Benchmark Targets Research Articles

Optimizing crystals-dilithium implementation in 16-bit MSP430 environment utilizing hardware multiplier

Dilithium was selected as one of NIST standard Post Quantum Digital Signature algorithms and is undergoing standardization as a Module Lattice Digital Signature Algorithm (ML-DSA). However, until now research on optimization in embedded environments has primarily been conducted on ARM architectures, which are the basic benchmark targets. To prepare for future quantum secure Internet of Things environments, performance optimization on resource-constrained must be considered. Thus, in this paper, for the first time, we propose an optimized implementation of Dilithium in the 16-bit MSP430 environment, a low-resource device. We redesign the state-of-the-art optimization strategies for Dilithium to suit the MSP430 environment. By taking full advantage of MSP430’s hardware multiplier in the NTT-based polynomial multiplication, we achieve 73.0% and 80.1% of performance improvement for NTT and NTT−1 compared to those in the reference implementation, which contributes about 5.5%–7.0%, 15.3%–17.5%, and 7.5%–10.0% of performance improvement compared to Dilithium’s public reference implementation for keypair generation, signing, and verification, respectively.

Advancing membrane-associated protein docking with improved sampling and scoring in Rosetta.

The oligomerization of protein macromolecules on cell membranes plays a fundamental role in regulating cellular function. From modulating signal transduction to directing immune response, membrane proteins (MPs) play a crucial role in biological processes and are often the target of many pharmaceutical drugs. Despite their biological relevance, the challenges in experimental determination have hampered the structural availability of membrane proteins and their complexes. Computational docking provides a promising alternative to model membrane protein complex structures. Here, we present Rosetta-MPDock, a flexible transmembrane (TM) protein docking protocol that captures binding-induced conformational changes. Rosetta-MPDock samples large conformational ensembles of flexible monomers and docks them within an implicit membrane environment. We benchmarked this method on 29 TM-protein complexes of variable backbone flexibility. These complexes are classified based on the root-mean-square deviation between the unbound and bound states (RMSDUB) as: rigid (RMSDUB <1.2 Å), moderately-flexible (RMSDUB ∈ [1.2, 2.2) Å), and flexible targets (RMSDUB > 2.2 Å). In a local docking scenario, i.e. with membrane protein partners starting ≈10 Å apart embedded in the membrane in their unbound conformations, Rosetta-MPDock successfully predicts the correct interface (success defined as achieving 3 near-native structures in the 5 top-ranked models) for 67% moderately flexible targets and 60% of the highly flexible targets, a substantial improvement from the existing membrane protein docking methods. Further, by integrating AlphaFold2-multimer for structure determination and using Rosetta-MPDock for docking and refinement, we demonstrate improved success rates over the benchmark targets from 64% to 73%. Rosetta-MPDock advances the capabilities for membrane protein complex structure prediction and modeling to tackle key biological questions and elucidate functional mechanisms in the membrane environment. The benchmark set and the code is available for public use at github.com/Graylab/MPDock.

Prenatal detection rates for congenital heart disease using abnormal obstetrical screening ultrasound alone as indication for fetal echocardiography.

To determine the live born prenatal detection rate of significant congenital heart disease (CHD) in a large, integrated, multi-center community-based health system using a strategy of referral only of patients with significant cardiac abnormalities on obstetrical screening ultrasound for fetal echocardiography. Detection rates were assessed for screening in both radiology and maternal fetal medicine (MFM). The impact on fetal echocardiography utilization was also assessed. This was a retrospective cohort study using an electronic health record, outside claims databases and chart review to determine all live births between 2016 and 2020 with postnatally confirmed sCHD that were prenatally detectable and resulted in cardiac surgery, intervention, or death within 1year. There were 214,486 pregnancies resulting in live births. Prenatally detectable significant CHD was confirmed in 294 infants. Of those 183 were detected for an overall live-born detection rate of 62%. Detection rates in MFM were 75% and in radiology were 52%. The number of fetal echocardiograms needed to detect (NND) sCHD was 7. A focus on quality and standardization of obstetrical screening ultrasound with referral to fetal echocardiography for cardiac abnormalities alone achieves benchmark targets for live-born detection of significant CHD requiring fewer fetal echocardiograms.

