Career Satisfaction and Perceived Salary Competitiveness among Individuals Who Completed Postdoctoral Research Training in Cancer Prevention.

Studies examining career satisfaction of biomedical scientists are limited, especially in the context of prior postdoctoral training. Here we focused on career satisfaction defined as satisfaction with one's career trajectory and perceived salary competitiveness among a predominantly Ph.D.-trained population of scientists who completed cancer prevention-related postdoctoral training between 1987-2011. National Cancer Institute (NCI) Cancer Prevention Fellowship Program (CPFP) alumni (n = 114), and previous recipients of NCI-sponsored Ruth L. Kirschstein National Research Service Award (NRSA/F32) postdoctoral fellowships (n = 140) completed online surveys. Associations of career satisfaction and perception of salary competitiveness with demographic, training, and employment-related factors were examined using logistic regression. Overall, 61% reported high levels of satisfaction with their career trajectory to-date. Higher salary (odds ratio [OR] = 2.86, 95% confidence interval [95% CI]: 1.07-7.69) and having more leadership roles (OR = 2.26, 95% CI:1.04-4.90) were independently associated with higher career satisfaction. Persons with race/ethnicity other than white (OR = 0.40, 95% CI: 0.20-0.82) or age ≥ 50 (OR = 0.40, 95%CI: 0.17-0.94) had lower career satisfaction levels. There were no statistically significant differences in career satisfaction levels by gender, scientific discipline, or employment sector. 74% perceived their current salary as competitive, but persons with 5-9, or ≥10 years in their current position reported lower levels (OR = 0.31, 95% CI: 0.15-0.65; and OR = 0.37, 95% CI: 0.16-0.87, respectively), as did individuals in government positions (OR = 0.33, 95% CI: 0.11-0.98). These data add to the understanding of career satisfaction of those with advanced training in biomedical research by examining these measures in relation to prior postdoctoral research training and across multiple career sectors

Career Satisfaction and Perceived Competitive Salary by Postdoctoral Cohort.

<p>Career Satisfaction and Perceived Competitive Salary by Postdoctoral Cohort.</p

Relative Odds of Selected Factors for Perceived Salary Competitiveness among Former Postdoctoral Fellows.

<p>Relative Odds of Selected Factors for Perceived Salary Competitiveness among Former Postdoctoral Fellows.</p

Selected Characteristics of the Study Population.

<p>Selected Characteristics of the Study Population.</p

Plasma volume expansion in pregnancy: Implications for biomarkers in population studies

There is a growing body of literature focused on endogenous hormone exposures during pregnancy and subsequent cancer risk for both mother and offspring. Examples of these studies include those focused on the biological mechanism for the association of pre-eclampsia with reduced risk of breast cancer for mother and female offspring or studies that have examined hormone concentrations during pregnancy between different ethnic groups who vary in their rates of breast cancer incidence. Although these studies seem relatively straightforward in conception and analysis, measurement of the concentration of hormones and other biomarkers in pregnant subjects is influenced by plasma volume expansion (PVE). During pregnancy, the maternal plasma volume expands 45% on average to provide for the greater circulatory needs of the maternal organs. Consequently, serum protein and hormone concentrations are greatly altered when comparing the pregnant with nonpregnant state. Assessing PVE also is complicated by the vast individual variation in PVE, ranging from minimal to a 2-fold increase. We propose that PVE needs to be evaluated when comparing biomarker concentrations during pregnancy in two populations that may differ with respect to PVE. Small body size is associated with lower PVE compared with higher body size. Therefore, we hypothesize that variation in PVE will influence the interpretation of differences in biomarker concentrations across population groups with respect to the etiologic significance of the biomarker to the disease under study (e.g., breast cancer). It is possible that some observations may be due only to differences in dilution between the two groups. We present PVE as a topic for consideration in population-based studies, examples of the types of studies where PVE may be relevant, and our own analysis of one such study in the text below

Comparison of Liquid Chromatography-Tandem Mass Spectrometry, RIA, and ELISA Methods for Measurement of Urinary Estrogens

Absolute and relative concentrations of estrogens and estrogen metabolites are important for clinical decisions as well as for epidemiologic, experimental, and clinical research on hormonal carcinogenesis. RIA and ELISA are routinely used for measuring estrogen metabolites in blood and urine due to efficiency and low cost. Here, we compare absolute and ranked concentrations of estrone, estradiol, and estriol measured by indirect RIA and of 2-hydroxyestrone and 16alpha-hydroxyestrone measured by ELISA to the concentrations obtained using a novel liquid chromatography-tandem mass spectrometry (LC-MS/MS) method, which measures 15 estrogen metabolites concurrently. We used overnight urine samples collected from control women (362 premenopausal and 168 postmenopausal) participating in a population-based case-control study of breast cancer among Asian American women ages 20 to 55 years. When comparing RIA or ELISA levels to LC-MS/MS, absolute concentrations for the five estrogen metabolites ranged from 1.6 to 2.9 and 1.4 to 11.8 times higher in premenopausal and postmenopausal women, respectively (all P \u3c 0.0001). However, LC-MS/MS measurements were highly correlated [Spearman r (r(s)) = 0.8-0.9] with RIA and ELISA measurements in premenopausal women and moderately correlated (r(s) = 0.4-0.8) in postmenopausal women. Measurements of the 2-hydroxyestrone:16alpha-hydroxyestrone ratio, a putative biomarker of breast cancer risk, were moderately correlated in premenopausal women (r(s) = 0.6-0.7) but only weakly correlated in postmenopausal women (r(s) = 0.2). LC-MS/MS had higher intraclass correlation coefficients (\u3e or =99.6%) and lower coefficients of variation (\u3c or =9.4%) than ELISA (\u3e or =97.2% and \u3c or =14.2%) and RIA (\u3e or =95.2% and \u3c or =17.8%). Comparison with the LC-MS/MS method suggests that the widely used RIA and ELISA estrogen metabolite measures may be problematic, especially at low estrogen metabolite levels characteristic of postmenopausal women