Appraising Drugs Based on Cost-effectiveness and Severity of Disease in Norwegian Drug Coverage Decisions

Importance: Rising health care costs are a major health policy challenge globally. Norway has implemented a priority-setting system intended to balance cost-effectiveness and concerns for fair distribution, but little is known about this strategy and whether it works in practice. Objective: To present and evaluate a systematic drug appraisal method that uses the severity of disease to account for a fair distribution of health in cost-effectiveness analysis, forming the basis for price negotiations and coverage decisions. Design, Setting, and Participants: This cross-sectional study uses confidential drug price information and publicly available data from health technology assessments and logistic and linear regression analyses to evaluate drug coverage decisions for the Norwegian specialized health care sector from 2014 to 2019. Main Outcomes and Measures: Drug coverage decisions by Norwegian authorities and incremental cost-effectiveness and severity of disease measured as absolute shortfall of quality adjusted life years. Results: Between 2014 and 2019, a total of 188 drugs were appraised, of which 113 were cancer drugs. The overall coverage rate was 73% (138 of 188). The number of annual appraisals increased during the observation period. Based on 83 chosen decisions, regression analysis showed that incremental cost-effectiveness ratios (ICER) based on negotiated drug prices, adjusted for severity-differentiated cost-effectiveness thresholds, was the variable that best projected drug approvals (OR, 0.60; 95% CI, 0.42-0.86). An increase in the ICER by $10 000 was associated with a reduction in the odds for approval of 40% for drugs assessed from 2018 to 2019. Conclusions and Relevance: This cross-sectional study demonstrated how concerns for efficiency and fair distribution of health can be implemented systematically into drug appraisals and reimbursement decisions. New, expensive drugs are expected to escalate health care costs in the years to come, and it may be feasible to control costs by negotiating the prices of new drugs while appraising both their cost-effectiveness and how their health benefits are distributed.publishedVersio

Genotyping errors in a calibrated DNA register: implications for identification of individuals

<p>Abstract</p> <p>Background</p> <p>The use of DNA methods for the identification and management of natural resources is gaining importance. In the future, it is likely that DNA registers will play an increasing role in this development. Microsatellite markers have been the primary tool in ecological, medical and forensic genetics for the past two decades. However, these markers are characterized by genotyping errors, and display challenges with calibration between laboratories and genotyping platforms. The Norwegian minke whale DNA register (NMDR) contains individual genetic profiles at ten microsatellite loci for 6737 individuals captured in the period 1997-2008. These analyses have been conducted in four separate laboratories for nearly a decade, and offer a unique opportunity to examine genotyping errors and their consequences in an individual based DNA register. We re-genotyped 240 samples, and, for the first time, applied a mixed regression model to look at potentially confounding effects on genotyping errors.</p> <p>Results</p> <p>The average genotyping error rate for the whole dataset was 0.013 per locus and 0.008 per allele. Errors were, however, not evenly distributed. A decreasing trend across time was apparent, along with a strong within-sample correlation, suggesting that error rates heavily depend on sample quality. In addition, some loci were more error prone than others. False allele size constituted 18 of 31 observed errors, and the remaining errors were ten false homozygotes (i.e., the <it>true </it>genotype was a heterozygote) and three false heterozygotes (i.e., the <it>true </it>genotype was a homozygote).</p> <p>Conclusions</p> <p>To our knowledge, this study represents the first investigation of genotyping error rates in a wildlife DNA register, and the first application of mixed models to examine multiple effects of different factors influencing the genotyping quality. It was demonstrated that DNA registers accumulating data over time have the ability to maintain calibration and genotyping consistency, despite analyses being conducted on different genotyping platforms and in different laboratories. Although errors were detected, it is demonstrated that if the re-genotyping of individual samples is possible, these will have a minimal effect on the database's primary purpose, i.e., to perform individual identification.</p

Sleep and physical activity from before conception to the end of pregnancy in healthy women: a longitudinal actigraphy study

Background Sleep and physical activity changes are common in pregnancy, but longitudinal data starting before conception are scarce. Our aim was to determine the changes of the daily total sleep time (TST) and physical activity duration (PAD) from before conception to end of pregnancies in respect of pregestational maternal factors. Methods This longitudinal observational study formed part of the CONIMPREG research project and recruited healthy women planning to become pregnant. Sleep and physical activity were recorded around-the-clock for ≥4 days via actigraphy before conception and during each trimester of pregnancy. Data were adjusted according to pregestational maternal body composition, parity and age. Results Among 123 women with eligible data, the unadjusted mean (95% confidence interval) TST increased from 415.3 min (405.5–425.2 min) before conception to 458.0 min (445.4–470.6 min) in the 1st trimester, remaining high through the 2nd and 3rd trimesters. Variation was substantial before conception (±2SD range: 307–523 min). The unadjusted mean PAD before conception was 363.7 min (±2SD range: 120–608 min), decreasing sharply to 262.1 min in the first trimester and more gradually thereafter. Vigorous and moderate activity decreased more than light activity. TST and PAD were significantly associated with age, parity, and pregestational body fat percentage; lean body mass was negatively correlated with TST. Results were generally unaffected by seasonal variations. Conclusion Marked variations were found in pregestational TST and PAD. Healthy women slept ≥30 min longer during pregnancy, while PAD decreased by ≥ 90 min in early pregnancy and continued to decrease thereafter.publishedVersio

