| Literature DB >> 35145344 |
Mohammed A Omair1, Rana Almadany2, Maha A Omair3, Hanan Al Rayes4, Haya M Almalag5, Aws Alshamsan6.
Abstract
BACKGROUND: The aim of this study was to evaluate rheumatologists' perceptions of biosimilar biologics and Non-Medical Switching (NMS).Entities:
Keywords: Biosimilars; Non-medical switching; Rheumatoid arthritis; Saudi Arabia
Year: 2021 PMID: 35145344 PMCID: PMC8802094 DOI: 10.1016/j.jsps.2021.10.012
Source DB: PubMed Journal: Saudi Pharm J ISSN: 1319-0164 Impact factor: 4.330
Baseline characteristics of the study participants.
| Characteristic | N (%) |
|---|---|
| Males | 85 (59.44) |
| Saudi nationality | 113 (79.02) |
| Mean age | 42.3 ± 9.13 |
| Mean Years of Practice | 10.3 ± 8.9 |
| Specialty | |
| Adult rheumatologist | 117 (81.82) |
| Pediatric rheumatologist | 26 (18.18) |
| Consultant level | 115 (80.42) |
| Type of practice | |
| Ministry of health | 62 (43.36) |
| Military institution | 28 (19.58) |
| Academic centre | 36 (25.17) |
| Private practice | 17 (11.89) |
| Ever used a biosimilar | 43 (30.07) |
| Performed Non-Medical Switching | 26 (18.18) |
Variable impact on participants’ responses.
| Question: What is the likelihood of prescribing a biosimilar to an eligible rheumatic disease patient at the current moment? | |||
| Variable | Odds ratio | CI | p value |
| Male gender | 1.553 | 0.728–3.311 | 0.255 |
| Non-Saudi nationality | 1.175 | 0.426–3.238 | 0.756 |
| Adult specialty | 2.183 | 0.84–5.677 | 0.109 |
| Consultant status | 1.18 | 0.473–2.944 | 0.722 |
| Type of practice | |||
| Academic | 1.169 | 0.499–2.737 | 0.72 |
| Military | 3.901 | 1.334–11.407 | |
| Private practice | 2.975 | 0.754–11.735 | 0.119 |
| Constant | 0.364 | – | 0.113 |
| Do you have a clear understanding on the concept of totality of evidence regarding the approval process of biosimilars? | |||
| Variable | Odds ratio | CI | p value |
| Male gender | 0.766 | 0.358–1.637 | 0.491 |
| Non-Saudi nationality | 0.409 | 0.149–1.127 | 0.084 |
| Adult specialty | 0.571 | 0.211–1.549 | 0.271 |
| Consultant status | 0.366 | 0.13–1.031 | 0.057 |
| Question: Do you believe that non-medical switching could be harmful? | |||
| Variable | Odds ratio | CI | p value |
| Female gender | 1.847 | 0.86–3.965 | 0.116 |
| Non-Saudi nationality | 1.727 | 0.616–4.842 | 0.299 |
| Adult specialty | 1.043 | 0.403–2.699 | 0.93 |
| Consultant status | 1.368 | 0.544–3.437 | 0.505 |
| Type of practice | |||
| Academic | 0.758 | 0.326–1.764 | 0.52 |
| Military | 2.386 | 0.865–6.581 | 0.093 |
| Private practice | 1.55 | 0.396–6.067 | 0.529 |
| Constant | 0.706 | – | 0.616 |
| Question: Do you believe that non-medical switching could lead to significant cost-savings? | |||
| Variable | Odds ratio | CI | p value |
| Female gender | 1.418 | 0.669–3.002 | 0.362 |
| Saudi nationality | 1.093 | 0.416–2.869 | 0.857 |
| Pediatric specialty | 1.341 | 0.514–3.5 | 0.548 |
| Trainee status | 1.789 | 0.679–4.716 | 0.239 |
| Type of practice | |||
| Academic | 0.705 | 0.282–1.764 | 0.455 |
| Military | 2.232 | 0.884–5.635 | 0.089 |
| Private practice | 1.4 | 0.394–4.97 | 0.603 |
| Constant | 0.952 | – | 0.925 |
Fig. 1Impact of demographics and practice characteristics on response to questions on biosimilar *p < 0.05.
Fig. 2Factors that affect biosimilar prescribing among participants.