Extensive red blood cell matching considering patient alloimmunization risk

BACKGROUND AND OBJECTIVES

Red blood cell (RBC) transfusions pose a risk of alloantibody development in patients. For patients with increased alloimmunization risk, extended preventive matching is advised, encompassing not only the ABO-D blood groups but also the most clinically relevant minor antigens: C, c, E, e, K, Fya, Fyb, Jka, Jkb, S and s. This study incorporates patient-specific data and the clinical consequences of mismatching into the allocation process.

MATERIALS AND METHODS

We have redefined the MINimize Relative Alloimmunization Risks (MINRAR) model to include patient group preferences in selecting RBC units from a finite supply. A linear optimization approach was employed, considering both antigen immunogenicity and the clinical impact of mismatches for specific patient groups. We also explore the advantages of informing the blood bank about scheduled transfusions, allowing for a more strategic blood distribution. The model is evaluated using historical data from two Dutch hospitals, measuring shortages and minor antigen mismatches.

RESULTS

The updated model, emphasizing patient group-specific considerations, achieves a similar number of mismatches as the original, yet shifts mismatches among patient groups and antigens, reducing expected alloimmunization consequences. Simultaneous matching for multiple hospitals at the distribution centre level, considering scheduled demands, led to a 30% decrease in mismatches and a 92% reduction in shortages.

CONCLUSION

The reduction of expected alloimmunization consequences by incorporating patient group preferences demonstrates our strategy's effectiveness for patient health. Substantial reductions in mismatches and shortages with multi-hospital collaboration highlights the importance of sharing information in the blood supply chain.

The added value of ferritin levels and genetic markers for the prediction of haemoglobin deferral

BACKGROUND AND OBJECTIVES

On-site haemoglobin deferral for blood donors is sometimes necessary for donor health but demotivating for donors and inefficient for the blood bank. Deferral rates could be reduced by accurately predicting donors' haemoglobin status before they visit the blood bank. Although such predictive models have been published, there is ample room for improvement in predictive performance. We aim to assess the added value of ferritin levels or genetic markers as predictor variables in haemoglobin deferral prediction models.

MATERIALS AND METHODS

Support vector machines with and without this information (the full and reduced model, respectively) are compared in Finland and the Netherlands. Genetic markers are available in the Finnish data and ferritin levels in the Dutch data.

RESULTS

Although there is a clear association between haemoglobin deferral and both ferritin levels and several genetic markers, predictive performance increases only marginally with their inclusion as predictors. The recall of deferrals increases from 68.6% to 69.9% with genetic markers and from 79.7% to 80.0% with ferritin levels included. Subgroup analyses show that the added value of these predictors is higher in specific subgroups, for example, for donors with minor alleles on single-nucleotide polymorphism 17:58358769, recall of deferral increases from 73.3% to 93.3%.

CONCLUSION

Including ferritin levels or genetic markers in haemoglobin deferral prediction models improves predictive performance. The increase in overall performance is small but may be substantial for specific subgroups. We recommend including this information as predictor variables when available, but not to collect it for this purpose only.

Predicting vasovagal reactions to needles with anticipatory facial temperature profiles

Around one-third of adults are scared of needles, which can result in adverse emotional and physical responses such as dizziness and fainting (e.g. vasovagal reactions; VVR) and consequently, avoidance of healthcare, treatments, and immunizations. Unfortunately, most people are not aware of vasovagal reactions until they escalate, at which time it is too late to intervene. This study aims to investigate whether facial temperature profiles measured in the waiting room, prior to a blood donation, can be used to classify who will and will not experience VVR during the donation. Average temperature profiles from six facial regions were extracted from pre-donation recordings of 193 blood donors, and machine learning was used to classify whether a donor would experience low or high levels of VVR during the donation. An XGBoost classifier was able to classify vasovagal groups from an adverse reaction during a blood donation based on this early facial temperature data, with a sensitivity of 0.87, specificity of 0.84, F1 score of 0.86, and PR-AUC of 0.93. Temperature fluctuations in the area under the nose, chin and forehead have the highest predictive value. This study is the first to demonstrate that it is possible to classify vasovagal responses during a blood donation using temperature profiles.

