Bilateral analysis based false positive reduction for computer-aided mass detection

We have developed a false positive (FP) reduction method based on analysis of bilateral mammograms for computerized mass detection systems. The mass candidates on each view were first detected by our unilateral computer-aided detection (CAD) system. For each detected object, a regional registration technique was used to define a region of interest (ROI) that is "symmetrical" to the object location on the contralateral mammogram. Texture features derived from the spatial gray level dependence matrices and morphological features were extracted from the ROI containing the detected object on a mammogram and its corresponding ROI on the contralateral mammogram. Bilateral features were then generated from corresponding pairs of unilateral features for each object. Two linear discriminant analysis (LDA) classifiers were trained from the unilateral and the bilateral feature spaces, respectively. Finally, the scores from the unilateral LDA classifier and the bilateral LDA asymmetry classifier were fused with a third LDA whose output score was used to distinguish true mass from FPs. A data set of 341 cases of bilateral two-view mammograms was used in this study, of which 276 cases with 552 bilateral pairs contained 110 malignant and 166 benign biopsy-proven masses and 65 cases with 130 bilateral pairs were normal. The mass data set was divided into two subsets for twofold cross-validation training and testing. The normal data set was used for estimation of FP rates. It was found that our bilateral CAD system achieved a case-based sensitivity of 70%, 80%, and 85% at average FP rates of 0.35, 0.75, and 0.95 FPs/image, respectively, on the test data sets with malignant masses. In comparison to the average FP rates for the unilateral CAD system of 0.58, 1.33, and 1.63, respectively, at the corresponding sensitivities, the FP rates were reduced by 40%, 44%, and 42% with the bilateral symmetry information. The improvement was statistically significance (p < 0.05) as estimated by JAFROC analysis.     

Social worker estimations of life span in terminal cancer patients

The objective of this study was to evaluate the accuracy of the social worker estimation (SWE) of the length of survival of patients who were seen at the end stage of their terminal illness, in home-based palliative care treatment. Estimates were filled out on a form every 2 weeks during the time of the visits until the patient's discharge or death. The wording used by the social worker was the 'average survival period'. Survival was measured from the time of each survival prognostication until death from any cause. Both SWE and actual survival were categorized into 12 weeks. Then, 29 estimates were analyzed using the SPSS statistical software package. The mean and median actual survivals of the total cohort were 6.5 and 5.1 weeks, respectively. The minimum and maximum weeks of actual survival were 0.1 and 23.1, respectively. The mean and median differences between SWE and actual survival were 2.1 and 1.6 weeks, respectively (range: 18.7, minimum and maximum differences of -7.3 and 11.4 weeks, respectively). The Pearson correlation coefficient between actual survival and SWE was 0.827 (P<0.001). Overall, 59% (17/29) were correctly assigned by social worker to the correct survival categories. Our study suggests that the oncology social worker can be a valuable resource for information about the patient's prognosis of life span.     

Depressions of bereavement

The clinical significance of the depressions of bereavement is controversial. Although evidence suggests that most of these depressions remit spontaneously, some of them do require professional attention. Using a trained, non-professional screener, a study to screen for depressions of bereavement at 6 and 12 months after loss of a spouse was performed to determine the rate of depression and its characteristics. The relative value of using a dimensional assessment of depression (20-item Center for Epidemiologic Studies Depression [CES-D] Scale) and a structured diagnostic schedule for depression (Structured Clinical Interview for the DSM [SCID]) as telephone screening measures was evaluated. We found that while the CES-D overestimated, the SCID more precisely reflected the true rate of depression as determined in a subsample. The criterion for depression in this analysis was a diagnostic interview by a psychiatrist using DSM-III criteria and the Hamilton Rating Scale for Depression (HRSD). The study confirmed the existing literature on the high rate of depressions at 6 months (32% of bereaved spouses) and 12 months (27% of bereaved spouses) after a loss. These depressions were more common in widows than widowers. Past personal history (PPH) of depression and family history (FH) of depression were common among bereaved spouses, but did not enhance the risk of depression. Most of these depressions lasted considerably longer than 1 month. Anxiety, restlessness, and psychomotor retardation were prominent; melancholia was occasionally observed; and intense grief was associated with the depression.     

Work factors and occupational class disparities in sickness absence: findings from the GAZEL cohort study

OBJECTIVES: To estimate the contribution of stress-related and physical work factors to occupational class disparities in sickness absence from work. METHODS: Our sample consisted of 8847 men and 2886 women participating in the French GAZEL cohort study. Occupational class and medically certified sickness absence data (1995-2001) were obtained from the participants' employer. Work characteristics (physical and stress-related) were self-reported. We calculated rate ratios with Poisson regression models; fractions of sickness absence attributable to work factors were estimated with the Miettinen formula. RESULTS: Sickness absence was distributed along an occupational gradient. Work characteristics accounted for 19% (women) and 21% (men) of all absences. Physical work conditions accounted for 42% and 13% of absences for musculoskeletal reasons, and work stress accounted for 48% and 40% of psychiatric absences. Overall, about 20% of the occupational class gradient in sickness absence could have been associated with deleterious work conditions. CONCLUSION: Work conditions contribute to sickness absence, particularly among manual workers and clerks. Policies that decrease ergonomic constraints and work stress also could reduce the burden of ill health and sickness absence among the lowest strata of working populations.     

Primary cerebellar glioblastoma multiforme

Primary glioblastoma multiforme of cerebellar hemispheres in adults is a rare condition. Most of them result from dedifferentiation of astrocytoma to glioblastoma. We present two cases of unusual de novo cerebellar glioblastomas, one of which is the giant-cell variant. We review their clinical behaviour with conventional MR imaging features and discuss the key findings that can lead to the correct diagnosis in sight of new MR imaging technologies.     

Assessment and the ubiquity of culture: threats to validity in measures of health-related quality of life

Social workers in health care settings are increasingly using patient-based assessments (PBAs) of health-related quality of life such as the SF-36. However, the validity of many PBAs for use with cultural minority groups is limited. To ensure that cultural minority groups are not misrepresented by standardized measures, social workers--as effective patient advocates--must be familiar with the underlying conceptual assumptions of measurement theory to articulate the strengths and limitations of measures used to investigate populations with which they have not been tested and advocate for cultural minority groups using language and terminology that measurement practitioners can understand and embrace.     

When is baseline adjustment useful in analyses of change? An example with education and cognitive change

In research on the determinants of change in health status, a crucial analytic decision is whether to adjust for baseline health status. In this paper, the authors examine the consequences of baseline adjustment, using for illustration the question of the effect of educational attainment on change in cognitive function in old age. With data from the US-based Assets and Health Dynamics Among the Oldest Old survey (n = 5,726; born before 1924), they show that adjustment for baseline cognitive test score substantially inflates regression coefficient estimates for the effect of schooling on change in cognitive test scores compared with models without baseline adjustment. To explain this finding, they consider various plausible assumptions about relations among variables. Each set of assumptions is represented by a causal diagram. The authors apply simple rules for assessing causal diagrams to demonstrate that, in many plausible situations, baseline adjustment induces a spurious statistical association between education and change in cognitive score. More generally, when exposures are associated with baseline health status, this bias can arise if change in health status preceded baseline assessment or if the dependent variable measurement is unreliable or unstable. In some cases, change-score analyses without baseline adjustment provide unbiased causal effect estimates when baseline-adjusted estimates are biased.