On the sequential massart algorithm for statistical model checking

Several schemes have been provided in Statistical Model Checking (SMC) for the estimation of property occurrence based on predefined confidence and absolute or relative error. Simulations might be however costly if many samples are required and the usual algorithms implemented in statistical model checkers tend to be conservative. Bayesian and rare event techniques can be used to reduce the sample size but they can not be applied without prerequisite or knowledge about the system under scrutiny. Recently, sequential algorithms based on Monte Carlo estimations and Massart bounds have been proposed to reduce the sample size while providing guarantees on error bounds which has been shown to outperform alternative frequentist approaches [15]. In this work, we discuss some features regarding the distribution and the optimisation of these algorithms.No Full Tex

Sequential schemes for frequentist estimation of properties in statistical model checking

National Research Foundation (NRF) Singapor

Rapid Diagnostic Algorithms as a Screening Tool for Tuberculosis: An Assessor Blinded Cross-Sectional Study

Background: A major obstacle to effectively treat and control tuberculosis is the absence of an accurate, rapid, and low-cost diagnostic tool. A new approach for the screening of patients for tuberculosis is the use of rapid diagnostic classification algorithms. Methods: We tested a previously published diagnostic algorithm based on four biomarkers as a screening tool for tuberculosis in a Central European patient population using an assessor-blinded cross-sectional study design. In addition, we developed an improved diagnostic classification algorithm based on a study population at a tertiary hospital in Vienna, Austria, by supervised computational statistics. Results: The diagnostic accuracy of the previously published diagnostic algorithm for our patient population consisting of 206 patients was 54% (CI: 47%–61%). An improved model was constructed using inflammation parameters and clinical information. A diagnostic accuracy of 86% (CI: 80%–90%) was demonstrated by 10-fold cross validation. An alternative model relying solely on clinical parameters exhibited a diagnostic accuracy of 85% (CI: 79%–89%). Conclusion: Here we show that a rapid diagnostic algorithm based on clinical parameters is only slightly improved by inclusion of inflammation markers in our cohort. Our results also emphasize the need for validation of new diagnostic algorithms in different settings and patient populations

About Low DFR for QC-MDPC Decoding

International audienceMcEliece-like code-based key exchange mechanisms using QC-MDPC codes can reach IND-CPA security under hardness assumptions from coding theory, namely quasi-cyclic syndrome decoding and quasi-cyclic codeword finding. To reach higher security requirements, like IND-CCA security, it is necessary in addition to prove that the decoding failure rate (DFR) is negligible, for some decoding algorithm and a proper choice of parameters. Getting a formal proof of a low DFR is a difficult task. Instead, we propose to ensure this low DFR under some additional security assumption on the decoder. This assumption relates to the asymptotic behavior of the decoder and is supported by several other works. We define a new decoder, Backflip, which features a low DFR. We evaluate the Backflip decoder by simulation and extrapolate its DFR under the decoder security assumption. We also measure the accuracy of our simulation data, in the form of confidence intervals, using standard techniques from communication systems

Kappa statistic to measure agreement beyond chance in free-response assessments

Abstract Background The usual kappa statistic requires that all observations be enumerated. However, in free-response assessments, only positive (or abnormal) findings are notified, but negative (or normal) findings are not. This situation occurs frequently in imaging or other diagnostic studies. We propose here a kappa statistic that is suitable for free-response assessments. Method We derived the equivalent of Cohen’s kappa statistic for two raters under the assumption that the number of possible findings for any given patient is very large, as well as a formula for sampling variance that is applicable to independent observations (for clustered observations, a bootstrap procedure is proposed). The proposed statistic was applied to a real-life dataset, and compared with the common practice of collapsing observations within a finite number of regions of interest. Results The free-response kappa is computed from the total numbers of discordant (b and c) and concordant positive (d) observations made in all patients, as 2d/(b + c + 2d). In 84 full-body magnetic resonance imaging procedures in children that were evaluated by 2 independent raters, the free-response kappa statistic was 0.820. Aggregation of results within regions of interest resulted in overestimation of agreement beyond chance. Conclusions The free-response kappa provides an estimate of agreement beyond chance in situations where only positive findings are reported by raters

A phase 1b/2b multicenter study of oral panobinostat plus azacitidine in adults with MDS, CMML or AML with less than or equal to 30% blasts

Treatment with azacitidine (AZA), a demethylating agent, prolonged overall survival (OS) vs conventional care in patients with higher-risk myelodysplastic syndromes (MDS). As median survival with monotherapy is <2 years, novel agents are needed to improve outcomes. This phase 1b/2b trial (n=113) was designed to determine the maximum tolerated dose (MTD) or recommended phase 2 dose (RP2D) of panobinostat (PAN)+AZA (phase 1b) and evaluate the early efficacy and safety of PAN+AZA vs AZA monotherapy (phase 2b) in patients with higher-risk MDS, chronic myelomonocytic leukemia or oligoblastic acute myeloid leukemia with <30% blasts. The MTD was not reached; the RP2D was PAN 30 mg plus AZA 75 mg/m2. More patients receiving PAN+AZA achieved a composite complete response ([CR)+morphologic CR with incomplete blood count+bone marrow CR (27.5% (95% CI, 14.6–43.9%)) vs AZA (14.3% (5.4–28.5%)). However, no significant difference was observed in the 1-year OS rate (PAN+AZA, 60% (50–80%); AZA, 70% (50–80%)) or time to progression (PAN+AZA, 70% (40–90%); AZA, 70% (40–80%)). More grade 3/4 adverse events (97.4 vs 81.0%) and on-treatment deaths (13.2 vs 4.8%) occurred with PAN+AZA. Further dose or schedule optimization may improve the risk/benefit profile of this regimen