Generating synthetic mixed discrete-continuous health records with mixed sum-product networks

OBJECTIVE

Privacy is a concern whenever individual patient health data is exchanged for scientific research. We propose using mixed sum-product networks (MSPNs) as private representations of data and take samples from the network to generate synthetic data that can be shared for subsequent statistical analysis. This anonymization method was evaluated with respect to privacy and information loss.

MATERIALS AND METHODS

Using a simulation study, information loss was quantified by assessing whether synthetic data could reproduce regression parameters obtained from the original data. Predictors variable types were varied between continuous, count, categorical, and mixed discrete-continuous. Additionally, we measured whether the MSPN approach successfully anonymizes the data by removing associations between background and sensitive information for these datasets.

RESULTS

The synthetic data generated with MSPNs yielded regression results highly similar to those generated with original data, differing less than 5% in most simulation scenarios. Standard errors increased compared to the original data. Particularly for smaller datasets (1000 records), this resulted in a discrepancy between the estimated and empirical standard errors. Sensitive values could no longer be inferred from background information for at least 99% of tested individuals.

DISCUSSION

The proposed anonymization approach yields very promising results. Further research is required to evaluate its performance with other types of data and analyses, and to predict how user parameter choices affect a bias-privacy trade-off.

CONCLUSION

Generating synthetic data from MSPNs is a promising, easy-to-use approach for anonymization of sensitive individual health data that yields informative and private data.

Determining optimal locations for blood distribution centers

BACKGROUND

Blood banks have to be thoughtful about supply chain decisions to effectively satisfy the blood product demand of hospitals. These decisions include the number and locations of distribution centers (DC), as this has a strong impact on both transportation cost and the ability to deliver emergency orders in time.

STUDY DESIGN AND METHODS

We propose a mixed-integer linear programming approach to find optimal DC locations for supplying individual hospitals. The model maximizes the number of hospitals reachable from a DC within a given time-limit, and minimizes transportation cost. The minimal amount of data required is a set of hospital locations. The model can be further attuned to the user's needs by adding various model extensions. The model's use is demonstrated by two case studies, considering the blood banks of the Netherlands and Finland.

RESULTS

For both case studies re-locating the DCs would result in a reduction of transportation cost of about 10% without affecting the reliability of delivery. In addition, to save facility exploitation costs, the number of DCs may be reduced in both countries while maintaining the reliability of delivery. The model was also shown to be robust against changes in hospital ordering behavior.

DISCUSSION

We demonstrated the general usability and added value of the model by successfully optimizing the blood supply chains of the Netherlands and Finland, which differ substantially. Nonetheless, in both countries potential savings in both transportation and facility exploitation cost could be shown. The model code is open source and freely accessible online.

Explainable haemoglobin deferral predictions using machine learning models: Interpretation and consequences for the blood supply

BACKGROUND AND OBJECTIVES

Accurate predictions of haemoglobin (Hb) deferral for whole-blood donors could aid blood banks in reducing deferral rates and increasing efficiency and donor motivation. Complex models are needed to make accurate predictions, but predictions must also be explainable. Before the implementation of a prediction model, its impact on the blood supply should be estimated to avoid shortages.

MATERIALS AND METHODS

Donation visits between October 2017 and December 2021 were selected from Sanquin's database system. The following variables were available for each visit: donor sex, age, donation start time, month, number of donations in the last 24 months, most recent ferritin level, days since last ferritin measurement, Hb at nth previous visit (n between 1 and 5), days since the nth previous visit. Outcome Hb deferral has two classes: deferred and not deferred. Support vector machines were used as prediction models, and SHapley Additive exPlanations values were used to quantify the contribution of each variable to the model predictions. Performance was assessed using precision and recall. The potential impact on blood supply was estimated by predicting deferral at earlier or later donation dates.

RESULTS

We present a model that predicts Hb deferral in an explainable way. If used in practice, 64% of non-deferred donors would be invited on or before their original donation date, while 80% of deferred donors would be invited later.

CONCLUSION

By using this model to invite donors, the number of blood bank visits would increase by 15%, while deferral rates would decrease by 60% (currently 3% for women and 1% for men).

