Estimates Of Benefits Research Articles

Development and validation of RSClin N+ tool for hormone receptor-positive (HR+), HER2-negative (HER2-), node-positive breast cancer.

508 Background: The RSClin tool was developed to provide estimates of recurrence risk and absolute chemotherapy benefit for patients with HR+/HER2- node-negative breast cancer using the 21-gene recurrence score (RS) and clinicopathologic factors. For patients with node-positive disease, we developed a new tool (RSClin N+) to increase the prognostic and predictive utility of risk estimates by combining RS with clinicopathologic factors and menopausal status. Methods: We used Cox regression to estimate 5-year risk of invasive disease or death (iDFS) and likelihood ratio (LR) tests to compare fit of RSClin N+ with RS alone and clinicopathologic factors (tumor grade, tumor size, positive lymph nodes [N1/N2], age) alone in 5283 node-positive patients treated with chemoendocrine therapy (CET) vs endocrine therapy alone (ET) in the S8814 (n=367: N1=227, N2=140, all postmenopausal) and RxPONDER (n/N1=4916) trials. Data from both studies were pooled and stratified by study for postmenopausal models; premenopausal models were fit only on RxPONDER data. Absolute CET benefit across combination of covariate values was estimated as the difference between ET and CET risk estimates. Validation of RSClin N+ was performed in 592 Nmic/N1 patients in the Clalit registry real-world dataset. Results: For pre- and postmenopausal patients, RSClin N+ provided significantly more prognostic information for iDFS than RS or clinicopathologic factors alone (LR Chi-square p<0.05). In postmenopausal patients, RS and clinicopathologic factors were independently prognostic, but only RS showed interaction with CET benefit (p=0.016). Absolute CET benefit for iDFS ranged from <0.1% to 21.5% as the RS increased from 0 to 50. Table shows examples of risk stratification and predicted benefit by RS within clinical low and high risk patients. In premenopausal patients, both RS and clinicopathologic factors remained prognostic but no interaction was observed between RS and CET.In external validation, RSClin N+ risk estimates were concordant with (Lin’s concordance=0.92) and prognostic for observed risk (HR 1.75; 95% CI 1.38 to 2.20). Conclusions: The RSClin N+ model provides improved estimates of prognostic risk and absolute CET benefit than clinical or genomic data alone in node-positive, HR+/HER2- breast cancer and could be used in patient counseling. [Table: see text]

A multicriteria decision analysis for selecting rainwater harvesting systems in rural areas: a tool for developing countries

Global water provision challenges have promoted decentralized water supply alternatives such as rainwater harvesting systems (RWHS). RWHS sustainability demands involve social, technical, and economic criteria in planning. Generally, in rural areas, water provision is more complex due to multiple uses of water, scattering of households, and low economies of scale. This research proposes a multicriteria tool for selecting RWHS in rural areas, considering social, technical, and economic criteria. The tool was developed by systematically identifying subcriteria and their hierarchization through the analytical hierarchy process (AHP), the technique for order of preference by similarity to ideal solution (TOPSIS), and a case study validation. Seven subcriteria were identified. The hierarchy of criteria was social (49.7%), technical (26.4%), and economic (23.9%). The tool involved: (i) users’ consultation about the perceived ease of use and availability of water sources other than rainwater; (ii) system dimensioning to establish supply size, maintenance requirements, and required water quality; and (iii) costs and benefits estimation. Tool validation in a rural area included the evaluation of the alternatives proposed: (a) alternative 1: potable domestic uses (PD) and non-potable (NPD); (b) alternative 2: PD and NPD, irrigation of crops and chicken farming for self-consumption; and alternative 3: PD and NPD and chicken farming for profit sale. The sensitivity analysis showed the tool’s consistency and robustness. Tool validation highlights the importance of integrating the three dimensions in selecting RWHS. The study provides a systematic methodology to assess and prioritize RWHS, appealing to policymakers, engineers, and practitioners facilitating water management and supply processes in rural areas.

Clinical and economic benefit of genomic testing strategies to guide the treatment of patients with HR+/HER2- breast cancer in the US.

