Evidence map›Paper›PMID 33200566›Full record

ArticleCPT: pharmacometrics & systems pharmacology2021

A Personalized Medicine Approach Using Clinical Utility Index and Exposure-Response Modeling Informed by Patient Preferences Data.

Insa Winzenborg, Ahmed M Soliman, Mohamad Shebley

Open access · goldAbstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 32% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
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

3 authors at 2 institutions in 2 countries.

Insa WinzenborgClinical Pharmacology and Pharmacometrics, AbbVie Deutschland GmbH & Co. KG, Ludwigshafen am Rhein, Germany.
Ahmed M SolimanHealth Economics & Outcomes Research, AbbVie, North Chicago, Illinois, USA.
Mohamad ShebleyClinical Pharmacology and Pharmacometrics, AbbVie, North Chicago, Illinois, USA.
AbbVie (United States) · USAbbVie (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Selection of a personalized dose for an individual patient can be informed by the patient's preferences, translated as weights on each of the clinically relevant safety and efficacy drug attributes, based on results from a brief patient preference elicitation questionnaire. In this analysis, the weighted attributes were simulated to represent various endometriosis patient profiles. Exposure-response simulations were performed for elagolix, a drug approved for management of moderate to severe pain associated with endometriosis, across a range of plasma exposures corresponding to a range of doses. The results were combined to calculate a personalized clinical utility index. An interactive user-friendly online application was developed and envisioned as a physician's desk tool to personalize the dose selection process based on individual patient preferences. This demonstration should serve as an example of how patient/physician conversation can be facilitated with quantitative tools for personalizing the dose.

Indexed as

Models, BiologicalPatient PreferenceAdolescentAdultAnalgesicsClinical Trials, Phase I as TopicClinical Trials, Phase III as TopicComputer SimulationDose-Response Relationship, DrugEndometriosisFemaleHumansHydrocarbons, FluorinatedLiver-Specific Organic Anion Transporter 1Middle AgedPainAnalgesicselagolixHydrocarbons, FluorinatedLiver-Specific Organic Anion Transporter 1PyrimidinesSLCO1B1 protein, human

Identifiers

PMID33200566
PMCPMC7825192
OpenAlexW3103947254

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.