Evidence map›Paper›PMID 38727995›Full record

ArticleDermatology and therapy2024

OPT-In; Optimized Patient Treatment Outcomes in Plaque Psoriasis: A 3-Year State-Transition Treatment-Sequencing Model in the Italian Setting.

Sarah Alulis, Nicoletta Bernardini, Martina Burlando, Antonio Costanzo, Pier Cesare Francesa Morel, Paolo Gisondi, Francesco Loconsole, Matteo Megna, Giovanni Pellacani, Stefano Piaserico and 4 more

Abstract read
In one paragraph

Article in Dermatology and therapy, 2024. 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
–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

0 citing papers in PubMed.

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

14 authors.

Sarah AlulisJanssen-Cilag A/S, Birkerød, Denmark.
Nicoletta BernardiniDermatology Unit "D. Innocenzi", Department of Medical and Surgical Sciences and Biotechnologies, Sapienza University of Rome-Polo Pontino, Latina, Italy.
Martina BurlandoClinica Dermatologica, DissaL, Ospedale Policlinico San Martino-IRCCS, Genoa, Italy.
Antonio CostanzoUnit of Dermatology, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy.
Pier Cesare Francesa MorelJanssen-Cilag, Via Michelangelo Buonarroti, 23, 20093, Cologno Monzese, MI, Italy. pfrances@its.jnj.com.ORCID http://orcid.org/0000-0002-9503-016X
Paolo GisondiSection of Dermatology and Venereology, Department of Medicine, University of Verona, Verona, Italy.
Francesco LoconsoleDepartment of Biomedical Sciences and Human Oncology, University of Bari Aldo Moro, Bari, Italy.
Matteo MegnaSection of Dermatology, Department of Clinical, Medicine and Surgery, University of Naples Federico II, Naples, Italy.
Giovanni PellacaniDermatology Clinic, Department of Clinical Internal, Anesthesiologic and Cardiovascular Sciences, Sapienza Medical School, Sapienza University of Rome, Rome, Italy.
Stefano PiasericoDermatology Unit, Department of Medicine (DIMED), University of Padua, Padua, Italy.
Francesca PrignanoDepartment of Health Sciences, Section of Dermatology, University of Florence, Florence, Italy.
Ottavio SecchiJanssen-Cilag, Via Michelangelo Buonarroti, 23, 20093, Cologno Monzese, MI, Italy.
Nevena SkrozaDermatology Unit "D. Innocenzi", Department of Medical and Surgical Sciences and Biotechnologies, Sapienza University of Rome-Polo Pontino, Latina, Italy.
Fareen HassanJanssen-Cilag Ltd, High Wycombe, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThere are several treatment options for plaque psoriasis (PsO), but uncertainty remains around the optimal sequencing of treatments. The aims of this study were to investigate how adopting a best-treatment-first treatment sequence impacts patient outcomes and healthcare systems and to quantify the cost of treatment failure to the healthcare system.

methodsA 3-year state-transition treatment-sequencing model which identifies all possible treatment sequences in PsO was adapted to the Italian healthcare setting. Treatments considered in the model are those with European Medicines Agency marketing authorization and reimbursement in Italy as of December 2022. Italian market share data (2019-2021) and list prices (2022) informed the current prescribed sequences; these sequences were compared against all possible sequences to determine opportunities for improvement. Both the national perspective in Italy as well as the local perspective from seven regions were considered. The cost of treatment failure was informed through a questionnaire circulated to Italian dermatologists.

resultsOverall, 1284 possible treatment sequences are possible when four lines of treatment are considered for patients with moderate-to-severe PsO in Italy. Within the estimated range of treatment failures across those sequences (0.97-2.56 per patient over 3 years), current prescribing behavior from the national perspective suggests patients will face 1.44 failures on average; this highlights the potential for improvement. For every treatment failure, the cost borne by the Italian National Healthcare Service (NHS) is €676.80. Overall, prescribing more optimized treatment sequences results in a 22.95% reduction in failures with a 2.27% increase in costs. The regional analyses found similar trends.

conclusionsResults suggest that selecting the most effective treatment sequences for incident patients provides the greatest opportunity to reduce treatment failures and maximize patient outcomes with a modest impact on costs. While regional variations exist, there is room for improvement across the board, which could translate to more efficient local healthcare systems.

Indexed as

ItalyPatient outcomesPlaque psoriasisTreatment failuresTreatment sequencesTreatment-sequencing model

Identifiers

PMID38727995
PMCPMC11116314

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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.