Effectiveness and Safety of Low-Threshold Opioid-Agonist Treatment in Hard-To-Reach Populations with Opioid Dependence

Objectives: Opioid-use disorder is related to premature death worldwide. Opioid-agonist treatment (OAT) is an effective treatment for opioid dependence. OAT delivery platforms may influence treatment access and outcomes, especially for the most vulnerable groups. The aim of this study was to determine the effectiveness and safety of low-threshold OAT compared to the standard treatment. Methods: Patients with diagnosed opioid dependence undergoing low-threshold OAT at the Bergen delivery platform in Norway were enrolled in a cohort study in 2014–2019. A national OAT cohort was the reference group. The main outcomes were treatment retention, the use of illicit opioids, non-fatal overdose, overdose death, and all-cause mortality during the first year following treatment initiation and the full treatment period. Additionally, healthcare utilization in the periods before and during OAT was investigated. Results: Compared to the reference cohort, the low-threshold cohort (n = 128, mean age: 38 years, women: 28%) showed treatment retention rates of 95% versus 92%, illicit opioid use of 7% versus 10%, non-fatal overdose of 7% versus 6%, and death at 1.0% versus 1.3%, respectively. The incident rate ratios (IRRs) for healthcare utilization increased substantially during the OAT period compared to the period before; the IRR increased by 3.3 (95% confidence interval (CI): 2.8, 3.9) and 3.4 (95% CI: 3.1, 3.9) for all in- and outpatient healthcare, respectively. Conclusions: Low-threshold OAT was at least as effective and safe as the standard OAT in terms of treatment retention, the use of illicit opioids, non-fatal overdose, and death. Healthcare utilization increased during the OAT compared to the period before. Lowering the threshold for OAT entrance within proper delivery platforms should be broadly considered to reduce harm and improve healthcare access among patients with opioid dependence.publishedVersio

Pre-apoptotic response to therapeutic DNA damage involves protein modulation of Mcl-1, Hdm2 and Flt3 in acute myeloid leukemia cells

<p>Abstract</p> <p>Background</p> <p>Acute myeloid leukemia (AML) cells are characterized by non-mutated <it>TP53</it>, high levels of Hdm2, and frequent mutation of the Flt3 receptor tyrosine kinase. The juxtamembrane mutation of <it>FLT3 </it>is the strongest independent marker for disease relapse and is associated with elevated Bcl-2 protein and p53 hyper-phosphorylation in AML. DNA damage forms the basic mechanism of cancer cell eradication in current therapy of AML.</p> <p>Hdm2 and pro-apoptotic Bcl-2 members are among the most intensely induced genes immediately after chemotherapy and Hdm2 is proposed a role in receptor tyrosine kinase regulation. Thus we examined the DNA damage related modulation of these proteins in relation to <it>FLT3 </it>mutational status and induction of apoptosis.</p> <p>Results</p> <p>Within one hour after exposure to ionizing radiation (IR), the AML cells (NB4, MV4-11, HL-60, primary AML cells) showed an increase in Flt3 protein independent of mRNA levels, while the Hdm2 protein decreased. The <it>FLT3 </it>mutant MV4-11 cells were resistant to IR accompanied by presence of both Mcl-1 and Hdm2 protein three hours after IR. In contrast, the <it>FLT3 </it>wild type NB4 cells responded to IR with apoptosis and pre-apoptotic Mcl-1 down regulation. Daunorubicin (DNR) induced continuing down regulation of Hdm2 and Mcl-1 in both cell lines followed by apoptosis.</p> <p>Conclusion</p> <p>Both IR and DNR treatment resulted in concerted protein modulations of Mcl-1, Hdm2 and Flt3. Cell death induction was associated with persistent attenuation of Mcl-1 and Hdm2. These observations suggest that defining the pathway(s) modulating Flt3, Hdm2 and Mcl-1 may propose new strategies to optimize therapy for the relapse prone <it>FLT3 </it>mutated AML patients.</p

Parent-of-origin-environment interactions in case-parent triads with or without independent controls

