Evidence map›Paper›PMID 39312160›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Weight of Evidence: Criteria and Applications.

Erika Colombo, Giuseppa Raitano, Edoardo Luca Viganò, Emilio Benfenati

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 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

4 authors.

Erika ColomboLaboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Science, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Giuseppa RaitanoLaboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Science, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Edoardo Luca ViganòLaboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Science, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Emilio BenfenatiLaboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Science, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy. emilio.benfenati@marionegri.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Toxicologists and authorities evaluate substances that in the traditional way refer to data and knowledge on the toxic mechanism. Non-testing methods (NTMs) proved to be a valuable resource for risk assessment of chemical substances. Indeed, they can be particularly useful when the information provided by different sources is integrated to increase confidence in the result. In this chapter, we will address data obtained from NTM, including in silico models and read-across. Typically, these two approaches are used separately, but in this way, we lose some information. The integration of different results can be sometimes difficult because different methods can lead to conflicting results and because a clear guideline for integrating information from different sources was not available in the recent past. In this chapter, we present and discuss the recently published guideline from EFSA for integrating and weighting evidence for scientific assessment, and how to proceed, manually or through novel integrated tool, SWAN. Moreover, practical examples of the application of these integration principles on evidence from different in silico models are shown. These examples represent a demonstration of the suitability and effectiveness of in silico methods for risk assessment, as well as a practical guide to end users to perform similar analyses on likely hazardous chemicals.

Indexed as

Computer SimulationHazardous SubstancesHumansRisk AssessmentSoftwareHazardous SubstancesNon-testing methodsQSAR modelsRead-acrossWeight of evidence

Identifiers

What OpenQuestion holds

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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.