Prediction of mesothelioma and lung cancer in a cohort of asbestos exposed workers

Gasparrini, Antonio; Pizzo, Anna Maria; Gorini, Giuseppe; Costantini, Adele Seniori; Silvestri, Stefano; Ciapini, C; Innocenti, A; Berry, Geoffrey

doi:10.1007/s10654-008-9257-z

Cited by 15 publications

(20 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In light of these limitations subsequent work undertook predictions at a national level using APC models that included a priori assumptions about period effects (Gasparrini et al 2008). For example, based on the large reduction in the use of asbestos in the Netherlands from 1984, Segura et al (2003) assumed that the risk of mesothelioma among those born between 1958-62 was 50 percent less than that of those born between 1953-57.…”

Section: Age-cohort Models and Age-period-cohort Modelsmentioning

confidence: 99%

“…For example, among Wittenoom crocidolite miners and millers (de Klerk et al 1989) (Berry 1991;Berry 1999;Berry et al 2012), or among the women who lived at Wittenoom who were nonoccupationally exposed to asbestos (Reid et al 2009), albeit at quite high levels. Similarly, this model was used to predict cases of mesothelioma among Italian railway workers with known estimates of asbestos exposure (Gasparrini et al 2008).The method involves calculating the mortality rate for the cohort to establish the excess deaths from all causes of death, lung cancer and mesothelioma in the cohort compared with the unexposed population. Then maximum likelihood estimates for the mesothelioma rate parameters ce, k and λ are derived from the cohort data, although because of correlation between k and λ, λ is often fixed at 6.7 percent and 15 percent per annum, and only k estimated (Reid et al 2009).…”

mentioning

confidence: 99%

“…For example, they couldn't account for the lower asbestos exposure experienced by the younger cohorts, after asbestos bans and exposure standards were introduced in the 1970s (Gasparrini et al 2008). The AC method assumed that the rate increased at the same rate by age for all cohorts and so was unreliable (Hodgson et al 2005).In light of these limitations subsequent work undertook predictions at a national level using APC models that included a priori assumptions about period effects (Gasparrini et al 2008). For example, based on the large reduction in the use of asbestos in the Netherlands from 1984, Segura et al (2003) assumed that the risk of mesothelioma among those born between 1958-62 was 50 percent less than that of those born between 1953-57.…”

mentioning

confidence: 99%

“…Compared with other predictions for Great Britain, this method projected a peak in 2018 of 2095 (95% CI 1978 -2210 Other factors that may have influenced mesothelioma rates but that were generally not accounted for in APC models include improvements in the diagnosis and reporting of mesothelioma over time, where earlier cases may have been missed. A further limitation of these methods is that the analyses were based on the age-cohort distribution of the general population, whereas the mesothelioma cases will mostly come from specific occupational populations (Gasparrini et al 2008) such as carpenters and asbestos textile workers. Also, many of these models predicted future cases among men only, because asbestos consumption records are an indicator of the use of asbestos exposure that men would incur in certain jobs, whereas women are more likely to obtain their asbestos exposure from sources other than work, e.g.…”

mentioning

confidence: 99%

“…They found that the model that best fit deaths from asbestosis between 1968 and 2004 used asbestos consumption per capita 48 years prior , and used this model to predict future deaths from asbestosis (dos Santos Antao et al 2009). However, predicted cases have not been revisited to compare against observed cases to determine the accuracy of their model.Future cases of lung cancer have been estimated among cohorts of workers exposed to asbestos (Berry 1991;de Klerk et al 1989;Gasparrini et al 2008), using methods 1 Asbestos production, plus imports, minus exports, minus changes to government and industry stocksThe effectiveness of predictive models for mesothelioma 10 similar to those reported above that used direct estimates of asbestos exposure, but where a rate for lung cancer mortality was derived instead of a rate for mesothelioma. None of these predictions have been revisited to compare against observed data.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Review of the effectiveness of predictive models for mesothelioma to identify lessons for asbestos-related policy

