Evidence map›Paper›PMID 37855974›Full record

ArticleAdvances in therapy2024

A Novel Method for Deriving Adverse Event Prevalence in Randomized Controlled Trials: Potential for Improved Understanding of Benefit-Risk Ratio and Application to Drug Labels.

Daria Piacentino, Ajay Ogirala, Robert Lew, Gregory Loftus, MaryAlice Worden, Kenneth S Koblan, Seth C Hopkins

Open access · hybridAbstract read
In one paragraph

Article in Advances in therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.7field-weighted citation impact, top 9% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Trial
  2. Article
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

7 authors at 2 institutions in 2 countries.

Daria PiacentinoSumitomo Pharma America, Inc. (Formerly Sunovion Pharmaceuticals, Inc.), 84 Waterford Drive, Marlborough, MA, 01752, USA.
Ajay OgiralaSumitomo Pharma America, Inc. (Formerly Sunovion Pharmaceuticals, Inc.), 84 Waterford Drive, Marlborough, MA, 01752, USA.
Robert LewSumitomo Pharma America, Inc. (Formerly Sunovion Pharmaceuticals, Inc.), 84 Waterford Drive, Marlborough, MA, 01752, USA.
Gregory LoftusSumitomo Pharma America, Inc. (Formerly Sumitovant Biopharma Inc.), Marlborough, MA, USA.
MaryAlice WordenSumitomo Pharma America, Inc. (Formerly Sunovion Pharmaceuticals, Inc.), 84 Waterford Drive, Marlborough, MA, 01752, USA.
Kenneth S KoblanSumitomo Pharma America, Inc. (Formerly Sunovion Pharmaceuticals, Inc.), 84 Waterford Drive, Marlborough, MA, 01752, USA.
Seth C HopkinsSumitomo Pharma America, Inc. (Formerly Sunovion Pharmaceuticals, Inc.), 84 Waterford Drive, Marlborough, MA, 01752, USA. seth.hopkins@sunovion.com.ORCID 0000-0003-3999-2281
Sunovion (United States) · USSunovion (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAdverse event (AE) data in randomized controlled trials (RCTs) allow quantification of a drug's safety risk relative to placebo and comparison across medications. The standard US label for Food and Drug Administration-approved drugs typically lists AEs by MedDRA Preferred Term that occur at ≥ 2% in drug and with greater incidence than in placebo. We suggest that the drug label can be more informative for both patients and physicians if it includes, in addition to AE incidence (percent of subjects who reported the AE out of the total subjects in treatment), the absolute prevalence (percent of subject-days spent with an AE out of the total subject-days spent in treatment) and expected duration (days required for AE incidence to be reduced by half). We also propose a new method to analyze AEs in RCTs using drug-placebo difference in AE prevalence to improve safety signal detection.

methodsAE data from six RCTs in schizophrenia were analyzed (five RCTs of the dopamine D

resultsA number of AEs with the same incidence had different absolute prevalence and expected duration. When accounting for these two parameters, AEs that did not appear in the 2% incidence tables of the drug label turned out to contribute substantially to drug tolerability. The percent contribution of a drug-related AE to the overall side effect burden increased the drug-placebo difference in AE prevalence, whereas the percent contribution of a placebo-related AE decreased such difference, revealing a continuum of risk between drug and placebo. AE prevalence curves for drug were generally greater than those for placebo. Ulotaront exhibited a small drug-placebo difference in AE prevalence curves due to a relatively low incidence and short duration of AEs in the ulotaront treatment arm as well as the emergence of disease-related AEs in the placebo arm.

conclusionReporting AE absolute prevalence and expected duration for each RCT and incorporating them in the drug label is possible, is clinically relevant, and allows standardized comparison of medications. Our new metric, the drug-placebo difference in AE prevalence, facilitates signal detection in RCTs. We piloted this metric in RCTs of several neuropsychiatric indications and drugs, offering a new way to compare AE burden and tolerability among treatments using existing clinical trial information.

Indexed as

Antipsychotic AgentsLurasidone HydrochlorideHumansOdds RatioPrevalenceRandomized Controlled Trials as TopicAntipsychotic AgentsLurasidone HydrochlorideAdverse eventsDurationLurasidonePrevalenceSignal detectionUlotaront

Identifiers

PMID37855974
PMCPMC10796692
OpenAlexW4387764965

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.