Evidence map›Paper›PMID 34575624›Full record

ArticleJournal of personalized medicine2021

A Cost Decision Model Supporting Treatment Strategy Selection in BRCA1/2 Mutation Carriers in Breast Cancer.

Nunzia Carbonara, Daniele La Forgia, Roberta Pellegrino, Cosmo Ressa, Stefania Tommasi

Abstract read
In one paragraph

Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Nunzia CarbonaraDepartments of Mechanics Mathematics and Management, Politecnico di Bari, 70126 Bari, Italy.ORCID 0000-0003-3618-6444
Daniele La ForgiaSSD Radiodiagnostica Senologica, I.R.C.C.S. Istituto Tumori "Giovanni Paolo II" di Bari, 70124 Bari, Italy.ORCID 0000-0002-3902-4523
Roberta PellegrinoDepartments of Mechanics Mathematics and Management, Politecnico di Bari, 70126 Bari, Italy.ORCID 0000-0002-1098-4547
Cosmo RessaS.C. Chirurgia Plastica e Ricostruttiva, I.R.C.C.S. Istituto Tumori "Giovanni Paolo II" di Bari, 70124 Bari, Italy.
Stefania TommasiSSD Diagnostica Molecolare e Farmacogenetica, I.R.C.C.S. Istituto Tumori "Giovanni Paolo II" di Bari, 70124 Bari, Italy.ORCID 0000-0002-2157-2978

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, a cost decision-making model that compares the healthcare costs for diverse treatment strategies is built for BRCA-mutated women with breast cancer. Moreover, this model calculates the cancer treatment costs that could potentially be prevented, if the treatment strategy with the lowest total cost, along the entire lifetime of the patient, is chosen for high-risk women with breast cancer. The benchmark of the healthcare costs for diverse treatment strategies is selected in the presence of uncertainty, i.e., considering, throughout the lifetime of the patient, the risks and complications that may arise in each strategy and, therefore, the costs associated with the management of such events. Our results reveal a clear economic advantage of adopting the cost decision-making model for benchmarking the healthcare costs for various treatment strategies for BRCA-mutated women with breast cancer. The cost savings were higher when all breast cancer patients underwent counseling and genetic testing before deciding on any diagnostic-therapeutic path, with a probability of obtaining savings of over 75%.

Indexed as

BRCA-carriers managementbreast cancercost decision modeleconomic evaluationuncertainty

Identifiers

PMID34575624
PMCPMC8470684

What OpenQuestion holds

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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.