Should beta-blocker therapy be reduced or withdrawn after an episode of decompensated heart failure? Results from COMET.

BACKGROUND: It is unclear whether beta-blocker therapy should be reduced or withdrawn in patients who develop acute decompensated heart failure (HF). We studied the relationship between changes in beta-blocker dose and outcome in patients surviving a HF hospitalisation in COMET. METHODS: Patients hospitalised for HF were subdivided on the basis of the beta-blocker dose administered at the visit following hospitalisation, compared to that administered before. RESULTS: In COMET, 752/3029 patients (25%, 361 carvedilol and 391 metoprolol) had a non-fatal HF hospitalisation while on study treatment. Of these, 61 patients (8%) had beta-blocker treatment withdrawn, 162 (22%) had a dose reduction and 529 (70%) were maintained on the same dose. One-and two-year cumulative mortality rates were 28.7% and 44.6% for patients withdrawn from study medication, 37.4% and 51.4% for those with a reduced dosage (n.s.) and 19.1% and 32.5% for those maintained on the same dose (HR,1.59; 95%CI, 1.28-1.98; p<0.001, compared to the others). The result remained significant in a multivariable model: (HR, 1.30; 95%CI, 1.02-1.66; p=0.0318). No interaction with the beneficial effects of carvedilol, compared to metoprolol, on outcome was observed (p=0.8436). CONCLUSIONS: HF hospitalisations are associated with a high subsequent mortality. The risk of death is higher in patients who discontinue beta-blocker therapy or have their dose reduced. The increase in mortality is only partially explained by the worse prognostic profile of these patients

Comparison of carvedilol and metoprolol on clinical outcomes in patients with chronic heart failure in the Carvedilol Or Metoprolol European Trial (COMET): randomised controlled trial

BACKGROUND: Beta blockers reduce mortality in patients who have chronic heart failure, systolic dysfunction, and are on background treatment with diuretics and angiotensin-converting enzyme inhibitors. We aimed to compare the effects of carvedilol and metoprolol on clinical outcome. METHODS: In a multicentre, double-blind, and randomised parallel group trial, we assigned 1511 patients with chronic heart failure to treatment with carvedilol (target dose 25 mg twice daily) and 1518 to metoprolol (metoprolol tartrate, target dose 50 mg twice daily). Patients were required to have chronic heart failure (NYHA II-IV), previous admission for a cardiovascular reason, an ejection fraction of less than 0.35, and to have been treated optimally with diuretics and angiotensin-converting enzyme inhibitors unless not tolerated. The primary endpoints were all-cause mortality and the composite endpoint of all-cause mortality or all-cause admission. Analysis was done by intention to treat. FINDINGS: The mean study duration was 58 months (SD 6). The mean ejection fraction was 0.26 (0.07) and the mean age 62 years (11). The all-cause mortality was 34% (512 of 1511) for carvedilol and 40% (600 of 1518) for metoprolol (hazard ratio 0.83 [95% CI 0.74-0.93], p=0.0017). The reduction of all-cause mortality was consistent across predefined subgroups. The composite endpoint of mortality or all-cause admission occurred in 1116 (74%) of 1511 on carvedilol and in 1160 (76%) of 1518 on metoprolol (0.94 [0.86-1.02], p=0.122). Incidence of side-effects and drug withdrawals did not differ by much between the two study groups. INTERPRETATION: Our results suggest that carvedilol extends survival compared with metoprolo

Expert consensus document: A 'diamond' approach to personalized treatment of angina.

In clinical guidelines, drugs for symptomatic angina are classified as being first choice (β-blockers, calcium-channel blockers, short-acting nitrates) or second choice (ivabradine, nicorandil, ranolazine, trimetazidine), with the recommendation to reserve second-choice medications for patients who have contraindications to first-choice agents, do not tolerate them, or remain symptomatic. No direct comparisons between first-choice and second-choice treatments have demonstrated the superiority of one group of drugs over the other. Meta-analyses show that all antianginal drugs have similar efficacy in reducing symptoms, but provide no evidence for improvement in survival. The newer, second-choice drugs have more evidence-based clinical data that are more contemporary than is available for traditional first-choice drugs. Considering some drugs, but not others, to be first choice is, therefore, difficult. Moreover, double or triple therapy is often needed to control angina. Patients with angina can have several comorbidities, and symptoms can result from various underlying pathophysiologies. Some agents, in addition to having antianginal effects, have properties that could be useful depending on the comorbidities present and the mechanisms of angina, but the guidelines do not provide recommendations on the optimal combinations of drugs. In this Consensus Statement, we propose an individualized approach to angina treatment, which takes into consideration the patient, their comorbidities, and the underlying mechanism of disease

Meta-analysis of individual-patient data from EVAR-1, DREAM, OVER and ACE trials comparing outcomes of endovascular or open repair for abdominal aortic aneurysm over 5 years

