Gina A. Lockwood

A randomized controlled trial of the effects of group psychological therapy on survival in women with metastatic breast cancer.

In order to test the effect of a psychological intervention on survival from cancer, 66 women with metastatic breast cancer, all receiving standard medical care, were randomly assigned into two groups; one group (n=30) attended the psychological intervention, consisting of 35 weekly, 2 h sessions of supportive plus cognitive behavioral therapy; the control group (n=36) received only a home study cognitive behavioral package. No significant difference was found in survival post‐randomization between the groups as assessed by a log rank test 5 years after the commencement of the study. As expected, several prognostic factors were significant predictors of survival: metastatic site, hormonal receptor status, and chemotherapy prior to randomization. While many personal and demographic variables did not influence survival, there was a significant effect of self‐reported exercise (possibly due to better health). A small subgroup of intervention subjects who attended outside support groups also survived significantly longer than those who did not.

A meta-analysis of studies of dietary fat and breast cancer risk.

There is strong evidence that breast cancer risk is influenced by environmental factors, and animal experiments and human ecological data suggest that increased dietary fat intake increases the incidence of the disease. Epidemiological evidence on the relationship of dietary fat to breast cancer from cohort and case control studies has however been inconsistent. To examine the available evidence we have carried out a meta-analysis to summarise quantitatively the large published literature on dietary fat in the aetiology of breast cancer. After assembling all of the published case control and cohort studies, we extracted the relative risk in each study that compared the highest to the lowest level of intake. We then calculated a summary relative risk for all studies. The summary relative risk for the 23 studies that examined fat as a nutrient was 1.12 (95% CI 1.04-1.21). Cohort studies had a summary relative risk of 1.01 (95% CI 0.90-1.13) and case control studies a relative risk of 1.21 (95% CI 1.10-1.34). Summary estimates of risk for specific types of fat excluded unity for only saturated fat. For the 19 studies that examined food intake, the summary relative risks were 1.18 (95% CI 1.06-1.32) for meat, 1.17 (95% CI 1.04-1.31) for milk, and 1.17 (95% CI 1.02-1.36) for cheese. Summary relative risks for total fat intake were examined for several potential modifying factors. Regression analysis showed that European studies were more likely than studies done in other countries to show an increased relative risk associated with dietary fat and breast cancer, after taking into account potential modifying factors that included study design and quality.

Predictive value of tumor thickness for cervical lymph-node involvement in squamous cell carcinoma of the oral cavity: a meta-analysis of reported studies.

Tumor thickness (TT) appears to be a strong predictor for cervical lymph‐node involvement in squamous cell carcinoma of the oral cavity (OSCC), but a precise clinically optimal TT cutoff point has not been established. To address this question, the authors conducted a meta‐analysis.

A relationship between perceived self-efficacy and quality of life in cancer patients.

The quality of life of cancer patients may be influenced by the degree of control they feel able to exert over stressful situations arising from having the disease. We were able to test this association using a newly developed instrument, the Stanford Inventory of Cancer Patient Adjustment which assesses perceived self-efficacy, that is, perceived ability to enact coping strategies. In a heterogeneous sample of 273 cancer patients a strong positive correlation was found between self-efficacy and quality of life and between self-efficacy and mood. Improvements in all three measures brought about by a brief, group program teaching coping skills were also highly correlated. By contrast, no significant association was seen between improvement in mood or quality of life and amount of home practice of coping skills.

Psychological response to long term group therapy: a randomized trial with metastatic breast cancer patients

Research has demonstrated that short term psychological interventions improve the quality of life of cancer patients. However, there is much less evidence for the efficacy of longer term interventions. We report the psychometric results from a randomized clinical trial (n=66) assessing the effects of an 8 month, weekly psychological intervention on 30 metastatic breast cancer patients. Subjects were assessed at baseline, 4, 8 and 14 months for mood, quality of life and adjustment to cancer. Results demonstrated little psychometric difference between the control (n=36) and intervention groups over this length of time, in spite of the fact that when the intervention subjects attended a weekend of support and training in coping skills, the usual significant, short term changes were observed. In the long term intervention, subjects did experience more anxious preoccupation and less helplessness than the controls but no recorded improvements in mood or quality of life. However, profound clinical changes were observed by the therapists, similar to those noted by Spiegel et al. (1981) . We conclude that many of the psychological changes made by subjects in longer term interventions may elude conventional psychometric assessment. Further research, of a rigorous qualitative nature, is required to develop a clearer understanding of the experience of living and eventually dying of cancer within the context of a long term intervention. Copyright

Symmetry of projection in the quantitative analysis of mammographic images

Mammographic parcnchymal patterns are among the strongest indicators of the risk of developing breast cancer. Risk evaluation through breast patterns may have an important role in studies of the aetiology of breast cancer and for monitoring changes in the breast in evaluating potential risk-modifying interventions. Typically, patterns are assessed by an experienced radiologist according to Wolfe grade, or on a coarse quantitative scale according to percent density. Parenchymal characterization methods, to overcome variability of classification by human observer, are under investigation. These include image segmentation using semi-automatic thresholding and automatic classification through textural and density measures. An important practical question relates to the extent to which information about mammographic pattern is carried by any one of the four views obtained in a typical examination. Specifically, variations of right-left breast symmetry and variations between the two standard views of each breast were tested. The mammograms of 30 premenopausal women, comprising 90 images [30 each of the right cranial-caudal (RCC), left cranialcaudal (LCC) and right medial-lateral oblique (RMLO)] were evaluated. Parameters included both subjective (radiologist classification and interactive image thresholding) and objective (fractal and skewness indices) quantitative measurements of parenchymal pattern. For the parameters tested, a high degree of correlation was observed for measurements on the RCC, LCC and RMLO views. Pearson correlation coefficients between 0.86-0.96 were found for the comparisons of quantitative parameters. The strong correlations suggest that, in the study and application of mammographic density classification, representative information is provided in a single view.