10584 Background: Multiple testing technologies are available to inform treatment decisions for hormone receptor positive (HR+) and human epidermal growth factor receptor 2 negative (HER2-) early-stage breast cancer, including tumor profiling and germline genetic testing (GGT). The 21-gene assay provides an estimate of distant recurrence risk and potential clinical benefit of chemotherapy. GGT identifies pathogenic variants which inform lifetime cancer risk as well may inform therapy options. This study explored the potential synergy of utilizing both tests by assessing the cost-effectiveness of this strategy compared to no testing from a societal perspective. Methods: A health economic model was developed using best practices to assess a patient cohort with HR+/HER2-, node-negative (N0) or node-positive (N1) breast cancer that was guided to surgical and adjuvant treatment by GGT ( ATM, BRCA1/2, CDH1, CHEK2, PALB2, PTEN,and TP53) and the 21-gene assay. Treatment effectiveness was informed by clinical trials (TAILORx and RxPONDER); costs for treatment, monitoring, and health utilities were sourced from literature. Clinical expert opinion and guidelines informed current US clinical practice. The base case analysis evaluated lifetime total costs, life-years, and quality-adjusted life years (QALYs) versus no testing. Scenario and sensitivity analyses were performed to evaluate model robustness. Results: The testing strategy was dominant (lower cost and higher QALYs gained) compared to no testing leading to a QALY improvement of 0.286 and cost savings of $16,463 in the N0 population (Table) and a 0.099 QALY improvement and $299 cost savings in the N1 population. Scenario analyses indicated that while the 21-gene assay was the primary driver of results, there were synergistic effects when tests were combined. Sensitivity analysis supported cost-effectiveness at most willingness-to-pay thresholds and identified the probability of chemotherapy and rate of distant recurrence as the most impactful model inputs. Conclusions: Using a testing strategy including both the 21-gene assay and GGT enables optimization of treatment decisions in early HR+/HER2- breast cancer, improving patient outcomes at reduced costs. [Table: see text]

Evaluating generalizability of landmark randomized controlled trials in common metastatic cancers using machine learning-based emulated trials.

e13618 Background: Randomized controlled trial (RCT) results often lack generalizability to real-world oncology patients (pts). We present TrialTranslator, a machine learning (ML) framework to evaluate the generalizability of Phase III oncology RCTs by emulating trials across prognostic risk groups. Methods: TrialTranslator was applied to 11 landmark RCTs encompassing the most prevalent advanced cancers – non-small cell lung (aNSCLC), breast (mBC), prostate (mPC), and colorectal (mCRC). Flatiron Health’s EHR-derived de-identified database was used for model development and trial emulation. In Stage I, ML models (gradient boosted [GBM], random forest, support vector machine and penalized Cox) were trained to predict survival from time of metastatic diagnosis. Models used 130 longitudinal demographic, cancer-related, lab, and biomarker features. In Stage II, trial emulation, pts meeting RCT cancer and biomarker eligibility criteria were stratified into low, medium, and high-risk groups based on the top-performing ML model. We used inverse probability of treatment weighted survival analysis for each risk group to compare the median overall survival (mOS) or median progression free survival (mPFS) between experimental and control arms. Results: GBM models achieved the highest time-dependent area under the receiver operating curve (AUC) in the test set in all cancer types. For example, the 1-year AUC for the aNSCLC GBM vs the Lung Cancer Prognostic Index (validated Cox model) was 0.783 vs 0.689. ML-predicted low-risk pts typically had similar mOS or mPFS as RCT populations (Table). In emulated trials for low-risk pts, real-world survival benefit – the absolute difference in mOS or mPFS between experimental and control arms – was similar to RCT results. In contrast, for high-risk pts, survival benefits were not statistically or clinically significant. For example, in the FLAURA trial, RCT mPFS for experimental arm (osimertinib) vs control (gefitinib or erlotinib) was 18.9 mos vs 10.2 months; mPFS was 17.1 vs 10.3 months for low-risk pts and 5.1 vs 4.2 months for high-risk pts. Conclusions: ML frameworks like TrialTranslator may facilitate individual patient-level estimation of real-world treatment benefits of novel oncology agents. TrialTranslator is accessible at trialtranslator.com. [Table: see text]

