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Tuesday, May 28, 2019

PharmacoEconomics

Correction to: Venetoclax for Treating Chronic Lymphocytic Leukaemia: An Evidence Review Group Perspective of a NICE Single Technology Appraisal

Open Access This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.



Correction to: The Impact of Hospital Costing Methods on Cost-Effectiveness Analysis: A Case Study

The Open Access license, which previously read.



Cost-Effectiveness Analysis in the Context of US Commercial Health Insurance


Pirfenidone for Treating Idiopathic Pulmonary Fibrosis: An Evidence Review Group Perspective of a NICE Single Technology Appraisal

Abstract

The National Institute for Health and Care Excellence (NICE) published guidance on the use of pirfenidone (Esbriet®, Roche) for the treatment of mild to moderate idiopathic pulmonary fibrosis (IPF) in 2013. NICE decided to review existing guidance following publication of an additional clinical trial, and invited the manufacturer of pirfenidone to submit evidence of its clinical and cost effectiveness for the treatment of mild to moderate IPF when compared with best supportive care (BSC) or nintedanib; nintedanib was a comparator only for moderate IPF. An independent Evidence Review Group (ERG) critiqued the company submission and this paper summarises their report and subsequent NICE guidance. The key clinical effectiveness evidence was based on three randomised controlled trials (RCTs) and an open-label extension study. Supportive data were provided from two additional RCTs conducted in Japan, while one additional open-label study was included for safety outcomes. Meta-analysis of the three key RCTs found pirfenidone to be effective at reducing disease progression compared with placebo, but statistically significant differences were not identified in all of the RCTs. A statistically significant reduction in all-cause mortality was only demonstrated when pooling data across studies. The treatment effects of pirfenidone and nintedanib were broadly similar, based on an indirect comparison using network meta-analysis, although they have slightly different adverse event profiles. There remains considerable uncertainty in the cost-effectiveness estimates for pirfenidone versus BSC, particularly due to uncertainty regarding the duration of treatment effect and the method used to implement the stopping rule within the economic model.



A Flexible Open-Source Decision Model for Value Assessment of Biologic Treatment for Rheumatoid Arthritis

Abstract

Objective

The nature of model-based cost-effectiveness analysis can lead to disputes in the scientific community. We propose an iterative and collaborative approach to model development by presenting a flexible open-source simulation model for rheumatoid arthritis (RA), accessible to both technical and non-technical end-users.

Methods

The RA model is a discrete-time individual patient simulation with 6-month cycles. Model input parameters were estimated based on currently available evidence and treatment effects were obtained with Bayesian network meta-analysis techniques. The model contains 384 possible model structures informed by previously published models. The model consists of the following components: (i) modifiable R and C++ source code available in a GitHub repository; (ii) an R package to run the model for custom analyses; (iii) detailed model documentation; (iv) a web-based user interface for full control over the model without the need to be well-versed in the programming languages; and (v) a general audience web-application allowing those who are not experts in modeling or health economics to interact with the model and contribute to value assessment discussions.

Results

A primary function of the initial version of RA model is to help understand and quantify the impact of parameter uncertainty (with probabilistic sensitivity analysis), structural uncertainty (with multiple competing model structures), the decision framework (cost-effectiveness analysis or multi-criteria decision analysis), and perspective (healthcare or limited societal) on estimates of value.

Conclusion

In order for a decision model to remain relevant over time it needs to evolve along with its supporting body of clinical evidence and scientific insight. Multiple clinical and methodological experts can modify or contribute to the RA model at any time due to its open-source nature.



Fulvestrant for Untreated Hormone-Receptor Positive Locally Advanced or Metastatic Breast Cancer: An Evidence Review Group Perspective of a NICE Single Technology Appraisal