With case–parent triad data, one can frequently deduce parent of origin of the child's alleles. This allows a parent‐of‐origin (PoO) effect to be estimated as the ratio of relative risks associated with the alleles inherited from the mother and the father, respectively. A possible cause of PoO effects is DNA methylation, leading to genomic imprinting. Because environmental exposures may influence methylation patterns, gene–environment interaction studies should be extended to allow for interactions between PoO effects and environmental exposures (i.e., PoOxE). One should thus search for loci where the environmental exposure modifies the PoO effect. We have developed an extensive framework to analyze PoOxE effects in genome‐wide association studies (GWAS), based on complete or incomplete case–parent triads with or without independent control triads. The interaction approach is based on analyzing triads in each exposure stratum using maximum likelihood estimation in a log‐linear model. Interactions are then tested applying a Wald‐based posttest of parameters across strata. Our framework includes a complete setup for power calculations. We have implemented the models in the R software package Haplin. To illustrate our PoOxE test, we applied the new methodology to top hits from our previous GWAS, assessing whether smoking during the periconceptional period modifies PoO effects on cleft palate only.publishedVersio

Correlation analysis of two-dimensional gel electrophoretic protein patterns and biological variables

BACKGROUND: Two-dimensional gel electrophoresis (2DE) is a powerful technique to examine post-translational modifications of complexly modulated proteins. Currently, spot detection is a necessary step to assess relations between spots and biological variables. This often proves time consuming and difficult when working with non-perfect gels. We developed an analysis technique to measure correlation between 2DE images and biological variables on a pixel by pixel basis. After image alignment and normalization, the biological parameters and pixel values are replaced by their specific rank. These rank adjusted images and parameters are then put into a standard linear Pearson correlation and further tested for significance and variance. RESULTS: We validated this technique on a set of simulated 2DE images, which revealed also correct working under the presence of normalization factors. This was followed by an analysis of p53 2DE immunoblots from cancer cells, known to have unique signaling networks. Since p53 is altered through these signaling networks, we expected to find correlations between the cancer type (acute lymphoblastic leukemia and acute myeloid leukemia) and the p53 profiles. A second correlation analysis revealed a more complex relation between the differentiation stage in acute myeloid leukemia and p53 protein isoforms. CONCLUSION: The presented analysis method measures relations between 2DE images and external variables without requiring spot detection, thereby enabling the exploration of biosignatures of complex signaling networks in biological systems

Identity, Resilience and Power in Self-Determination Conflicts

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Impaired cerebrovascular reactivity may predict delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage

Introduction: Delayed cerebral ischemia (DCI) is a major cause of disability and death after aneurysmal subarachnoid hemorrhage. The literature suggests that impaired cerebrovascular reactivity (CVR) may be a predictor for DCI; still no CVR based prediction model has been developed. Increased knowledge about possible predictors of DCI can improve patient management in high-risk patients and allow for shorter hospital stay in low-risk patients. Method: CVR was examined in 42 patients with aneurysmal subarachnoid hemorrhage and 37 patients treated for unruptured intracranial aneurysm, using acetazolamide test with transcranial Doppler monitoring of blood flow velocities. Patients were followed for development of DCI, separated into clinical deterioration and radiographic infarction. Results: For all patients, regardless of aneurysm rupture status, CVR was on average 5.5 percentage points lower on the ipsilateral side of aneurysm treatment. Patients with clinical deterioration due to DCI had lower CVR than patients without DCI, and the difference was larger on the contralateral side (33.9% vs. 49.2%). Two prediction models were constructed for clinical deterioration due to DCI. The area under the receiver operating characteristic curve was 0.82 in the model using established predictors, and 0.86 in the model that also included CVR. Conclusion: Our findings support the hypothesis that impaired CVR may be an independent predictor of clinical deterioration due to DCI, and may assist in identifying patients at risk after aneurysmal subarachnoid hemorrhage. Ipsilateral CVR reduction occurs in all patients after aneurysm treatment, regardless of DCI development, thus highlighting the need to evaluate ipsi- and contralateral CVR separately.publishedVersio

Clinical proteomics of myeloid leukemia

Myeloid leukemias are a heterogeneous group of diseases originating from bone marrow myeloid progenitor cells. Patients with myeloid leukemias can achieve long-term survival through targeted therapy, cure after intensive chemotherapy or short-term survival because of highly chemoresistant disease. Therefore, despite the development of advanced molecular diagnostics, there is an unmet need for efficient therapy that reflects the advanced diagnostics. Although the molecular design of therapeutic agents is aimed at interacting with specific proteins identified through molecular diagnostics, the majority of therapeutic agents act on multiple protein targets. Ongoing studies on the leukemic cell proteome will probably identify a large number of new biomarkers, and the prediction of response to therapy through these markers is an interesting avenue for future personalized medicine. Mass spectrometric protein detection is a fundamental technique in clinical proteomics, and selected tools are presented, including stable isotope labeling with amino acids in cell culture (SILAC), isobaric tags for relative and absolute quantification (iTRAQ) and multiple reaction monitoring (MRM), as well as single cell determination. We suggest that protein analysis will play not only a supplementary, but also a prominent role in future molecular diagnostics, and we outline how accurate knowledge of the molecular therapeutic targets can be used to monitor therapy response