Evidence map›Paper›PMID 39410710›Full record

ReviewClinical pharmacology and therapeutics2025

The Potential of Disease Progression Modeling to Advance Clinical Development and Decision Making.

Mary Summer Starling, Lindsay Kehoe, Bruce K Burnett, Phil Green, Karthik Venkatakrishnan, Rajanikanth Madabushi

Abstract readReview
In one paragraph

Review in Clinical pharmacology and therapeutics, 2025. 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
–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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Mary Summer StarlingThe Clinical Trials Transformation Initiative, Duke Clinical Research Institute, Durham, North Carolina, USA.ORCID 0000-0002-1710-3079
Lindsay KehoeThe Clinical Trials Transformation Initiative, Duke Clinical Research Institute, Durham, North Carolina, USA.ORCID 0000-0001-5434-443X
Bruce K BurnettDivision of Allergy, Immunology and Transplantation, National Institutes of Health, Bethesda, Maryland, USA.
Phil GreenPatient Advocate, Winchester, California, USA.
Karthik VenkatakrishnanEMD Serono Research and Development Institute, Inc., Billerica, Massachusetts, USA.ORCID 0000-0003-4039-9813
Rajanikanth MadabushiFood and Drug Administration, Silver Spring, Maryland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While some model-informed drug development frameworks are well recognized as enabling clinical trials, the value of disease progression modeling (DPM) in impacting medical product development has yet to be fully realized. The Clinical Trials Transformation Initiative assembled a diverse project team from across the patient, academic, regulatory, and industry sectors of practice to advance the use of DPM for decision making in clinical trials and medical product development. This team conducted a scoping review to explore current applications of DPM and convened a multi-stakeholder expert meeting to discuss its value in medical product development. In this article, we present the scoping review and expert meeting output and propose key questions that medical product developers and regulators may use to inform clinical development strategy, appreciate the therapeutic context and endpoint selection, and optimize trial design with disease progression models. By expanding awareness of the unique value of DPM, this article does not aim to be technical in nature but rather aims to highlight the potential of DPM to improve the quality and efficiency of medical product development.

Indexed as

Decision MakingDisease ProgressionDrug DevelopmentClinical Trials as TopicHumans

Identifiers

PMID39410710
PMCPMC11739755

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.