The Role of Private International Law in Corporate Social Responsibility

__Abstract__ This contribution firstly reviews developments in the EU and in the United States on corporate social responsibility and conflict of laws. It concludes with reference to some related themes, in particular on the piercing of the corporate veil and with some remarks on compliance strategy, and compliance reality, for corporations

Managing pregnancy of unknown location based on initial serum progesterone and serial serum hCG: development and validation of a two-step triage protocol.

A uniform rationalized management protocol for pregnancies of unknown location (PUL) is lacking. We developed a two-step triage protocol based on presenting serum progesterone (step 1) and hCG ratio two days later (step 2) to select PUL at high-risk of ectopic pregnancy (EP).Cohort study of 2753 PUL (301 EP), involving a secondary analysis of prospectively and consecutively collected PUL at two London-based university teaching hospitals. Using a chronological split we used 1449 PUL for development and 1304 for validation. We aimed to select PUL as low-risk with high confidence (high negative predictive value, NPV) while classifying most EP as high-risk (high sensitivity). The first triage step selects low-risk PUL at presentation using a serum progesterone threshold. The remaining PUL are triaged using a novel logistic regression risk model based on hCG ratio and initial serum progesterone (second step), defining low-risk as an estimated EP risk <5%.On validation, initial serum progesterone ≤2nmol/l (step 1) selected 16.1% PUL as low-risk. Second step classification with the risk model M6P selected an additional 46.0% of all PUL as low-risk. Overall, the two-step protocol classified 62.1% of PUL as low-risk, with an NPV of 98.6% and a sensitivity of 92.0%. When the risk model was used in isolation (i.e. without the first step), 60.5% of PUL were classified as low-risk with 99.1% NPV and 94.9% sensitivity.The two-step protocol can efficiently classify PUL into being at high or low risk of complications

Flawed external validation study of the ADNEX model to diagnose ovarian canceron behalf of TG6 of the STRATOS initiative

External validation studies of prediction models are of utmost importance in order to assess the performance a prediction model in different locations. We therefore read with interest the recent external validation study of the ADNEX model 1 For patients with a persistent adnexal tumor who underwent surgery, the ADNEX model predicts the risk of five tumor types: benign, borderline malignant, stage I cancer, stage II-IV cancer, or secondary metastatic cancer. The model was developed on data from 5909 patients collected at 24 centers, in 10 countries, between 1999 and 2012. ADNEX aims to assist clinicians in making appropriate clinical decisions for patients presenting with an adnexal mass. For the ADNEX model, it is natural to first evaluate the prediction of malignancy, followed by an evaluation of the multiclass prediction of malignancy subtypes, similar to other multiclass validation studies [4]. This approach is followed in the recent paper, but there are a number of important issues around the design, analysis, and reporting we wish to raise.</p

Treatment of steroid-induced elevated intraocular pressure with anecortave acetate: a randomized clinical trial.

PURPOSE: The present study is the first randomized clinical trial designed to evaluate the intraocular pressure (IOP)-lowering effect of anecortave acetate (AA) administered at 3 doses (3, 15, or 30 mg) as an anterior juxtascleral depot (AJD) in patients experiencing elevated IOP due to corticosteroid therapy. METHODS: This was a double-masked, randomized, placebo-controlled, multicenter, parallel group trial. Eligible patients had an IOP of at least 24 mmHg and an IOP increase of at least 10 mmHg relative to their IOP before treatment with steroids. A target IOP was established for each patient at baseline. Patients were randomized to 1 of the 4 treatment groups: vehicle, 3 mg AA, 15 mg AA, or 30 mg AA. All patients then received a 0.5 mL AJD of the assigned treatment. Patients returned for scheduled examination visits at weeks 1, 2, 4, 6, months 3, 4, 5, and 6. IOP was measured at each visit as well as best corrected visual acuity (logMAR), ocular motility, eyelid responsiveness, slit lamp examination, and assessment of any adverse events. In addition, at baseline and at exit, a dilated fundus examination was carried out and the lens was examined using LOCS II criteria. RESULTS: Seventy patients were randomized to treatment. At week 4, eyes in the vehicle group showed a 3.4 mmHg (9.1%) decrease from baseline. Reductions for the 3 mg AA (3.1 mmHg, 10.7%) and the 30 mg AA groups (5.4 mmHg, 16.6%) were not significantly different than for vehicle control. However, IOP for the 15 mg AA group at week 4 was reduced 11.5 mmHg (31.3%) from baseline, which was statistically significant (P=0.0487). The mean time to treatment failure was 32.2, 38.9, 56.3, and 32.6 days for the vehicle, 3 mg AA, 15 mg AA, and 30 mg AA groups, respectively. Adverse events were assessed at each post-treatment visit. There were no serious adverse events that were determined to be related to the test article or its administration. CONCLUSIONS: AA can be of benefit to some patients requiring treatment with corticosteroids, but suffering from the side effect of elevated IOP

Evaluation of clinical prediction models (part 1):from development to external validation

Evaluating the performance of a clinical prediction model is crucial to establish its predictive accuracy in the populations and settings intended for use. In this article, the first in a three part series, Collins and colleagues describe the importance of a meaningful evaluation using internal, internal-external, and external validation, as well as exploring heterogeneity, fairness, and generalisability in model performance

Potential for Inhalation Exposure to Engineered Nanoparticles from Nanotechnology-Based Cosmetic Powders

Background: The market of nanotechnology-based consumer products is rapidly expanding, and the lack of scientific evidence describing the accompanying exposure and health risks stalls the discussion regarding its guidance and regulation