Discovery - University of Dundee - Online Publications

Library & Learning Centre

Identifying suspected breast cancer

Standard

Identifying suspected breast cancer : Development and validation of a clinical prediction rule. / McCowan, C.; Donnan, P.T.; Thompson, A.; Dewar, J.; Fahey, T.

In: British Journal of General Practice, Vol. 61, No. 586, 2011.

Research output: Contribution to journalArticle

Harvard

McCowan, C, Donnan, PT, Thompson, A, Dewar, J & Fahey, T 2011, 'Identifying suspected breast cancer: Development and validation of a clinical prediction rule' British Journal of General Practice, vol 61, no. 586., 10.3399/bjgp11X572391

APA

McCowan, C., Donnan, P. T., Thompson, A., Dewar, J., & Fahey, T. (2011). Identifying suspected breast cancer: Development and validation of a clinical prediction rule. British Journal of General Practice, 61(586). 10.3399/bjgp11X572391

Vancouver

McCowan C, Donnan PT, Thompson A, Dewar J, Fahey T. Identifying suspected breast cancer: Development and validation of a clinical prediction rule. British Journal of General Practice. 2011;61(586). Available from: 10.3399/bjgp11X572391

Author

McCowan, C.; Donnan, P.T.; Thompson, A.; Dewar, J.; Fahey, T. / Identifying suspected breast cancer : Development and validation of a clinical prediction rule.

In: British Journal of General Practice, Vol. 61, No. 586, 2011.

Research output: Contribution to journalArticle

Bibtex - Download

@article{465b462cc15c4d618e47985df7d9fb5b,
title = "Identifying suspected breast cancer: Development and validation of a clinical prediction rule",
author = "C. McCowan and P.T. Donnan and A. Thompson and J. Dewar and T. Fahey",
year = "2011",
doi = "10.3399/bjgp11X572391",
volume = "61",
number = "586",
journal = "British Journal of General Practice",
issn = "0960-1643",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Identifying suspected breast cancer

T2 - Development and validation of a clinical prediction rule

A1 - McCowan,C.

A1 - Donnan,P.T.

A1 - Thompson,A.

A1 - Dewar,J.

A1 - Fahey,T.

AU - McCowan,C.

AU - Donnan,P.T.

AU - Thompson,A.

AU - Dewar,J.

AU - Fahey,T.

PY - 2011

Y1 - 2011

N2 - Background: An evidence-based approach is needed to identify women with breast symptoms who are most likely to have breast cancer so that timely and appropriate referral can take place. Aim: To report the development and validation of a clinical prediction rule for the diagnosis of breast cancer. Design and setting: Cohort study with two prospective groups of women: those presenting to a symptomatic breast clinic (derivation cohort) and a separate cohort presenting to 11 general practices (validation cohort) in Tayside, Scotland. Method: Regression analysis was used to derive a clinical prediction rule from presenting symptoms, personal and family history, and clinical findings. Validation consisted of estimating the number of breast cancers predicted to occur compared with the actual number of observed breast cancers across deciles of risk. Results: In the derivation cohort of 802 patients, 59 (7%) were diagnosed with breast cancer. Independent clinical predictors for breast cancer were: increasing age by year (adjusted odds ratio [AOR] 1.10, 95% confidence interval [CI] = 1.07 to 1.13); presence of a discrete lump (AOR 15.20, 95% CI = 4.88 to 47.34); breast thickening (AOR 7.64, 95% CI = 2.23 to 26.11); lymphadenopathy (AOR 3.63, 95% CI = 1.33 to 9.92); and lump =2 cm(AOR 5.41, 95% CI = 2.36 to 12.38). All eight patients with skin tethering had breast cancer. The regression model had good predictive power, identifying all five breast cancers in the validation cohort of 97 patients in the top two deciles of risk. Conclusion: The clinical prediction rule discriminates between patients at high risk of breast cancer from those at low risk, and can be implemented as an evidence-based recommendation to enhance appropriate referral from general practice to a symptomatic breast clinic. Ongoing validation in further populations is required. ©British Journal of General Practice.

AB - Background: An evidence-based approach is needed to identify women with breast symptoms who are most likely to have breast cancer so that timely and appropriate referral can take place. Aim: To report the development and validation of a clinical prediction rule for the diagnosis of breast cancer. Design and setting: Cohort study with two prospective groups of women: those presenting to a symptomatic breast clinic (derivation cohort) and a separate cohort presenting to 11 general practices (validation cohort) in Tayside, Scotland. Method: Regression analysis was used to derive a clinical prediction rule from presenting symptoms, personal and family history, and clinical findings. Validation consisted of estimating the number of breast cancers predicted to occur compared with the actual number of observed breast cancers across deciles of risk. Results: In the derivation cohort of 802 patients, 59 (7%) were diagnosed with breast cancer. Independent clinical predictors for breast cancer were: increasing age by year (adjusted odds ratio [AOR] 1.10, 95% confidence interval [CI] = 1.07 to 1.13); presence of a discrete lump (AOR 15.20, 95% CI = 4.88 to 47.34); breast thickening (AOR 7.64, 95% CI = 2.23 to 26.11); lymphadenopathy (AOR 3.63, 95% CI = 1.33 to 9.92); and lump =2 cm(AOR 5.41, 95% CI = 2.36 to 12.38). All eight patients with skin tethering had breast cancer. The regression model had good predictive power, identifying all five breast cancers in the validation cohort of 97 patients in the top two deciles of risk. Conclusion: The clinical prediction rule discriminates between patients at high risk of breast cancer from those at low risk, and can be implemented as an evidence-based recommendation to enhance appropriate referral from general practice to a symptomatic breast clinic. Ongoing validation in further populations is required. ©British Journal of General Practice.

UR - http://www.scopus.com/inward/record.url?scp=79957475787&partnerID=8YFLogxK

U2 - 10.3399/bjgp11X572391

DO - 10.3399/bjgp11X572391

M1 - Article

JO - British Journal of General Practice

JF - British Journal of General Practice

SN - 0960-1643

IS - 586

VL - 61

ER -

Documents

Library & Learning Centre

Contact | Accessibility | Policy