Background: The erosion of the early mortality advantage of elective endovascular aneurysm repair (EVAR) compared with open repair of abdominal aortic aneurysm remains without a satisfactory explanation. Methods: An individual-patient data meta-analysis of four multicentre randomized trials of EVAR versus open repair was conducted to a prespecified analysis plan, reporting on mortality, aneurysm-related mortality and reintervention. Results: The analysis included 2783 patients, with 14 245 person-years of follow-up (median 5·5 years). Early (0–6 months after randomization) mortality was lower in the EVAR groups (46 of 1393 versus 73 of 1390 deaths; pooled hazard ratio 0·61, 95 per cent c.i. 0·42 to 0·89; P = 0·010), primarily because 30-day operative mortality was lower in the EVAR groups (16 deaths versus 40 for open repair; pooled odds ratio 0·40, 95 per cent c.i. 0·22 to 0·74). Later (within 3 years) the survival curves converged, remaining converged to 8 years. Beyond 3 years, aneurysm-related mortality was significantly higher in the EVAR groups (19 deaths versus 3 for open repair; pooled hazard ratio 5·16, 1·49 to 17·89; P = 0·010). Patients with moderate renal dysfunction or previous coronary artery disease had no early survival advantage under EVAR. Those with peripheral artery disease had lower mortality under open repair (39 deaths versus 62 for EVAR; P = 0·022) in the period from 6 months to 4 years after randomization. Conclusion: The early survival advantage in the EVAR group, and its subsequent erosion, were confirmed. Over 5 years, patients of marginal fitness had no early survival advantage from EVAR compared with open repair. Aneurysm-related mortality and patients with low ankle : brachial pressure index contributed to the erosion of the early survival advantage for the EVAR group. Trial registration numbers: EVAR-1, ISRCTN55703451; DREAM (Dutch Randomized Endovascular Aneurysm Management), NCT00421330; ACE (Anévrysme de l'aorte abdominale, Chirurgie versus Endoprothèse), NCT00224718; OVER (Open Versus Endovascular Repair Trial for Abdominal Aortic Aneurysms), NCT00094575

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk

BACKGROUND: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). RESULTS: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer

BACKGROUND: Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer. METHODS: In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients. RESULTS: The most significant global associations for all genes in the pathway were seen in endometrioid (p = 0.082) and clear cell (p = 0.083), with the most significant gene level association seen with TGFBR2 (p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 (p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA (p = 0.035, endometrioid and mucinous), LGALS1 (p = 0.03, mucinous), STAT5B (p = 0.022, clear cell), TGFBR1 (p = 0.021 endometrioid) and TGFBR2 (p = 0.017 and p = 0.025, endometrioid and mucinous, respectively). CONCLUSIONS: Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients

Analysis and design of randomised clinical trials involving competing risks endpoints

<p>Abstract</p> <p>Background</p> <p>In randomised clinical trials involving time-to-event outcomes, the failures concerned may be events of an entirely different nature and as such define a classical competing risks framework. In designing and analysing clinical trials involving such endpoints, it is important to account for the competing events, and evaluate how each contributes to the overall failure. An appropriate choice of statistical model is important for adequate determination of sample size.</p> <p>Methods</p> <p>We describe how competing events may be summarised in such trials using cumulative incidence functions and Gray's test. The statistical modelling of competing events using proportional cause-specific and subdistribution hazard functions, and the corresponding procedures for sample size estimation are outlined. These are illustrated using data from a randomised clinical trial (SQNP01) of patients with advanced (non-metastatic) nasopharyngeal cancer.</p> <p>Results</p> <p>In this trial, treatment has no effect on the competing event of loco-regional recurrence. Thus the effects of treatment on the hazard of distant metastasis were similar via both the cause-specific (unadjusted <it>csHR </it>= 0.43, 95% CI 0.25 - 0.72) and subdistribution (unadjusted <it>subHR </it>0.43; 95% CI 0.25 - 0.76) hazard analyses, in favour of concurrent chemo-radiotherapy followed by adjuvant chemotherapy. Adjusting for nodal status and tumour size did not alter the results. The results of the logrank test (<it>p </it>= 0.002) comparing the cause-specific hazards and the Gray's test (<it>p </it>= 0.003) comparing the cumulative incidences also led to the same conclusion. However, the subdistribution hazard analysis requires many more subjects than the cause-specific hazard analysis to detect the same magnitude of effect.</p> <p>Conclusions</p> <p>The cause-specific hazard analysis is appropriate for analysing competing risks outcomes when treatment has no effect on the cause-specific hazard of the competing event. It requires fewer subjects than the subdistribution hazard analysis for a similar effect size. However, if the main and competing events are influenced in opposing directions by an intervention, a subdistribution hazard analysis may be warranted.</p