Effect of Context Specificity on Response to the Shortened WOMAC Function Scale in Patients Undergoing Total Knee Arthroplasty

ObjectiveTo determine, in patients undergoing total knee arthroplasty (TKA), whether increasing context specificity of selected items of the shortened version of the Western Ontario and McMaster Universities Osteoarthritis Index function (WOMAC-F) scale (ShortMAC-F) (1) enhanced the convergent validity of the ShortMAC-F with performance-based mobility measures (ii) affected mean scale score, structural validity, reliability, and interpretability. DesignSecondary analysis of randomized clinical trial data. SettingA tertiary teaching hospital. ParticipantsPatients undergoing TKA (N=114). InterventionsNot applicable. Main Outcome MeasuresThe ShortMAC-F was modified by specifying the “ascending stairs” and “rising from sitting” items to enquire about difficulty in performing the tasks without reliance on compensatory strategies, whereas the modified “level walking” item enquired about difficulty in walking 400 m. Before and 12 weeks after TKA, patients completed the WOMAC-F questionnaire, modified ShortMAC-F questionnaire, knee pain scale questionnaire, sit-to-stand test, fast gait speed test, and stair climb test. Interpretability was evaluated by calculating anchor-based substantial clinical benefit estimates. ResultsThe modified ShortMAC-F correlated significantly more strongly than ShortMAC-F or WOMAC-F with pooled performance measures (differences in correlation values, 0.12-0.14). Increasing item context specificity of the ShortMAC-F did not influence its psychometric properties of unidimensionality (comparative fit and Tucker–Lewis indices, >0.95; root mean square error of approximation, 0.05-0.08), reliability (Cronbach's α, 0.75-0.83), correlation with pain intensity (correlation values, 0.48-0.52), and substantial clinical benefit estimates (16 percentage points); however, it resulted in lower mean score (4.5-4.8 points lower). ConclusionsThe modified ShortMAC-F showed sufficient measurement properties for clinical application, and it seemed more adept than WOMAC-F at correlating with performance-based measures in TKA.

Comparison theorem for systems of differential equations and its application to estimate the average time benefit from resource collection

One of the versions of the comparison theorem for systems of ordinary differential equations is proved, the consequence of which is the property of monotonicity of solutions with respect to initial data. We consider the problem of estimating the average time profit from resource extraction for a structured population consisting of individual species $x_1,\ldots,x_n$, or divided into $n$ age groups. We assume that the dynamics of the population in the absence of exploitation is given by a system of differential equations $\dot x =f(x)$, and at times $\tau(k)=kd$, $d>0$, a certain share of the biological resource is extracted from the population $u(k)=(u_1(k),\ldots,u_n(k))\in [0,1]^n$, $k=1,2,\ldots.$ It is shown that using the comparison theorem it is possible to find estimates of the average time benefit in cases when analytical solutions for relevant systems are not known. The results obtained are illustrated for models of interaction between two species, such as symbiosis and competition. It is shown that for models of symbiosis, commensalism and neutralism, the greatest value of the average time profit is achieved with the simultaneous exploitation of two types of resources. For populations between which an interaction of the “competition” type is observed, cases in which it is advisable to extract only one type of resource are highlighted.

On ferry users’ willingness to pay for improving environmental quality: A case study for the Canary Islands

This study, using a contingent valuation framework, provides an initial assessment of the environmental benefits derived from the hypothetical adoption of a low-carbon fuel path, and onshore power supply, by the ferry sector in the Canary Islands in compliance with the FuelEU Maritime Initiative. To this end, a sample of 502 respondents was asked about their willingness to pay (WTP) for the increase in their well-being resulting from improvements in air quality and noise pollution. Special attention was paid to the problem of zero responses and the possible presence of self-selection due to protest responses. The results show that about 75% of the respondents expressed their WTP extra for a single ferry ticket between the most populated cities in the archipelago, with an estimated mean WTP of €13.12. This would represent a 33% increase in current ferry tickets. Aggregating the mean WTP across the population affected, has resulted in a conservative estimate of the total benefits derived from this policy of €65.9 million over a 30-year horizon time, and €94.2 million over a longer horizon time (100 years). In short, this study aims to fill an existing research gap while providing a quantitative basis for decision-making in densely populated port cities connected by ferry.

