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Background This meta-analysis evaluated the real-world effectiveness of onabotulinumtoxinA (BOTOX®), the first preventive treatment FDA-approved specifically for chronic migraine in 2010. Methods We systematically reviewed onabotulinumtoxinA observational data in chronic migraine published between 1 January 2010 and 31 March 2021. Random-effects models evaluated available data for primary and secondary endpoints defined in onabotulinumtoxinA pivotal trials at approximately 24 weeks and 52 weeks. Results Of the 44 full-text eligible studies (29 prospective; 13 retrospective; 2 other), seven evaluated change from baseline (mean[confidence interval]) at ∼24 weeks and ∼52 weeks, respectively, for onabotulinumtoxinA in: number of headache days/month: (–10.64 [–12.31, –8.97]; –10.32 [−14.92, –5.73]); number of days of acute headache pain medication intake per month (–7.40 [–13.04, –1.77]; overlapping CIs at 52 weeks); total Headache Impact Test-6 score (–11.70 [–13.86, –9.54]); –11.80 [14.70, –8.90]); and Migraine-Specific Quality-of-Life v2.1 score (MSQ; 23.60 [CI: 21.56, 25.64]; 30.90 [CI: 28.29, 33.51]). At ∼24 weeks onabotulinumtoxinA showed total Migraine Disability Assessment score of 44.74 [28.50, 60.99] and ≥50% reduction in migraine days response rate of 46.57% [29.50%, 63.65%]. A sensitivity analysis at study-end suggested durability of onabotulinumtoxinA effectiveness on MSQ. Conclusion The meta-analysis reflecting real-world practice broadly corroborated with evidence from pivotal and long-term open-label studies of onabotulinumtoxinA in chronic migraine preventive treatment.

BACKGROUND AND AIMS Finerenone (FIN: an oral, nonsteroidal mineralocorticoid receptor antagonist) and canagliflozin (CAN: a sodium-glucose cotransporter 2 inhibitor) demonstrated cardiorenal efficacy in patients with chronic kidney disease and type 2 diabetes on top of renin–angiotensin system blockade in phase III placebo-controlled studies (FIDELIO-DKD [NCT02540993] for FIN; CREDENCE [NCT02065791] for CAN) [3,2]. In the absence of head-to-head studies, we assessed FIN and CAN in this patient population while appropriately accounting for meaningful differences between the trials. METHOD We performed an anchored matching-adjusted indirect comparison (MAIC), with placebo (PBO) as a common comparator, to generate measures of efficacy and safety while accounting for differences between the two study populations [3]. Individual patient-level data from FIDELIO-DKD and published data from CREDENCE were used [1,[2]. Weights were calculated and assigned to each patient in FIDELIO-DKD so the weighted population of FIDELIO-DKD matched that of CREDENCE for selected baseline characteristics, e.g. mean estimated glomerular filtration rate (eGFR; 44.3 and 56.2 mL/min/1.73 m2 in FIDELIO-DKD and CREDENCE, respectively). Weights were obtained from a logistic regression model of the odds of enrolment in CREDENCE and FIDELIO-DKD for baseline characteristics believed to be effect modifiers. Hazard ratios (HRs) with 95% confidence intervals (CIs) comparing FIN and PBO for time-to-event endpoints were estimated based on the weighted population of FIDELIO-DKD. HRs with 95% CIs comparing FIN and CAN were then calculated from results of the previous step and published data from CREDENCE [2]. This analysis evaluated the cardiorenal composite endpoint from CREDENCE (kidney failure [dialysis, transplantation or sustained eGFR RESULTS Calculation of the weights for the FIDELIO-DKD population (N = 5674) resulted in an effective sample size of 1288 for the pseudo-population formed by the weighting to compare with the CREDENCE population (N = 4401). For the cardiorenal composite endpoint, the HR (95% CI) for FIN and PBO based on reweighted FIDELIO-DKD data was 0.72 (0.59–0.90) and the MAIC-based HR (95% CI) for FIN and CAN was 1.03 (0.79–1.35) (P = 0.802). For hyperkalaemia, the MAIC-based HR (95% CI) for FIN and CAN was 2.25 (1.67–3.03) (P CONCLUSION The MAIC for FIDELIO-DKD and CREDENCE enabled more robust assessment of FIN and CAN when a similar patient population was considered. There was no evidence of a significant difference between FIN and CAN in the cardiorenal composite endpoint as assessed in CREDENCE. These results are consistent with a recent analysis using a different payer-accepted method that also accounted for differences between the FIDELIO-DKD and CREDENCE inclusion criteria and endpoints [3,4].