The analysis of PIK3CA mutations in gastric carcinoma and metanalysis of literature suggest that exon-selectivity is a signature of cancer type

BACKGROUND: PIK3CA is one of the genes most frequently mutated in human cancers and it is a potential target for personalized therapy. The aim of this study was to assess the frequency and type of PIK3CA mutations in gastric carcinoma and compare them with their clinical pathological correlates. METHODS: We analysed 264 gastric cancers, including 39 with microsatellite instability (MSI), for mutations in the two PIK3CA hotspots in exons 9 and 20 by direct sequencing of DNA obtained from microdissected cancer cells. RESULTS: The cases harbouring mutations were 42 (16%). All were heterozygous missense single base substitutions; the most common was H1047R (26/42; 62%) in exon 20 and the second was Q546K (4/42; 9.5%) in exon 9. All the mutated MSI cases (8/39) carried the H1047R mutation. No other association between PI3KCA mutations and clinical pathological covariates was found. A metanalysis of the mutations occurring in the same regions in 27 publications showed that ratio between exon 20 and exon 9 prevalences was 0.6 (95% CI: 0.5 -0.8) for colon, 1.6 (95% CI: 1.1 -2.3) for breast, 2.7 (95% CI: 1.6 -4.9) for gastric and 4.1 (95% CI: 1.9 -10.3) for endometrial cancer. CONCLUSIONS: The overall prevalence of PIK3CA mutations implies an important role for PIK3CA in gastric cancer. The lack of association with any clinical-pathological condition suggests that mutations in PIK3CA occur early in the development of cancer. The metanalysis showed that exon-selectivity is an important signature of cancer type reflecting different contexts in which tumours arise

Cyclical changes in seroprevalence of leptospirosis in California sea lions: endemic and epidemic disease in one host species?

BackgroundLeptospirosis is a zoonotic disease infecting a broad range of mammalian hosts, and is re-emerging globally. California sea lions (Zalophus californianus) have experienced recurrent outbreaks of leptospirosis since 1970, but it is unknown whether the pathogen persists in the sea lion population or is introduced repeatedly from external reservoirs.MethodsWe analyzed serum samples collected over an 11-year period from 1344 California sea lions that stranded alive on the California coast, using the microscopic agglutination test (MAT) for antibodies to Leptospira interrogans serovar Pomona. We evaluated seroprevalence among yearlings as a measure of incidence in the population, and characterized antibody persistence times based on temporal changes in the distribution of titer scores. We conducted multinomial logistic regression to determine individual risk factors for seropositivity with high and low titers.ResultsThe serosurvey revealed cyclical patterns in seroprevalence to L. interrogans serovar Pomona, with 4-5 year periodicity and peak seroprevalence above 50%. Seroprevalence in yearling sea lions was an accurate index of exposure among all age classses, and indicated on-going exposure to leptospires in non-outbreak years. Analysis of titer decay rates showed that some individuals probably maintain high titers for more than a year following exposure.ConclusionThis study presents results of an unprecedented long-term serosurveillance program in marine mammals. Our results suggest that leptospirosis is endemic in California sea lions, but also causes periodic epidemics of acute disease. The findings call into question the classical dichotomy between maintenance hosts of leptospirosis, which experience chronic but largely asymptomatic infections, and accidental hosts, which suffer acute illness or death as a result of disease spillover from reservoir species

Contemporary accuracy of death certificates for coding prostate cancer as a cause of death : Is reliance on death certification good enough? A comparison with blinded review by an independent cause of death evaluation committee

BACKGROUND: Accurate cause of death assignment is crucial for prostate cancer epidemiology and trials reporting prostate cancer-specific mortality outcomes. METHODS: We compared death certificate information with independent cause of death evaluation by an expert committee within a prostate cancer trial (2002-2015). RESULTS: Of 1236 deaths assessed, expert committee evaluation attributed 523 (42%) to prostate cancer, agreeing with death certificate cause of death in 1134 cases (92%, 95% CI: 90%, 93%). The sensitivity of death certificates in identifying prostate cancer deaths as classified by the committee was 91% (95% CI: 89%, 94%); specificity was 92% (95% CI: 90%, 94%). Sensitivity and specificity were lower where death occurred within 1 year of diagnosis, and where there was another primary cancer diagnosis. CONCLUSIONS: UK death certificates accurately identify cause of death in men with prostate cancer, supporting their use in routine statistics. Possible differential misattribution by trial arm supports independent evaluation in randomised trials