Quantification of the Impact of Photon Distinguishability on Measurement-Device- Independent Quantum Key Distribution

Measurement-Device-Independent Quantum Key Distribution (MDI-QKD) is a two-photon protocol devised to eliminate eavesdropping attacks that interrogate or control the detector in realized quantum key distribution systems. In MDI-QKD, the measurements are carried out by an untrusted third party, and the measurement results are announced openly. Knowledge or control of the measurement results gives the third party no information about the secret key. Error-free implementation of the MDI-QKD protocol requires the crypto-communicating parties, Alice and Bob, to independently prepare and transmit single photons that are physically indistinguishable, with the possible exception of their polarization states. In this paper, we apply the formalism of quantum optics and Monte Carlo simulations to quantify the impact of small errors in wavelength, bandwidth, polarization and timing between Alice’s photons and Bob’s photons on the MDI-QKD quantum bit error rate (QBER). Using published single-photon source characteristics from two-photon interference experiments as a test case, our simulations predict that the finite tolerances of these sources contribute (4.04±20/√Nsifted )% to the QBER in an MDI-QKD implementation generating an Nsifted-bit sifted key

Clinical judgement and therapeutic decision making

AbstractClinical decision making is under increased scrutiny due to concerns about the cost and quality of medical care. Variability in physician decision making is common, in part because of deficiencies in the knowledge base, but also due to the difference in physicians' approaches to clinical problem solving. Evaluation of patient prognosis is a critical factor in the selection of therapy, and careful attention to methodology is essential to provide reliable information.Randomized controlled clinical trials provide the most solid basis for the establishment of broad therapeutic principles. Because randomized studies cannot be performed to address every question, observational studies will continue to play a complementary role in the evaluation of therapy. Randomized studies in progress, meta analyses of existing data, and increased use of administrative and collaborative clinical data bases will improve the knowledge base for decision making in the future

Importance of clinical measures of ischemia in the prognosis of patients with documented coronary artery disease

AbstractTo examine the value of clinical measures of ischemia for stratifying prognosis, 5,886 consecutive patients who had symptomatic significant (≥75% stenosis) coronary artery disease were studied. Using the Cox regression model in a randomly selected half of the patients, the prognostically independent clinical variables were weighted and arranged into a simple angina score: angina score = angina course × (1 + daily angina frequency) + ST-T changes, where angina course was equal to 3 if unstable or variant angina was present, 2 if the patient's angina was progressive with nocturnal episodes, 1 if it was progressive without nocturnal symptoms and 0 if it was stable; 6 points were added for the presence of “ischemic” ST-T changes. This angina score was then validated in an independent patient sample.The score was a more powerful predictor of prognosis than was any individual anginal descriptor. Furthermore, the angina score added significant independent prognostic information to the patient's age, sex, coronary anatomy and left ventricular function. Patients with three vessel disease and a normal ventricle (n = 1,233) had a 2 year infarction-free survival rate of 90% with an angina score of 0 and a 68% survival rate with an angina score ≥9. With an ejection fraction <50% and three vessel disease (n = 1,116), the corresponding infarction-free survival figures were 76 and 56%. Thus, a careful summarization of clinical markers of ischemia in the form of an angina score can provide a powerful prognostic tool and may aid clinicians in identifying high risk patients who are candidates for aggressive therapeutic interventions

Centerscope

Centerscope, formerly Scope, was published by the Boston University Medical Center "to communicate the concern of the Medical Center for the development and maintenance of improved health care in contemporary society.

An assessment of existing models for individualized breast cancer risk estimation in a screening program in Spain

Background: The aim of this study was to evaluate the calibration and discriminatory power of three predictive models of breast cancer risk. Methods: We included 13,760 women who were first-time participants in the Sabadell-Cerdanyola Breast Cancer Screening Program, in Catalonia, Spain. Projections of risk were obtained at three and five years for invasive cancer using the Gail, Chen and Barlow models. Incidence and mortality data were obtained from the Catalan registries. The calibration and discrimination of the models were assessed using the Hosmer-Lemeshow C statistic, the area under the receiver operating characteristic curve (AUC) and the Harrell’s C statistic. Results: The Gail and Chen models showed good calibration while the Barlow model overestimated the number of cases: the ratio between estimated and observed values at 5 years ranged from 0.86 to 1.55 for the first two models and from 1.82 to 3.44 for the Barlow model. The 5-year projection for the Chen and Barlow models had the highest discrimination, with an AUC around 0.58. The Harrell’s C statistic showed very similar values in the 5-year projection for each of the models. Although they passed the calibration test, the Gail and Chen models overestimated the number of cases in some breast density categories. Conclusions: These models cannot be used as a measure of individual risk in early detection programs to customize screening strategies. The inclusion of longitudinal measures of breast density or other risk factors in joint models of survival and longitudinal data may be a step towards personalized early detection of BC.This study was funded by grant PS09/01340 and The Spanish Network on Chronic Diseases REDISSEC (RD12/0001/0007) from the Health Research Fund (Fondo de Investigación Sanitaria) of the Spanish Ministry of Health

Predicting survival in malignant pleural effusion: development and validation of the LENT prognostic score

BACKGROUND: Malignant pleural effusion (MPE) causes debilitating breathlessness and predicting survival is challenging. This study aimed to obtain contemporary data on survival by underlying tumour type in patients with MPE, identify prognostic indicators of overall survival and develop and validate a prognostic scoring system. METHODS: Three large international cohorts of patients with MPE were used to calculate survival by cell type (univariable Cox model). The prognostic value of 14 predefined variables was evaluated in the most complete data set (multivariable Cox model). A clinical prognostic scoring system was then developed and validated. RESULTS: Based on the results of the international data and the multivariable survival analysis, the LENT prognostic score (pleural fluid lactate dehydrogenase, Eastern Cooperative Oncology Group (ECOG) performance score (PS), neutrophil-to-lymphocyte ratio and tumour type) was developed and subsequently validated using an independent data set. Risk stratifying patients into low-risk, moderate-risk and high-risk groups gave median (IQR) survivals of 319 days (228–549; n=43), 130 days (47–467; n=129) and 44 days (22–77; n=31), respectively. Only 65% (20/31) of patients with a high-risk LENT score survived 1 month from diagnosis and just 3% (1/31) survived 6 months. Analysis of the area under the receiver operating curve revealed the LENT score to be superior at predicting survival compared with ECOG PS at 1 month (0.77 vs 0.66, p<0.01), 3 months (0.84 vs 0.75, p<0.01) and 6 months (0.85 vs 0.76, p<0.01). CONCLUSIONS: The LENT scoring system is the first validated prognostic score in MPE, which predicts survival with significantly better accuracy than ECOG PS alone. This may aid clinical decision making in this diverse patient population