Mapping anticipated advantages and disadvantages of implementation of extensive donor genotyping: A focus group approach

BACKGROUND AND OBJECTIVES

Current genotyping techniques allow typing of all relevant red cell, human leukocyte and platelet antigens in a single analysis. Even genetic markers related to donor health can be added. Implementation of this technology will affect various stakeholders within the transfusion chain. This study aims to systematically map the anticipated advantages and disadvantages of a national rollout of blood group genotyping of donors, which will affect the availability of rare donors and the implementation of an extensively typed blood transfusion policy.

MATERIALS AND METHODS

Two focus-group sessions were held with a wide representation of stakeholders, including representatives of donor and patient organisations. A dedicated software tool was used to collect the reflections of participants on genotyping for blood group antigens and extensive matching. Additionally, stakeholders and experts discussed various prepared propositions. All information collected was categorised.

RESULTS

From 162 statements collected, 59 statements (36%) were labelled as 'hopes' and 77 (48%) as 'fears'. Twenty-six (16%) statements remained unlabelled. The statements were divided in 18 categories under seven main themes: patient health, genotyping, privacy issues and ethical aspects, donor management, inventory management and logistics, hospital and transfusion laboratory and general aspects. The discussion on the propositions was analysed and summarised.

CONCLUSION

Stakeholders believe that a genotyped donor pool can result in a reduction of alloimmunization and higher availability of typed blood products. There are concerns regarding logistics, costs, consent for extended typing, data sharing, privacy issues and donor management. These concerns need to be carefully addressed before further implementation.

A robust autonomous method for blood demand forecasting

Background

Blood supply chain management requires estimates about the demand of blood products. The more accurate these estimates are, the less wastage and fewer shortages occur. While the current literature demonstrates tangible benefits from statistical forecasting approaches, it highlights issues that discourage their use in blood supply chain optimization: there is no single approach that works everywhere, and there are no guarantees that any favorable method performance continues into the future.

Study Design and Methods

We design a novel autonomous forecasting system to solve the aforementioned issues. We show how possible changes in blood demand could affect prediction performance using partly synthetic demand data. We use these data then to investigate the performances of different method selection heuristics. Finally, the performances of the heuristics and single method approaches were compared using historical demand data from Finland and the Netherlands. The development code is publicly accessible.

Results

We find that a shift in the demand signal behavior from stochastic to seasonal would affect the relative performances of the methods. Our autonomous system outperforms all examined individual methods when forecasting the synthetic demand series, exhibiting meaningful robustness. When forecasting with real data, the most accurate methods in Finland and in the Netherlands are the autonomous system and the method average, respectively.

Discussion

Optimal use of method selection heuristics, as with our autonomous system, may overcome the need to constantly supervise forecasts in anticipation of changes in demand while being sufficiently accurate in the absence of such changes.

Associations Between Symptoms, Donor Characteristics and IgG Antibody Response in 2082 COVID-19 Convalescent Plasma Donors

Many studies already reported on the association between patient characteristics on the severity of COVID-19 disease outcome, but the relation with SARS-CoV-2 antibody levels is less clear. To investigate this in more detail, we performed a retrospective observational study in which we used the IgG antibody response from 11,118 longitudinal antibody measurements of 2,082 unique COVID convalescent plasma donors. COVID-19 symptoms and donor characteristics were obtained by a questionnaire. Antibody responses were modelled using a linear mixed-effects model. Our study confirms that the SARS-CoV-2 antibody response is associated with patient characteristics like body mass index and age. Antibody decay was faster in male than in female donors (average half-life of 62 versus 72 days). Most interestingly, we also found that three symptoms (headache, anosmia, nasal cold) were associated with lower peak IgG, while six other symptoms (dry cough, fatigue, diarrhoea, fever, dyspnoea, muscle weakness) were associated with higher IgG concentrations.

Predicting vasovagal reactions to a virtual blood donation using facial image analysis

Background

People with needle fear experience not only anxiety and stress but also vasovagal reactions (VVR), including nausea, dizziness, sweating, pallor changes, or even fainting. However, the mechanism behind needle fear and the VVR response are not yet well understood. The aim of our study was to explore whether fluctuations in facial temperature in several facial regions are related to the level of experienced vasovagal reactions, in a simulated blood donation.

