J

J E Campbell

Mount Sinai Hospital

Publishes on Global Cancer Incidence and Screening, AI in cancer detection, Digital Radiography and Breast Imaging. 4 papers and 328 citations.

4Publications
328Total Citations

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Top publicationsby citations

Body Weight and Prognosis in Breast Cancer<xref ref-type="fn" rid="FN2">2</xref><xref ref-type="fn" rid="FN3">3</xref><xref ref-type="fn" rid="FN4">4</xref>
N F Boyd, J E Campbell, Germanson, Terry et al.|JNCI Journal of the National Cancer Institute|1981
Cited by 135

We have examined the relationship between risk factors for breast cancer incidence and the subsequent prognosis of breast cancer among patients in a randomized controlled trial of adjuvant ovarian ablation. Body weight was the only risk factor found to be associated with statistically significant differences in survival. This finding could not be explained by a disproportionate number of anatomically more advanced tumors in the heavier women. In premenopausal women aged 45 years or more, the only group to benefit from adjuvant ovarian ablation, there was an interaction of treatment and weight, suggesting that weight exerts its influence on prognosis by a hormonal mechanism. The prognostic effect of weight was generally most marked in patients with tumors whose prognostic characteristics were favorable, and in these patients weight loss as an adjuvant treatment may reduce the frequency of disease recurrence.

Mammographic patterns and bias in breast cancer detection.
N F Boyd, Brian O’Sullivan, J E Campbell et al.|Radiology|1982
Cited by 15

Wolfe's finding that some mammographic patterns (P2 and DY) are associated with an increased risk of breast cancer has been challenged by some authors who suggest that this is due to denser patterns concealing cancers present on the first examination: these cancers, it is argued, are diagnosed in later years, creating the spurious impression of increased cancer incidence. The authors examined this hypothesis in a series of patients with breast cancer but failed to find any evidence that the diagnosis was subject to systematic delay in patients with the P2 or DY pattern. Moreover, studies of a hypothetical model showed that bias in the detection of breast cancer was unlikely to account for more than a small increase in apparent cancer incidence. Thus it appears unlikely that such a bias is responsible for the risk of breast cancer observed in patients with these mammographic patterns.