Constructing a robust data envelopment analysis model to evaluate the profitability efficiency of banks with financial loss

ABSTRACT This paper introduces a robust data envelopment analysis (DEA) model to address the limitations of traditional models in handling nonpositive data and applies it to measure the profitability efficiency of banks, including those facing financial losses. The proposed model offers several advantages over current approaches. The model is designed to resist the influence of extreme values and effectively handle variables with positive values for some banks and nonpositive values for others, can be applied under various returns-to-scale conditions and does not require any prior knowledge, overcomes the lack of translation invariance, considers nonradial input or output slack, and uses benchmark targets with economic interpretation. Numerical examples are provided to illustrate its effectiveness, and the results are compared with those obtained from commonly used methods, highlighting its superior performance in handling nonpositive data. Finally, the proposed method is applied to measure the profitability efficiency of commercial banks, demonstrating its practicality in real-world scenarios.

Supporting Fracture Liaison Services in England and Wales: A role for pharmacists?

Abstract Introduction Fracture Liaison Service (FLS) deliver secondary fracture prevention to adults aged 50 years and over. Performance is measured against ten benchmarks [B1-10]: cases identified [B1], spine fractures [B2], assessment within 90 days [B3], dual x-ray absorptiometry (DXA) within 90 days [B4], falls risk assessment [B5], bone treatment recommended [B6], strength and balance by 16 weeks [B7], 16-week follow-up [B8], treatment by first follow-up [B9] and 1-year drug adherence check [B10]. Each indicator has standards for meeting &amp;gt;80% of target (green), 50-79% (amber) and &amp;lt;50% (red). For Spine fractures [B2], &amp;gt;20% identified denotes green, amber for 11-19% and red for &amp;lt;10%. For bone treatment recommended [B6], green denotes &amp;gt;50% and red &amp;lt;50%. Audit data is uploaded to the Fracture Liaison Service Database (FLS-DB).1 Aim To establish whether FLSs meet performance targets and identify how pharmacists could support the service. Methods This work was done as part of a PhD project at the University of Nottingham looking at how pharmacists could improve osteoporosis medication adherence. Therefore, an existing service which encounters people with osteoporosis (FLS) was investigated to see if it required support. Approval reference: 017-2021. National averages for benchmarks were analysed to see if targets were being met over a 5-year period (2016-2020).1 The Royal Osteoporosis Society (ROS) Clinical Standards for FLSs2 were reviewed to identify areas where pharmacists could support the service. Findings were reviewed by two authors of the Clinical Standards for FLSs. Results Less than half (49%) of FLSs’ in England and Wales submitted data consistently between 2016-2020. Of those who submitted, only recommendations to initiate bone treatment [B6] met the required target (&amp;gt;50% of patients) in 2018 (53%), 2019 (52.4%) and 2020 (52.9%). However, B9: Treatment by 1st follow-up targets were not met. Possibly due to the lack of data for pharmacy support, the ROS Clinical Standards for FLSs do not mention pharmacists. Staffing data shows no pharmacists employed at FLSs. However, the research team identified eleven areas where implementation of referral pathways between community pharmacy (CP) and FLSs could support patient management. These were related to identification of people aged over 50 years with a fragility fracture (1.1), investigations of fragility fracture risk within 12 weeks of a fracture diagnosis (2.1, 2.2), provision of information to patients and healthcare professionals (3.1, 3.2, 3.3, 3.4), interventions such as drug treatment initiation, reviews, referrals to falls prevention services (4.1, 4.2, 4.3) and integration of the wider healthcare system to ensure long term management of osteoporosis (5.1). Multi-disciplinary working and incorporating primary and secondary fracture prevention and medicines review outcomes,3 would help inform transfer of care on this pathway. Discussion/Conclusion FLSs’ needs support to ensure benchmark targets are met especially related to anti-osteoporosis medication initiation and adherence. Due to their expertise, pharmacists could support the FLS, particularly with treatment initiation and adherence related monitoring. Implementation of a two-way referral pathway between FLSs’ and community pharmacy could help improve patient outcomes. Limitation: There is missing data as not all FLSs upload to the FLS-DB.