Study design and methods

We recruited 45 students at Tilburg University and filmed them throughout a virtual blood donation procedure using an Infrared Thermal Imaging (ITI) camera. Participants reported their fear of needles and level of experienced vasovagal reactions. ITI data pre‐processing was completed on each video frame by detecting facial landmarks and image alignment before extracting the mean temperature from the six regions of interest.

Results

Temperatures of the chin and left and right cheek areas increased during the virtual blood donation. Mixed‐effects linear regression showed a significant association between self‐reported vasovagal reactions and temperature fluctuations in the area below the nose.

Discussion

Our results suggest that the area below the nose may be an interesting target for measuring vasovagal reactions using video imaging techniques. This is the first in a line of studies, which assess whether it is possible to automatically detect levels of fear and vasovagal reactions using facial imaging, from which the development of e‐health solutions and interventions can benefit.

Extended red blood cell matching for all transfusion recipients is feasible

OBJECTIVE

To demonstrate the feasibility and effectiveness of extended matching of red blood cells (RBC) in practice.

BACKGROUND

At present, alloimmunisation preventing matching strategies are only applied for specific transfusion recipient groups and include a limited number of RBC antigens. The general assumption is that providing fully matched RBC units to all transfusion recipients is not feasible. In this article we refute this assumption and compute the proportion of alloimmunisation that can be prevented, when all donors and transfusion recipients are typed for A, B, D plus twelve minor blood group antigens (C, c, E, e, K, Fy^a , Fy^b , Jk^a , Jk^b , M, S and s).

METHODS

We developed a mathematical model that determines the optimal sequence for antigen matching. The model allows for various matching strategies, issuing policies and inventory sizes.

RESULTS

For a dynamic inventory composition (accounting for randomness in the phenotypes supplied and requested) and an antigen identical issuing policy 97% and 94% of alloimmunisation events can be prevented, when respectively one and two RBC units per recipient are requested from an inventory of 1000 units. Although this proportion decreases with smaller inventory sizes, even for an inventory of 60 units almost 50% of all alloimmunisation events can be prevented.

CONCLUSION

In case antigen of both donors and recipients are comprehensively typed, extended preventive matching is feasible for all transfusion recipients in practice and will significantly reduce transfusion-induced alloimmunisation and (alloantibody-induced) haemolytic transfusion reactions.

Preventing alloimmunization using a new model for matching extensively typed red blood cells

BACKGROUND AND OBJECTIVES

Alloimmunization is a well-known adverse event associated with red blood cell (RBC) transfusions, caused by phenotype incompatibilities between donor and patient RBCs that may lead to haemolytic transfusion reactions on subsequent transfusions. Alloimmunization can be prevented by transfusing fully matched RBC units. Advances in RBC genotyping render the extensive typing of both donors and patients affordable in the foreseeable future. However, the exponential increase in the variety of extensively typed RBCs asks for a software-driven selection to determine the 'best product for a given patient'.

MATERIALS AND METHODS

We propose the MINimize Relative Alloimmunization Risks (MINRAR) model for matching extensively typed RBC units to extensively typed patients to minimize the risk of alloimmunization. The key idea behind this model is to use antigen immunogenicity to represent the clinical implication of a mismatch. Using simulations of non-elective transfusions in Caucasian donor and patient populations, the effect on the alloimmunization rate of the MINRAR model is compared with that of a baseline model that matches antigens A, B and RhD only.

RESULTS

Our simulations show that with the MINRAR model, even for small inventories, the expected number of alloimmunizations can be reduced by 78.3% compared with a policy of only matching on antigens A, B and RhD. Furthermore, a reduction of 93.7% can be achieved when blood is issued from larger inventories.

CONCLUSION

Despite an exponential increase in phenotype variety, matching of extensively typed RBCs can be effectively implemented using our MINRAR model, effectuating a substantial reduction in alloimmunization risk without introducing additional outdating or shortages.

Evaluating privacy of individuals in medical data

Although data protection is compulsory when personal data is shared, there is no systematic method available to evaluate to what extent each individual is at risk of a privacy breach. We use a collection of measures that quantify how much information is needed to uncover sensitive information. Combined with visualization techniques, our approach can be used to perform a detailed privacy analysis of medical data. Because privacy is evaluated per variable, these adjustments can be made while incorporating how likely it is that these variables will be exploited to uncover sensitive information in practice, as is mandatory in the European Union. Additionally, the analysis of privacy can be used to evaluate to what extent knowledge on specific variables in the data can contribute to privacy breaches, which can subsequently guide the use of anonymization techniques, such as generalization.

