Cost comparison of asthma treatments in 12-week study : caution about matching and short observational follow-up

This review was funded by Observational and Pragmatic Research Institute Pte Ltd.Peer reviewedPublisher PD

Cost-effectiveness of continuous glucose monitoring and intensive insulin therapy for type 1 diabetes

<p>Abstract</p> <p>Background</p> <p>Our objective was to determine the cost-effectiveness of Continuous Glucose Monitoring (CGM) technology with intensive insulin therapy compared to self-monitoring of blood glucose (SMBG) in adults with type 1 diabetes in the United States.</p> <p>Methods</p> <p>A Markov cohort analysis was used to model the long-term disease progression of 12 different diabetes disease states, using a cycle length of 1 year with a 33-year time horizon. The analysis uses a societal perspective to model a population with a 20-year history of diabetes with mean age of 40. Costs are expressed in $US 2007, effectiveness in quality-adjusted life years (QALYs). Parameter estimates and their ranges were derived from the literature. Utility estimates were drawn from the EQ-5D catalogue. Probabilities were derived from the Diabetes Control and Complications Trial (DCCT), the United Kingdom Prospective Diabetes Study (UKPDS), and the Wisconsin Epidemiologic Study of Diabetic Retinopathy. Costs and QALYs were discounted at 3$23,552, resulting in an ICER of approximately $45,033/QALY. For a willingness-to-pay (WTP) of$100,000/QALY, CGM with intensive insulin therapy was cost-effective in 70% of the Monte Carlo simulations.</p> <p>Conclusions</p> <p>CGM with intensive insulin therapy appears to be cost-effective relative to SMBG and other societal health interventions.</p

Prognostic predictors relevant to end-of-life palliative care in Parkinson's disease and related disorders: A systematic review

Parkinson's disease and related disorders (PDRD) are the second most common neurodegenerative disease and a leading cause of death. However, patients with PDRD receive less end-of-life palliative care (hospice) than other illnesses, including other neurologic illnesses. Identification of predictors of PDRD mortality may aid in increasing appropriate and timely referrals. To systematically review the literature for causes of death and predictors of mortality in PDRD to provide guidance regarding hospice/end-of-life palliative care referrals. We searched MEDLINE, PubMed, EMBASE and CINAHL databases (1970-2020) of original quantitative research using patient-level, provider-level or caregiver-level data from medical records, administrative data or survey responses associated with mortality, prognosis or cause of death in PDRD. Findings were reviewed by an International Working Group on PD and Palliative Care supported by the Parkinson's Foundation. Of 1183 research articles, 42 studies met our inclusion criteria. We found four main domains of factors associated with mortality in PDRD: (1) demographic and clinical markers (age, sex, body mass index and comorbid illnesses), (2) motor dysfunction and global disability, (3) falls and infections and (4) non-motor symptoms. We provide suggestions for consideration of timing of hospice/end-of-life palliative care referrals. Several clinical features of advancing disease may be useful in triggering end-of-life palliative/hospice referral. Prognostic studies focused on identifying when people with PDRD are nearing their final months of life are limited. There is further need for research in this area as well as policies that support need-based palliative care for the duration of PDRD

Cost-Effectiveness of Asthma Step-Up Therapy as an Increased Dose of Extrafine-Particle Inhaled Corticosteroid or Add-On Long-Acting Beta2-Agonist

The analyses were funded by an unrestricted grant from Teva Pharmaceuticals Limited of Petach Tikva, Israel. Access to data from the Optimum Patient Care Research Database was co-funded by Research in Real-Life Ltd (RiRL), Cambridge, UK. All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this manuscript, take responsibility for the integrity of the work as a whole, and have given final approval to the version to be published. The authors thank Julie von Ziegenweidt for assistance with data extraction.Peer reviewedPublisher PD

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

The “E” in cost-effectiveness analyses. A case study of omalizumab efficacy and effectiveness for cost-effectiveness analysis evidence

This article is a call for increased use of real-world evidence in health technology assessment and related policy and decision making. There is currently a disconnect between evidence used to guide regulatory approval of therapies and evidence used to inform therapeutic coverage and reimbursement decisions. Public and private payers need to understand not only whether an intervention works but also whether it offers good value compared with licensed alternatives (not placebo) as they are used in the real-world practice and population (not in a controlled trial environment). Addressing such concerns requires evidence to be drawn from a wide range of study designs, but with consideration and weighting given to their relative strengths and weaknesses, as well as their position on the pragmatic–explanatory (i.e., effectiveness–efficacy) continuum. The potential impact of using different types of evidence to inform cost-effectiveness analysis (CEA) is discussed for omalizumab, comparing and contrasting a CEA model informed by an omalizumab efficacy trial to a CEA model drawing primarily on evidence from effectiveness observational studies of omalizumab. There was reasonable agreement between the two omalizumab CEA models, although the incremental cost-effectiveness ratio generated by the effectiveness observational study-driven model was more favorable for omalizumab. Health technology assessment bodies and payers must use their judgment to determine which components of efficacy-based and effectiveness-based CEA evidence are most closely aligned with their goals. For each CEA evidence component, perhaps the two E’s form bounds of the truth as well as a fuller picture of the uncertainty surrounding the truth