Empirical model of mesothelioma potency factors for different mineral fibers based on their chemical composition and dimensionality

Our plain-English summary of Empirical model of mesothelioma potency factors for different mineral fibers based on their chemical composition and dimensionality, by A. Korchevskiy, J.O. Rasmuson, E.J. Rasmuson (Inhalation Toxicology, 2019).

The study

• Authors: A. Korchevskiy, J.O. Rasmuson, E.J. Rasmuson
• Journal: Inhalation Toxicology
• Published: 2019;31(5):180-191
• Cited by: 32 articles, as counted by NIH iCite
• Read it: PubMed · Publisher

Abstract

Context: The potency of various mineral fiber types to produce mesothelioma was previously evaluated for numerous cohorts, but the differences in potencies for distinct fiber types have yet to be explained. Objective: To develop an empirical model that would reconstruct mesothelioma potency factors for various types of fiber based on their chemical composition and dimensionality. Methods: Typical chemical composition and dimensionality metrics (aspect ratios) were obtained and combined with mesothelioma potency factors estimated by Hodgson and Darnton method for Quebec chrysotile, South Africa amosite, South Africa and Australian crocidolite, Russian anthophyllite, Libby amphiboles, and Turkey erionite. The forward stepwise log-log regression method was utilized to determine the best combination of input parameters. Results: Mesothelioma potency factors (RM) for selected cohorts were effectively reconstructed utilizing the median aspect ratio of fibers and equivalent fractions of SiO2, total Fe oxides or total equivalent Fe3+ as Fe2O3, and MgO. Modeled potency factors increase as the aspect ratio, SiO2, and total Fe oxide (or Fe2O3) content grow, and as the MgO content diminishes. Correlation coefficients up to 0.999, p < 0.01, were achieved. The models also yield reasonable estimates of mesothelioma potencies for other fiber types, including Bolivian crocidolite, Russian chrysotile, fluoro-edenite, and others. Conclusion: In spite of the empirical approach, the proposed models provide a starting point for targeted studies of mesothelioma mechanisms by elucidating significant contributing physicochemical factors. The models have an exploratory and preliminary character but can potentially be useful to introduce quantitative structure-activity relationship approaches for the toxicology of fibrous minerals.

In plain English

This study built a statistical model; it did not follow any people. The authors used mesothelioma potency factors (RM) for seven groups exposed directly to naturally occurring fibers: published values for Quebec chrysotile, South African amosite, South African and Australian crocidolite and Libby amphibole, and values they calculated from earlier studies for Russian anthophyllite and Turkish erionite. Using log–log regression, they related these values to each fiber's chemical make-up and median aspect ratio (length divided by width). In their models, potency rose with higher aspect ratio, silica (SiO2) and iron oxide content, and fell with higher magnesium oxide (MgO) content. Correlation coefficients reached up to 0.999. Magnesium oxide accounted for 72% of the variance in the main model. When each group was left out in turn, predictions were generally within a factor of about two to three of published values. The models also gave estimates for fibers without published potencies, such as 0.015 to 0.023 for tremolite from Pakistan and 0.06 to 0.09 for Bolivian crocidolite. The authors concluded that the models are exploratory and preliminary, and said the statistics should be read as approximate.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Empirical statistical modeling study (forward stepwise log–log regression) using mesothelioma potency factors and published mineral data. No new human or animal data were collected.
• Who was studied: Seven previously studied cohorts exposed directly to naturally occurring fibrous minerals, not to manufactured products: Quebec chrysotile, South African amosite, South African (Cape Province) and Australian crocidolite, Libby amphibole (US), Russian anthophyllite, and Turkish erionite. Potency values for five cohorts came from Hodgson and Darnton (2000) and Darnton (2010). The authors calculated the Russian anthophyllite value from their earlier study of a population around a Russian anthophyllite mine, and the Turkish erionite value from IARC (1989) data.
• Exposure: Mineral fiber types studied were chrysotile, amosite, crocidolite, Libby amphibole, anthophyllite and erionite, with others included for prediction. Each was described by its typical chemical composition (silica, iron oxides, magnesium oxide and other oxides, as weight-percent) and by the median aspect ratio of its fibers.
• Main results:
  • In both final models, potency rose with silica (SiO2), aspect ratio and iron oxide content, and fell with magnesium oxide (MgO) content.
  • Correlation coefficients of up to 0.999 (p less than 0.01) were achieved for the fit to the seven cohorts' potency factors.
  • In the main model (using Fe2O3), magnesium oxide accounted for 72% of the variance, aspect ratio for 16%, silica for 6% and Fe2O3 for 5%.
  • Each cohort's potency was removed in turn and predicted from the others, using the Fe2O3 model only. These predictions were generally within a factor of about two to three of the published values.
  • The modeled ratio of potency for crocidolite (average of South African and Australian) to South African amosite to Quebec chrysotile was 541:116:1 for the total iron model and 566:72:1 for the Fe2O3 model.
  • For fibers without published potencies, the models estimated an RM of 0.015 to 0.023 for tremolite (Pakistan) and 0.06 to 0.09 for Bolivian crocidolite. For fluoro-edenite from Biancavilla, Italy, the estimate was 0.11 (Fe2O3 model) or 0.14 (total iron model).
• The authors' conclusion: The authors concluded that the models can be seen as a tool for preliminary assessment of mesothelioma potency for elongate mineral particles of unknown potency, but that they are exploratory and preliminary in character.
• Limitations the authors state:
  • The best models were chosen by stepwise selection rather than by testing a hypothesis set in advance, so confidence intervals and other statistics should be read as approximate and qualitative.
  • Chemical composition, aspect ratios and potency factors were entered as single central values, ignoring their variability.
  • The amphibole hypothesis (that pure chrysotile may have little or no ability to cause mesothelioma) was not explored. Chrysotile was assigned a potency of 0.0009 rather than near zero.
  • It is unclear whether potencies of tremolite and similar fibers (actinolite, Libby amphibole) can be evaluated without accounting for the proportion of asbestiform and non-asbestiform fibers.
  • Results depended on which chemical constituents were included. Including aluminum oxide changed the outcomes significantly.
  • Fiber length, width, effective area and biopersistence in human lungs were not included.
  • The authors list other limitations: the log–log model shape was fixed in advance, there were few input cohorts for a comparatively large number of variables, the model appeared sensitive to small input changes, and published fiber dimension values may not be representative.

Topics

The National Library of Medicine indexes this study under subjects our site covers: Anthophyllite, Chrysotile, Crocidolite, Lung cancer, Mesothelioma.

Medical terms in this study, explained in our Lexicon: Mesothelioma, Mineral Fiber, Aspect Ratio (Length-to-diameter ratio), Quebec Chrysotile, Amosite, Crocidolite, Anthophyllite, Libby amphiboles.

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