Evaluation of breast cancer service screening programme with a Bayesian approach: Mortality analysis in a Finnish region

Jenny Chia Yun Wu, Ahti Anttila, Amy Ming Fang Yen, Matti Hakama, Irma Saarenmaa, Tytti Sarkeala, Nea Malila, Anssi Auvinen, Sherry Yueh Hsia Chiu, Tony Hsiu Hsi Chen

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Evaluation of long-term effectiveness of population-based breast cancer service screening program in a small geographic area may suffer from self-selection bias and small samples. Under a prospective cohort design with exposed and non-exposed groups classified by whether women attended the screen upon invitation, we proposed a Bayesian acyclic graphic model for correcting self-selection bias with or without incorporation of prior information derived from previous studies with an identical screening program in Sweden by chronological order and applied it to an organized breast cancer service screening program in Pirkanmaa center of Finland. The relative mortality rate of breast cancer was 0.27 (95% CI 0.12-0.61) for the exposed group versus the non-exposed group without adjusting for self-selection bias. With adjustment for selection-bias, the adjusted relative mortality rate without using previous data was 0.76 (95% CI 0.49-1.15), whereas a statistically significam result was achieved [0.73 (95% CI 0.57-0.93)] with incorporation of previous information. With the incorporation of external data sources from Sweden in chronological order, adjusted relative mortality rate was 0.67 (0.55-0.80). We demonstrated how to apply a Bayesian acyclic graphic model with self-selection bias adjustment to evaluating an organized but non-randomized breast cancer screening program in a small geographic area with a significant 27% mortality reduction that is consistent with the previous result but more precise. Around 33% mortality was estimated by taking previous randomized controlled data from Sweden.

Original languageEnglish
Pages (from-to)671-678
Number of pages8
JournalBreast Cancer Research and Treatment
Volume121
Issue number3
DOIs
Publication statusPublished - Jun 2010
Externally publishedYes

Fingerprint

Bayes Theorem
Selection Bias
Early Detection of Cancer
Breast Neoplasms
Sweden
Mortality
Information Storage and Retrieval
Finland
Population

Keywords

  • Bayesian acyclic graphic model
  • Breast cancer screening
  • Mortality reduction
  • Self-selection bias

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Evaluation of breast cancer service screening programme with a Bayesian approach : Mortality analysis in a Finnish region. / Wu, Jenny Chia Yun; Anttila, Ahti; Yen, Amy Ming Fang; Hakama, Matti; Saarenmaa, Irma; Sarkeala, Tytti; Malila, Nea; Auvinen, Anssi; Chiu, Sherry Yueh Hsia; Chen, Tony Hsiu Hsi.

In: Breast Cancer Research and Treatment, Vol. 121, No. 3, 06.2010, p. 671-678.

Research output: Contribution to journalArticle

Wu, JCY, Anttila, A, Yen, AMF, Hakama, M, Saarenmaa, I, Sarkeala, T, Malila, N, Auvinen, A, Chiu, SYH & Chen, THH 2010, 'Evaluation of breast cancer service screening programme with a Bayesian approach: Mortality analysis in a Finnish region', Breast Cancer Research and Treatment, vol. 121, no. 3, pp. 671-678. https://doi.org/10.1007/s10549-009-0604-x
Wu, Jenny Chia Yun ; Anttila, Ahti ; Yen, Amy Ming Fang ; Hakama, Matti ; Saarenmaa, Irma ; Sarkeala, Tytti ; Malila, Nea ; Auvinen, Anssi ; Chiu, Sherry Yueh Hsia ; Chen, Tony Hsiu Hsi. / Evaluation of breast cancer service screening programme with a Bayesian approach : Mortality analysis in a Finnish region. In: Breast Cancer Research and Treatment. 2010 ; Vol. 121, No. 3. pp. 671-678.
@article{a512c3ace0384bd59677b7d00892c3ed,
title = "Evaluation of breast cancer service screening programme with a Bayesian approach: Mortality analysis in a Finnish region",
abstract = "Evaluation of long-term effectiveness of population-based breast cancer service screening program in a small geographic area may suffer from self-selection bias and small samples. Under a prospective cohort design with exposed and non-exposed groups classified by whether women attended the screen upon invitation, we proposed a Bayesian acyclic graphic model for correcting self-selection bias with or without incorporation of prior information derived from previous studies with an identical screening program in Sweden by chronological order and applied it to an organized breast cancer service screening program in Pirkanmaa center of Finland. The relative mortality rate of breast cancer was 0.27 (95{\%} CI 0.12-0.61) for the exposed group versus the non-exposed group without adjusting for self-selection bias. With adjustment for selection-bias, the adjusted relative mortality rate without using previous data was 0.76 (95{\%} CI 0.49-1.15), whereas a statistically significam result was achieved [0.73 (95{\%} CI 0.57-0.93)] with incorporation of previous information. With the incorporation of external data sources from Sweden in chronological order, adjusted relative mortality rate was 0.67 (0.55-0.80). We demonstrated how to apply a Bayesian acyclic graphic model with self-selection bias adjustment to evaluating an organized but non-randomized breast cancer screening program in a small geographic area with a significant 27{\%} mortality reduction that is consistent with the previous result but more precise. Around 33{\%} mortality was estimated by taking previous randomized controlled data from Sweden.",
keywords = "Bayesian acyclic graphic model, Breast cancer screening, Mortality reduction, Self-selection bias",
author = "Wu, {Jenny Chia Yun} and Ahti Anttila and Yen, {Amy Ming Fang} and Matti Hakama and Irma Saarenmaa and Tytti Sarkeala and Nea Malila and Anssi Auvinen and Chiu, {Sherry Yueh Hsia} and Chen, {Tony Hsiu Hsi}",
year = "2010",
month = "6",
doi = "10.1007/s10549-009-0604-x",
language = "English",
volume = "121",
pages = "671--678",
journal = "Breast Cancer Research and Treatment",
issn = "0167-6806",
publisher = "Springer New York",
number = "3",

