Evidence map›Paper›PMID 38141214›Full record

SynthesisToxicological sciences : an official journal of the Society of Toxicology2024

Ten years of using key characteristics of human carcinogens to organize and evaluate mechanistic evidence in IARC Monographs on the identification of carcinogenic hazards to humans: Patterns and associations.

Ivan Rusyn, Fred A Wright

Abstract readSystematic Review
In one paragraph

Synthesis in Toxicological sciences : an official journal of the Society of Toxicology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Guideline
  3. Article
  4. Review
  5. Article
  6. A workflow for human health hazard evaluation using transcriptomic data and Key Characteristics-based gene sets.Toxicological sciences : an official journal of the Society of Toxicology · 2025
    Article
  7. The key characteristics concept.Current opinion in toxicology · 2025
    Article
  8. Article
  9. Incorporating new approach methods (NAMs) data in dose-response assessments: The future is now!Journal of toxicology and environmental health. Part B, Critical reviews · 2025
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Ivan RusynDepartment of Veterinary Pharmacology and Physiology, Texas A&M University, College Station, Texas 77843, USA.
Fred A WrightDepartment of Statistics, Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27606, USA.

Funding

Single cell, multi-parametric high throughput platform to classify endocrine disruptor potential of mixturesP42ES027704 · NIEHS · TEXAS A&M UNIVERSITY · PI Thomas Joseph McDonald · 2017 to 2026
$21.2M
EPA RD84045001NIEHS NIH HHS P42 ES027704
6 · The paper itself

Abstract

Systematic review and evaluation of mechanistic evidence using the Key Characteristics approach was proposed by the International Agency for Research on Cancer (IARC) in 2012 and used by the IARC Monographs Working Groups since 2015. Key Characteristics are 10 features of agents known to cause cancer in humans. From 2015 to 2022, a total of 19 Monographs (73 agents combined) used Key Characteristics for cancer hazard classification. We hypothesized that a retrospective analysis of applications of the Key Characteristics approach to cancer hazard classification using heterogenous mechanistic data on diverse agents would be informative for systematic reviews in decision-making. We extracted information on the conclusions, data types, and the role mechanistic data played in the cancer hazard classification from each Monograph. Statistical analyses identified patterns in the use of Key Characteristics, as well as trends and correlations among Key Characteristics, data types, and ultimate decisions. Despite gaps in data for many agents and Key Characteristics, several significant results emerged. Mechanistic data from in vivo animal, in vitro animal, and in vitro human studies were most impactful in concluding that an agent could cause cancer via a Key Characteristic. To exclude the involvement of a Key Characteristic, data from large-scale systematic in vitro testing programs such as ToxCast, were most informative. Overall, increased availability of systemized data streams, such as human in vitro data, would provide the basis for more confident and informed conclusions about both positive and negative associations and inform expert judgments on cancer hazard.

Indexed as

CarcinogensNeoplasmsAnimalsCarcinogenicity TestsHumansInternational AgenciesRisk AssessmentCarcinogenscancer risk assessmentrisk assessmentsafety evaluation

Identifiers

PMID38141214
PMCPMC10901152

What OpenQuestion holds

Textmetadata
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.