The use of a binary composite endpoint and sample size requirement: influence of endpoints overlap

Although composite endpoints (CE) are common in clinical trials, the impact of the relationship between the components of a binary CE on the sample size requirement (SSR) has not been addressed. We performed a computational study considering 2 treatments and a CE with 2 components: the relevant endpoint (RE) and the additional endpoint (AE). We assessed the strength of the components’ interrelation by the degree of relative overlap between them, which was stratified into 5 groups. Within each stratum, SSR was computed for multiple scenarios by varying the events proportion and the effect of the therapy. A lower SSR using CE was defined as the best scenario for using the CE. In 25 of 66 scenarios the degree of relative overlap determined the benefit of using CE instead of the RE. Adding an AE with greater effect than the RE leads to lower SSR using the CE regardless of the AE proportion and the relative overlap. The influence of overlapping decreases when the effect on RE increases. Adding an AE with lower effect than the RE constitutes the most uncertain situation. In summary, the interrelationship between CE components, assessed by the relative overlap, can help to define the SSR in specific situations and it should be considered for SSR computation.Peer ReviewedPostprint (published version

Persistence with dual antiplatelet therapy after percutaneous coronary intervention for ST-segment elevation acute coronary syndrome: a population-based cohort study in Catalonia (Spain)

Objectives: Guidelines recommending 12-month dual antiplatelet therapy (DAPT) in patients with ST-elevation acute coronary syndrome (STEACS) undergoing percutaneous coronary intervention (PCI) were published in year 2012. We aimed to describe the influence of guideline implementation on the trend in 12-month persistence with DAPT between 2010 and 2015 and to evaluate its relationship with DAPT duration regimens recommended at discharge from PCI hospitals. Design: Observational study based on region-wide registry data linked to pharmacy billing data for DAPT follow-up. Setting: All PCI hospitals (10) belonging to the acute myocardial infarction (AMI) code network in Catalonia (Spain). Participants: 10 711 STEACS patients undergoing PCI between 2010 and 2015 were followed up. Primary and secondary outcome measures: Primary outcome was 12-month persistence with DAPT. Calendar year quarter, publication of guidelines, DAPT duration regimen recommended in the hospital discharge report, baseline patient characteristics and significant interactions were included in mixed-effects logistic regression based interrupted time-series models. Results: The proportion of patients on-DAPT at 12 months increased from 58% (56-60) in 2010 to 73% (71-75) in 2015. The rate of 12-month persistence with DAPT significantly increased after the publication of clinical guidelines with a time lag of 1 year (OR=1.20; 95% CI 1.11 to 1.30). A higher risk profile, more extensive and complex coronary disease, use of drug-eluting stents (OR=1.90; 95% CI 1.50 to 2.40) and a 12-month DAPT regimen recommendation at discharge from the PCI hospital (OR=5.76; 95% CI 3.26 to 10.2) were associated with 12-month persistence. Conclusion: Persistence with 12-month DAPT has increased since publication of clinical guidelines. Even though most patients were discharged on DAPT, only 73% with potential indication were on-DAPT 12 months after PCI. A guideline-based recommendation at PCI hospital discharge was highly associated with full persistence with DAPT. Establishing evidence-based, common prescribing criteria across hospitals in the AMI-network would favour adherence and reduce variability

The use of a binary composite endpoint and sample size requirement: influence of endpoints overlap

Although composite endpoints (CE) are common in clinical trials, the impact of the relationship between the components of a binary CE on the sample size requirement (SSR) has not been addressed. We performed a computational study considering 2 treatments and a CE with 2 components: the relevant endpoint (RE) and the additional endpoint (AE). We assessed the strength of the components’ interrelation by the degree of relative overlap between them, which was stratified into 5 groups. Within each stratum, SSR was computed for multiple scenarios by varying the events proportion and the effect of the therapy. A lower SSR using CE was defined as the best scenario for using the CE. In 25 of 66 scenarios the degree of relative overlap determined the benefit of using CE instead of the RE. Adding an AE with greater effect than the RE leads to lower SSR using the CE regardless of the AE proportion and the relative overlap. The influence of overlapping decreases when the effect on RE increases. Adding an AE with lower effect than the RE constitutes the most uncertain situation. In summary, the interrelationship between CE components, assessed by the relative overlap, can help to define the SSR in specific situations and it should be considered for SSR computation.Peer Reviewe

Breast cancer genomes from CHEK2 c.1100delC mutation carriers lack somatic TP53 mutations and display a unique structural variant size distribution profile

