The anatomy of missed breast cancers

Reintgen, Douglas S.; Berman, Claudia G.; Cox, Charles E.; Baekey, Paul; Nicosia, Santo V.; Greenberg, Harvey; Bush, Carrie M.; Lyman, GH; Clark, Robert A.

doi:10.1016/0960-7404(93)90046-2

Cited by 45 publications

(28 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…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.…”

Section: Explanatory Variable Number Of Patients Number With Cancer (%)supporting

confidence: 80%

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

McCowan¹,

Donnan²,

Dewar³

et al. 2011

Br J Gen Pract

View full text Add to dashboard Cite

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...

show abstract

Section: Explanatory Variable Number Of Patients Number With Cancer (%)supporting

confidence: 80%

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

McCowan¹,

Donnan²,

Dewar³

et al. 2011

Br J Gen Pract

View full text Add to dashboard Cite

show abstract

“…The sensitivity and specificity of mammography in the detection of breast cancer have been reported in several screening studies (Tabar et al, 1984;Baines et al, 1986;Bird, 1989;Sickles et al, 1990;Robertson, 1993) and diagnostic (consultative) studies (Wolfe et al, 1987;Hansell et al, 1988;Reintgen et al, 1993;Robertson, 1993;Sienko et al, 1993). However, in diagnostic studies, these parameters have frequently been determined retrospectively in pathologically proven breast cancers (Hansell et al, 1988;Reintgen et al, 1993). Moreover, the follow-up period has usually been 12 months or less (Wolfe et al, 1987;Robertson, 1993), and the proportion of patients lost to follow-up has not been well defined in many of the studies (Baines et al, 1986;Bird, 1989;Sienko et al, 1993).…”

mentioning

confidence: 87%

Sensitivity, specificity and predictive values of breast imaging in the detection of cancer

Duijm

Guit²,

Zaat³

et al. 1997

Br J Cancer

View full text Add to dashboard Cite

Summary In an observational follow-up study we determined whether the combined use of mammography and breast ultrasonography is an appropriate diagnostic tool to select patients with symptomatic breast disease who need additional pathological evaluation. Mammography and ultrasound were used as complementary diagnostic modalities in 3014 consecutively referred and mainly symptomatic patients. Sensitivity, specificity, predictive values and likelihood ratios were calculated according to standard procedures. Virtually complete follow-up was obtained by correlating the radiological diagnosis with clinical records, final pathological findings, records from the Cancer Register and data from questionnaires sent to the general practitioners of all the referred patients. After an average follow-up period of 30 months, the sensitivity for breast cancer detection was 92.0% and the specificity 97.7%. A positive predictive value of 68.0%, a negative predictive value of 99.6%, a positive likelihood ratio of 40 and a negative likelihood ratio of 0.08 were found. The mean diagnostic delay as a result of false negative examinations was 9 months (range 0-20 months). We conclude that breast imaging in routine daily practice, consisting of the integral use of mammography and ultrasonography, is an appropriate tool in the detection of cancer and should be included in the work-up of symptomatic breast disease.Keywords: breast neoplasm; mammography; ultrasonography; sensitivity; specificity In many Western countries breast cancer is the most common cause of death in women aged 35-55. The sensitivity and specificity of mammography in the detection of breast cancer have been reported in several screening studies (Tabar et al, 1984;Baines et al, 1986;Bird, 1989;Sickles et al, 1990;Robertson, 1993) and diagnostic (consultative) studies (Wolfe et al, 1987;Hansell et al, 1988;Reintgen et al, 1993;Robertson, 1993;Sienko et al, 1993). However, in diagnostic studies, these parameters have frequently been determined retrospectively in pathologically proven breast cancers (Hansell et al, 1988;Reintgen et al, 1993). Moreover, the follow-up period has usually been 12 months or less (Wolfe et al, 1987;Robertson, 1993), and the proportion of patients lost to follow-up has not been well defined in many of the studies (Baines et al, 1986;Bird, 1989;Sienko et al, 1993). For these reasons, the actual sensitivity and specificity of breast imaging in the detection of breast cancer will be lower than reported.The value of ultrasound examination of the breast as an adjunct to mammography, in the work-up of symptomatic breast disease is well established (Fleischer et al, 1983;Bassett et al, 1987;Warwick et al, 1988;Jackson, 1995). No prospective series with well-specified follow-up have been published in which both modalities are used as an integrated approach to determine the sensitivity and specificity in symptomatic patients.To overcome the restrictions mentioned, we performed a prospective study with extensive follow-up of over 3000 consecutive

show abstract

“…Figure 1 demonstrates this relationship based on the population study reported by Tabar et al (7), and underscores the importance of developing screening devices that can detect smaller tumors. For example, the average-size breast tumor detected by conventional mammography is on the order of 10-12 mm in diameter (8). Using the exponential relationship given in Figure 1, a new imaging technology that could reliably detect breast tumors 5 mm in diameter would increase survival rates by 8%-10%.…”

Section: Figurementioning

confidence: 99%

Breast CT

Glick

2007

Annu. Rev. Biomed. Eng.

View full text Add to dashboard Cite

Breast cancer is a serious disease that accounts for approximately 40,000 deaths per year in the United States. Unfortunately, there is no known cause of breast cancer, and therefore the best way to prevent mortality is early detection. In the past 15 years, breast cancer mortality has been reduced significantly, which is in part due to screening with film-screen mammography. Nonetheless, conventional mammography lacks sensitivity, especially for certain subgroups of women such as those with dense breast tissue, those under 50 years old, and pre- or perimenopausal women. In addition, mammography has a very poor positive predictive value for biopsy, with 70%-90% of biopsies performed turning out negative. By improving visualization of breast tissue, X-ray computerized tomography (CT) of the breast can potentially provide improvements in diagnostic accuracy over conventional mammography. Owing to recent technological developments in digital detector technology, flat-panel CT imagers dedicated to imaging of the breast are now feasible. A number of academic groups are currently researching dedicated breast CT and prototype systems are currently being evaluated in the clinical setting.

show abstract

The anatomy of missed breast cancers

Cited by 45 publications

References 19 publications

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

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

Sensitivity, specificity and predictive values of breast imaging in the detection of cancer

Breast CT

Contact Info

Product

Resources

About