIA) on a 3-year time horizon. Uncertainty was handled with deterministic (tornado and scenario) and probabilistic (Monte Carlo simulations) sensitivity analyses.

resultsCompared with the continued use of octreotide LAR at a dose of 30 mg every 28 days, the incremental budget impact of conducting two surgeries per month, considering a cure rate of 55%, could bring savings of approximately US$879,362.18 (95% CI 860,176.29-898,548.08) over 3 years. Depending on the key variable values, the savings amplitude ranged from US$431,836.39 to US$1,519,132.04.

conclusionsImproving access to surgery could result in significant cost reductions in acromegaly treatment. The present study stands out for being the first to estimate the costs of transsphenoidal surgery in the context of the public health system in Brazil.

Identifiers

PMID30390240
PMCPMC6533371

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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.