Abstract

Clinical and cost-effectiveness evidence on fulvestrant for untreated hormone-receptor positive locally advanced or metastatic breast cancer was submitted to the single technology appraisal process of the National Institute for Health and Care Excellence by the manufacturer of fulvestrant. The Southampton Health Technology Assessments Centre was commissioned by the National Institute for Health and Care Excellence as an independent Evidence Review Group to critique the company's submitted evidence. Fulvestrant was compared directly with anastrozole in two randomised controlled trials and was compared indirectly by means of a network meta-analysis with anastrozole, letrozole and tamoxifen. This article summarises the Evidence Review Group's review of the company's submission and summarises the guidance the National Institute for Health and Care Excellence Appraisal Committee issued in January 2018. The Evidence Review Group had several concerns, the most important of which related to the degree to which fulvestrant might confer a benefit in overall survival. This was because mature data were not available from the key phase III trial FALCON. The economic model was sensitive to changes in overall survival and the Evidence Review Group considered the incremental cost-effectiveness ratio was uncertain and likely to increase once mature results from FALCON become available. The National Institute for Health and Care Excellence Appraisal Committee concluded that fulvestrant could not be recommended for treating locally advanced or metastatic estrogen-receptor-positive breast cancer in postmenopausal women who have not received previous endocrine therapy.



Estimation of Cost for Endoscopic Screening for Esophageal Cancer in a High-Risk Population in Rural China: Results from a Population-Level Randomized Controlled Trial

Abstract

Background and Objective

Population-level endoscopic screening for esophageal cancer has been conducted in China for years. In this study, we aim to provide an updated and precise cost estimation for esophageal cancer screening based on a randomized controlled trial in a high-risk area in China.

Methods

We estimated the cost of esophageal cancer screening with chromoendoscopy using a micro-costing approach based on primary data of the ESECC (Endoscopic Screening for Esophageal Cancer in China) randomized controlled trial (NCT01688908) from a health sector perspective. Unit costs and quantities of resources were collected to obtain annual screening costs. The screening project was then theoretically expanded to a 10-year period to explore long-term trends of costs. Costs were adjusted to US dollars for the year 2018.

Results

In the ESECC trial, screening cost per endoscopy with a valid pathologic diagnosis was $196, accounting for 3.82% of the gross domestic product per capita in Hua County, and the costs for detecting one esophageal cancer and one early-stage esophageal cancer were $26,347 and $37,687, respectively. In conventional screening in which protocol-driven costs were excluded, costs as above were $134, $18,074, and $25,853. The cost for detecting one gastric cardia cancer or stomach cancer was nine times higher than detecting one esophageal cancer owing to low prevalences of the two cancers. In a simulated 10-year screening project, annual cost decreased notably over time.

Conclusions

Despite the relatively low absolute cost, population-level endoscopic screening will still be a heavy burden on local government considering the socioeconomic conditions. Long-lasting programs would be less costly and population-level screening would make little sense in non-high-risk regions.



Cost Effectiveness of Nusinersen in the Treatment of Patients with Infantile-Onset and Later-Onset Spinal Muscular Atrophy in Sweden

Abstract

Background

Spinal muscular atrophy is a rare neuromuscular disorder with a spectrum of severity related to age at onset and the number of SMN2 gene copies. Infantile-onset (≤ 6 months of age) is the most severe spinal muscular atrophy and is the leading monogenetic cause of infant mortality; patients with later-onset (> 6 months of age) spinal muscular atrophy can survive into adulthood. Nusinersen is a new treatment for spinal muscular atrophy.

Objective

The objective of this study was to evaluate the cost effectiveness of nusinersen for the treatment of patients with infantile-onset spinal muscular atrophy and later-onset spinal muscular atrophy in Sweden.

Methods

One Markov cohort health-state transition model was developed for each population. The infantile-onset and later-onset models were based on the efficacy results from the ENDEAR phase III trial and the CHERISH phase III trial, respectively. The cost effectiveness of nusinersen in both models was compared with standard of care in Sweden.

Results

For a time horizon of 40 years in the infantile-onset model and 80 years in the later-onset model, treatment with nusinersen resulted in 3.86 and 9.54 patient incremental quality-adjusted life-years and 0.02 and 2.39 caregiver incremental quality-adjusted life-years and an incremental cost of 21.9 and 38.0 million SEK (Swedish krona), respectively. These results translated into incremental cost-effectiveness ratios (including caregiver quality-adjusted life-years) of 5.64 million SEK (€551,300) and 3.19 million SEK (€311,800) per quality-adjusted life-year gained in the infantile-onset model and later-onset model, respectively.

