ObjectiveSince 2004, the National Institute of Health and Clinical Excellence (NICE) has required manufacturers to conduct a probabilistic sensitivity analysis (PSA) in their technology appraisals. The objective of this review is to assess the cost-effectiveness of different technology appraisals and compare them with the actual decision made by the NICE based on PSA.MethodsThe search term ‘probabilistic sensitivity analysis’ was used on the NICE home page (25 January 2012). The appraisals identified in the search were assessed and subjected to further review, if a probability of being cost-effective was provided, regardless of the threshold indicated. If several probabilities were provided, the number provided by the evidence review group was used. If several scenarios were presented, the base case scenario was chosen. Finally, the probabilities of being cost-effective were compared with the actual decision made, which could result in two outcomes: recommended or not recommended.ResultsA total of 31 assessments were included for the final review. The results were plotted on a graph to illustrate whether there was a relationship between the PSA outcomes and the final recommendation. The assessments were ranked according to their probability of being cost-effective.ConclusionA higher probability of a technology being cost-effective was correlated with more positive decision-making. There appeared to be a clear threshold at which technologies with a 40% certainty of being cost-effective tended to be recommended, whereas those below the threshold were not recommended. The reports suggested that the incremental cost-effectiveness ratios (ICER) estimate was not a robust driver of decision-making. A NICE applicant should pay increased attention to the PSA in addition to the ICER estimate.

AimTo identify a potential efficacy–effectiveness gap and possible explanations (drivers of effectiveness) for differences between results of randomized controlled trials (RCTs) and observational studies investigating glucose-lowering drugs.MethodsA systematic literature review was conducted in English language articles published between 1 January, 2000 and 31 January, 2015 describing either RCTs or observational studies comparing glucagon-like peptide-1 analogs (GLP-1) with insulin or comparing dipeptidyl peptidase-4 inhibitors (DPP-4i) with sulfonylurea, all with change in glycated hemoglobin (HbA1c) as outcome. Medline, Embase, Current Content, and Biosis were searched. Information on effect estimates, baseline characteristics of the study population, publication year, study duration, and number of patients, and for observational studies, characteristics related to confounding adjustment and selection- and information bias were extracted.ResultsFrom 312 hits, 11 RCTs and 7 observational studies comparing GLP-1 with insulin, and from 474 hits, 16 RCTs and 4 observational studies comparing DPP-4i with sulfonylurea were finally included. No differences were observed in baseline characteristics of the study populations (age, sex, body mass index, time since diagnosis of type 2 diabetes mellitus, and HbA1c) or effect sizes across study designs. Mean effect sizes ranged from −0.43 to 0.91 and from −0.80 to 1.13 in RCTs and observational studies, respectively, comparing GLP-1 with insulin, and from −0.13 to 2.70 and −0.20 to 0.30 in RCTs and observational studies, respectively, comparing DPP-4i and sulfonylurea. Generally, the identified observational studies held potential flaws with regard to confounding adjustment and selection- and information bias.ConclusionsNeither potential drivers of effectiveness nor an efficacy–effectiveness gap were identified. However, the limited number of studies and potential problems with confounding adjustment, selection- and information bias in the observational studies, may have hidden a true efficacy-effectiveness gap.

BackgroundChanneling bias may occur when a newly marketed drug and an established drug, despite similar indications, are prescribed to patients with different prognostic characteristics (ie, confounding).AimTo investigate channeling bias and its impact on relative effectiveness of glucagon-like peptide-1 (GLP-1) analogs versus basal insulin and dipeptidyl peptidase-4 inhibitors (DPP-4i) versus sulfonylurea.MethodsIn the UK Clinical Practice Research Datalink, patients with type 2 diabetes initiating treatment between 2006 and 2015 were included. Analyses were stratified by years since first prescription of GLP-1 and DPP-4i, respectively. The characteristics of GLP-1 versus insulin and DPP-4i versus sulfonylurea initiators were compared over time. After propensity score matching, the relative effectiveness regarding 6-month changes in glycated hemoglobin (HbA1c) and body weight was estimated.ResultsIn total, 8,398 GLP-1, 14,807 insulin, 24,481 DPP-4i, and 33,505 sulfonylurea initiators were identified. No major channeling was observed. Considerable overlap in distributions of characteristics allowed for propensity score-matched analyses. Relative effectiveness was similar across time. The overall relative effect of GLP-1 versus insulin showed no difference for HbA1c and relative increase in body weight (3.57 kg [95% confidence interval {CI}: 3.21, 3.92]) for insulin. The overall relative effect of DPP-4i versus sulfonylurea showed relative decrease in HbA1c (−0.34% [95% CI: −0.38, −0.30]) and increase in body weight (1.58 kg [95% CI: 1.38, 1.78]) for sulfonylurea.ConclusionNo major channeling was identified in the investigated glucose-lowering drugs. Relative effectiveness could be estimated already in the first year after launch and was consistent in the years thereafter.

clinical trials. These DOE should be explored to better design clinical trials. Objectives:To identify effect-modifiers of antipsychotic drugs, in schizophrenia treatment.Methods: Data were retrieved from the CGS observational cohort study, including 1859 schizophrenia inpatients and outpatients aged 15-65 years old through 177 centres in France. Patients were followed-up at 3, 6, 9 and 12 months.Patients who initiated or switched APD were identified and schizophrenia symptoms evolution was measured 3 to 6 months later, using the BPRS-18 scale (∆BPRS).First, potential DOE of APD were identified through a focused literature search, which was reviewed by 3 schizophrenia specialized psychiatrists. Five DOE were short-listed: (1) shorter duration of illness, (2) higher level of negative symptoms, (3) poor adherence, (4) cannabis/drug use and (5) tobacco use.Effect modification was assessed using sub-group analyses, with comparisons of the ∆BPRS in the 2 strata of each DOE. Two-sided Welch t-tests were used with a "non-conservative" type-I error α = 0.2. Multivariate analyses were not performed due to limited sample size.Results: Out of 1859 schizophrenia patients, 116 patients initiated drug B, 272 patients initiated drug D and 204 patients initiated drug K. Other drugs were initiated by too few patients. The mean decreases in BPRS were: -7.2 points (SD = 16.3) in "drug B initiators", -7.5 points (SD = 15.3) in "drug D initiators" -3.9 points (SD = 14.1) in "drug K initiators". The level of symptoms improvement was higher in patients with a "higher level of negative symptoms" for all drugs (p<0.012) and "poorer adherence", for drugs D and K (p<0.013). The level of symptoms improvement was also better in patients who did not smoke, however not significantly. Cannabis use was not an effect-modifier, in all drugs. Conclusions:Overall, "adherence", "tobacco smoking" and "negative symptoms" may be drivers of effectiveness. These factors should be adequately captured and explored in pre-launch clinical trials to avoid an efficacy-effectiveness gap. Background: Beneficial effects of drugs can be divided into efficacy and effectiveness. An understanding of the efficacy-effectiveness gap is important for patients, health care professionals, payers, regulators and the pharmaceutical industry to provide effective treatments. A Systematic Literature Review on the Efficacy-Effectiveness Gap: Comparison of Randomized Controlled Trials and Observational Studies of Glucose-Lowering Drugs

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