Analyses of quality of life in cancer drug trials - a review of measurements and analytical choices in post-reimbursement studies.

OBJECTIVES: For drugs reimbursed with limited evidence of patient benefits, confirmatory evidence of overall survival (OS) and quality of life (QoL) benefits is important. For QoL data to serve as valuable input to patients and decision-makers, it must be measured and analyzed using appropriate methods. We aimed to assess the measurement and analyses of post-reimbursement QoL data for cancer drugs introduced in Swedish healthcare with limited evidence at the time of reimbursement. METHODS: We reviewed any published post-reimbursement trial data on QoL for cancer drugs reimbursed in Sweden between 2010 and 2020 with limited evidence of improvement in QoL and OS benefits at the time of reimbursement. We extracted information on the instruments used, frequency of measurement, extent of missing data, statistical approaches, and the use of pre-registration and study protocols. RESULTS: Out of 22 drugs satisfying our inclusion criteria, we identified published QoL data for 12 drugs in 22 studies covering multiple cancer types. The most frequently used QoL instruments were EORTC QLQ-C30 and EQ-5D-3/5L. We identified three areas needing improvement in QoL measurement and analysis: (i) motivation for the frequency of measurements, (ii) handling of the substantial missing data problem, and (iii) inclusion and adherence to QoL analyses in clinical trial pre-registration and study protocols. CONCLUSIONS: Our review shows that the measurements and analysis of QoL data in our sample of cancer trials covering drugs initially reimbursed without any confirmed QoL or OS evidence have significant room for improvement. The increasing use of QoL assessments must be accompanied by a stricter adherence to best-practice guidelines to provide valuable input to patients and decision-makers.

Place or patient as the driver of regional variation in healthcare spending - Discrepancies by category of care.

We study how much regional variation in healthcare spending is driven by place- and patient-specific factors using a random sample of 53,620 regional migrants in Sweden. We find notable differences depending on the category of care, with place-specific factors having a significantly larger impact on specialized outpatient care compared to inpatient and pharmaceutical care. The place effect is estimated to 75% of variation in specialized outpatient care, but 26% or less in variations in inpatient care, and 5% in prescription drug spending. We also find that the empirical estimator has a substantial impact on the estimates of the place-specific effect. The results based on the traditional approach in the literature with two-way fixed effects and event-study models produce much larger estimates of the place-specific effect compared to results based on recently developed heterogeneity-robust models. For total healthcare spending, the traditional two-way fixed effects model estimates a place effect of 78%, while the heterogeneity-robust estimator finds a place effect around 10%. This finding indicates that previous results in this literature, all based on traditional two-way fixed-effects regressions, should be interpreted with care.

Cancer Drugs Reimbursed with Limited Evidence on Overall Survival and Quality of Life: Do Follow-Up Studies Confirm Patient Benefits?

BACKGROUND AND OBJECTIVE: Cancer drug costs have increased considerably within healthcare systems, but many drugs lack quality-of-life (QoL) and overall survival (OS) data at the time of reimbursement approval. This study aimed to review the extent of subsequent literature documenting improvements in OS and QoL for cancer drug indications where no such evidence existed at the time of reimbursement approval. METHODS: Drug indications with claims of added therapeutical value but a lack of evidence on OS and QoL that were reimbursed between 2010 and 2020 in Sweden were included for review. Searches were conducted in PubMed and ClinicalTrial.gov for randomized controlled trials examining OS and QoL. RESULTS: Of the 22 included drug indications, seven were found to have at least one trial with conclusive evidence of improvements in OS or QoL after a mean follow-up of 6.6 years. The remaining 15 drug indications either lacked subsequent randomized controlled trial data on OS or QoL (n = 6) or showed no statistically significant improvements (n = 9). Only one drug demonstrated evidence of improvement in both OS and QoL for its indication. CONCLUSIONS: A considerable share of reimbursed cancer drug indications continue to lack evidence of improvement in both OS and QoL. With limited healthcare resources and an increasing cancer burden, third-party payers have strong incentives to require additional post-reimbursement data to confirm any improvements in OS and QoL.

Sleep researchers' rankings of sleep journals.