Cardiovascular risk prediction - now and the future

Current cardiovascular risk estimation systems that estimate 10-year risk based on cohort studies starting at around age 40 have probably reached their limits based on current methods. The challenges are to develop new systems that will permit personalised risk estimation earlier in life with better estimates of true lifetime risk and likely treatment benefits. We outline approaches to address these issues.

Integrating decision modeling and machine learning to inform treatment stratification.

There is increasing interest in moving away from "one size fits all (OSFA)" approaches toward stratifying treatment decisions. Understanding how expected effectiveness and cost-effectiveness varies with patient covariates is a key aspect of stratified decision making. Recently proposed machine learning (ML) methods can learn heterogeneity in outcomes without pre-specifying subgroups or functional forms, enabling the construction of decision rules ('policies') that map individual covariates into a treatment decision. However, these methods do not yet integrate ML estimates into a decision modeling framework in order to reflect long-term policy-relevant outcomes and synthesize information from multiple sources. In this paper, we propose a method to integrate ML and decision modeling, when individual patient data is available to estimate treatment-specific survival time. We also propose a novel implementation of policy tree algorithms to define subgroups using decision model output. We demonstrate these methods using the SPRINT (Systolic Blood Pressure Intervention Trial), comparing outcomes for "standard" and "intensive" blood pressure targets. We find that including ML into a decision model can impact the estimate of incremental net health benefit (INHB) for OSFA policies. We also find evidence that stratifying treatment using subgroups defined by a tree-based algorithm can increase the estimates of the INHB.

The effect of growth, deforestation, forest fires, and volcanoes on Indonesian regional air quality

As a rapidly developing country, Indonesia faces a challenge in improving air quality that is made more difficult by frequent forest fires linked to deforestation and volcanic eruptions. This paper analyses the link between development and air pollution in 30 Indonesian cities from 2002 to 2019. Air quality is measured using two novel regional air quality indicators (AQIs) for PM2.5 and PM10 estimated from weather observations and NASA satellite data on Aerosol Optical Depth (AOD). Results from an Environmental Kuznets Curve (EKC) analysis, based on a dynamic panel data model, show that forest fires and volcanic activity have significantly worsened regional air quality in Indonesia. The model also shows that the EKC hypothesis is rejected for Indonesia as cities have followed a monotonically increasing trend in air pollution with respect to economic growth. An additional 1% of economic growth increased long run pollution as measured by AQI PM2.5 and PM10 by 0.35% and 0.46%, and forest fire events by 0.11% and 0.06%. A partial Benefit-Cost Analysis (BCA) of forest fires shows that particulate matter pollution is excessive. Decreasing the frequency of forest fires by 1% would generate a net benefit of between US$17 million to 145 million. The lower estimate of the health benefits exceeds the agricultural benefits of forest fire without accounting for other non-market costs due to forest fires. Our results imply that, as Indonesia grows economically, air quality is likely to continue deteriorating. Further, regions affected by regular volcanic activity and wildfires should apply tighter emission standards to controllable point source emissions from industry and non-point source emissions such as agricultural forest fires.

STABILITY ANALYSIS FOR HETEROGENEOUS TRAFFIC FLOW WITH LANE-CHANGE DISTURBANCE

Stability analysis and benefit estimation have substantial implications for lane-change decision-making to reduce delay and variation. Connected platoons drive with minor headway to increase capacity, whereas dividing or reforming platoons significantly impacts traveling efficiency. Therefore, this article focuses on the instability of the platoon caused by an en-route lane-change. Construction of platoon forming, combination rules, and car-following models for various vehicle types are presented to describe driving behaviours. Then, a velocity adjustment and a model for lane-change preparation and recovery are proposed. In addition, a group of stability recognition indexes and related stability evaluation factors are presented. Experiments involving numerical comparisons of the proposed factors are conducted to demonstrate the propagation properties of the instability and reveal the fluctuation degree. The variation duration, velocity variation range, and total delay are the primary indicators for evaluating lane-change feasibility. The models and findings can be applied effectively in practice to determine the optimal time and location for en-route lane-change and to assist with traffic management and lane selection at the entrance.