Conclusions

Treatment with nusinersen resulted in overall survival and quality-adjusted life-year benefits but with incremental costs above 21 million SEK (€2 million) [mainly associated with maintenance treatment with nusinersen over a patient's lifespan]. Nusinersen was not cost effective when using a willingness-to-pay threshold of 2 million SEK (€195,600), which has been considered in a recent discussion by the Dental and Pharmaceutical Benefits Agency as a reasonable threshold for rare disease. Nonetheless, nusinersen gained reimbursement in Sweden in 2017 for paediatric patients (below 18 years old) with spinal muscular atrophy type I–IIIa.



Cost Effectiveness of Sodium-Glucose Cotransporter-2 (SGLT2) Inhibitors, Glucagon-Like Peptide-1 (GLP-1) Receptor Agonists, and Dipeptidyl Peptidase-4 (DPP-4) Inhibitors: A Systematic Review

Abstract

Objective

This study aimed to systematically review cost-effectiveness studies of newer antidiabetic medications.

Methods

The PubMed/MEDLINE, EMBASE, CINAHL Plus, Cochrane Library–NHS Economic Evaluation Database (Wiley), Cochrane Library–Health Technology Assessment Database (Wiley), Cochrane Library–Database of Abstracts of Reviews of Effects (Wiley), and the Cost-Effectiveness Analysis Registry databases (from 1 January 2000 to 1 June 2018) were searched. The search strategies included the Medical Subject Heading (MeSH) term 'economics', and the MeSH entry terms 'cost', 'cost effectiveness', 'value', and 'cost utility', as well as all names for GLP-1 receptor agonists, DPP-4 inhibitors, and SGLT2 inhibitors. Inclusion criteria included (1) cost-effectiveness studies of the newer antidiabetic medications, including sodium-glucose cotransporter-2 (SGLT2) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, and dipeptidyl peptidase-4 (DPP-4) inhibitors; and (2) full-text publications in English. Two reviewers independently screened the titles, abstracts, and full-text articles to select studies for data extraction. Discrepancies were resolved by discussion and consensus. The quality of reporting cost-effectiveness analyses was assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) guideline.

Results

Among 85 studies selected, 82 clearly stated the types of diabetes model used (e.g. CORE model), and 70 studied used validated diabetes models. Seventy-four (87%) studies were funded by pharmaceutical companies, and 72 (85%) studies were conducted from a payer's perspective. Seventy-six (89%) studies presented were of good quality (20–24 CHEERS items), and nine were of moderate quality (14–19 items). Thirty studies compared newer antidiabetic medications with insulin, 3 studies compared newer antidiabetic medications with thiazolidinediones (TZDs), 15 studies compared newer antidiabetic medications with sulfonylureas, 40 studies compared new antidiabetic medications with alternative newer antidiabetic medication, and 9 studies compared other antidiabetic agents that were not included above. Newer antidiabetic medications were reported to be cost-effective in 26 of 30 (87%) studies compared with insulin, and 13 of 15 (87%) studies compared with sulfonylureas.

Conclusions

Most economic evaluations of antidiabetic medications have good reporting quality and use validated diabetes models. The newer antidiabetic medications in most of the reviewed studies were found to be cost effective, compared with insulin, TZDs, and sulfonylureas.



Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges

Abstract

Combinations of healthcare claims data with additional datasets provide large and rich sources of information. The dimensionality and complexity of these combined datasets can be challenging to handle with standard statistical analyses. However, recent developments in artificial intelligence (AI) have led to algorithms and systems that are able to learn and extract complex patterns from such data. AI has already been applied successfully to such combined datasets, with applications such as improving the insurance claim processing pipeline and reducing estimation biases in retrospective studies. Nevertheless, there is still the potential to do much more. The identification of complex patterns within high dimensional datasets may find new predictors for early onset of diseases or lead to a more proactive offering of personalized preventive services. While there are potential risks and challenges associated with the use of AI, these are not insurmountable. As with the introduction of any innovation, it will be necessary to be thoughtful and responsible as we increasingly apply AI methods in healthcare.



Alexandros Sfakianakis
Anapafseos 5 . Agios Nikolaos
Crete.Greece.72100
2841026182
6948891480

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