Digoxin treatment is associated with an increased incidence of breast cancer: a population-based case-control study

INTRODUCTION. Laboratory and epidemiologic studies have suggested a modifying effect of cardiac glycosides (for example, digoxin and digitoxin) on cancer risk. We explored the association between digoxin treatment and invasive breast cancer incidence among postmenopausal Danish women. METHODS. We used Danish registries to identify 5,565 postmenopausal women diagnosed with incident invasive breast carcinoma between 1 January 1991 and 31 December 2007, and 55,650 matched population controls. Cardiac glycoside prescriptions were ascertained from county prescription registries. All subjects had at least 2 years of recorded prescription drug and medical history data. We estimated the odds ratio associating digoxin use with breast cancer in conditional logistic regression models adjusted for age, county of residence, and use of anticoagulants, non-steroidal anti-inflammatory drugs (NSAIDs), aspirin, and hormone replacement therapy. We also explored the impact of confounding by indication and detection bias. RESULTS. Digoxin was the sole cardiac glycoside prescribed to subjects during the study period. There were 324 breast cancer cases (5.8%) and 2,546 controls (4.6%) with a history of digoxin use at least 1 year before their index date (adjusted odds ratio (OR): 1.30; 95% confidence interval: 1.14 to 1.48). The breast cancer OR increased modestly with increasing duration of digoxin exposure (adjusted OR for 7 to 18 years of digoxin use: 1.39; 95% confidence interval: 1.10 to 1.74). The association was robust to adjustment for age, receipt of hormone replacement therapy, coprescribed drugs, and confounding by indication. A comparison of screening mammography rates between cases and controls showed no evidence of detection bias. CONCLUSIONS. Our results suggest that digoxin treatment increases the risk of invasive breast cancer among postmenopausal women.Congressionaly Directed Medical Research Programs (BC073012); Karen Elise Jensen Foundation; Western Danish Research Forum for Health Science

H2G-Net: A multi-resolution refinement approach for segmentation of breast cancer region in gigapixel histopathological images

Over the past decades, histopathological cancer diagnostics has become more complex, and the increasing number of biopsies is a challenge for most pathology laboratories. Thus, development of automatic methods for evaluation of histopathological cancer sections would be of value. In this study, we used 624 whole slide images (WSIs) of breast cancer from a Norwegian cohort. We propose a cascaded convolutional neural network design, called H2G-Net, for segmentation of breast cancer region from gigapixel histopathological images. The design involves a detection stage using a patch-wise method, and a refinement stage using a convolutional autoencoder. To validate the design, we conducted an ablation study to assess the impact of selected components in the pipeline on tumor segmentation. Guiding segmentation, using hierarchical sampling and deep heatmap refinement, proved to be beneficial when segmenting the histopathological images. We found a significant improvement when using a refinement network for post-processing the generated tumor segmentation heatmaps. The overall best design achieved a Dice similarity coefficient of 0.933±0.069 on an independent test set of 90 WSIs. The design outperformed single-resolution approaches, such as cluster-guided, patch-wise high-resolution classification using MobileNetV2 (0.872±0.092) and a low-resolution U-Net (0.874±0.128). In addition, the design performed consistently on WSIs across all histological grades and segmentation on a representative × 400 WSI took ~ 58 s, using only the central processing unit. The findings demonstrate the potential of utilizing a refinement network to improve patch-wise predictions. The solution is efficient and does not require overlapping patch inference or ensembling. Furthermore, we showed that deep neural networks can be trained using a random sampling scheme that balances on multiple different labels simultaneously, without the need of storing patches on disk. Future work should involve more efficient patch generation and sampling, as well as improved clustering.publishedVersio

H2G-Net: A multi-resolution refinement approach for segmentation of breast cancer region in gigapixel histopathological images