Are Lentil (Lens culinaris) Farms Productive, Profitable, and Efficient in Resource Allocation? A Cross‐Sectional Study From Nepal

ABSTRACTThe study was based on primary data from 473 lentil farmers selected randomly to analyze productivity, profitability, efficiency, and sensitivity of lentil farms in Nepal. Methods like benefit–cost, break‐even, margin safety, and sensitivity analysis, scaling technique, Cobb–Douglas type of production function, and stochastic frontier were adopted to derive farm economics, allocative, and cost efficiency levels. With average productivity of 672 kg/ha, lentil farmers in the study area were earning about 41% profit as of gross return with a profitability index of 0.78. About 45% margin of safety and estimates of benefit–cost ratio above one on all sensitivity measures is indicative of low risk and robust enterprise. Resources allocated in lentil production were found inefficient, and to achieve maximum return, expenses on land preparation, seed, nutrient, and plant protection cum irrigation should be increased by 27.6%, 80%, 33.1%, and 97%, respectively. Similarly, expenses on labor and harvesting activities need to be decreased by 30.1% and 23.6%. Labor cost and seed cost were the most important variables, and a 1% increase would surge the total production costs by 0.42% and 0.19%, respectively. The cost efficiency was estimated as 1.137 mean value, meaning that over 13.7% of the costs in lentil farms is wasted while comparing best‐practiced farm. Only about 48% of farms is fairly efficient at efficiency levels 1.0 to 1.09, but the majority is inefficient, which needs to minimize the waste of resources. Although suffering from climatic risks and production‐related problems, lentil enterprise is profitable, less risky, less sensitive, and fairly to inefficient in resource use. Wise attention is need on the part of farm management and resource utilization. Farmers are suggested to maintain farm size around 0.5 ha or below 1 ha, use only improved varietal seed, cut labor expenses with the use of machinery, and perform adequate tillage during sowing followed by effective disease management practices.

Kinetic energy harvesting for enhancing sustainability of refrigerated transportation

The industry of temperature-controlled transportation has shown significant growth in recent years, and this growth is expected to continue in the future. As the sector expands, it's crucial to focus on reducing energy consumption and greenhouse gas emissions related to transport refrigeration systems to meet the planned decarbonization goals. In this study, the energy and environmental benefits of implementing an electric Kinetic Energy Recovery System (KERS) on a refrigerated light-duty commercial van, equipped with a vapor compression refrigeration (VCR) system, are assessed by means of dynamic simulation. The KERS considered involves a LiFePO4 battery as electricity storage system, a brushless motor-generator unit and a hybrid inverter able to both charge the battery and power the refrigeration system. For each component of the system, i.e. the engine, the alternator, the transmission system and the KERS, the real efficiencies have been considered. The dynamic behaviour of the KERS is simulated by using data obtained by performing a real urban single-delivery 40 km mission, during which the vehicle operating conditions, as well as the electricity demand of the refrigeration system, have been measured. The estimation of the potential benefits of the proposed solution has been performed by comparing the electricity produced by the KERS (and available for use) and the measured energy demand of the refrigeration system.The results have shown that the electricity available for use could cover more than 47% of the total electricity demand. This means that nearly half of the primary energy/fuel consumption can be saved by employing a KERS in refrigerated-light duty vehicles. In particular, emissions savings ranging between 9 and 13 gCO2,e and cost savings between 0.4 and 0.7 c€ per kilometer travelled can be achieved, resulting in an average payback period of 8 years. In addition, when considering the entire useful life of a refrigerated van equal to 10 years, CO2,e savings of 4515–6710 kgCO2,e are obtained.The low complexity of the proposed system and the availability of the components on the market, together with the results obtained by simulation, make using KERS in refrigerated transport a promising solution throughout the decarbonization of the refrigerated transport sector.

Estimating Vitamin K Antagonist Anticoagulation Benefit in People With Atrial Fibrillation Accounting for Competing Risks: Evidence From 12 Randomized Trials.