An analysis of sub-sectoral level carbon budget allocation for India's iron and steel sector

The global carbon budget, defined as the cumulative amount of permissible carbon emissions to meet the temperature targets, is widely used to study climate change. This carbon budget is rapidly decreasing, with a high probability of it getting exhausted in the coming few decades. The extensive use of non-renewable resources has resulted in a rapid depletion of the global carbon budget. Currently, there is a lack of studies assessing the long-term impact of various sectors on the rapidly decreasing global carbon budget. The recent budget estimates have further reduced by 200 GtCO2 in the past decade, creating conflicts among the nations towards getting a higher share of the remaining budget.This study focuses on allocating the global carbon budget to a sub-sectoral level for India's iron and steel sector. First, the global carbon budget is allocated using different approaches, giving India a range of carbon budgets. Further, the allocation is done to the sectoral and sub-sectoral levels to obtain the benchmark targets between 2020 and 2050 from the national carbon budget. Projections have been made for the production capacity and the expected emissions till 2050 for India's iron and steel sector using three scenarios based on specific CO2 emission reduction. The results indicate that the carbon emissions for the “specific CO2 emission stagnation” scenario for 2 °C temperature target are 66% to 726% above the benchmark carbon budget allocated to the iron and steel sector using different allocation methods. The study also shows the benchmark carbon budget of the iron and steel sector for the 2 °C, 1.7 °C, and 1.5 °C temperature targets will deplete between 2023 and 2046 for the different emission scenarios.

Sodium content targets for pre-packaged foods, China: a quantitative study and proposal.

To determine the contribution of pre-packaged foods to population sodium intake in China, and to propose sodium content targets for food subcategories used for the World Health Organization's (WHO's) global sodium benchmarks. The impact of four different approaches to reducing the sodium content of pre-packaged foods on population sodium intake was estimated using data from national databases covering the nutrient content and ingredients of 51 803 food products and food consumption by 15 670 Chinese adults. We recategorized food products using a food categorization framework developed for WHO's global sodium benchmarks and adapted for China-specific foods. Pre-packaged foods, including condiments, contributed 1302.5mg/day of sodium intake per adult in 2021, accounting for 30.1% of population sodium intake in China. Setting maximum sodium content levels using a 90th-percentile target would reduce sodium intake from pre-packaged foods by 96.2mg/day, corresponding to a 1.9% reduction in population intake. Using the 75th-percentile, a fixed 20% reduction and WHO benchmark targets would further reduce intake by 262.0mg/day (5.2% population intake), 302.8mg/day (6.0% population intake) and 701.2mg/day per person (13.9% population intake), respectively. Maximum sodium content levels based on revised 20% reduction targets were proposed because they should result in substantial and acceptable reductions in sodium content for most food subcategories: overall sodium intake would decline by 305.0mg/day per person, and population intake by 6.1%. This study provides the scientific rationale for government policy on setting targets for food sodium content in China. Simultaneous action on discretionary salt use should also be taken.

Exploratory analysis using discrete event simulation modelling of the wait times and service costs associated with the maximum wait time guarantee policy applied in a rheumatology central intake clinic

ABSTRACT Adherence to wait time benchmark targets for the diagnosis and initiation of interventions for rheumatoid arthritis is crucial in altering the disease trajectory. We analysed the impact of the maximum wait time guarantee (MWTG) policy for routing referrals for the initial rheumatologist consults on the waiting and service costs. We modelled a central intake system for a rheumatology clinic as a discrete event simulation (DES) model. Using data from a central intake and rheumatology clinic as input to the model of the system, we simulated the arrival of referrals and rheumatologist visits of patients. We demonstrated the impact of the referral policy on system performance and compared the system costs in an MWTG policy and first-available-appointment policy scenarios. MWTG policy is an option for a wait time management strategy but comes with essential cost considerations. Healthcare managers and policymakers should consider the DES approach to support referral decision policy choices.

AGA Institute Quality Indicator Development and Uses

The Affordable Care Act, which was signed into law in 2010, established several national priorities for health care delivery, including reinforcing the importance of high-value health care. Cost and quality are fundamental functions of value. Although costs may be clearly definable, quality can be more elusive to calculate and measure. The use of structured quality measures, which are standardized tools to quantify health care processes and outcomes, can reduce variability in quality reporting. One prominent example of a gastroenterology-focused quality measure is the adenoma detection rate, which reflects the percentage of average-risk screening colonoscopies in which at least 1 adenoma is detected. Like adenoma detection rate, all quality measures require discrete specifications for calculating a numerator and denominator to allow widespread standardization and reliable measurement across practices. Ultimately, this reproducibility permits the establishment of benchmark targets, which in turn allow insights into variable measure adherence and opportunity to develop and implement improvement.