The relationship of anthropometric measures to radiological features of the breast in premenopausal women.

We studied 273 premenopausal women recruited from mammography units who had different degrees of density of the breast parenchyma on mammography, in whom we measured height, weight and skinfold thicknesses. Mammograms were digitized to high spatial resolution by a scanning densitometer and images analysed to measure the area of dense tissue and the total area of the breast. Per cent density and the area of non-dense tissue were calculated from these measurements. We found that the mammographic measures had different associations with body size. Weight and the Quetelet index of obesity were strongly and positively associated with the area of non-dense tissue and with the total area of the breast, but less strongly and negatively correlated with the area of dense tissue. We also found a strong inverse relationship between the areas of radiologically dense and non-dense breast tissue. Statistical models containing anthropometric variables explained up to 8% of the variance in dense area, but explained up to 49% of the variance in non-dense area and 43% of variance in total area. These results suggest that aetiological studies in breast cancer that use mammographic density should consider dense and non-dense tissues separately. In addition to per cent density, methods should be examined that combine information from these two tissues.

Automated analysis of mammographic densities and breast carcinoma risk

There is considerable evidence that one of the strongest risk factors for breast carcinoma can be assessed from the mammographic appearance of the breast. However, the magnitude of the risk factor and the reliability of the prediction depend on the method of classification. Subjective classification requires specialized observer training and suffers from inter‐ and intraobserver variability. Furthermore, the categoric scales make it difficult to distinguish small differences in mammographic appearance. To address these limitations, automated analysis techniques that characterize mammographic density on a continuous scale have been considered, but as yet, these have been evaluated only for their ability to reproduce subjective classifications of mammographic parenchyma.

Mammographic Densities and Breast Cancer Risk

The radiological appearance of the female breast varies among individuals because of differences in the relative amounts and X-ray attenuation characteristics of fat and epithelial and stromal tissues. Fat is radiolucent and appears dark on a mammogram, and epithelium and stroma are radiodense and appear light. We review here the evidence that these variations, known as mammographic parenchymal patterns, are related to risk of breast cancer. Studies that used quantitative measurement to classify mammographic patterns have consistently found that women with dense tissue in more than 60-75% of the breast are at four to six times greater risk of breast cancer than those with no densities. These risk estimates are independent of the effects of other risk factors and have been shown to persist over at least 10 years of follow up. Estimates of attributable risk suggest that this risk factor may account for as many as 30% of breast cancer cases. Mammographically dense breast tissue is associated both with epithelial proliferation and with stromal fibrosis. The relationship between these histological features and risk of breast cancer may by explained by the known actions of growth factors that are thought to play important roles in breast development and carcinogenesis. Mammographically dense tissue differs from most other breast cancer risk factors in the strength of the associated relative and attributable risks for breast cancer, and because it can be changed by hormonal and dietary interventions. This risk factor may be most useful as a means of investigating the etiology of breast cancer and of testing hypotheses about potential preventive strategies.

Breast cancer risk and measured mammographic density.

It has been well established that there is a positive correlation between the dense appearance of breast stroma and parenchyma on a mammogram and the risk of breast cancer. Subjective assessment by radiologists indicated relative risks on the order of 4 to 6 for the group of women whose mammograms showed a density of over 75% or more of the projected area compared to those with an absence of density. In order to obtain a more quantitative, continuous and reproducible means of estimating breast density, which is sensitive to small changes, we have developed quantitative methods for the analysis of mammographic density, which can be applied to digitized mammograms. These techniques have been validated in a nested case-control study on 708 women aged 40–59 years(on entry) who participated in a national mammographic screening study. An interactive image segmentation method and two completely automated techniques based on image texture and grey scale histogram measures have been developed and evaluated. While our methods all show statistically significant risk factors for dense breasts, the interactive method currently provides the highest risk values (relative risk 4.0, 95% confidence interval (CI) = 2.12–7.56) compared to a measure based on the shape of the image histogram (relative risk 3.35, 95% CI = 1.57–7.12) or the fractal dimension of the mammogram (relative risk 2.54, 95% CI = 1.14–5.68), All methods were highly consistent between images of the left and right breast and between the two standard views (cranio-caudal and medio-lateral oblique) of each breast, so that studies can be done by sampling only one of the four views per examination. There is a large number of factors in addition to breast density which affect the appearance of the mammogram. In particular, the assessment of density is made difficult where the breast is not uniformly compressed, e.g. at the periphery. We have designed and are currently evaluating an image processing algorithm that effectively corrects for this problem and have considered methods for controlling some of the variables of image acquisition in prospective studies. Measurements of breast density may be helpful in assigning risk groups to women. Such measurements might guide the frequency of mammographic screening, aid the study of breast cancer aetiology, and be useful in monitoring possible risk-modifying interventions. Using our techniques, we have been able to show that reduction of the proportion of fat in the diet can result in reductions of breast density, although the direct connection to risk has not yet been made. The relationship between breast density and hormone-related and genetic factors is also of great interest. It is often not possible or ethical to obtain mammograms on some groups of women for whom information on density would be very useful. This includes younger women as well as groups in which it would be desirable to obtain such information at frequent intervals. For this reason, we are exploring the use of imaging approaches such as ultrasound and magnetic resonance imaging, which do not require ionizing radiation, to make measurements analogous to those now being performed by using X-ray mammograms.