The impact factor is used to rank the quality of scientific journals but has been criticised for a number of reasons. The aim of the study was to investigate sleep researchers' perceptions of sleep journals to determine whether subjective rankings of journals were in line with the journals' impact factors. Clarivate's Journal Citation Reports website was used to identify journals containing the words 'sleep' or 'dream' in the titles with an impact factor since 2018, resulting in 12 journals. A survey including questions about how the respondent would rank these journals (e.g., three most prestigious journals) was developed. A total of 122 sleep researchers completed the survey. Sleep, Sleep Medicine Reviews and Journal of Sleep Research were ranked as the three most prestigious sleep journals, in line with the impact factors of the journals. For the rest of the journals, the subjective rankings and impact factors did not correspond as much.

Vaccination nudges: A study of pre-booked COVID-19 vaccinations in Sweden.

A nudge changes people's actions without removing their options or altering their incentives. During the COVID-19 vaccine rollout, the Swedish Region of Uppsala sent letters with pre-booked appointments to inhabitants aged 16-17 instead of opening up manual appointment booking. Using regional and municipal vaccination data, we document a higher vaccine uptake among 16- to 17-year-olds in Uppsala compared to untreated control regions (constructed using the synthetic control method as well as neighboring municipalities). The results highlight pre-booked appointments as a strategy for increasing vaccination rates in populations with low perceived risk.

The effect of robot interventions on sleep in adults: a systematic review and network meta-analysis.

STUDY OBJECTIVES: Robotic pets or companion robots have demonstrated positive effects on several emotional and physiological factors in humans. Robots could constitute a complementary or alternative method to treat sleep problems, but individual studies on robots' effectiveness regarding sleep show mixed results. The aim of the current study was to compare the effects of robots, plush toys, and treatment as usual on sleep in adults. METHODS: The current study is a systematic review and frequentist network meta-analysis of all randomized and cluster randomized controlled trials comparing the effects of robots, plush toys, and treatment as usual on total sleep time in adults. RESULTS: Four studies were included in the analysis. Three studies were considered to have a high risk of bias, whereas one was rated with some concerns. The studies comprised 381 participants. These participants were older adults, with or without dementia, living in nursing homes. The total sleep time was the only common sleep measure included in all 4 studies. The network meta-analysis showed no statistically significant differences between the 3 experimental groups. CONCLUSIONS: The robot interventions were not found to have positive effects on total sleep time in older adults compared with plush toys or treatment as usual. Future studies should use robots especially made to target sleep, include a thorough screening of the participants, and exclude people with adequate sleep, select appropriate sleep measures, and report the results appropriately for future meta-analyses. CITATION: Støre SJ, Beckman L, Jakobsson N. The effect of robot interventions on sleep in adults: a systematic review and network meta-analysis. J Clin Sleep Med. 2022;18(7):1877-1884.

The impact of cost-sharing on prescription drug demand: evidence from a double-difference regression kink design.

Pharmaceuticals represent the third-largest expenditure item in health care spending in the OECD countries, and cost growth is around 5% per year in many OECD countries. One possible way to contain the rise in pharmaceutical spending is the use of cost-sharing schemes that makes insured individuals directly bear parts of the cost of a drug. This study estimates the price sensitivity of demand for prescription drugs using data on all prescription drug purchases from a random sample of 400,000 Swedes followed from 2010 to 2013. We use a regression kink design (RKD) by exploiting the kinked Swedish cost-sharing scheme to assess the price elasticity. Further, since the cost-sharing scheme has changed over time, we also use a double-difference RKD to account for potential confounding nonlinearities around the kink. Our results indicate that the standard RKD results are biased and exaggerate the price sensitivity. Our preferred double-difference RKD specifications show no or minor price sensitivity (95% CI price elasticity from - 0.12 to 0.02). The results are similar in several sub-group analyses across age groups, sexes, and income quartiles.

Do home fire and safety checks by on-duty firefighters decrease the number of fires? Quasi-experimental evidence from Southern Sweden.