Symptoms to surgery: factors associated with delays to carotid endarterectomy for symptomatic stenosis in an Irish tertiary vascular centre

Introduction: Carotid endarterectomy (CEA) is the accepted treatment for stroke risk reduction in patients with symptomatic 50–99% carotid artery stenosis. Best practice guidelines recommend surgery be performed within 14 days of index symptoms to achieve maximum benefit; however, achieving this target can be difficult. Late presentation and presentation to hospitals without onsite vascular capabilities are two recurring reasons for delayed CEA across the literature. Methods: All symptomatic CEAs performed between January 2017 and December 2019 were retrospectively extracted from an electronic institutional database and analysed to determine the proportion of CEAs meeting benchmark targets and to assess factors contributing to delays. Results: A total of 124 CEAs were performed for 62 strokes and 62 transient ischaemic attacks (TIAs); 71.8% (n=89) were male and the median (range) age was 71.0 years (43–88). The median delay between initial symptom and CEA was 14 days (range 1–183). Sixty-six patients (55%) had surgery within 14 days of the index symptom. Patients presenting with ‘Face Arms Speech Time’ (FAST) symptoms were significantly more likely to undergo timely CEA, largely due to earlier presentation to hospital (p=0.021, OR 2.563, 95% CI 1.143 to 5.747). Presentation directly to a tertiary vascular centre was significantly associated with CEA within 14 days compared with referrals from external hospitals (p=0.002), with a median symptom-to-surgery interval of 12.0 days and 25.0 days, respectively (p=0.001) Conclusions: Our results are comparable to UK and Australian national audits, although a significant number of CEAs fell outside the 14-day target. Protected pathways between referring hospitals and vascular centres are needed to ensure all patients have equal access to urgent CEA. Designating CEA within 14 days as a key performance indicator for stroke management will hopefully incentivise hospitals to expedite this high-risk cohort. Furthermore, re-auditing with an emphasis on patients turned down for intervention due to recurrent events while awaiting CEA may further highlight the need to prioritise symptomatic carotids.

Synergy and Complementarity between Focused Machine Learning and Physics-Based Simulation in Affinity Prediction.

We present results on the extent to which physics-based simulation (exemplified by FEP+) and focused machine learning (exemplified by QuanSA) are complementary for ligand affinity prediction. For both methods, predictions of activity for LFA-1 inhibitors from a medicinal chemistry lead optimization project were accurate within the applicable domain of each approach. A hybrid model that combined predictions by both approaches by simple averaging performed better than either method, with respect to both ranking and absolute pKi values. Two publicly available FEP+ benchmarks, covering 16 diverse biological targets, were used to test the generality of the synergy. By identifying training data specifically focused on relevant ligands, accurate QuanSA models were derived using ligand activity data known at the time of the original series publications. Results across the 16 benchmark targets demonstrated significant improvements both for ranking and for absolute pKi values using hybrid predictions that combined the FEP+ and QuanSA predicted affinity values. The results argue for a combined approach for affinity prediction that makes use of physics-driven methods as well as those driven by machine learning, each applied carefully on appropriate compounds, with hybrid prediction strategies being employed where possible.

Ligand Strain Energy in Large Library Docking

While small molecule internal strain is crucial to molecular docking, using it in evaluating ligand scores has remained elusive. Here, we investigate a technique that calculates strain using relative torsional populations in the Cambridge Structural Database, enabling fast precalculation of these energies. In retrospective studies of large docking screens of the dopamine D4 receptor and of AmpC β-lactamase, where close to 600 docking hits were tested experimentally, including such strain energies improved hit rates by preferentially reducing the ranks of strained high-scoring decoy molecules. In a 40-target subset of the DUD-E benchmark, we found two thresholds that usefully distinguished between ligands and decoys: one based on the total strain energy of the small molecules and another based on the maximum strain allowed for any given torsion within them. Using these criteria, about 75% of the benchmark targets had improved enrichment after strain filtering. Relying on precalculated population distributions, this approach is rapid, taking less than 0.04 s to evaluate a conformation on a standard core, making it pragmatic for precalculating strain in even ultralarge libraries. Since it is scoring function agnostic, it may be useful to multiple docking approaches; it is openly available at http://tldr.docking.org.