Background: CHEK2 c.1100delC was the first moderate-risk breast cancer (BC) susceptibility allele discovered. Despite several genomic, transcriptomic and functional studies, however, it is still unclear how exactly CHEK2 c.1100delC promotes tumorigenesis. Since the mutational landscape of a tumor reflects the processes that have operated on its development, the aim of this study was to uncover the somatic genomic landscape of CHEK2-associated BC. Methods: We sequenced primary BC (pBC) and normal genomes of 20 CHEK2 c.1100delC mutation carriers as well as their pBC transcriptomes. Including pre-existing cohorts, we exhaustively compared CHEK2 pBC genomes to those from BRCA1/2 mutation carriers, those that displayed homologous recombination deficiency (HRD) and ER− and ER+ pBCs, totaling to 574 pBC genomes. Findings were validated in 517 metastatic BC genomes subdivided into the same subgroups. Transcriptome data from 168 ER+ pBCs were used to derive a TP53-mutant gene expression signature and perform cluster analysis with CHEK2 BC transcriptomes. Finally, clinical outcome of CHEK2 c.1100delC carriers was compared with BC patients displaying somatic TP53 mutations in two well-described retrospective cohorts totaling to 942 independent pBC cases. Results: BC genomes from CHEK2 mutation carriers were most similar to ER+ BC genomes and least similar to those of BRCA1/2 mutation carriers in terms of tumor mutational burden as well as mutational signatures. Moreover, CHEK2 BC genomes did not show any evidence of HRD. Somatic TP53 mutation frequency and the size distribution of structural variants (SVs), however, were different compared to ER+ BC. Interestingly, BC genomes with bi-allelic CHEK2 inactivation lacked somatic TP53 mutations and transcriptomic analysis indicated a shared biology with TP53 mutant BC. Moreover, CHEK2 BC genomes had an increased frequency of > 1 Mb deletions, inversions and tandem duplications with peaks at specific sizes. The high chromothripsis frequency among CHEK2 BC genomes appeared, however, not associated with this unique SV size distribution profile. Conclusions: CHEK2 BC genomes are most similar to ER+ BC genomes, but display unique features that may further unravel CHEK2-driven tumorigenesis. Increased insight into this mechanism could explain the shorter survival of CHEK2 mutation carriers that is likely driven by intrinsic tumor aggressiveness rather than endocrine resistance

Clinical Risk Prediction in Patients With Left Ventricular Myocardial Noncompaction

Left ventricular noncompaction (LVNC) is a heterogeneous entity with uncertain prognosis. This study sought to develop and validate a prediction model of major adverse cardiovascular events (MACE) and to identify LVNC cases without events during long-term follow-up. This is a retrospective longitudinal multicenter cohort study of consecutive patients fulfilling LVNC criteria by echocardiography or cardiovascular magnetic resonance. MACE were defined as heart failure (HF), ventricular arrhythmias (VAs), systemic embolisms, or all-cause mortality. A total of 585 patients were included (45 ± 20 years of age, 57% male). LV ejection fraction (LVEF) was 48% ± 17%, and 18% presented late gadolinium enhancement (LGE). After a median follow-up of 5.1 years, MACE occurred in 223 (38%) patients: HF in 110 (19%), VAs in 87 (15%), systemic embolisms in 18 (3%), and 34 (6%) died. LVEF was the main variable independently associated with MACE (P 35% (P < 0.05). A prediction model of MACE was developed using Cox regression, composed by age, sex, electrocardiography, cardiovascular risk factors, LVEF, and family aggregation. C-index was 0.72 (95% confidence interval: 0.67-0.75) in the derivation cohort and 0.72 (95% confidence interval: 0.71-0.73) in an external validation cohort. Patients with no electrocardiogram abnormalities, LVEF ≥50%, no LGE, and negative family screening presented no MACE at follow-up. LVNC is associated with an increased risk of heart failure and ventricular arrhythmias. LVEF is the variable most strongly associated with MACE; however, LGE confers additional risk in patients without severe systolic dysfunction. A risk prediction model is developed and validated to guide management.The project was partially funded by a grant from the Catalan Society of Cardiology (Barcelona, Spain). Hospital Universitario Virgen de la Arrixaca (Murcia, Spain) was supported by a grant from the Foundation Marató TV3 (218/C/2015) (Barcelona, Spain). Hospital Universitario y Politécnico La Fe (Valencia, Spain) was partially supported by Fondo Europeo de Desarrollo Regional (“Unión Europea, Una forma de hacer Europa”) (Madrid, Spain) and the Instituto de Salud Carlos III (La Fe Biobank PT17/0015/ 0043) (Madrid, Spain). Dr Guala was supported by funding from the Spanish Ministry of Science, Innovation and Universities (IJC2018-037349-I) (Madrid, Spain). Dr La Mura was supported by a research grant from the Cardiopath PhD program (Naples, Italy). Prof de la Pompa was supported by grants PID2019-104776RB-I00 and CB16/11/00399 (CIBER CV) from the Spanish Ministry of Science, Innovation and Universities. Dr Bayes-Genis was supported by grants from CIBER Cardiovascular (CB16/11/00403 and 16/11/00420) (Madrid, Spain) and AdvanceCat 2014-2020 (Barcelona, Spain); and has received advisory board and lecture fees from Novartis, Boehringer Ingelheim, Vifor, Roche Diagnostics, and Critical Diagnostics. Dr Pontone has received speaker honorarium and/or institutional research grants from GE Healthcare, Bracco, Boehringer Ingelheim, and HeartFlow. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.S

Proceedings Of The 23Rd Paediatric Rheumatology European Society Congress: Part Two

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