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  4. Tumor Size Can Have An Impact On TheOutcomes of Epidemiological Studies On Second Cancers After Radiotherapy

Tumor Size Can Have An Impact On TheOutcomes of Epidemiological Studies On Second Cancers After Radiotherapy

U Schneider1,2*, L Walsh2 , W Newhauser3 , (1) Klinik Hirslanden, Zurich, Zurich, (2) University Zurich, Zurich, ZH, (3) Louisiana State University, Baton Rouge, LA

Presentations

(Sunday, 7/29/2018) 3:00 PM - 6:00 PM

Room: Exhibit Hall

Purpose: Many challenges are associated with obtaining a correct dose-response relationship for radiation induced cancer after radiotherapy with an epidemiological study. In order to gain a better understanding, some aspects of an epidemiological study on breast cancer following radiotherapy of Hodgkin’s disease were simulated with Monte-Carlo methods.

Methods: Linear and non-linear mechanistic models which predict risk of cancer induction as a function of dose were applied randomly to a typical treatment plan. The study aspects chosen for consideration with simulations were the sizes and locations of the second tumor and the predicted radiation doses to the second tumor. The simulations provided information on how the dose variations can be directly influenced by the tumor size variations.

Results: The resulting study risk to predicted-dose-response-characteristic was analyzed. If a linear dose-response relationship for cancer induction was applied to calculate the theoretical doses at the simulated cancer sites, all Monte-Carlo realizations of the epidemiological study yielded strong evidence for a linear risk to predicted-dose-response. However, if a non-linear dose-response of cancer induction was applied to calculate the theoretical doses, the Monte Carlo simulated epidemiological study resulted in a non-linear risk to predicted-dose-response relationship only if the tumor size was small (< 1.5 cm). If the diagnosed breast cancers exceeded an average diameter of 1.5 cm, an applied non-linear mechanistic theoretical-dose-response relationship for second cancer falsely resulted in strong evidence for a linear predicted-dose relationship from the epidemiological study realizations. For a typical distribution of breast cancer sizes, the model selection probability for a predicted-dose linear model was 61% although a mechanistic non-linear theoretical-dose-response relationship for cancer induction had been applied.

Conclusion: Epidemiologically obtained dose-response relationships for cancer induction can be wrong, although the epidemiological study was correctly performed due to the finite size of the diagnosed second tumor.

Keywords

Dose Response

Taxonomy

IM- Radiation dose and risk: General (Most Aspects)

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