The presence of sodium content and sodium-containing food additives in packaged foods and beverages sold in Turkey

Excess sodium (Na) intake is a significant leading cause of the development of non-communicable diseases. However, there is no scientific evidence on Na content (and its variation) in packaged products sold in Turkey. This study aimed to determine Na levels and Na-containing food additives of packaged products that are available in supermarkets across Turkey in 2020 in addition to evaluating the proportion of foods that comply with the World Health Organization global Na benchmark targets (2021). Of the 2975 packaged products analyzed, 60.3 % of products contained salt and 53.5 % of them contained a Na-containing food additive. A total of 31.8 % of products were classified as having a high Na content and the highest median Na levels were among the soy sauces and fish sauce group (4280 mg/100 g or ml; followed by olive group (2160 mg/100 g or ml), and soft to medium ripened cheese group (1880 mg/100 g or ml). The most used Na-containing food additive was sodium carboxymethyl cellulose. New regulations can be developed for the reformulation of packaged products containing high Na content and the progress of reducing Na intake of the population and improved health outcomes can be monitored over time.

Minimum distance efficiency measure in bank production: A directional slack inefficiency approach

In the non-radial efficiency measurement literature, it is common to estimate technical (in)efficiency by maximising weighted slacks primarily from the computational viewpoint. This means that efficiency measures and targets are obtained based on farthest distance projections. However, when the decision making units (DMUs) operate at less than the efficient scale, such modelling approach can be very restrictive. This paper proposes a minimum distance Data Envelopment Analysis (DEA) model in order to evaluate the efficiency of Japanese banking sector over the period 2013–2019. The proposed model is based on Koopmans notion of strong efficiency. When comparing our findings from the minimum distance slack inefficiency model with those against the traditional slack inefficiency model, we find significant differences. These differences are primarily based on the way the benchmark targets have been set in the two methodological frameworks. Finally our finding brings forward the importance and the implications on bank efficiency measurement, when non-feasible targets are set during the bank efficiency evaluation.

Protein Structure Refinement Using Multi-Objective Particle Swarm Optimization with Decomposition Strategy.

Protein structure refinement is a crucial step for more accurate protein structure predictions. Most existing approaches treat it as an energy minimization problem to intuitively improve the quality of initial models by searching for structures with lower energy. Considering that a single energy function could not reflect the accurate energy landscape of all the proteins, our previous AIR 1.0 pipeline uses multiple energy functions to realize a multi-objectives particle swarm optimization-based model refinement. It is expected to provide a general balanced conformation search protocol guided from different energy evaluations. However, AIR 1.0 solves the multi-objective optimization problem as a whole, which could not result in good solution diversity and convergence on some targets. In this study, we report a decomposition-based method AIR 2.0, which is an updated version of AIR, for protein structure refinement. AIR 2.0 decomposes a multi-objective optimization problem into a number of subproblems and optimizes them simultaneously using particle swarm optimization algorithm. The solutions yielded by AIR 2.0 show better convergence and diversity compared to its previous version, which increases the possibilities of digging out better structure conformations. The experimental results on CASP13 refinement benchmark targets and blind tests in CASP 14 demonstrate the efficacy of AIR 2.0.

M-theory cosmology, octonions, error correcting codes

We study M-theory compactified on twisted 7-tori with G2-holonomy. The effective 4d supergravity has 7 chiral multiplets, each with a unit logarithmic Kähler potential. We propose octonion, Fano plane based superpotentials, codifying the error correcting Hamming (4, 7) code. The corresponding 7-moduli models have Minkowski vacua with one flat direction. We also propose superpotentials based on octonions/error correcting codes for Minkowski vacua models with two flat directions. We update phenomenological α-attractor models of inflation with 3α = 7, 6, 5, 4, 3, 1, based on inflation along these flat directions. These inflationary models reproduce the benchmark targets for detecting B-modes, predicting 7 different values of r=12alpha /{N}_e^2 in the range 10−2 ≳ r ≳ 10−3, to be explored by future cosmological observations.

M-theory, black holes and cosmology.

