Evidence map›Paper›PMID 40677737›Full record

ArticleBioinformatics advances2025

The

Nicolas Kubista, Danielle Braun, Giovanni Parmigiani

Abstract read
In one paragraph

Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Nicolas KubistaDepartment of Biostatistics Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.ORCID https://orcid.org/0009-0001-7800-0305
Danielle BraunDepartment of Biostatistics Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.ORCID https://orcid.org/0000-0002-5177-8598
Giovanni ParmigianiDepartment of Biostatistics Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.ORCID https://orcid.org/0000-0002-8783-5961

Funding

Precision approaches to refining TP53-associated cancer riskR01CA242218 · NCI · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI AMOS, CHRISTOPHER I., GARBER, JUDY E. · 2019 to 2023
$8.5M
NCI NIH HHS R01 CA242218
6 · The paper itself

Abstract

Motivation: Reliable tools and software for penetrance (age-specific risk among those who carry a genetic variant) estimation are critical to improving clinical decision making and risk assessment for hereditary syndromes. However, there is a lack of easily usable software for penetrance estimation in family-based studies that implements a Bayesian estimation approach. Results: We introduce Availability and implementation: The

Identifiers

PMID40677737
PMCPMC12270257

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.