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Optimal breast cancer screening poli...

Chen, Junxiang.

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Optimal breast cancer screening policies.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Optimal breast cancer screening policies./
Author:	Chen, Junxiang.
Description:	48 p.
Notes:	Source: Masters Abstracts International, Volume: 51-05.
Contained By:	Masters Abstracts International51-05(E).
Subject:	Engineering, Computer. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1536243
ISBN:	9781303042386

Optimal breast cancer screening policies.
Chen, Junxiang.

Optimal breast cancer screening policies. - 48 p.

Source: Masters Abstracts International, Volume: 51-05.

Thesis (M.S.)--Northeastern University, 2013.

Breast cancer is the most common non-preventable cancer among women. Although it has been demonstrated in randomized trials that mammography screening reduces the breast cancer mortality rate, the optimal screening policy is not known. When screening should start and stop, and the optimal interval between screening sessions are controversial issues. In this thesis, we present dynamic programming algorithms that find optimal variable-interval screening policies that can either minimize lifetime cancer mortality risk or maximize life expectancy. We evaluate these policies using a simulation based on the MISCAN-Fadia breast cancer model. By applying the optimal policies, we can typically either increase life expectancy by 4.0 days or reduce the lifetime cancer mortality risk by 0.16% , which is equivalent to saving 3200 women annually from breast cancer death, compared to the standard constant-interval screening guidelines, without increasing the number of screenings. We also find that increasing life expectancy and decreasing cancer mortality risk can be contradictory goals. We demonstrate that variable screening intervals can increase the effectiveness of screening. We show that the benefits of optimizing screenings policies vary according to the cancer incidence risk of the women; but also that optimizing policies over each risk subgroups does not give promising results.

ISBN: 9781303042386Subjects--Topical Terms:

1669061
Engineering, Computer.

Optimal breast cancer screening policies.
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008 150210s2013 ||||||||||||||||| ||eng d
020 $a 9781303042386
035 $a (MiAaPQ)AAI1536243
035 $a AAI1536243
040 $a MiAaPQ $c MiAaPQ
100 1 $a Chen, Junxiang. $3 2099843
245 1 0 $a Optimal breast cancer screening policies.
300 $a 48 p.
500 $a Source: Masters Abstracts International, Volume: 51-05.
500 $a Adviser: Waleed Meleis.
502 $a Thesis (M.S.)--Northeastern University, 2013.
520 $a Breast cancer is the most common non-preventable cancer among women. Although it has been demonstrated in randomized trials that mammography screening reduces the breast cancer mortality rate, the optimal screening policy is not known. When screening should start and stop, and the optimal interval between screening sessions are controversial issues. In this thesis, we present dynamic programming algorithms that find optimal variable-interval screening policies that can either minimize lifetime cancer mortality risk or maximize life expectancy. We evaluate these policies using a simulation based on the MISCAN-Fadia breast cancer model. By applying the optimal policies, we can typically either increase life expectancy by 4.0 days or reduce the lifetime cancer mortality risk by 0.16% , which is equivalent to saving 3200 women annually from breast cancer death, compared to the standard constant-interval screening guidelines, without increasing the number of screenings. We also find that increasing life expectancy and decreasing cancer mortality risk can be contradictory goals. We demonstrate that variable screening intervals can increase the effectiveness of screening. We show that the benefits of optimizing screenings policies vary according to the cancer incidence risk of the women; but also that optimizing policies over each risk subgroups does not give promising results.
590 $a School code: 0160.
650 4 $a Engineering, Computer. $3 1669061
650 4 $a Engineering, Biomedical. $3 1017684
690 $a 0464
690 $a 0541
710 2 $a Northeastern University. $b Electrical and Computer Engineering. $3 1018491
773 0 $t Masters Abstracts International $g 51-05(E).
790 $a 0160
791 $a M.S.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1536243