ArticleRadiation and environmental biophysics2010
Use of the individual data of the A-bomb survivors for biologically based cancer models.
Article in Radiation and environmental biophysics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Adjusting for bias due to measurement error in functional quantile regression models with error-prone functional and scalar covariates.Biostatistics & epidemiology · 2024Article
- Versatile Poly(Diallyl Dimethyl Ammonium Chloride)-Layered Nanocomposites for Removal of Cesium in Water Purification.Materials (Basel, Switzerland) · 2018Article
- Neutron relative biological effectiveness in Hiroshima and Nagasaki atomic bomb survivors: a critical review.Journal of radiation research · 2016Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
All recent analyses of the data on solid cancer incidence of the atomic bomb survivors are corrected for migration and random dose errors. In the usual treatment with grouped data and regression calibration, the calibration of doses depends on the used dose response. For solid cancers, it usually is linear. Here, an individual likelihood is presented which works without further adjustment for all dose responses. When the same assumptions are made as in the usual Poisson regression, equivalent results are obtained. But, the individual likelihood has the potential to use more detailed models for dose errors and to estimate non-linear dose responses without recalibration. As an example for the potential of the individual data set for the analysis of risk at low doses, signals for a saturating bystander effect are investigated.
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Registered trials
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.