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Record W2048281752 · doi:10.1080/10937404.2012.659140

A Meta-Analysis of Evidence for Hormesis in Animal Radiation Carcinogenesis, Including a Discussion of Potential Pitfalls in Statistical Analyses to Detect Hormesis

2012· review· en· W2048281752 on OpenAlexaff
Kenny S. Crump, P. Duport, Huixia Jiang, Natalia S. Shilnikova, Daniel Krewski, Jan M. Zielinski

Bibliographic record

VenueJournal of Toxicology and Environmental Health Part B · 2012
Typereview
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsHealth CanadaUniversity of Ottawa
Fundersnot available
KeywordsHormesisMeta-analysisOutlierStatistical powerBiologyToxicologyStatisticsMedicineNuclear medicineMathematicsInternal medicine

Abstract

fetched live from OpenAlex

A database containing 800 datasets on the incidence of specific tumor types from 262 radiation carcinogenicity experiments identified in a comprehensive literature search through September 2000 was analyzed for evidence of hormesis. This database includes lifetime studies of tumorigenic responses in mice, rats, and dogs to exposures to alpha, beta, gamma, neutron, or x-ray radiation. A J-shaped dose response, in the form of a significant decreased response at some low dose followed by a significant increased response at a higher dose, was found in only four datasets from three experiments. Three of these datasets involved the same control animals and two also shared dosed animals; the J shape in the fourth dataset appeared to be the result of an outlier within an otherwise monotonic dose response. A meta-analysis was conducted to determine whether there was an excess of dose groups with decreases in tumor response below that in controls at doses below no-observed-effect levels (NOELs) in individual datasets. Because the probability of a decreased response is generally not equal to the probability of an increased response even in the null case, the meta-analysis focused on comparing the number of statistically significant diminished responses to the number expected, assuming no dose effect below the NOEL. Only 54 dose groups out of the total of 2579 in the database had doses below the dataset-specific NOEL and that satisfied an a priori criterion for sufficient power to detect a reduced response. Among these 54, a liberal criterion for defining a significant decreases identified 15 such decreases, versus 54 × 0.2 = 10.8 expected. The excess in significant reductions was accounted for almost entirely by the excess from neutron experiments (10 observed, 6.2 expected). Nine of these 10 dose groups involved only 2 distinct control groups, and 2 pairs from the 10 even shared dosed animals. Given this high degree of overlap, this small excess did not appear remarkable, although the overlap prevented a formal statistical analysis. A comprehensive post hoc evaluation using a range of NOEL definitions and alternative ways of restricting the data entering the analysis did not produce materially different results. A second meta-analysis found that, in every possible low dose range ([0, d] for every dose, d) of each of the radiation types, the number of dose groups with significantly increased tumorigenic responses was either close to or exceeded the number showing significantly reduced responses. This meta-analysis was considered to be the more definitive one. Not only did it take dose into account by looking for consistent evidence of hormesis throughout defined low-dose ranges, it was also potentially less susceptible to limitations in experimental protocols that would cause individual animals to respond in a non-independent fashion. Overall, this study found little evidence in a comprehensive animal radiation database to support the hormesis hypothesis. However, the ability of the database to detect a hormetic effect was limited both by the small number of dose groups with doses below the range where positive effects have been found in epidemiological studies (≤ 0.1 Gy) and by the limited power of many of these dose groups for detecting a decrease in response.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.082
metaresearch head score (Gemma)0.181
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score0.434

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0820.181
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0100.039
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.399
GPT teacher head0.499
Teacher spread0.100 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designMeta-analysis
DomainMethods
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2012
Admission routes1
Has abstractyes

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