Patients with atrial fibrillation have a high mortality rate that is only partially attributable to vascular outcomes. The competing risk of death may affect the expected anticoagulant benefit. We determined if competing risks materially affect the guideline-endorsed estimate of anticoagulant benefit. We conducted a secondary analysis of 12 randomized controlled trials that randomized patients with atrial fibrillation to vitamin K antagonists (VKAs) or either placebo or antiplatelets. For each participant, we estimated the absolute risk reduction (ARR) of VKAs to prevent stroke or systemic embolism using 2 methods-first using a guideline-endorsed model (CHA2DS2-VASc) and then again using a competing risk model that uses the same inputs as CHA2DS2-VASc but accounts for the competing risk of death and allows for nonlinear growth in benefit. We compared the absolute and relative differences in estimated benefit and whether the differences varied by life expectancy. A total of 7933 participants (median age, 73 years, 36% women) had a median life expectancy of 8 years (interquartile range, 6-12), determined by comorbidity-adjusted life tables and 43% were randomized to VKAs. The CHA2DS2-VASc model estimated a larger ARR than the competing risk model (median ARR at 3 years, 6.9% [interquartile range, 4.7%-10.0%] versus 5.2% [interquartile range, 3.5%-7.4%]; P<0.001). ARR differences varied by life expectancies: for those with life expectancies in the highest decile, 3-year ARR difference (CHA2DS2-VASc model - competing risk model 3-year risk) was -1.3% (95% CI, -1.3% to -1.2%); for those with life expectancies in the lowest decile, 3-year ARR difference was 4.7% (95% CI, 4.5%-5.0%). VKA anticoagulants were exceptionally effective at reducing stroke risk. However, VKA benefits were misestimated with CHA2DS2-VASc, which does not account for the competing risk of death nor decelerating treatment benefit over time. Overestimation was most pronounced when life expectancy was low and when the benefit was estimated over a multiyear horizon.

Cost‐effectiveness of Resonance® metallic ureteral stent compared with standard polyurethane ureteral stents in malignant ureteric obstruction: A cost‐utility analysis

AbstractBackgroundMalignant ureteral obstruction (MUO) is a frequent challenge for urologists. Patients have poor prognoses, treatment aims to improve quality‐of‐life while optimising renal function. Standard practice in the United Kingdom is to use polyurethane stents, which require frequent surgical replacements for blockages and encrustation. More durable metallic stents are available, although these incur an increased initial purchase price.AimsWe aim to assess whether the use of polyurethane double‐J (JJ) or metallic stent, Resonance® is more cost‐effective for managing MUO in the UK healthcare setting.MethodsA Markov model was parameterised to 5 years with costs and health‐related quality‐of‐life consequences for treating MUO with Resonance metallic stent (Cook Medical), versus standard JJ stents, from the UK care system perspective, with 3.5% discounting. Deterministic and probabilistic sensitivity analyses were undertaken to assess the effect of uncertainty.ResultsOver 5 years, approximately four fewer repeat surgical interventions were estimated in the metallic stent arm compared with the JJ stent, driving a 23.4% reduction in costs. The mean estimates of costs and benefits indicate that treatment of MUO with Resonance for 5 years is dominant over JJ stents. Over 5 years a cost‐saving of £2164.74 and a health gain of +0.046 quality‐adjusted life years (QALYs) per patient is estimated. With a maximum willingness to pay of £20 k per QALY, a net monetary benefit (NMB) of £3077.83 is estimated. Probabilistic sensitivity analysis at a willingness to pay threshold of £20 000 indicates an 89.3% probability of Resonance being cost‐effective over JJ stents. Within 1‐year savings of £726.53 are estimated driven by a reduction of two fewer repeat surgical interventions when using the metallic stent.ConclusionsResonance metallic stents for the treatment of MUO reduce the number of repeat procedures and could be a cost‐effective option for the treatment, potentially offering efficiencies to the healthcare system.

