A Monte Carlo analysis of breast screening randomized trials. Issue 12 (December 2016)

• Record Type: Journal Article
• Authors: Zamora, Luis I.; Forastero, Cristina; Guirado, Damián; Lallena, Antonio M.
• Is Part Of: Physica medica. Volume 32:Issue 12(2016)
• Page Start: 1609
• Page End: 1614
• Publication Date: 2016-12
• Subjects: Breast cancer -- Screening trials -- Simulation -- Monte Carlo -- Internal and external validities; Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2016.11.116
• Languages: English
• ISSNs: 1120-1797

Abstract

Highlights: A Monte Carlo tool to analyze breast screening randomized trials is developed. Monte Carlo results reproduce very well those of various randomized trials. Discrepancies are found with trials that show up methodological problems. Our tool is useful to investigate breast screening controlled randomized trials. Monte Carlo simulations may help in designing the trial strategies. Abstract: Purpose: To analyze breast screening randomized trials with a Monte Carlo simulation tool. Methods: A simulation tool previously developed to simulate breast screening programmes was adapted for that purpose. The history of women participating in the trials was simulated, including a model for survival after local treatment of invasive cancers. Distributions of time gained due to screening detection against symptomatic detection and the overall screening sensitivity were used as inputs. Several randomized controlled trials were simulated. Except for the age range of women involved, all simulations used the same population characteristics and this permitted to analyze their external validity. The relative risks obtained were compared to those quoted for the trials, whose internal validity was addressed by further investigating the reasons of the disagreements observed. Results: The Monte Carlo simulations produce results that are in good agreement with most of the randomized trials analyzed, thus indicating their methodological quality and external validity. A reduction of the breast cancer mortality around 20% appears to be a reasonable value according to the results of the trials that are methodologically correct. Discrepancies observed with Canada I and II trials may be attributed to a low mammography quality and some methodological problems. Kopparberg trial appears to show a low methodological quality. Conclusion: Monte Carlo simulations are a powerful tool to investigate breast screening controlled randomized trials, helping to establish those whose results are reliable enough to be extrapolated to other populations and to design the trial strategies and, eventually, adapting them during their development.