INTRODUCTION: Fire and rescue services Syd, in the south of Sweden, started to conduct home fire and safety checks on a large scale in 2010. The goal was to reduce the damages from residential fires. METHOD: We estimate the effects of the intervention on the incidence of residential fires and evaluate its economic effect. We use a difference-in-kinks design to analyze time-varying intervention effects and conduct a cost-benefit analysis for the economic evaluation. RESULTS: The results demonstrate that fires and developed fires decrease by a maximum of approximately 6% and 8% per year (assuming 100% causality) and that the intervention has positive economic effects, with the benefits estimated to be maximum 8-11 times higher than the costs. Practical applications: The results should be valuable as input when deciding whether to implement home fire and safety checks elsewhere.

Effects of primary care cost-sharing among young adults: varying impact across income groups and gender.

We estimate the price sensitivity in health care among adolescents and young adults, and assess how it varies across income groups and gender, using a regression discontinuity design. We use the age differential cost-sharing in Swedish primary care as our identification strategy. At the 20th birthday, the copayment increases from €0 to approx. €10 per primary care physician visit and close to this threshold the copayment faced by each person is distributed almost as good as if randomized. The analysis is performed using high-quality health care and economic register data of 73,000 individuals aged 18-22. Our results show that the copayment decreases the average number of visits by 7%. Among women visits are reduced by 9%, for low-income individuals by 11%, and for low-income women by 14%. In conclusion, modest copayments have significant utilization effects, and even in a policy context with relatively low income inequalities, the effect is substantially larger in low-income groups and among women.

The impact of community-based interventions for the older population: a quasi-experimental study of a hip-fracture prevention program in Norway.

BACKGROUND: Hip fractures among older adults are a major public health problem in many countries. Hip fractures are associated with expensive health care treatments, and serious adverse effects on patients' health and quality-of-life. In this paper, we estimate the effect of a community-based hip fracture prevention program that was initiated in 16 Norwegian municipalities in 2007. Specifically, the participating municipalities implemented one or more of the following interventions: exercise programs for older adults, information and education campaigns to communicate how to effectively reduce falls to care workers and older adults, and preventive home safety assessment and modification help services. METHODS: We used a difference-in-difference design, and identified control municipalities by matching on pre-intervention trends in the outcome. The outcome measure was the incidence of hip-fractures among older adults (≥65 years). RESULTS: We found no statistically significant effects of the implemented program on the incidence of hip fractures, on average, in older subgroups (≥80 years) or in municipality-specific analyses. CONCLUSIONS: It is unclear whether the interventions managed to achieve a change in hip fracture rates at the population level.

Regional variation in health care utilization in Sweden - the importance of demand-side factors.

BACKGROUND: Differences in health care utilization across geographical areas are well documented within several countries. If the variation across areas cannot be explained by differences in medical need, it can be a sign of inefficiency or misallocation of public health care resources. METHODS: In this observational, longitudinal panel study we use regional level data covering the 21 Swedish regions (county councils) over 13 years and a random effects model to assess to what degree regional variation in outpatient physician visits is explained by observed demand factors such as health, demography and socio-economic factors. RESULTS: The results show that regional mortality, as a proxy for population health, and demography do not explain regional variation in visits to primary care physicians, but explain about 50% of regional variation in visits to outpatient specialists. Adjusting for socio-economic and basic supply-side factors explains 33% of the regional variation in primary physician visits, but adds nothing to explaining the variation in specialist visits. CONCLUSION: 50-67% of regional variation remains unexplained by a large number of observable regional characteristics, indicating that omitted and possibly unobserved factors contribute substantially to the regional variation. We conclude that variations in health care utilization across regions is not very well explained by underlying medical need and demand, measured by mortality, demographic and socio-economic factors.

Are fire safe cigarettes actually fire safe? Evidence from changes in US state laws.

OBJECTIVE: To estimate the effects of fire safe cigarette laws on fire mortality and cigarette-related fires in the USA. METHODS: We examined the gradual implementation of the laws to identify their average effects, using difference-in-differences analysis to account for common year effects, time-invariant state effects, state-specific trends and observable time-varying state-level covariates. RESULTS: We found no statistically significant effects on all-cause fire mortality, residential fire mortality or cigarette-caused fire rates. The estimates for cigarette-caused fire deaths were significant under some specifications, but were not robust to the inclusion of state-specific trends or comparisons to effects on other cause-determined fires. CONCLUSIONS: Given the mixed state of our results, we conclude that previous claims regarding the effects of fire safe cigarette laws may be premature.

