Identifying suspected breast cancer: development and validation of a clinical prediction rule

Abstract

BackgroundAn 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. AimTo report the development and validation of a clinical prediction rule for the diagnosis of breast cancer. Design and settingCohort 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. MethodRegression 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. ResultsIn 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. ConclusionThe 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.Keywords breast cancer; diagnosis; primary care. methodological standards. Conventionally, clinical prediction rules go through three distinct stages before full implementation in a clinical setting:1. Development of the clinical prediction rule, establishing the independent and combined effect of explanatory variables that can include symptoms, signs, or diagnostic tests.2. Narrow and broad validation: the explanatory variables or clinical predictors in the derivation clinical prediction rule set are assessed in separate populations.3. Impact analysis of the clinical prediction rule, assessed by means of a randomised controlled trial: the impact of applying the clinical prediction rule in a clinical setting is measured either by patient outcome, health-professional behaviour, resource use, or any combination of these outcomes. 21The aim of this study was to develop and validate a clinical prediction rule in women presenting with breast symptoms, so that a more evidence-based approach to referral -which would include urgent referral under the 2-week rule -could be implemented as part of clinical-practice guidance. METHOD Study design and participantsThe study comprised two cohorts of p...

Reported breast symptoms in the National Breast and Cervical Cancer Early Detection Program

“…For example, there is some evidence that the sensitivity and specificity of ultrasound is greater than mammography in patients with breast symptoms for the detection of cancer, especially in younger women (23). More granular NBCCEDP monitoring tools, or the development of clinical prediction rules (24) may also be possible to encourage providers to deliver appropriate and timely follow-up for certain women with breast symptoms who may be at higher risk for cancer (24). Our results, along with evidence-based guidelines, can aid clinicians in the evaluation and diagnosis of many breast concerns.…”

Diretrizes para detecção precoce do câncer de mama no Brasil. II - Novas recomendações nacionais, principais evidências e controvérsias

“…Still, they indicated that protocols for priority referral from primary care have a cancer detection rate of some 10% 39 and sensitivity of some 90% 39,40,41 . The sign most commonly associated with breast cancer is breast lump, present in 90% of cases confirmed subsequently as cancer 42,43,44 .…”

Symptoms and risk factors to identify women with suspected cancer in primary care: derivation and validation of an algorithm

“…31 This prediction rule was derived from a secondary care setting and only had 59 cases in the derivation cohort and five in the validation cohort which the authors recognise was likely to be under-powered. 31 While both the current study and McGowan's found breast lump and skin tethering and increasing age were predictive of a diagnosis of breast cancer, this study's risk ratios were substantially higher for a breast lump (risk ratio = 51 compared with odds ratio = 15) although similar for skin tethering (risk ratio =9 compared with odds ratio = 8). Unlike the McGowan study, it was found that alcohol, family history of breast cancer, breast pain, post-menopausal bleeding, increasing affluence, and venous thromboembolism were independently predictive of a diagnosis of breast cancer.…”