Testing M2T/T2M Transformations

Presentado en: 16th International Conference on Model Driven Engineering Languages and Systems (MODELS 2013). Del 29 de septiembre al 4 de octubre. Miami, EEUU.Testing model-to-model (M2M) transformations is becoming a prominent topic in the current Model-driven Engineering landscape. Current approaches for transformation testing, however, assume having explicit model representations for the input domain and for the output domain of the transformation. This excludes other important transformation kinds, such as model-to-text (M2T) and text-to-model (T2M) transformations, from being properly tested since adequate model representations are missing either for the input domain or for the output domain. The contribution of this paper to overcome this gap is extending Tracts, a M2M transformation testing approach, for M2T/T2M transformation testing. The main mechanism we employ for reusing Tracts is to represent text within a generic metamodel. By this, we transform the M2T/T2M transformation specification problems into equivalent M2M transformation specification problems. We demonstrate the applicability of the approach by two examples and present how the approach is implemented for the Eclipse Modeling Framework (EMF). Finally, we apply the approach to evaluate code generation capabilities of several existing UML tools.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Proyecto TIN2011-2379

Effect of glucagon-like peptide-1 receptor agonists and dipeptidyl peptidase-4 inhibitors on colorectal cancer incidence and its precursors

Incretin-based antihyperglycemic therapies increase intestinal mucosal expansion and polyp growth in mouse models. We aimed to evaluate the effect of dipeptidyl peptidase-4 inhibitors (DPP-4i) or glucagon-like peptide-1 receptor agonists (GLP-1ra) initiation on colorectal cancer incidence

Propensity Score Estimation to Address Calendar Time-Specific Channeling in Comparative Effectiveness Research of Second Generation Antipsychotics

BackgroundChanneling occurs when a medication and its potential comparators are selectively prescribed based on differences in underlying patient characteristics. Drug safety advisories can provide new information regarding the relative safety or effectiveness of a drug product which might increase selective prescribing. In particular, when reported adverse effects vary among drugs within a therapeutic class, clinicians may channel patients toward or away from a drug based on the patient's underlying risk for an adverse outcome. If channeling is not identified and appropriately managed it might lead to confounding in observational comparative effectiveness studies.ObjectiveTo demonstrate channeling among new users of second generation antipsychotics following a Food and Drug Administration safety advisory and to evaluate the impact of channeling on cardiovascular risk estimates over time.Data SourceFlorida Medicaid data from 2001–2006.Study DesignRetrospective cohort of adults initiating second generation antipsychotics. We used propensity scores to match olanzapine initiators with other second generation antipsychotic initiators. To evaluate channeling away from olanzapine following an FDA safety advisory, we estimated calendar time-specific propensity scores. We compare the performance of these calendar time-specific propensity scores with conventionally-estimated propensity scores on estimates of cardiovascular risk.Principal FindingsIncreased channeling away from olanzapine was evident for some, but not all, cardiovascular risk factors and corresponded with the timing of the FDA advisory. Covariate balance was optimized within period and across all periods when using the calendar time-specific propensity score. Hazard ratio estimates for cardiovascular outcomes did not differ across models (Conventional PS: 0.97, 95%CI: 0.81–3.18 versus calendar time-specific PS: 0.93, 95%CI: 0.77–3.04).ConclusionsChanges in channeling over time was evident for several covariates but had limited impact on cardiovascular risk estimates, possibly due to unmeasured confounding. Although calendar time-specific propensity scores appear to improve covariate balance, the impact on comparative effectiveness results is limited in this setting

Electronic Medical Record Cancer Incidence over Six Years Comparing New Users of Glargine with New Users of NPH Insulin

Background: Recent studies suggested that insulin glargine use could be associated with increased risk of cancer. We compared the incidence of cancer in new users of glargine versus new users of NPH in a longitudinal clinical cohort with diabetes for up to 6 years. Methods and Findings: From all patients who had been regularly followed at Massachusetts General Hospital from 1/01/2005 to 12/31/2010, 3,680 patients who had a medication record for glargine or NPH usage were obtained from the electronic medical record (EMR). From those we selected 539 new glargine users (age: 60.1±13.6 years, BMI: 32.7±7.5 kg/m2) and 343 new NPH users (61.5±14.1 years, 32.7±8.3 kg/m2) who had no prevalent cancer during 19 months prior to glargine or NPH initiation. All incident cancer cases were ascertained from the EMR requiring at least 2 ICD-9 codes within a 2 month period. Insulin exposure time and cumulative dose were validated. The statistical analysis compared the rates of cancer in new glargine vs. new NPH users while on treatment, adjusted for the propensity to receive one or the other insulin. There were 26 and 28 new cancer cases in new glargine and new NPH users for 1559 and 1126 person-years follow-up, respectively. There were no differences in the propensity-adjusted clinical characteristics between groups. The adjusted hazard ratio for the cancer incidence comparing glargine vs. NPH use was 0.65 (95% CI: 0.36–1.19). Conclusions: Insulin glargine is not associated with development of cancers when compared with NPH in this longitudinal and carefully retrieved EMR data

Tamoxifen Initiation After Ductal Carcinoma In Situ

Endocrine therapy initiation after ductal carcinoma in situ (DCIS) is highly variable and largely unexplained. National guidelines recommend considering tamoxifen for women with estrogen receptor-positive (ER+) DCIS or who undergo excision alone. We evaluated endocrine therapy use after DCIS over a 15-year period in an integrated health care setting to identify factors related to initiation

Cancer Incidence Among Those Initiating Insulin Therapy With Glargine Versus Human NPH Insulin

OBJECTIVE To add to the evidence on comparative long-term effects of insulin analog glargine versus human NPH insulin on the risk for cancer. RESEARCH DESIGN AND METHODS We identified cohorts of initiators of glargine and human NPH without an insulin prescription during the prior 19 months among patients covered by the Inovalon Medical Outcomes Research for Effectiveness and Economics Registry (MORE2 Registry) between January 2003 and December 2010. Patients were required to have a second prescription of the same insulin within 180 days and to be free of cancer. We balanced cohorts on risk factors for cancer outcomes based on comorbidities, comedication, and health care use during the prior 12 months using inverse probability of treatment weighting. Incident cancer was defined as having two claims for cancer (any cancer) or the same cancer (breast, prostate, colon) within 2 months. We estimated adjusted hazard ratios (HRs) and their 95% CI using weighted Cox models censoring for stopping, switching, or augmenting insulin treatment, end of enrollment, and mortality. RESULTS More patients initiated glargine (43,306) than NPH (9,147). Initiators of glargine (NPH) were followed for 1.2 (1.1) years and 50,548 (10,011) person-years; 993 (178) developed cancer. The overall HR was 1.12 (95% CI 0.95–1.32). Results were consistent for breast cancer, prostate cancer, and colon cancer; various durations of treatment; and sensitivity analyses. CONCLUSIONS Patients initiating insulin glargine rather than NPH do not seem to be at an increased risk for cancer. While our study contributes significantly to our evidence base for long-term effects, this evidence is very limited mainly based on actual dynamics in insulin prescribing

Investigating differences in treatment effect estimates between propensity score matching and weighting: A demonstration using STAR*D trial data

The choice of propensity score (PS) implementation influences treatment effect estimates not only because different methods estimate different quantities, but also because different estimators respond in different ways to phenomena such as treatment effect heterogeneity and limited availability of potential matches. Using effectiveness data, we describe lessons learned from sensitivity analyses with matched and weighted estimates