Influence of lack of blinding on the estimation of medication-related harms: a retrospective cohort study of randomized controlled trials

BackgroundEmpirical evidence suggests that lack of blinding may be associated with biased estimates of treatment benefit in randomized controlled trials, but the influence on medication-related harms is not well-recognized. We aimed to investigate the association between blinding and clinical trial estimates of medication-related harms.MethodsWe searched PubMed from January 1, 2015, till January 1, 2020, for systematic reviews with meta-analyses of medication-related harms. Eligible meta-analyses must have contained trials both with and without blinding. Potential covariates that may confound effect estimates were addressed by restricting trials within the comparison or by hierarchical analysis of harmonized groups of meta-analyses (therefore harmonizing drug type, control, dosage, and registration status) across eligible meta-analyses. The weighted hierarchical linear regression was then used to estimate the differences in harm estimates (odds ratio, OR) between trials that lacked blinding and those that were blinded. The results were reported as the ratio of OR (ROR) with its 95% confidence interval (CI).ResultsWe identified 629 meta-analyses of harms with 10,069 trials. We estimated a weighted average ROR of 0.68 (95% CI: 0.53 to 0.88, P < 0.01) among 82 trials in 20 meta-analyses where blinding of participants was lacking. With regard to lack of blinding of healthcare providers or outcomes assessors, the RORs were 0.68 (95% CI: 0.53 to 0.87, P < 0.01 from 81 trials in 22 meta-analyses) and 1.00 (95% CI: 0.94 to 1.07, P = 0.94 from 858 trials among 155 meta-analyses) respectively. Sensitivity analyses indicate that these findings are applicable to both objective and subjective outcomes.ConclusionsLack of blinding of participants and health care providers in randomized controlled trials may underestimate medication-related harms. Adequate blinding in randomized trials, when feasible, may help safeguard against potential bias in estimating the effects of harms.

Cumulative impacts in environmental justice: Insights from economics and policy

Disparities in health and socioeconomic well-being are a result of the cumulative impacts from multiple coinciding environmental, health, and social stressors. Addressing cumulative impacts is seen as a crucial step toward environmental justice (EJ). Using the case of the United States, we compare different methods to operationalize the concept for real-world application. We empirically demonstrate the extent to which non-White and low-income neighborhoods are subject to a wide array of burdens and how these burdens are reflected in national EJ indices and housing prices. We find that non-White and low-income neighborhoods are correlated with measures of multiple environmental burdens and social stressors but correlate to a lesser extent with natural disaster risk. Two existing EJ indices are only moderately correlated and more correlated with low-income status than with percent non-White. Models that employ the housing market for benefits estimation may fail to capture preferences to avoid multiple stressors due to issues including data availability and market frictions, such as discrimination. Finally, we highlight the challenges in cumulative impacts analysis for research and policy-making.

Evaluating the Effectiveness of Speed Cameras on Philadelphia’s Roosevelt Boulevard

This paper employs Bayesian negative binomial and Poisson models to examine the effectiveness of speed cameras at reducing crashes, injuries, and fatalities on and immediately around Roosevelt Boulevard, a particularly dangerous urban arterial in Philadelphia, PA. Camera installation also coincided with rapidly changing traffic safety outcomes throughout the summer after COVID-19 lockdowns and protests against police violence. To find the most appropriate control segments for our analysis, we use k-means clustering to identify the five most similar roadways. Compared with these roadways and other geographic controls, the treated sections of Roosevelt Boulevard experienced decreased crashes, injuries, and fatalities after camera installation. These decreases are on the high end of what is found in the academic literature on speed cameras. The findings for total crashes, traffic injuries, fatalities, and pedestrian injuries are statistically different from zero with a high degree of confidence. Differences in pedestrian fatalities are statistically different from zero with 90% confidence. Based on our findings, we recommend that the Commonwealth of Pennsylvania and City of Philadelphia extend and expand the automated speed enforcement pilot. Estimates of the economic benefits of reduced crashes substantially exceed the total fines paid by violators. Despite this positive safety effect, additional treatments will be required to make Roosevelt Boulevard substantially safer. The roadway still accounts for around 8% of all traffic fatalities in Philadelphia.

