Anogenital Distance and Phthalate Exposure: Swan et al. Respond

Reproduced with permission from Environmental Health Perspectives. DOI:10.1289/ehp.114-a20Swan et al. respond to several points made by McEwen and Renner regarding their recent study comparing anogenital distance (AGD) as a measure of androgen action in humans

Breast cancer risk, worry, and anxiety: Effect on patient perceptions of false-positive screening results

OBJECTIVE: The impact of mammography screening recall on quality-of-life (QOL) has been studied in women at average risk for breast cancer, but it is unknown whether these effects differ by breast cancer risk level. We used a vignette-based survey to evaluate how women across the spectrum of breast cancer risk perceive the experience of screening recall. METHODS: Women participating in mammography or breast MRI screening were recruited to complete a vignette-based survey. Using a numerical rating scale (0-100), women rated QOL for hypothetical scenarios of screening recall, both before and after benign results were known. Lifetime breast cancer risk was calculated using Gail and BRCAPRO risk models. Risk perception, trait anxiety, and breast cancer worry were assessed using validated instruments. RESULTS: The final study cohort included 162 women at low (n = 43, 26%), intermediate (n = 66, 41%), and high-risk (n = 53, 33%). Actual breast cancer risk was not a predictor of QOL for any of the presented scenarios. Across all risk levels, QOL ratings were significantly lower for the period during diagnostic uncertainty compared to after benign results were known (p \u3c 0.05). In multivariable regression analyses, breast cancer worry was a significant predictor of decreased QoL for all screening scenarios while awaiting results, including scenarios with non-invasive imaging alone or with biopsy. High trait anxiety and family history predicted lower QOL scores after receipt of benign test results (p \u3c 0.05). CONCLUSIONS: Women with high trait anxiety and family history may particularly benefit from discussions about the risk of recall when choosing a screening regimen

Decrease in Anogenital Distance among Male Infants with Prenatal Phthalate Exposure

Prenatal phthalate exposure impairs testicular function and shortens anogenital distance (AGD) in male rodents. We present data from the first study to examine AGD and other genital measurements in relation to prenatal phthalate exposure in humans. A standardized measure of AGD was obtained in 134 boys 2–36 months of age. AGD was significantly correlated with penile volume (R = 0.27, p = 0.001) and the proportion of boys with incomplete testicular descent (R = 0.20, p = 0.02). We defined the anogenital index (AGI) as AGD divided by weight at examination [AGI = AGD/weight (mm/kg)] and calculated the age-adjusted AGI by regression analysis. We examined nine phthalate monoester metabolites, measured in prenatal urine samples, as predictors of age-adjusted AGI in regression and categorical analyses that included all participants with prenatal urine samples (n = 85). Urinary concentrations of four phthalate metabolites [monoethyl phthalate (MEP), mono-n-butyl phthalate (MBP), monobenzyl phthalate (MBzP), and monoisobutyl phthalate (MiBP)] were inversely related to AGI. After adjusting for age at examination, p-values for regression coefficients ranged from 0.007 to 0.097. Comparing boys with prenatal MBP concentration in the highest quartile with those in the lowest quartile, the odds ratio for a shorter than expected AGI was 10.2 (95% confidence interval, 2.5 to 42.2). The corresponding odds ratios for MEP, MBzP, and MiBP were 4.7, 3.8, and 9.1, respectively (all p-values < 0.05). We defined a summary phthalate score to quantify joint exposure to these four phthalate metabolites. The age-adjusted AGI decreased significantly with increasing phthalate score (p-value for slope = 0.009). The associations between male genital development and phthalate exposure seen here are consistent with the phthalate-related syndrome of incomplete virilization that has been reported in prenatally exposed rodents. The median concentrations of phthalate metabolites that are associated with short AGI and incomplete testicular descent are below those found in one-quarter of the female population of the United States, based on a nationwide sample. These data support the hypothesis that prenatal phthalate exposure at environmental levels can adversely affect male reproductive development in humans

Analysis of mass spectrometry data from the secretome of an explant model of articular cartilage exposed to pro-inflammatory and anti-inflammatory stimuli using machine learning