This paper is dedicated to Michael J. Duff on the occasion of his 70th birthday. I discuss some issues of M-theory/string theory/supergravity closely related to Mike's interests. I describe a relation between STU black hole entropy, the Cayley hyperdeterminant, the Bhargava cube and a three-qubit Alice-Bob-Charlie triality symmetry. I shortly describe my recent work with Gunaydin, Linde and Yamada on M-theory cosmology (Gunaydin et al. 2020 M-theory cosmology, octonions, error-correcting codes (http://arxiv.org/abs/2008.01494)), inspired by the work of Duff with Ferrara and Borsten, Levay, Marrani et al. Here, we have seven-qubits, a party including Alice, Bob, Charlie, Daisy, Emma, Fred and George. Octonions and Hamming error-correcting codes are at the base of these models. They lead to seven benchmark targets of future cosmic microwave background missions looking for primordial gravitational waves from inflation. I also show puzzling relations between the fermion mass eigenvalues in these cosmological models, the exceptional Jordan eigenvalue problem and black hole entropy. The symmetry of our cosmological models is illustrated by beautiful pictures of a Coxeter projection of the root system of E7.

Evaluation of consensus scoring methods for AutoDock Vina, smina and idock

We investigated the application of consensus scoring using the freely available and open source structure-based virtual screening docking programs AutoDock Vina, smina and idock. These individual programs and several simple consensus scoring methods were tested for their ability to identify hits against 20 DUD-E benchmark targets using the AUC and EF1 metrics. We found that all of the consensus scoring methods, however normalized, fared worse, on average, than simply using the output from a single program, smina. Additionally, the effect of a significant increase in the run time of all three programs was tested to find if a longer run time yielded improved results. Our results indicated that a longer run time than the default had little impact on the performance of these three programs or on consensus scoring methods based on their output. Thus, we have found that using the smina program alone at default settings is the best approach for researchers that do not have access to a suite of commercial docking software packages.

Windshield Defrost Simplified CFD Model

Abstract The windshield defrost system, in general, is a vehicle safety feature. Thus, its restricted by variety of directives. However, the OMEs’ benchmark targets could be even more demanding as the deicing process is in addition also part of passengers comfort. From vehicle design point of view the wind-shield defrost system is typically connected to HVAC unit (Heating, Ventilation and Air Conditioning). In the technical solution the windshield is heated via hot air convection. Nevertheless, other methods are becoming more and more popular, like directly heated glass by hot wire ohmic heating (heated glasses). The defrost CFD model should predict the ice layer thickness in time and space and in environmental conditions defined according to appropriate directives and technical solution. The accurate and fast modelling technique is essential part of a vehicle development, especially nowadays, where the optimization techniques area widely used and requires hundreds of simulations runs. Modelling requests are even increasing with modern pure electric vehicles (EVs), were the thermal and energy management is more demanding compared to the classical internal combustion engine (ICE) vehicles. The aim of the work is to verify possibility to model the ice layer thickness with simplified approach, which could be beneficial from computational time burden.

Flemish breast cancer screening programme: 15\u2009years of key performance indicators (2002\u20132016)

BackgroundWe examined 15 years of key performance indicators (KPIs) of the population-based mammography screening programme (PMSP) in Flanders, Belgium.MethodsIndividual screening data were linked to the national cancer registry to obtain oncological follow-up. We benchmarked crude KPI results against KPI-targets set by the European guidelines and KPI results of other national screening programmes. Temporal trends were examined by plotting age-standardised KPIs against the year of screening and estimating the Average Annual Percentage Change (AAPC).ResultsPMSP coverage increased significantly over the period of 15 years (+ 7.5% AAPC), but the increase fell to + 1.6% after invitation coverage was maximised. In 2016, PMSP coverage was at 50.0% and opportunistic coverage was at 14.1%, resulting in a total coverage by screening of 64.2%. The response to the invitations was 49.8% in 2016, without a trend. Recall rate decreased significantly (AAPC -1.5% & -5.0% in initial and subsequent regular screenings respectively) while cancer detection remained stable (AAPC 0.0%). The result was an increased positive predictive value (AAPC + 3.8%). Overall programme sensitivity was stable and was at 65.1% in 2014.In initial screens of 2015, the proportion of DCIS, tumours stage II+, and node negative invasive cancers was 18.2, 31.2, and 61.6% respectively. In subsequent regular screens of 2015, those proportions were 14.0, 24.8, and 65.4% respectively. Trends were not significant.ConclusionBesides a suboptimal attendance rate, most KPIs in the Flemish PMSP meet EU benchmark targets. Nonetheless, there are several priorities for further investigation such as a critical evaluation of strategies to increase screening participation, organising a biennial radiological review of interval cancers, analysing the effect that preceding opportunistic screening has on the KPI for initial screenings, and efforts to estimate the impact on breast cancer mortality.