Biomedical subjects

Tim E Aldrich

Publications and source records attributed to Tim E Aldrich.

3 recordsLinked to original sources

PubMed2006

Unstaged lung cancer in Kentucky.

Comparisons were made for unstaged lung cancer cases both to "staged" lung cancer cases and to unstaged cases from all other sites, in Kentucky for 1996-2000. Principal findings were that the likelihood of the lung cancer cases to be unstaged was greater when the cancer incidence report came from sources other than a hospital. This may implicate data system forces [for availability of necessary data for completing stage at diagnosis] rather than differences between cases per se. The risk of being unstaged by smoking status was reversed between lung cancer (lower risk) than for all other cancer sites (higher risk), an unexpected pattern. No difference for survival was found for unstaged versus staged lung cancer cases, as well as no differences for race and gender. The finding of no differences suggests that other forces (eg, age, source of payment) may contribute more greatly to one's likelihood of being unstaged with a diagnosis of lung cancer than for "all other cancer sites." These patterns pose provocative implications for how smoking status may influence clinical perspectives and those of persons faced with a diagnosis of cancer.

Adult↗

PubMed2005

Scale and shape issues in focused cluster power for count data.

BACKGROUND: Interest in the development of statistical methods for disease cluster detection has experienced rapid growth in recent years. Evaluations of statistical power provide important information for the selection of an appropriate statistical method in environmentally-related disease cluster investigations. Published power evaluations have not yet addressed the use of models for focused cluster detection and have not fully investigated the issues of disease cluster scale and shape. As meteorological and other factors can impact the dispersion of environmental toxicants, it follows that environmental exposures and associated diseases can be dispersed in a variety of spatial patterns. This study simulates disease clusters in a variety of shapes and scales around a centrally located single pollution source. We evaluate the power of a range of focused cluster tests and generalized linear models to detect these various cluster shapes and scales for count data. RESULTS: In general, the power of hypothesis tests and models to detect focused clusters improved when the test or model included parameters specific to the shape of cluster being examined (i.e. inclusion of a function for direction improved power of models to detect clustering with an angular effect). However, power to detect clusters where the risk peaked and then declined was limited. CONCLUSION: Findings from this investigation show sizeable changes in power according to the scale and shape of the cluster and the test or model applied. These findings demonstrate the importance of selecting a test or model with functions appropriate to detect the spatial pattern of the disease cluster.

Journal Article↗

PubMedDate not supplied

Mentorship and competencies for applied chronic disease epidemiology.

To understand the potential and establish a framework for mentoring as a method to develop professional competencies of state-level applied chronic disease epidemiologists, model mentorship programs were reviewed, specific competencies were identified, and competencies were then matched to essential public health services. Although few existing mentorship programs in public health were identified, common themes in other professional mentorship programs support the potential of mentoring as an effective means to develop capacity for applied chronic disease epidemiology. Proposed competencies for chronic disease epidemiologists in a mentorship program include planning, analysis, communication, basic public health, informatics and computer knowledge, and cultural diversity. Mentoring may constitute a viable strategy to build chronic disease epidemiology capacity, especially in public health agencies where resource and personnel system constraints limit opportunities to recruit and hire new staff.

Chronic Disease↗