TY - JOUR
T1 - Innovation Rating in Italy: Analysis of 77 Drug/Indication Reports (2017-2020) from AIFA
AU - Berto, P.
AU - Aiello, A.
AU - Sironi, Emiliano
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - drug
KW - drug
UR - http://hdl.handle.net/10807/179420
U2 - 10.1016/j.jval.2020.08.033
DO - 10.1016/j.jval.2020.08.033
M3 - Meeting Abstract
SN - 1098-3015
VL - 23
SP - S403-S403
JO - Value in Health
JF - Value in Health
ER -