The Evaluation of Drug Innovativeness in Italy: Key Determinants and Internal Consistency.


Journal

PharmacoEconomics - open
ISSN: 2509-4254
Titre abrégé: Pharmacoecon Open
Pays: Switzerland
ID NLM: 101700780

Informations de publication

Date de publication:
May 2023
Historique:
accepted: 16 01 2023
medline: 11 2 2023
pubmed: 11 2 2023
entrez: 10 2 2023
Statut: ppublish

Résumé

Innovative medicines are provided with dedicated funds and immediate market access in Italy. Innovativeness evaluation considers unmet need, added therapeutic value, and quality of the evidence. We aimed to evaluate the internal consistency and drivers of the innovativeness appraisal process. Appraisal reports on innovativeness refer to 1997-2021. We used both a descriptive approach and probabilistic multivariate analysis, using logistic regression models to compute odds ratios and 95% confidence intervals. The dependent variable is innovativeness status (innovative vs. non-innovative; full innovativeness vs. conditional innovativeness). Explanatory variables, besides the three above-mentioned domains, are the year of evaluation, drug type, target disease and population, and the number and type of available studies. Among the 141 medicines scrutinized, 31.9%, 29.8%, and 38.3% were evaluated as fully innovative, conditionally innovative, and non-innovative, respectively. Added therapeutic value and the quality of the evidence were associated with the odds of receiving innovative status, and full compared with conditional innovativeness; unmet need was not a predictive variable. Other factors played a minor role: medicines for both solid tumours and rare diseases are more likely to be judged innovative; conditional innovativeness is more probable for medicines for rare diseases. Innovativeness status is driven by the added therapeutic value and quality of evidence. The appraisal process is internally consistent and predictable. This provides industry with a clear indication of what is needed to ensure that access to their medicines is prioritized.

Sections du résumé

BACKGROUND BACKGROUND
Innovative medicines are provided with dedicated funds and immediate market access in Italy. Innovativeness evaluation considers unmet need, added therapeutic value, and quality of the evidence.
OBJECTIVE OBJECTIVE
We aimed to evaluate the internal consistency and drivers of the innovativeness appraisal process.
METHODS METHODS
Appraisal reports on innovativeness refer to 1997-2021. We used both a descriptive approach and probabilistic multivariate analysis, using logistic regression models to compute odds ratios and 95% confidence intervals. The dependent variable is innovativeness status (innovative vs. non-innovative; full innovativeness vs. conditional innovativeness). Explanatory variables, besides the three above-mentioned domains, are the year of evaluation, drug type, target disease and population, and the number and type of available studies.
RESULTS RESULTS
Among the 141 medicines scrutinized, 31.9%, 29.8%, and 38.3% were evaluated as fully innovative, conditionally innovative, and non-innovative, respectively. Added therapeutic value and the quality of the evidence were associated with the odds of receiving innovative status, and full compared with conditional innovativeness; unmet need was not a predictive variable. Other factors played a minor role: medicines for both solid tumours and rare diseases are more likely to be judged innovative; conditional innovativeness is more probable for medicines for rare diseases.
CONCLUSIONS CONCLUSIONS
Innovativeness status is driven by the added therapeutic value and quality of evidence. The appraisal process is internally consistent and predictable. This provides industry with a clear indication of what is needed to ensure that access to their medicines is prioritized.

Identifiants

pubmed: 36763319
doi: 10.1007/s41669-023-00393-3
pii: 10.1007/s41669-023-00393-3
pmc: PMC10169980
doi:

Types de publication

Journal Article

Langues

eng

Pagination

373-381

Subventions

Organisme : MSD
ID : MSD Oncology Policy Grant Program

Informations de copyright

© 2023. The Author(s).

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Auteurs

Claudio Jommi (C)

Department of Pharmaceutical Sciences, Università del Piemonte Orientale, Novara, Italy. claudio.jommi@unibocconi.it.
Cergas (Centre for Research on Health and Social Care Management), SDA Bocconi, Bocconi University, Milan, Italy. claudio.jommi@unibocconi.it.

Carlotta Galeone (C)

Biostatistics & Outcome Research, Statinfo, Milan, Italy.
Bicocca Applied Statistics Center (B-ASC), Università degli Studi di Milano-Bicocca, Milan, Italy.

Classifications MeSH