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Despite the known contributions of genes, genetic-guided pharmacotherapy has not been routinely implemented for venous thromboembolism (VTE). To examine evidence on cost-effectiveness of genetic-guided pharmacotherapy for VTE, we searched six databases, websites of four HTA agencies and citations, with independent double-reviewers in screening, data extraction, and quality rating. The ten eligible studies, all model-based, examined heterogeneous interventions and comparators. Findings varied widely; testing was cost-saving in two base-cases, cost-effective in four, not cost-effective in three, dominated in one. Of 22 model variables that changed decisions about cost-effectiveness, effectiveness/relative effectiveness of the intervention was the most frequent, albeit of poor quality. Studies consistently lacked details on the provision of interventions and comparators as well as on model development and validation. Besides improving the reporting of interventions, comparators, and methodological details, future economic evaluations should examine strategies recommended in guidelines and testing key model variables for decision uncertainty, to advise clinical implementations.

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ObjectivesBiologicals play a crucial role in managing some of the rheumatological diseases, thus it is important for clinicians, healthcare institutions and policy-makers to understand why biologicals are initiated or refused so as to make better decisions to improve patients’ disease outcomes. Although there have been many studies investigating factors associated with the initiation of biologicals for patients with rheumatological conditions, there have been no systematic reviews that provide a comprehensive summary. We aim to provide a summary of factors associated with biologicals' initiation for patients with rheumatological conditions.MethodsWe performed a literature search in PubMed, Embase and PsycINFO. We identified and screened studies according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Factors were presented according to patient, disease-related, therapy-related, healthcare team-related and system in-place factors.ResultsA total 1755 articles were reviewed and 24 articles were found to be relevant to our objective. Forty four factors reviewed were placed into five main categories: patient factors (n=13); disease-related factors (n=11); therapy-related factors (n=7); healthcare team-related factors (n=4) and system in-place-related factors (n=9). The factors studied by the published papers found to be associated with decisions to initiate biologicals varied widely.ConclusionForty two factors of five different categories were found to be associated with biologicals' initiation for patients with rheumatological conditions. Clinicians need to be mindful of the complex nature of these factors to optimise therapy of patients with rheumatological conditions. Healthcare institutions and policy- makers ought to be aware of any potential barriers to successful biologicals' treatment and address them accordingly.

Background: Medication adherence measures are often dichotomized to classify patients into those with good or poor adherence using a cut-off value ⩾80%, but this cut-off may not be universal across diseases or medication classes. This study aimed to examine the cut-off value that optimally distinguish good and poor adherence by using the medication possession ratio (MPR) and proportion of days covered (PDC) as adherence measures and glycated hemoglobin (HbA1c) as outcome measure among type 2 diabetes mellitus (T2DM) patients.Method: We used pharmacy dispensing data of 1461 eligible T2DM patients from public primary care clinics in Malaysia treated with oral antidiabetic drugs between January 2018 and May 2019. Adherence rates were calculated during the period preceding the HbA1c measurement. Adherence cut-off values for the following conditions were compared: adherence measure (MPR versusPDC), assessment period (90-day versus180-day), and HbA1c target (⩽7.0% versus⩽8.0%).Results: The optimal adherence cut-offs for MPR and PDC in predicting HbA1c ⩽7.0% ranged between 86.1% and 98.3% across the two assessment periods. In predicting HbA1c ⩽8.0%, the optimal adherence cut-offs ranged from 86.1% to 92.8%. The cut-off value was notably higher with PDC as the adherence measure, shorter assessment period, and a stricter HbA1c target (⩽7.0%) as outcome.Conclusion: We found that optimal adherence cut-off appeared to be slightly higher than the conventional value of 80%. The adherence thresholds may vary depending on the length of assessment period and outcome definition but a reasonably wise cut-off to distinguish good versuspoor medication adherence to be clinically meaningful should be at 90%.

Background: The aim of our study was to synthesize evidence on the occurrence of malignancy in spondyloarthritis (SpA), from randomized controlled trials (RCTs) comparing biologics with non-biologics and biologics to each other.Methods: We systematically searched Medline, Cochrane Library, EMBASE, Scopus and ClinicalTrials.gov from inception until 31 October 2018. RCTs with ⩾24-week follow-up were included. We extracted data using standardized forms and assessed the risk of bias using the Cochrane Risk of Bias Tool. We performed pair-wise meta-analyses and network meta-analyses to compare the risk of malignancy for each biologics class and SpA type. We reported the Peto odds ratio (OR) of any malignancy along with 95% confidence intervals (95% CI). Bayesian posterior probabilities comparing risk of malignancy of each biologic class with non-biologics were computed as supplementary measures.Results: Fifty-four trials were included; most (44/54) had follow-up <1 year. Among 14,245 patients, 63 developed a malignancy. While most Peto ORs were >1, they had wide 95% CI and p>0.05. The overall Peto OR comparing biologics with non-biologics was 1.42 (95% CI 0.80–2.53). Only interleukin-17 inhibitors in peripheral SpA had p<0.05 (Peto OR 2.77, 95% CI 1.07–7.13); the posterior probability that the risk was higher than non-biologics was 98%. Stratified analyses revealed no consistent trend by prior exposure to biologics, duration of follow-up, study quality, study-arm crossover, analytical approaches and type of malignancy.Conclusions: Our findings indicate no overall elevated risk of malignancy with biologics in SpA. As our meta-analyses are unable to conclude on the long-term risk, long-term pharmacovigilance of biologics in SpA may still be warranted.