Objectives This review intends to provide an overview of revealed preferences of decision-makers for recommendations of cancer drugs in health technology assessment (HTA) among the different agencies. Methods A systematic literature search was performed in MEDLINE and EMBASE databases from inception to July 2020. The studies were eligible for inclusion if they conducted a quantitative analysis of HTA’s previous decisions for cancer drugs. The factors with p-values below the significance level of .05 were considered as the statistically significant factors for HTA decisions. Results A total of nine studies for six agencies in Australia, Belgium, France, South Korea, the UK, and Canada were eligible to be included. From the univariable analysis, improvements in clinical outcomes and cost-effectiveness were found as significant factors for the agencies in Belgium, South Korea, and Canada. From the multivariable analysis, cost-effectiveness was found as a positive factor for the agencies in the UK, South Korea, and Canada. Few factors related to characteristics of disease and technology were found to be significant among the included agencies. Conclusions Despite the different drug reimbursement systems and the socioeconomic situations, cost-effectiveness and/or improvement on clinical outcomes seemed to be the most important factors for recommendations of cancer drugs among the agencies.

Multicriteria decision analysis (MCDA) represents a promising method for benefit-risk assessment. Our goal was to develop features of pragmatic MCDA (EVIDEM [Evidence and Value: Impact on DEcisionMaking]) addressing real-life regulatory decision-making needs, incorporate advanced pharmacoepidemiology, and test the resulting benefit-risk framework using a case study.The Intervention Outcomes domain of EVIDEM was transformed into a generic benefit-risk framework including clinical efficacy, patient-reported outcomes, and adverse event (AE) criteria. The concept of relative benefit-risk balance (RBRB) was developed for comparability across products and therapeutic areas and over time. Evidence matrix was designed to include most relevant data from trials, observational studies, and models, including Bayesian and longitudinal modeling. The framework was tested with a panel of stakeholders using efalizumab for psoriasis as retrospective case study. Uncertainty was explored.The MCDA benefit-risk tree was adapted with psoriasis-specific subcriteria. Panelists assigned similar weights to benefits (0.48; SD, 0.20-0.70) and risks (0.52; SD, 0.10-0.60), with large variations reflecting diverse perspectives. Panelist scores reflected higher efficacy versus placebo, lower efficacy versus active comparators, and serious and fatal AEs identified postlicensing. Efalizumab's RBRB was positive at licensing in 2004 (0.29, scale -1 to +1) and ranged from -0.41 (vs active comparators) to 0.01 (vs placebo) in 2009, when its market authorization was withdrawn. Retesting indicated good reproducibility. Panelists acknowledged good face validity and the importance of criteria beyond benefit-risk in real-life assessments.The approach allows quantification and visualization of benefit-risk over time and across comparators. Combination of pragmatic MCDA designed to integrate criteria beyond benefit-risk and advanced statistics supports application of MCDA to further accountable benefit-risk assessments for real-life decision making.

The need to support clinical decision making and cost-effectiveness analyses in medicine, despite a dearth of head-to-head treatment comparisons, has encouraged the development of methods enabling indirect comparisons of treatment alternatives, including network meta-analysis (NMA). Valid application of NMA requires close similarity of compared trials, including their design, patient characteristics, and methods of diagnosis and symptomatic assessment. When biological or other objective measures of outcomes are not available, as is the case in psychiatric disorders, subtle differences in characteristics of trials or participants may lead to unrecognized incoherence within a network and thus to inconsistent results. By considering comparative-efficacy analyses of psychotropic drugs in major psychiatric disorders as working examples, we underscore the risks of violating the fundamental transitivity assumption in the context of NMA and suggest precautions for creating a coherent network. We conclude that with thoughtful and critical application, NMA can add useful information concerning the comparative benefits, risks, and costs of specific treatments in psychiatry.

A graph G is called ( H ; k ) -vertex stable if G contains a subgraph isomorphic to H even after removing any k of its vertices. By stab ( H ; k ) we denote the minimum size among the sizes of all ( H ; k ) -vertex stable graphs. In this paper we present a general result concerning ( H ; 1 ) -vertex stable graphs. Namely, for an arbitrary graph H we give a lower bound for stab ( H ; 1 ) in terms of the order, connectivity and minimum degree of H . The bound is nearly sharp.

Given a convex subset D of a vector space and a constant t ∈ (0,1) , a function f : D → R is called t -quasiconvex if, for all x,y ∈ D , f (tx+(1− t)y) max{ f (x), f (y)}; f is called strictly t -quasiconvex if, for all x,y ∈ D such that f (x) = f (y) , f (tx+(1− t)y) < max{ f (x), f (y)}. The following Kuhn–type theorem is proved: If f is t -quasiconvex and strictly t -quasiconvex then it is (1/2) -quasiconvex and strictly (1/2) -quasiconvex. It is also shown that lower semicontinuous strictly t -quasiconvex functions are quasiconvex, which generalizes the well-known Karamardian’s theorem. Mathematics subject classification (2000): Primary 26A51, 39B62.

A distance magic labeling of a graph G = (V,E) with |V | = n is a bijection ℓ from V to the set {1, . . . , n} such that the weight w(x) = ∑y∈NG(x) ℓ(y) of every vertex x ∈ V is equal to the same element μ, called the magic constant. In this paper, we study unions of distance magic graphs as well as some properties of such graphs.