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William H. Goodson III, MD; Dan H. Moore II, PhD

Arch Surg. 2002;137:1152-1156.

Hypothesis  A standardized description of clinical breast examination (CBE) can predict the risk of delayed diagnosis of breast cancer.

Design  Survey of case series.

Setting  Breast surgery referral practice.

Patients  Consecutive sample of 371 women with 386 breast cancers of any stage for whom overall characteristics of CBE were recorded at the initial consultation.

Intervention  None.

Main Outcome Measures  Overall breast "durity" (from Latin duritia, meaning "hardness") was recorded as the inverse of whether rib edges could be felt through breast tissue in the most "dur" (firm or hard) part of the breast, usually the upper outer quadrant adjacent to the areola. "Nodularity" was recorded in this same area by means of an ordinal scale ranging from "surface is smooth" to "coarse nodularity." Delayed diagnosis was tabulated if the patient was told that cancer was not present when there was a sign of cancer on CBE, mammogram, and/or pathology slides. Relative risk of delayed diagnosis was determined within categories of nodularity or durity and within nodularity and durity categories combined.

Results  Diagnosis was delayed for 35 (9.1%) of cancers. Delay was least common (2 [2.2%] of 92) for less dur and less nodular breasts (relative risk, 1.0), most common (18 [13.5%] of 133) for less dur and more nodular breasts (relative risk, 6.23; 95% confidence interval, 3.58-10.22), and intermediate for other descriptions (² = 9.08; P = .03). Neither nodularity alone nor durity alone correlated with delay.

Conclusions  A standardized system to describe CBE will alert physicians to an increased risk of delayed diagnosis of breast cancer (especially for women with less dur and more nodular breasts), help improve interpretation of CBE, and reduce delayed diagnosis of breast cancer.

From the Department of Surgery, California Pacific Medical Research Institute (Dr Goodson), Geraldine Brush Cancer Research Institute, California Pacific Medical Research Institute (Dr Moore), and Department of Epidemiology and Biostatistics, University of California, San Francisco (Dr Moore), San Francisco.

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