Background: Osteoarthritis (OA) is an inflammatory disease of synovial joints involving the loss and degeneration of articular cartilage. The gold standard for evaluating cartilage loss in OA is the measurement of joint space width on standard radiographs. However, in most cases the diagnosis is made well after the onset of the disease, when the symptoms are well established. Identification of early biomarkers of OA can facilitate earlier diagnosis, improve disease monitoring and predict responses to therapeutic interventions. Methods: This study describes the bioinformatic analysis of data generated from high throughput proteomics for identification of potential biomarkers of OA. The mass spectrometry data was generated using a canine explant model of articular cartilage treated with the pro-inflammatory cytokine interleukin 1 β (IL-1β). The bioinformatics analysis involved the application of machine learning and network analysis to the proteomic mass spectrometry data. A rule based machine learning technique, BioHEL, was used to create a model that classified the samples into their relevant treatment groups by identifying those proteins that separated samples into their respective groups. The proteins identified were considered to be potential biomarkers. Protein networks were also generated; from these networks, proteins pivotal to the classification were identified. Results: BioHEL correctly classified eighteen out of twenty-three samples, giving a classification accuracy of 78.3% for the dataset. The dataset included the four classes of control, IL-1β, carprofen, and IL-1β and carprofen together. This exceeded the other machine learners that were used for a comparison, on the same dataset, with the exception of another rule-based method, JRip, which performed equally well. The proteins that were most frequently used in rules generated by BioHEL were found to include a number of relevant proteins including matrix metalloproteinase 3, interleukin 8 and matrix gla protein. Conclusions: Using this protocol, combining an in vitro model of OA with bioinformatics analysis, a number of relevant extracellular matrix proteins were identified, thereby supporting the application of these bioinformatics tools for analysis of proteomic data from in vitro models of cartilage degradation

Preparing construction supply chains for blockchain technology:An investigation of its potential and future directions

Blockchain, a peer-to-peer, controlled, distributed database structure, has the potential to profoundly affect current business transactions in the construction industry through smart contracts, cryptocurrencies, and reliable asset tracking. The construction industry is often criticized for being slow in embracing emerging technologies and not effectively diffusing them through its supply chains. Often, the extensive fragmentation, traditional procurement structures, destructive competition, lack of collaboration and transparency, low-profit margins, and human resources are shown as the main culprits for this. As blockchain technology makes its presence felt strongly in many other industries like finance and banking, this study investigates the preparation of construction supply chains for blockchain technology through an explorative analysis. Empirical data for the study were collected through semistructured interviews with 17 subject experts. Alongside presenting a strengths, weaknesses, opportunities, and threats analysis (SWOT), the study exhibits the requirements for and steps toward a construction supply structure facilitated by blockchain technology

Methods for Measuring Temporary Health States for Cost-Utility Analyses

A variety of methods are available to measure preferences for temporary health states for cost-utility analyses. The objectives of this review were to summarize the available temporary health-state valuation methods, identify advantages and disadvantages of each, and identify areas for future research. We describe the key aspects of each method and summarize advantages and disadvantages of each method in terms of consistency with QALY theory, relevance to temporary health-state-specific domains, ease of use, time preference, and performance in validation studies. Two broad categories of methods were identified: traditional and adapted. Traditional methods were health status instruments, time trade-off (TTO), and the standard gamble (SG). Methods adapted specifically for temporary health-state valuation were TTO with specified duration of the health state, TTO with a lifespan modification, waiting trade-off, chained approaches for TTO and SG, and sleep trade-off. Advantages and disadvantages vary by method and no 'gold standard' method emerged. Selection of a method to value temporary health states will depend on the relative importance of the following considerations: ability to accurately capture the unique characteristics of the temporary health state, level of respondent burden and cognition, theoretical consistency of elicited preference values with the overall purpose of the study, and resources available for study development and data collection. Further research should focus on evaluating validity, reliability and feasibility of temporary health-state valuation methods.

A Patient-Centered Utility Index for Non–Small Cell Lung Cancer in the United States

Background. A preference-based quality-of-life index for non–small cell lung cancer was developed with a subset of Functional Assessment of Cancer Therapy (FACT)–General (G) and FACT–Lung (L) items, based on clinician input and the literature. Design. A total of 236 non–small cell lung carcinoma patients contributed their preferences, randomly allocated among three survey groups to decrease burden. The FACT-L Utility Index (FACT-LUI) was constructed with two methods: 1) multiattribute utility theory (MAUT), where a visual analog scale (VAS)–based index was transformed to standard gamble (SG); and 2) an unweighted index, where items were summed, normalized to a 0 to 1.0 scale, and the result transformed to a scale length equivalent to the VAS or SG MAUT-based model on a Dead to Full Health scale. Agreement between patients’ direct utility and the indexes for current health was assessed. Results. The agreement of the unweighted index with direct SG was superior to the MAUT-based index (intraclass correlation for absolute agreement: 0.60 v. 0.35; mean difference: 0.03 v. 0.19; and mean absolute difference 0.09 v. 0.21, respectively). Mountain plots showed substantial differences, with the unweighted index demonstrating a median bias of 0.02 versus the MAUT model at 0.2. There was a significant difference ( P = 0.0002) between early (I-II) and late stage (III-IV) patients, the mean difference for both indexes being greater than distribution-based estimates of minimal important difference. Limitations. The population was limited to non–small cell lung cancer patients. However, most quality-of-life literature consulted and the FACT instruments do not differentiate between lung cancer cell types. Minorities were also limited in this sample. Conclusions. The FACT-LUI shows early evidence of validity for informing economic analysis of lung cancer treatments