Methodological problems in epidemiological data: the case of correlation between radon level and lung cancer

Reszczyńska, Joanna; Pylak, Maciej; Fornalski, Krzysztof W.; Mortazavi, Shahrzad; Dobrzyński, L.

doi:10.1504/ijlr.2020.113541

Cited by 1 publication

(18 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To illustrate this point, Malinovsky et al, 9 having reduced all their data into 4 bins only, calculated their weighted median values of ORs (Odds ratios), obtaining an OR of 1.35 with impressive credibility ( P < 0.0001) for their highest median radon concentration of 283 Bq/m 3 . In our recent paper (Reszczyńska et al) 22 we contested their work and their conclusions. Indeed, as pointed out by Scott, 18,47,48 if one considers the variability of natural background measurements, an OR value of 1.35 may not be realistic, which supports our view.…”

Section: Discussionmentioning

confidence: 90%

“…Although the above methodology, employed in our recent paper, 22 appears to be simple, in reality one has to consider the scatter of points with respect to their claimed accuracy, which may lead to questionable final results. Therefore, we decided to use the Maximum Entropy Method (which is also, as described, a Bayesian method 20 ) to analyze cancer probability against 2 simultaneous parameters, i. e. radon concentration and altitude, or radon concentration and level (intensity) of UVB.…”

Section: The Maximum Entropy Methodsmentioning

confidence: 99%

“…We first performed this verification in a manner described earlier. 22 In our second step, we also took the inaccuracy of the input data into account. Full details of this non-standard procedure are given in the following paragraph.…”

Section: The Maximum Entropy Methodsmentioning

confidence: 99%

“…On the other hand, application of the Bayesian method is recommended in the analysis of scattered data points or of data with apparent outliers. However, if this scatter is too large, there may be no advantage to be gained by the Bayesian approach, as shown by Reszczyńska et al 22 Within the Bayesian methodology, determination of the validity of a given theoretical hypothesis T commences by establishing the relationship between its prior and its posterior probability functions, as a new set of experimental data, E, is delivered:…”

Section: Bayesian Analysismentioning

confidence: 99%

“…21,25 This approach was applied in our earlier meta-analyses of radon data. 17,21,22 Randomized (Monte Carlo) Data Binning…”

Section: Bayesian Analysismentioning

confidence: 99%

See 4 more Smart Citations

Analysis of Indoor Radon Data Using Bayesian, Random Binning, and Maximum Entropy Methods

et al. 2021

Self Cite

View full text Add to dashboard Cite

Three statistical methods: Bayesian, randomized data binning and Maximum Entropy Method (MEM) are described and applied in the analysis of US radon data taken from the US registry. Two confounding factors—elevation of inhabited dwellings, and UVB (ultra-violet B) radiation exposure—were considered to be most correlated with the frequency of lung cancer occurrence. MEM was found to be particularly useful in extracting meaningful results from epidemiology data containing such confounding factors. In model testing, MEM proved to be more effective than the least-squares method (even via Bayesian analysis) or multi-parameter analysis, routinely applied in epidemiology. Our analysis of the available residential radon epidemiology data consistently demonstrates that the relative number of lung cancers decreases with increasing radon concentrations up to about 200 Bq/m3, also decreasing with increasing altitude at which inhabitants live. Correlation between UVB intensity and lung cancer has also been demonstrated.

show abstract