Not a crystal ball: Mapping opportunities and threats for the future demand of red blood cells in the Netherlands using a scenario approach

BACKGROUND

As Western blood transfusion practices are changing, there is interest and need in anticipating the future demand of blood products and how a blood establishment can actively prepare for various long-term developments. This article provides an overview of how a scenario approach was used to prioritize key categories of drivers for the future demand of red blood cells and the organizational implications thereof for Sanquin, the Dutch national blood establishment.

STUDY DESIGN AND METHODS

Based on previously identified drivers from interviews and a literature review (Step 1), we conducted scenario sessions and a survey to rank a list of drivers ("themes") with its related opportunities and threats (Step 2), to identify mitigating measures per theme through focus groups (Step 3).

RESULTS

In Step 2, 10 themes were found that were classified in terms of importance and uncertainty. These were plotted on a two-dimensional graph with an ellipse to indicate the interquartile ranges per theme. Experts rated the top three most important themes to be the blood supply organization, precision medicine, and red blood cell replacements. In Step 3, focus groups identified specific mitigating measures per theme. These measures had parallel ideas, such as the need for an innovative mentality, internal and external communication and collaboration, and building Sanquin's reputation and trust with the public.

CONCLUSION

Having identified the most important themes with suggestions for mitigating measures, Sanquin can take steps to become adaptive and proactive. Other blood establishments may also use a scenario approach to create contextualized long-term strategies.

West Nile virus and blood transfusion safety: A European perspective

BACKGROUND AND OBJECTIVES

There is a growing concern for the transmission of arboviral infections by blood transfusion in Europe. However, no assessment of the risk of transmission through all European blood supplies has been reported. Risk regulations at a European level should take differences in local transmission risk and the risk of transmission by travelling donors into consideration.

MATERIALS AND METHODS

A risk model and publicly available tool were developed to calculate the risk of transmission by all European blood supplies for arboviral outbreaks within Europe. Data on individual European blood supplies from Council of Europe reports and inter-European travel data from EUROSTAT were used to populate this model.

RESULTS

Each neuroinvasive case of WNV reported in Europe will on average result in 0·43 (95%CI: 0·32-0·55) infected blood product by locally infected donors and 0·010 (95%CI: 0·006-0·015) infected products by travelling donors. On basis of the 1373 neuroinvasive human WNV cases reported in the outbreak of 2018, it is estimated that without safety interventions this outbreak would have resulted in 708 (95%CI: 523-922) infected components derived from resident donors. Noncompliance to European regulations, which requires donor deferral or testing of donors who visited WNV-infected areas, would have resulted in 7.4 (95%CI: 4·7-11·1) infected blood components derived from infectious travelling donors exposed in outbreak areas throughout Europe.

CONCLUSION

The risk of WNV transmission by a local outbreak is on average 113 times (95%CI: 95-139), so two orders of magnitude higher than the risk of transmission by travelling donors in Europe.

Reduction of anti-K-mediated hemolytic disease of newborns after the introduction of a matched transfusion policy: A nation-wide policy change evaluation study in the Netherlands

BACKGROUND

During pregnancy, maternal red blood cell (RBC) antibodies can lead to life-threatening fetal hemolysis and anemia. Women can become immunized by a pregnancy or an unmatched transfusion. Our aim was to quantify the effect of a nationwide K-matched transfusion policy for women of childbearing age potential to prevent K-immunization in pregnancy.

STUDY DESIGN AND METHODS

In this nation-wide policy change evaluation study we determined the occurrence of RBC antibodies before and after introduction of a K-matched transfusion policy and evaluated the cause K alloimmunization 10 years after introduction of this measure. K-matched transfusion for females under 45 years of age is advised in the Dutch transfusion guideline since 2004. We used laboratory data from pregnancies with RBC antibodies identified in the period 1999-2018 obtained as part of a population-based screening program in the Netherlands.