The mortality burden attributable to wood heater smoke particulate matter (PM2.5) in Australia

Air pollution is the leading environmental risk factor for mortality worldwide. In Australia, residential wood heating is the single largest source of pollution in many regions of the country. Estimates around the world and in some limited locations across Australia have shown that the health burden attributable to wood heating PM2.5 is considerable, and that there is great potential to reduce this burden. Here, we aimed to calculate the mortality burden attributable to wood heating emissions (WHE)-related PM2.5 throughout Australia and estimate the potential health benefits of reducing WHE-related air pollution, by replacing wood heaters with cleaner heating technologies. In summary, we used a four-stage process to (1) compile a nationwide WHE inventory, (2) generate annual exposure estimates of WHE-PM2.5, (3) estimate the annual mortality burden attributable to wood heater use across Australia for the year 2015, and (4) assess the potential health benefits of replacing existing wood heaters with cleaner heating technologies. We estimated that population weighted WHE-PM2.5 exposure across Australia for 2015 ranged between 0.62 μg/m3 and 1.35 μg/m3, with differing exposures across State/Territories. We estimated a considerable mortality burden attributable to WHE-PM2.5 ranging between 558 (95 % CI, 364–738) and 1555 (95 % CI, 1180–1740) deaths annually, depending on the scenario assessed. We calculated that replacing 50 % of the current wood heater stock, with zero or lower emission technologies could produce relevant health benefits, of between $AUD 1.61 and $AUD 1.93 billion per year (303–364 attributable deaths). These findings provide a preliminary and likely conservative assessment of the health burden of wood heater smoke across Australia, and an estimation of the potential benefits from replacing the current wood heater stock with cleaner technologies. The results presented here underscore the magnitude of the health burden attributable to wood heating in Australia.

Personalized decision-making for aneurysm treatment of aneurysmal subarachnoid hemorrhage: development and validation of a clinical prediction tool

BackgroundIn patients with aneurysmal subarachnoid hemorrhage suitable for endovascular coiling and neurosurgical clip-reconstruction, the aneurysm treatment decision-making process could be improved by considering heterogeneity of treatment effect and durability of treatment. We aimed to develop and validate a tool to predict individualized treatment benefit of endovascular coiling compared to neurosurgical clip-reconstruction.MethodsWe used randomized data (International Subarachnoid Aneurysm Trial, n = 2143) to develop models to predict 2-month functional outcome and to predict time-to-rebleed-or-retreatment. We modeled for heterogeneity of treatment effect by adding interaction terms of treatment with prespecified predictors and with baseline risk of the outcome. We predicted outcome with both treatments and calculated absolute treatment benefit. We described the patient characteristics of patients with ≥ 5% point difference in the predicted probability of favorable functional outcome (modified Rankin Score 0–2) and of no rebleed or retreatment within 10 years. Model performance was expressed with the c-statistic and calibration plots. We performed bootstrapping and leave-one-cluster-out cross-validation and pooled cluster-specific c-statistics with random effects meta-analysis.ResultsThe pooled c-statistics were 0.72 (95% CI: 0.69–0.75) for the prediction of 2-month favorable functional outcome and 0.67 (95% CI: 0.63–0.71) for prediction of no rebleed or retreatment within 10 years. We found no significant interaction between predictors and treatment. The average predicted benefit in favorable functional outcome was 6% (95% CI: 3–10%) in favor of coiling, but 11% (95% CI: 9–13%) for no rebleed or retreatment in favor of clip-reconstruction. 134 patients (6%), young and in favorable clinical condition, had negligible functional outcome benefit of coiling but had a ≥ 5% point benefit of clip-reconstruction in terms of durability of treatment.ConclusionsWe show that young patients in favorable clinical condition and without extensive vasospasm have a negligible benefit in functional outcome of endovascular coiling – compared to neurosurgical clip-reconstruction – while at the same time having a substantially lower probability of retreatment or rebleeding from neurosurgical clip-reconstruction – compared to endovascular coiling. The SHARP prediction tool (https://sharpmodels.shinyapps.io/sharpmodels/) could support and incentivize a multidisciplinary discussion about aneurysm treatment decision-making by providing individualized treatment benefit estimates.