Evidence map›Paper›PMID 37408165›Full record

Trial reportClinical and translational science2023

A decade comparison of regulatory decision patterns for oncology products to all other non-oncology products among Swissmedic, European Medicines Agency, and US Food and Drug Administration.

Ulrich-P Rohr, Mario Iovino, Leonie Rudofsky, Qiyu Li, Stephanie Juritz, Arunas Gircys, Oliver Wildner, Magda Bujar, Claus Bolte, Simon Dalla Torre di Sanguinetto and 1 more

Abstract readClinical Trial
In one paragraph

Trial report in Clinical and translational science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

11 authors.

Ulrich-P RohrDivision Clinical Assessment, Authorization Sector Swiss Agency for Therapeutic Products, Swissmedic, Bern, Switzerland.
Mario IovinoDivision Clinical Assessment, Authorization Sector Swiss Agency for Therapeutic Products, Swissmedic, Bern, Switzerland.
Leonie RudofskyDivision Clinical Assessment, Authorization Sector Swiss Agency for Therapeutic Products, Swissmedic, Bern, Switzerland.
Qiyu LiDivision Clinical Assessment, Authorization Sector Swiss Agency for Therapeutic Products, Swissmedic, Bern, Switzerland.
Stephanie JuritzDivision Clinical Assessment, Authorization Sector Swiss Agency for Therapeutic Products, Swissmedic, Bern, Switzerland.
Arunas GircysDivision Clinical Assessment, Authorization Sector Swiss Agency for Therapeutic Products, Swissmedic, Bern, Switzerland.
Oliver WildnerDivision Clinical Assessment, Authorization Sector Swiss Agency for Therapeutic Products, Swissmedic, Bern, Switzerland.
Magda BujarCentre for Innovation in Regulatory Science (CIRS), London, UK.
Claus BolteDivision Clinical Assessment, Authorization Sector Swiss Agency for Therapeutic Products, Swissmedic, Bern, Switzerland.
Simon Dalla Torre di SanguinettoDivision Clinical Assessment, Authorization Sector Swiss Agency for Therapeutic Products, Swissmedic, Bern, Switzerland.
Anita WolferDivision Clinical Assessment, Authorization Sector Swiss Agency for Therapeutic Products, Swissmedic, Bern, Switzerland.ORCID 0000-0002-7109-2286

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Consensus of regulatory decisions on the same Marketing Authorization Application (MAA) are critical for stakeholders. In this context, regulatory decision patterns from the Swissmedic (SMC), the US Food and Drug Administration (FDA), and the European Medicines Agency (EMA) were analyzed for hemato-oncology products (OP) and non-oncology products (NOP). We compared 336 SMC regulatory decisions between 2009 and 2018 on new active substances with the EMA and the FDA for OP (n = 77) and NOP (n = 259) regarding approval rates, consensus, and divergent decisions. For OP MAA, we analyzed the underlying reasons for divergent decisions; for consensus decisions, the similarity and strictness of labeling. For OP, the approval rate for the SMC was 88.4%, the EMA 91.3%, and the FDA 95.7%. For NOP, the SMC had an approval rate of 86.2%, the EMA of 93.8%, and the FDA of 88.8%. The consensus decision rate among agencies was 88.4% for OP and 84.4% for NOP. The main clinical driver for divergent decisions for OP was nonrandomized trial design and low patient numbers. Comparing the approved indication wordings, the highest similarity was between the SMC and the EMA, and lowest for the FDA and the EMA. Investigating label strictness, the FDA numerically had the highest but not-statistically significant number of strict labels. The approval rate stratified by disease area (OP and NOP) differed among the SMC, the EMA, and the FDA. High concordance in regulatory decisions was observed between agencies for OP as well as NOP. Reasons for divergent decisions regarding OP were mainly due to scientific uncertainties. Comparing strictness of indications, numerical but no statistically significant differences were observed between agencies.

Indexed as

Drug ApprovalEuropeHumansUncertaintyUnited StatesUnited States Food and Drug Administration

Identifiers

PMID37408165
PMCPMC10499418

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Registered trials

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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.