Incidence and prevalence analysis of non-small-cell and small-cell lung cancer using administrative data

Treatment of lung cancer depends on the stage of the tumor and the histological type. In recent years, the histological confirmation of lung non-small-cell lung cancer has become crucial since the availability of selective target therapeutic approaches. The aim of the study was to develop a validated procedure to estimate the incidence and prevalence of non-small-cell and small-cell lung cancer from healthcare administrative data. A latent class model for categorical variables was applied. The following observed variables were included in the analysis: ICD-9-CM codes in the Hospital Discharge Registry, ATC codes of medications dispensed present in the Drugs Prescriptions Registry, and the procedure codes in the Outpatient Registry. The proportion of non-small-cell lung cancer diagnoses was estimated to be 85% of the total number of lung cancer on the cohort of incident cases and 89% on the cohort of prevalent cases. External validation on a cohort of 107 patients with a lung cancer diagnosis and histological confirmation showed a sensitivity of 95.6% (95%CI: 89–98.8%) and specificity of 94.1% (95%CI: 71.3–99.9%). The procedure is an easy-to-use tool to design subpopulation-based studies on lung cancer and to better plan resource allocation, which is important since the introduction of new targeted therapies in non-small-cell lung carcinoma

Dual Effect of Methylprednsolone Pulses on Apoptosis of Peripheral Leukocytes in Patients with Renal Diseases

It is well known that change in apoptosis may modulate the natural story of illness, and that many drugs may act through modulation of apoptosis, but the role of steroids in acting through apoptosis in different settings, including renal diseases, has still to be elucidated. We studied the in vivo effects of steroids by oral assumption (10 to 25 mg/deltacortene) or by intravenous pulses (300 to 1000 mg/dose) on apoptosis and cellular subsets of peripheral lymphocytes, by evaluating DNA-fragmentation and lymphocyte subsets in 79 subjects: 22 controls and 57 patients with various renal diseases (25 Lupus-GN, 19 membranous-GN (MGN), 6 rapidly progressive-GN (RPGN), 2 acute interstitial nephritis (AIN), 5 on chronic dialysis. Baseline apoptosis was present in 1/22 (4.5%) of controls, 3/25 (12%) SLE, 2/6 (33.3%) RPGN and 10/19 (52.6%) MGN. A significant decrease in CD3+CD8+ cell count and a significant increase of the CD3+CD4/CD3+CD8+ ratio were found in apoptosis-positive subjects. DNA fragmentation did not change after oral steroids, paralleling a 22 to 32% decrease in total lymphocytes. Following intravenous methylprednisolone pulses, a deeper drop of all lymphocyte subsets was observed, while DNA fragmentation turned from present to absent in 2 MGN, but not in 2 RPGN, and from absent to present in 1 ARF and 1 SLE, independently of the dosage. We demonstrated that the presence of apoptosis in renal diseases is associated with decreased CD3+CD8+ cell count. Furthermore, steroid intravenous pulses, besides inducing a profound decrease in lymphocyte subsets, do exert a dual effect on baseline leukocyte apoptosis, eventually leading to a reversal of baseline patterns, either turning from negative to positive or from positive to negative. Oral steroid therapy did not influence baseline apoptosis

A meta-model for software protections and reverse engineering attacks

Software protection techniques are used to protect valuable software assets against man-at-the-end attacks. Those attacks include reverse engineering to steal confidential assets, and tampering to break the software’s integrity in unauthorized ways. While their ultimate aims are the original assets, attackers also target the protections along their attack path. To allow both humans and tools to reason about the strength of available protections (and combinations thereof) against potential attacks on concrete applications and their assets, i.e., to assess the true strength of layered protections, all relevant and available knowledge on the relations between the relevant aspects of protections, attacks, applications, and assets need to be collected, structured, and formalized. This paper presents a software protection meta-model that can be instantiated to construct a formal knowledge base that holds precisely that information. The presented meta-model is validated against existing models and taxonomies in the domain of software protection, and by means of prototype tools that we developed to help non-modelling-expert software defenders with populating a knowledge base and with extracting and inferring practically useful information from it. All discussed tools are available as open source, and we evaluate their use as part of a software protection work flow on an open source application and industrial use cases