Over the past decades, histopathological cancer diagnostics has become more complex, and the increasing number of biopsies is a challenge for most pathology laboratories. Thus, development of automatic methods for evaluation of histopathological cancer sections would be of value. In this study, we used 624 whole slide images (WSIs) of breast cancer from a Norwegian cohort. We propose a cascaded convolutional neural network design, called H2G-Net, for segmentation of breast cancer region from gigapixel histopathological images. The design involves a detection stage using a patch-wise method, and a refinement stage using a convolutional autoencoder. To validate the design, we conducted an ablation study to assess the impact of selected components in the pipeline on tumor segmentation. Guiding segmentation, using hierarchical sampling and deep heatmap refinement, proved to be beneficial when segmenting the histopathological images. We found a significant improvement when using a refinement network for post-processing the generated tumor segmentation heatmaps. The overall best design achieved a Dice similarity coefficient of 0.933±0.069 on an independent test set of 90 WSIs. The design outperformed single-resolution approaches, such as cluster-guided, patch-wise high-resolution classification using MobileNetV2 (0.872±0.092) and a low-resolution U-Net (0.874±0.128). In addition, the design performed consistently on WSIs across all histological grades and segmentation on a representative × 400 WSI took ~ 58 s, using only the central processing unit. The findings demonstrate the potential of utilizing a refinement network to improve patch-wise predictions. The solution is efficient and does not require overlapping patch inference or ensembling. Furthermore, we showed that deep neural networks can be trained using a random sampling scheme that balances on multiple different labels simultaneously, without the need of storing patches on disk. Future work should involve more efficient patch generation and sampling, as well as improved clustering

MR-proADM as a Prognostic Marker in Patients With ST-Segment-Elevation Myocardial Infarction - DANAMI-3 (a Danish Study of Optimal Acute Treatment of Patients With STEMI) Substudy

Background Midregional proadrenomedullin ( MR ‐pro ADM ) has demonstrated prognostic potential after myocardial infarction ( MI ). Yet, the prognostic value of MR ‐pro ADM at admission has not been examined in patients with ST‐segment–elevation MI ( STEMI ). Methods and Results The aim of this substudy, DANAMI‐3 (The Danish Study of Optimal Acute Treatment of Patients with ST ‐segment–elevation myocardial infarction), was to examine the associations of admission concentrations of MR ‐pro ADM with short‐ and long‐term mortality and hospital admission for heart failure in patients with ST ‐segment–elevation myocardial infarction. Outcomes were assessed using Cox proportional hazard models and area under the curve using receiver operating characteristics. In total, 1122 patients were included. The median concentration of MR ‐pro ADM was 0.64 nmol/L (25th–75th percentiles, 0.53–0.79). Within 30 days 23 patients (2.0%) died and during a 3‐year follow‐up 80 (7.1%) died and 38 (3.4%) were admitted for heart failure. A doubling of MR ‐pro ADM was, in adjusted models, associated with an increased risk of 30‐day mortality (hazard ratio, 2.67; 95% confidence interval, 1.01–7.11; P =0.049), long‐term mortality (hazard ratio, 3.23; 95% confidence interval, 1.97–5.29; P &lt;0.0001), and heart failure (hazard ratio, 2.71; 95% confidence interval, 1.32–5.58; P =0.007). For 30‐day and 3‐year mortality, the area under the curve for MR ‐pro ADM was 0.77 and 0.78, respectively. For 3‐year mortality, area under the curve (0.84) of the adjusted model marginally changed (0.85; P =0.02) after addition of MR ‐pro ADM . Conclusions Elevation of admission MR ‐pro ADM was associated with long‐term mortality and heart failure, whereas the association with short‐term mortality was borderline significant. MR ‐pro ADM may be a marker of prognosis after ST‐segment–elevation myocardial infarction but does not seem to add substantial prognostic information to established clinical models. Clinical Trial Registration URL : http:/www.ClinicalTrials.gov /. Unique identifiers: NCT 01435408 and NCT 01960933. </jats:sec