Reid¹

2016

Evidence Base

View full text Add to dashboard Cite

Predictions of future cases of asbestos-related disease have been undertaken at a national level to inform government policy and planning for future health needs. In general, we can separate the methods used to predict future cases of mesothelioma into models that use a) direct or b) indirect estimates of asbestos exposure. Direct estimates are those that have been derived mostly for occupationally exposed cohorts, where airborne fibre levels were measured over time. Indirect estimates tend to be information about total or fibre-specific asbestos imports or use from a range of time points. Most predictions undertaken at the national level have predicted future cases for males only and assume that indirect estimates of asbestos consumption reflect occupational asbestos exposure. These models tend to fit the observed data reasonably well but have undergone several refinements in order to improve their fit. Fewer attempts have been made to predict cases of mesothelioma resulting from non-occupational asbestos exposure, and most have not subsequently revisited their prediction to ascertain its accuracy so the robustness of these methods is unclear. Because of the change in asbestos use in recent decades, more attention should be paid to understanding the risks and burden of future cases arising from non-occupational exposure. A range of current data exist that should be sufficient to incorporate into models to predict future cases of mesothelioma arising from non-occupational asbestos exposure. Models could be tested for their accuracy by comparing them against the most recent 10 years of observed cases or against cases in women, whose most common source of exposure is non-occupational.Predictions of the future burden of disease are undertaken for a variety of policy and planning reasons. Knowledge about the future number of cases of a particular disease can assist health planners to allocate resources for primary prevention, screening and diagnosis, treatment, and palliative care. Estimates of the future burden of disease can also be used to evaluate prevention programs. For example, the number of observed cases after the introduction of a prevention program could be evaluated against the number of expected cases, assuming that the disease trends before the program was introduced continued into the future. In the same vein, a prediction that estimated a heavy future burden of a particular disease could alert public health specialists to instigate a prevention program in order to avoid that prediction scenario (Bray and Moller 2006).The simplest type of cancer prediction extrapolates past trends of cancer incidence or mortality to some date in to the future, but more information is required in order to estimate more complex scenarios. Ideally, information about the effect of a risk factor on the cancer of interest would be known by sex and age group for the past, present and future. In addition, the prevalence of exposure to that risk factor in the population would also be known. This information would then ...

show abstract

Section: Age-cohort Models and Age-period-cohort Modelsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Review of the effectiveness of predictive models for mesothelioma to identify lessons for asbestos-related policy

Reid¹

2016

Evidence Base

View full text Add to dashboard Cite

show abstract

Biocompatible Iron–Boron Nanoparticles Designed for Neutron Capture Therapy Guided by Magnetic Resonance Imaging

Torresan

Guadagnini

Badocco

et al. 2020

Adv Healthcare Materials

View full text Add to dashboard Cite

The combination of multiple functions in a single nanoparticle (NP) represents a key advantage of nanomedicine compared to traditional medical approaches. This is well represented by radiotherapy in which the dose of ionizing radiation should be calibrated on sensitizers biodistribution. Ideally, this is possible when the drug acts both as radiation enhancer and imaging contrast agent. Here, an easy, one‐step, laser‐assisted synthetic procedure is used to generate iron–boron (Fe–B) NPs featuring the set of functions required to assist neutron capture therapy (NCT) with magnetic resonance imaging. The Fe–B NPs exceed by three orders of magnitude the payload of boron isotopes contained in clinical sensitizers. The Fe–B NPs have magnetic properties of interest also for magnetophoretic accumulation in tissues and magnetic hyperthermia to assist drug permeation in tissues. Besides, Fe–B NPs are biocompatible and undergo slow degradation in the lysosomal environment that facilitates in vivo clearance through the liver–spleen–kidneys pathway. Overall, the Fe–B NPs represent a new promising tool for future exploitation in magnetic resonance imaging‐guided boron NCT at higher levels of efficacy and tolerability.

show abstract

The therapeutic efficacy of S-1 against orthotopically implanted human pleural mesothelioma cells in severe combined immunodeficient mice

Hashimoto

Kakiuchi

Sato

et al. 2010

Cancer Chemother Pharmacol

View full text Add to dashboard Cite

PurposeMalignant pleural mesothelioma (MPM) is a highly lethal neoplasm. S-1 has been developed as a novel oral antineoplastic agent based on the modulation of 5-fluorouracil (5-FU) bioactivity. This study was conducted to investigate the preclinical therapeutic effect of S-1 on MPM.MethodsWe used three human MPM cell lines, Y-MESO-14, NCI-H290 and MSTO-211H. In vitro proliferation of human MPM cells was determined by MTT assay. Human MPM cells were orthotopically implanted into thoracic cavity of SCID mice. Tumor-bearing mice were treated with S-1 or vehicle.ResultsThe combination of 5-FU and 5-chloro-2,4-dihydroxypyridine (CDHP) was more effective than 5-FU alone in inhibiting MPM cell proliferation in vitro. This combination was most effective in Y-MESO-14 cells, which co-expressed high protein level of dihydropyrimidine dehydrogenase (DPD) and thymidine phosphorylase (TP). In vivo data showed that treatment with S-1 significantly reduced thoracic tumors and pleural effusion produced by Y-MESO-14 cells. Moreover, treatment with S-1 prolonged the survival of Y-MESO-14 cell-bearing SCID mice.ConclusionsWe demonstrated that S-1 was effective for inhibiting the proliferation of MPM cells, particularly with both DPD and TP expressions, suggesting that S-1 might be therapeutically effective for control of MPM.

show abstract

Prediction of mesothelioma and lung cancer in a cohort of asbestos exposed workers

Cited by 15 publications

References 27 publications

Review of the effectiveness of predictive models for mesothelioma to identify lessons for asbestos-related policy

Review of the effectiveness of predictive models for mesothelioma to identify lessons for asbestos-related policy

Biocompatible Iron–Boron Nanoparticles Designed for Neutron Capture Therapy Guided by Magnetic Resonance Imaging

The therapeutic efficacy of S-1 against orthotopically implanted human pleural mesothelioma cells in severe combined immunodeficient mice

Contact Info

Product

Resources

About