Innovation Rating in Italy: Analysis of 77 Drug/Indication Reports (2017-2020) from AIFA

Emiliano Sironi, P. Berto, A. Aiello

Risultato della ricerca: Contributo in rivistaAbstract


Objectives: In 2017 the Italian Medicines Agency (AIFA) published its revised model to assess the degree of innovation for new drugs/indications. High rating allows funding from a dedicated 1BV fund (0.5BV each allocated to oncology and non-oncology indications), andfaster access tolocal/regional formularies.Asof June2020, 77reportswere published on the AIFA website, allowing examination of some determinants of the Agency’s decision-making. Methods: An ordinal regression model was applied to address determinants of innovation status. According to AIFA’s reports, innovation status is a categorical variable ranked into the following descending categories: full innovation (FI), conditional innovation(CI),noinnovation(NI).The set ofmainpredictors supposedly affecting innovation status includes: 1) Therapeutic Need (TN), 2) Added Therapeutic Value (ATV), 3) Quality of Evidence (QE) (rated according to the GRADE method). Two additional control variables are also considered: orphan drug designation (ODD) (yes/no) and therapeutic macro-area (oncological vs. non oncological). Results: Of 77 published drug/indication submissions, 50 (65%) are oncological; 32 (42%) are orphan. 28 (36%) drug/indications were classified as FI; 23 (30%) CI and 26 (34%) NI. Regression estimates confirmthat QEis fully significant (p,0.001) in determining innovation status, with high quality of evidence being positively associated to innovation status. TN and ATV are also positively associated to innovationstatus, even ifmulticollinearity undermines estimates for a model including both indicators. Conversely, orphan designation and therapeutic macro-area seem not to affect innovation status, when controlling for TN, ATV and QE. Conclusions: Although the sample size is still relatively limited, our results show that QE, rooted in the application of the objective standardized GRADE methodology, represents an important determinant of Innovation Status. Multicollinearity of TN and ATV highlights strict inter-correlation between the two variables. ODD or oncology macroarea per se do not grant positive innovation rating in Italy.
Lingua originaleEnglish
pagine (da-a)S403-S403
RivistaValue in Health
Stato di pubblicazionePubblicato - 2020


  • drug

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