Copayments and physicians visits: A panel data study of Swedish regions 2003-2012.

OBJECTIVE: This paper analyzes how primary care physician visits are affected by the level of copayment in Sweden. DATA SOURCE: We use data between the years 2003-2012 from 21 Swedish health care regions that have the mandate to set their own level of copayment. The copayment per visit varies between €10 and €20 for these years and regions. STUDY DESIGN: Our strategy to identify the causal effect and deal with unobserved endogeneity of price changes on physician visits is based on a panel data model using fixed effects to control for region and time and regional-variation in time trends. PRINCIPAL FINDING: We cannot reject that the copayment has no statistical or economic effect of significance, and we estimate the "zero effect" with very high precision. CONCLUSION: In a setting with sub-national regions with autonomy to set co-payments the results points to that the copayment is not an important predictor for the number of health care visits. The result is in line with some previous studies on European data where the range of copayments used tends to be relatively low.

Attitudes toward same-sex marriage: the case of Scandinavia.

The purpose of this study was to examine the variables that explain attitudes toward same-sex marriage. Using recently collected Scandinavian data (from Norway and Sweden) with a high response rate, this study shows that gender, regular participation in religious activities, political ideology, education, whether the respondent lived in the capital city, and attitudes toward gender equality were important for attitudes toward same-sex marriage. Age and income were not important for attitudes toward same-sex marriage. Although both Norwegians and Swedes clearly favor same-sex marriage, Swedes are significantly more positive than Norwegians.

Modeling and optimization of preparative reversed-phase liquid chromatography for insulin purification.

This paper presents a model for reversed-phase purification of insulin from desamido insulin. The system is described by a reaction dispersive model with a competitive Langmuir isotherm. A model building and calibration method is presented and the model's region of validity is defined. The model is calibrated using only two-component experiments on the raw mixture by the inverse method and then experimentally validated. The model is then used to optimize the system's production rate with both purity and yield requirements. The yield requirement is varied between 80 and 95% to study the effect on the production rate and the operating point. The operating points found with the optimization were found outside the model's region of validity, but the experimental validation of the operating points shows that the model can be extrapolated to the interesting operating points.

Model based robustness analysis of an ion-exchange chromatography step.

Process development, optimization and robustness analysis for chromatographic separation are often entirely based on experimental work and generic knowledge. This paper describes a model-based approach that can be used to gain process knowledge and assist in the robustness analysis of an ion-exchange chromatography step using a model-based approach. A kinetic dispersive model, where the steric mass action model accounts for the adsorption is used to describe column performance. Model calibration is based solely on gradient elution experiments at different gradients, flow rates, pH and column loads. The position and shape of the peaks provide enough information to calibrate the model and thus single-component experiments can be avoided. The model is calibrated to the experiments and the confidence intervals for the estimated parameters are used to account for the model error throughout the analysis. The model is used to predict the result of a robustness analysis conducted as a factorial experiment and to design a robust pooling approach. The confidence intervals are used in a "worst case" approach where the parameters for the components are set at the edge of their confidence intervals to create a worst case for the removal of impurities at each point in the factorial experiment. The pooling limit was changed to ensure product quality at every point in the factorial analysis. The predicted purities and yields were compared to the experimental results to ensure that the prediction intervals cover the experimental results.

Constrained optimization of a preparative ion-exchange step for antibody purification.

Today, the optimization of chromatographic separation is usually based on experimental work and rule of thumb. The process and analytical technology (PAT) initiative, of the US Food and Drug Administration, has provided the opportunity of using model-based approach when designing downstream processing of pharmaceutical substances. A nonlinear chromatography model was used in this study to optimize a preparative ion-exchange separation step involving two components. Separation was simulated with the general rate model employing Langmuir kinetics. Optimization was performed with an indirect method allowing constraints on the purity, thus avoiding sub-optimization, which can lead to noisy objective functions. The six decision variables used in the optimizations were flow rate, loading volume, initial salt concentration in the elution, final salt concentration in the linear elution gradient and the two cut points. A graphical representation of the effect of the decision variables on the objective function was used to verify that the optimization had converged to the true optimum. The optimal operating points, using productivity and yield separately as objective functions, were found and compared with the product of productivity and yield as objective function. The optimum obtained with this objective function had a lower productivity, than the productivity function, but much higher yield, which makes it a good substitute for a cost function.