}

TY - JOUR

T1 - Evaluation of breast cancer service screening programme with a Bayesian approach

T2 - Mortality analysis in a Finnish region

AU - Wu, Jenny Chia Yun

AU - Anttila, Ahti

AU - Yen, Amy Ming Fang

AU - Hakama, Matti

AU - Saarenmaa, Irma

AU - Sarkeala, Tytti

AU - Malila, Nea

AU - Auvinen, Anssi

AU - Chiu, Sherry Yueh Hsia

AU - Chen, Tony Hsiu Hsi

PY - 2010/6

Y1 - 2010/6

N2 - Evaluation of long-term effectiveness of population-based breast cancer service screening program in a small geographic area may suffer from self-selection bias and small samples. Under a prospective cohort design with exposed and non-exposed groups classified by whether women attended the screen upon invitation, we proposed a Bayesian acyclic graphic model for correcting self-selection bias with or without incorporation of prior information derived from previous studies with an identical screening program in Sweden by chronological order and applied it to an organized breast cancer service screening program in Pirkanmaa center of Finland. The relative mortality rate of breast cancer was 0.27 (95% CI 0.12-0.61) for the exposed group versus the non-exposed group without adjusting for self-selection bias. With adjustment for selection-bias, the adjusted relative mortality rate without using previous data was 0.76 (95% CI 0.49-1.15), whereas a statistically significam result was achieved [0.73 (95% CI 0.57-0.93)] with incorporation of previous information. With the incorporation of external data sources from Sweden in chronological order, adjusted relative mortality rate was 0.67 (0.55-0.80). We demonstrated how to apply a Bayesian acyclic graphic model with self-selection bias adjustment to evaluating an organized but non-randomized breast cancer screening program in a small geographic area with a significant 27% mortality reduction that is consistent with the previous result but more precise. Around 33% mortality was estimated by taking previous randomized controlled data from Sweden.

AB - Evaluation of long-term effectiveness of population-based breast cancer service screening program in a small geographic area may suffer from self-selection bias and small samples. Under a prospective cohort design with exposed and non-exposed groups classified by whether women attended the screen upon invitation, we proposed a Bayesian acyclic graphic model for correcting self-selection bias with or without incorporation of prior information derived from previous studies with an identical screening program in Sweden by chronological order and applied it to an organized breast cancer service screening program in Pirkanmaa center of Finland. The relative mortality rate of breast cancer was 0.27 (95% CI 0.12-0.61) for the exposed group versus the non-exposed group without adjusting for self-selection bias. With adjustment for selection-bias, the adjusted relative mortality rate without using previous data was 0.76 (95% CI 0.49-1.15), whereas a statistically significam result was achieved [0.73 (95% CI 0.57-0.93)] with incorporation of previous information. With the incorporation of external data sources from Sweden in chronological order, adjusted relative mortality rate was 0.67 (0.55-0.80). We demonstrated how to apply a Bayesian acyclic graphic model with self-selection bias adjustment to evaluating an organized but non-randomized breast cancer screening program in a small geographic area with a significant 27% mortality reduction that is consistent with the previous result but more precise. Around 33% mortality was estimated by taking previous randomized controlled data from Sweden.

KW - Bayesian acyclic graphic model

KW - Breast cancer screening

KW - Mortality reduction

KW - Self-selection bias

UR - http://www.scopus.com/inward/record.url?scp=77953122378&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77953122378&partnerID=8YFLogxK

U2 - 10.1007/s10549-009-0604-x

DO - 10.1007/s10549-009-0604-x

M3 - Article

C2 - 19890708

AN - SCOPUS:77953122378

VL - 121

SP - 671

EP - 678

JO - Breast Cancer Research and Treatment

JF - Breast Cancer Research and Treatment

SN - 0167-6806

IS - 3

ER -