Evidence map›Paper›PMID 23164155›Full record

ArticleBMC cancer2012

Assessing risk of breast cancer in an ethnically South-East Asia population (results of a multiple ethnic groups study).

Fei Gao, David Machin, Khuan-Yew Chow, Yu-Fan Sim, Stephen W Duffy, David B Matchar, Chien-Hui Goh, Kee-Seng Chia

Abstract read
In one paragraph

Article in BMC cancer, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Gail Model Underestimates Breast Cancer Risk in Thai Population.Asian Pacific journal of cancer prevention : APJCP · 2019
    Article
  9. Long-term excess risk of breast cancer after a single breast density measurement.European journal of cancer (Oxford, England : 1990) · 2019
    Article
  10. Article
  11. Article
  12. Article
  13. Development of a risk assessment tool for projecting individualized probabilities of developing breast cancer for Chinese women.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2014
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Fei GaoDivision of Clinical Trials and Epidemiological Sciences, National Cancer Centre Singapore, 11 Hospital Drive, Singapore 169610. gao.fei@nhcs.com.sg
David Machin
Khuan-Yew Chow
Yu-Fan Sim
Stephen W Duffy
David B Matchar
Chien-Hui Goh
Kee-Seng Chia

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGail and others developed a model (GAIL) using age-at-menarche, age-at-birth of first live child, number of previous benign breast biopsy examinations, and number of first-degree-relatives with breast cancer as well as baseline age-specific breast cancer risks for predicting the 5-year risk of invasive breast cancer for Caucasian women. However, the validity of the model for projecting risk in South-East Asian women is uncertain. We evaluated GAIL and attempted to improve its performance for Singapore women of Chinese, Malay and Indian origins.

methodsData from the Singapore Breast Screening Programme (SBSP) are used. Motivated by lower breast cancer incidence in many Asian countries, we utilised race-specific invasive breast cancer and other cause mortality rates for Singapore women to produce GAIL-SBSP. By using risk factor information from a nested case-control study within SBSP, alternative models incorporating fewer then additional risk factors were determined. Their accuracy was assessed by comparing the expected cases (E) with the observed (O) by the ratio (E/O) and 95% confidence interval (CI) and the respective concordance statistics estimated.

resultsFrom 28,883 women, GAIL-SBSP predicted 241.83 cases during the 5-year follow-up while 241 were reported (E/O=1.00, CI=0.88 to 1.14). Except for women who had two or more first-degree-relatives with breast cancer, satisfactory prediction was present in almost all risk categories. This agreement was reflected in Chinese and Malay, but not in Indian women. We also found that a simplified model (S-GAIL-SBSP) including only age-at-menarche, age-at-birth of first live child and number of first-degree-relatives performed similarly with associated concordance statistics of 0.5997. Taking account of body mass index and parity did not improve the calibration of S-GAIL-SBSP.

conclusionsGAIL can be refined by using national race-specific invasive breast cancer rates and mortality rates for causes other than breast cancer. A revised model containing only three variables (S-GAIL-SBSP) provides a simpler approach for projecting absolute risk of invasive breast cancer in South-East Asia women. Nevertheless its role in counseling the individual women regarding their risk of breast cancer remains problematical and needs to be validated in independent data.

Indexed as

AdolescentAdultAgedAged, 80 and overBiopsyBreast NeoplasmsCase-Control StudiesChildChild, PreschoolEthnicityFemaleFollow-Up StudiesHumansInfantInfant, NewbornMiddle Aged

Identifiers

PMID23164155
PMCPMC3529190

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.