Optimisation and robustness analysis of a hydrophobic interaction chromatography step.

Process development, optimisation and robustness analysis for chromatography separations are often entirely based on experimental work and generic knowledge. The present study proposes a method of gaining process knowledge and assisting in the robustness analysis and optimisation of a hydrophobic interaction chromatography step using a model-based approach. Factorial experimental design is common practice in industry today for robustness analysis. The method presented in this study can be used to find the critical parameter variations and serve as a basis for reducing the experimental work. In addition, the calibrated model obtained with this approach is used to find the optimal operating conditions for the chromatography column. The methodology consists of three consecutive steps. Firstly, screening experiments are performed using a factorial design. Secondly, a kinetic-dispersive model is calibrated using gradient elution and column load experiments. Finally, the model is used to find optimal operating conditions and a robustness analysis is conducted at the optimal point. The process studied in this work is the separation of polyclonal IgG from BSA using hydrophobic interaction chromatography.

Using computer simulation to assist in the robustness analysis of an ion-exchange chromatography step.

This paper presents a methodology to gain process knowledge and assist in the robustness analysis of an ion-exchange step in a protein purification process using a model-based approach. Factorial experimental design is common practice in industry today to obtain robustness characterization of unit operations with respect to variations in process parameters. This work aims at providing a better insight into what process variations affect quality and to further reduce the experimental work to the regions of process variation that are of most interest. This methodology also greatly increases the ability to predict process performance and promotes process understanding. The model calibration part of the methodology involves three consecutive steps to calibrate a steric mass action (SMA) ion-exchange chromatography model. Firstly, a number of gradient elution experiments are performed. Secondly, experimental breakthrough curves have to be generated for the proteins if the adsorption capacity of the medium for each component is not known. Thirdly, a multi-component loading experiment is performed to calibrate the multi-component effects that cannot be determined from the single-component experiments. The separation process studied in this work is the separation of polyclonal IgG from a mixture containing IgG, myoglobin and BSA. The calibrated model is used to simulate six process variations in a full factorial experiment. The results of the simulations provide information about the importance of the different process variations and the simulations are also used to determine the crucial points for the process parameter variations. The methodology can be used to assist in the robustness analysis normally performed in the pharmaceutical industry today as it is able to predict the impact on process performance resulting from variations in salt concentration, column load, protein concentration and flow rate.

Model-based optimization of a preparative ion-exchange step for antibody purification.

A method using a model-based approach to design and optimize an ion-exchange step in a protein purification process is proposed for the separation of IgG from a mixture containing IgG, BSA and myoglobin. The method consists of three steps. In the first step, the model is calibrated against carefully designed experiments. The chromatographic model describes the convective and dispersive flow in the column, the diffusion in the adsorbent particles, and the protein adsorption using Langmuir kinetics with mobile phase modulators (MPM). In the second step, the model is validated against a validation experiment and analyzed. In the third and final step, the operating conditions are optimized. In the optimization step, the loading volume and the elution gradient are optimized with regard to the most important costs: the fixed costs and the feed cost. The optimization is achieved by maximizing the objective functions productivity (i.e. the production rate for a given amount of stationary phase) and product yield (i.e. the fraction of IgG recovered in the product stream). All optimization is conducted under the constraint of 99% purity of the IgG. The model calibration and the analysis show that this purification step is determined mainly by the kinetics, although as large a protein as IgG is used in the study. The two different optima resulting from this study are a productivity of 2.7 g IgG/(s m3) stationary phase and a yield of 90%. This model-based approach also gives information of the robustness of the chosen operating conditions. It is shown that the bead diameter could only be increased from 15 microm to 35 microm with maximum productivity and a 99% purity constraint due to increased diffusion hindrance in larger beads.