Design and Performance of the Hotrod Melt-Tip Ice-Drilling System

We introduce the design and performance of a melt-tip ice-drilling system designed to insert a temperature sensor cable into ice. The melt tip is relatively simple and low cost, designed for a one-way trip to the ice-bed interface. The drilling system consists of a melt tip, umbilical cable, winch, interface, power supply, and support items. The melt tip and the winch are the most novel elements of the drilling system, and we make the hardware and electrical designs of these components available open access. Tests conducted in a laboratory ice well indicate that the melt tip has an electrical energy to forward melting heat transfer efficiency of ~35 % with a theoretical maximum penetration rate of ~12 m/hr at maximum 6.0 kW power. In contrast, ice-sheet testing suggests the melt tip has an analogous heat transfer efficiency of ~15 % with a theoretical maximum penetration rate of ~6 m/hr. We expect the efficiency gap between laboratory and field performance to decrease with increasing operator experience. Umbilical freeze-in due to borehole refreezing is the primary depth-limiting factor of the drilling system. Enthalpy-based borehole refreezing assessments predict refreezing below critical umbilical diameter in ~4 hours at -20 ˚C ice temperatures and ~20 hours at -2 ˚C. This corresponds to a theoretical depth limit of up to ~200 m, depending on firn thickness, ice temperature and operator experience.</p

Feasibility of a standardized ultrasound examination in patients with rheumatoid arthritis: A quality improvement among rheumatologists cohort.

BACKGROUND: Quality improvement is important to facilitate valid patient outcomes. Standardized examination procedures may improve the validity of US. The aim of this study was to investigate the learning progress for rheumatologists during training of US examination of the hand in patients with rheumatoid arthritis (RA). METHODS: Rheumatologists with varying degrees of experience in US were instructed by skilled tutors. The program consisted of two days with hands-on training followed by personal US examinations performed in their individual clinics. Examinations were sent to the tutors for quality control. The US examinations were evaluated according to a scoring sheet containing 144 items. An acceptable examination was defined as > 80% correct scores. RESULTS: Thirteen rheumatologists participated in the study. They included a total of 104 patients with RA. Only few of the initial examinations were scored below 80%, and as experience increased, the scores improved (p = 0.0004). A few participants displayed decreasing scores. The mean time spent performing the standardized examination procedure decreased from 34 min to less than 10 minutes (p = 0.0001). CONCLUSION: With systematic hands-on training, a rheumatologist can achieve a high level of proficiency in the conduction of US examinations of the joints of the hand in patients with RA. With experience, examination time decreases, while the level of correctness is maintained. The results indicate that US may be applied as a valid measurement tool suitable for clinical practice and in both single- and multi-centre trials

Comparison of Short-Term Estrogenicity Tests for Identification of Hormone-Disrupting Chemicals

The aim of this study was to compare results obtained by eight different short-term assays of estrogenlike actions of chemicals conducted in 10 different laboratories in five countries. Twenty chemicals were selected to represent direct-acting estrogens, compounds with estrogenic metabolites, estrogenic antagonists, and a known cytotoxic agent. Also included in the test panel were 17β-estradiol as a positive control and ethanol as solvent control. The test compounds were coded before distribution. Test methods included direct binding to the estrogen receptor (ER), proliferation of MCF-7 cells, transient reporter gene expression in MCF-7 cells, reporter gene expression in yeast strains stably transfected with the human ER and an estrogen-responsive reporter gene, and vitellogenin production in juvenile rainbow trout. 17β-Estradiol, 17α-ethynyl estradiol, and diethylstilbestrol induced a strong estrogenic response in all test systems. Colchicine caused cytotoxicity only. Bisphenol A induced an estrogenic response in all assays. The results obtained for the remaining test compounds—tamoxifen, ICI 182.780, testosterone, bisphenol A dimethacrylate, 4-n-octylphenol, 4-n-nonylphenol, nonylphenol dodecylethoxylate, butylbenzylphthalate, dibutylphthalate, methoxychlor, o,p′-DDT, p,p′-DDE, endosulfan, chlomequat chloride, and ethanol—varied among the assays. The results demonstrate that careful standardization is necessary to obtain a reasonable degree of reproducibility. Also, similar methods vary in their sensitivity to estrogenic compounds. Thus, short-term tests are useful for screening purposes, but the methods must be further validated by additional interlaboratory and interassay comparisons to document the reliability of the methods