Summary
This clinical prediction rule shows that increasing age, presence of a discrete lump, presence of a lump ≥2 cm in size, thickening of the breast, lymphadenopathy, and the presence of a lump tethered to the skin or chest wall all independently increase the probability of a woman having breast cancer. Validation of the rule shows that probability of breast cancer is higher with an increasing number of these independent clinical predictive factors.
Use of the clinical prediction rule may enable a more rational and evidence-based approach to clinical assessment in primary care and would allow stratification in terms of routine and urgent referral to specialist breast care clinics. For women with a low probability of breast cancer, the clinical prediction rule would also enable alternative strategies, aside from immediate referral, such as watchful waiting.
Strengths and limitations
There are several strengths to this study. It is a pragmatic study, with few women excluded in the derivation dataset, ensuring high external validity. By generating independent clinical risk factors, the key relevant clinical ingredients can be gathered in a relatively easy way. By providing weighted scores, the incremental value of elements from the clinical prediction rule enables a quantified, continuous, risk-based approach.
The limitations of the study relate principally to the validation cohort, which is underpowered and, in terms of strength of evidence, represents a narrow validation of the clinical prediction rule.20,21 Only 97 of the 202 patients identified as eligible for the validation cohort consented to the study and, based on known prevalence figures, these numbers are low; it would seem likely that the practices may have not recruited all eligible women to the validation cohort. These shortcomings create a potential for spectrum bias.
There are other limitations of this study: the size of the validation cohort relative to the number of predictors is limited, and further validation is necessary in different primary care population groups that have larger numbers of cases of breast cancer. This is so that the robustness of the clinical values contained in the clinical prediction rule can be further assessed.27
Comparison with existing literature
A total of 7% of patients in the derivation cohort who were referred were found to have breast cancer, a figure similar to that given in two other UK studies of patients in breast care clinics who were referred.12,13 This enhances the external validity of this study's findings.20,21 In a US breast care clinic, breast cancer occurred in 22.8% of women who were referred; this higher figure probably reflects the differing referral and access patterns between healthcare systems in the UK and the US. Indeed, in the US cohort, referral was restricted only to women with a palpable breast lump.24,28,29
The five (5%) women who had breast cancer in the validation cohort set in 11 general practices is comparable to previous studies examining the underlying cause in women presenting with breast symptoms in US primary care.30,31
The clinical variables included in the clinical prediction rule have clinical and content validity. The presence of a breast lump is the most common presenting symptom in patients with breast cancer32 and is also the most predictive symptom and sign.28,31 Finding a lump of ≥2 cm increases the risk of cancer;24 additionally the incidence of breast cancer is consistently shown to be associated with increasing age.24,29
Implications for research and practice
Current clinical guidelines do not appear to offer clear advantages in terms of enhancing the referral process with regard to correctly prioritising urgent referrals, correctly reducing the number of breast cancer cases among non-urgent referrals, or diminishing the number of unnecessary referrals (women at low risk who could be ‘watchfully waited’ or reassured in primary care without recourse to be referred to a specialist breast clinic).12
A simplified scoring system based on the regression model using a standard technique can be generated; this is shown in Table 4.33 This would allow GPs to construct a simple score for patients who are symptomatic. If we selected a referral threshold based around a score of ≥4, this would be equivalent to a post-test probability of breast cancer of 5–8%.
Table 4 Scoring systemfor onward referral for breast cancer.a
Selecting a referral threshold would require more analysis — preferably within a much larger validation study — and would also need to acknowledge an acceptable trade-off, in terms of cost-effectiveness, between missed cancers and unnecessary investigations.
Using the regression model to calculate individual risk, these data would suggest that a 40-year-old woman with a discrete lump of ≥2.0 cm would have a 13% risk of breast cancer; a 60-year-old woman with a discrete lump, a 20% risk of breast cancer; and a 60-year-old woman with a discrete lump of ≥2.0 cm, a 60% risk of breast cancer. Estimated breast cancer risk could easily be accomplished by use of a programmed personal digital assessment that links to management strategies — namely watchful waiting or immediate referral — based on the regression co-efficients.34
A high proportion of patients with cancer in the derivation cohort presented with a discrete lump (90%, 53/59), while 53 of 284 (19%) women in the derivation cohort with a discrete lump had breast cancer. However, it is important to emphasise that the absence of a lump does not preclude breast cancer, as seen in 10% of this cohort, and that clinical breast examination may not detect all lumps in cases of breast cancer.35,36
This study is consistent with the emerging literature, which shows that the referral threshold of GPs to specialist breast clinics is falling. Previous studies report referral rates of >30% of women who are symptomatic and seen in primary care,4 whereas three-quarters of patients in the validation cohort were referred for assessment.
Factors driving a lower referral threshold are likely to be multifactorial and include patient preferences (women being averse to reassurance without specialist assessment), health professional related factors (lack of awareness concerning indications for referral or risk aversion, missing a case of breast cancer) and health system related factors (ease of availability of breast care clinic).
In the derivation cohort, over a third (36%) of patients did not meet referral criteria based on past history, symptoms, and signs, and would constitute a group of women at low risk of having breast cancer. Although GPs may have had other reasons to refer them, most likely due to patient preference, such a large proportion of referrals will have several untoward consequences, such as delaying assessment of patients at higher risk, while placing women at low risk at greater risk of iatrogenic harm through unnecessary diagnostic work-up.
Further validation of the rule, as well as assessment of its impact on referral practice, influence of improved prioritisation, and timely identification of women whose breast symptoms warrant urgent assessment, is needed. Future studies should compare these potential benefits against current clinical guidelines.