RESULTS

Tests of 36 286 pregnancies produced a positive antibody screening result which concerned anti-K in 1550 pregnancies. The occurrence of anti-K decreased from 67.9 to 20.2 per 100 000 pregnancies. The relative risk reduction was 0.70 which largely exceeded the relative risk reduction of 0.27 for antibodies against RBC antigens for which no preventive matching is required. The number of pregnancies at risk for anti-K-mediated disease decreased from 9.7 to 4.2 per 100 000 pregnancies.

CONCLUSIONS

A K-matched transfusion policy is associated with a major decrease in a number of pregnant women with anti-K and pregnancies at risk for anti-K-mediated disease. A relatively simple measure is now shown to impact prevention of hemolytic disease in the fetus and newborn.

A WHO tool for risk-based decision making on blood safety interventions

Background

Risk‐based decision making is increasingly recognized as key to support national blood policy makers and blood operators concerning the implementation of safety interventions, especially to address emerging infectious threats and new technology opportunities. There is an urgent need for practical decision support tools, especially for low‐ and middle‐income countries that may not have the financial or technical capability to develop risk models. WHO supported the development of such a tool for blood safety. The tool enables users to perform both a quantitative Multi‐Criteria Decision Assessment and a novel step‐by‐step qualitative assessment.

Study Design and Methods

This paper summarizes the content, functionalities, and added value of the new WHO tool. A fictitious case study of a safety intervention to reduce the risk of HIV transmission by transfusion was used to demonstrate the use and usefulness of the tool.

Results

Application of the tool highlighted strengths and weaknesses of both the quantitative and qualitative approaches. The quantitative approach facilitates assessment of the robustness of the decision but lacks nuances and interpretability especially when multiple constraints are taken into consideration. Conversely, while unable to provide an assessment of robustness, the step‐by‐step qualitative approach helps structuring the thought process and argumentation for a preferred intervention in a systematic manner.

Conclusion

The relative strengths and weaknesses of the quantitative and step‐by‐step qualitative approach to risk‐based decision making are complementary and mutually enhancing. A combination of the two approaches is therefore advisable to support the selection of appropriate blood safety interventions for a particular setting.

First results of a ferritin-based blood donor deferral policy in the Netherlands

BACKGROUND

Whole blood donors are at risk of becoming iron deficient. To monitor iron stores, Sanquin implemented a new deferral policy based on ferritin levels, in addition to the traditional hemoglobin measurements.

METHODS

Ferritin levels are determined in every fifth donation, as well as in all first-time donors. Donors with ferritin levels <15 ng/mL (WHO threshold) are deferred for 12 months; those ≥15 and ≤30 ng/mL for 6 months. The first results were analyzed and are presented here.

RESULTS

The results show that 25% of women (N = 20151, 95% CI 24%-25%) and 1.6% of men (N = 10391, 95% CI 1.4%-1.8%) have ferritin levels ≤30 ng/mL at their first blood center visit. For repeat (non-first-time) donors, these proportions are higher: 53% of women (N = 28329, 95% CI 52%-54%) and 42% of men (N = 31089, 95% CI 41%-43%). After a 6-month deferral, in 88% of returning women (N = 3059, 95% CI 87%-89%) and 99% of returning men (N = 3736, 95% CI 98%-99%) ferritin levels were ≥15 ng/mL. After a 12-month deferral, in 74% of returning women (N = 486, 95% CI 70%-78%) and 95% of returning men (N = 479, 95% CI 94%-97%) ferritin levels increased to ≥15 ng/mL.

CONCLUSION

Deferral of donors whose pre-donation ferritin levels were ≤30 ng/mL might prevent donors from returning with ferritin levels <15 ng/mL. This policy is promising to mitigate effects of repeated donations on iron stores.

An assessment of the risk, cost-effectiveness, and perceived benefits of anti-parvovirus B19 tested blood products

BACKGROUND

Parvovirus B19 (B19V) can cause severe anemia, hydrops foetalis, and even death in vulnerable patients. To prevent transfusion-transmitted B19V infection of at-risk patients, B19V antibody screening of blood donors was implemented. The cost-effectiveness of this intervention is unclear, as the likelihood of transmission through blood and subsequent complications for recipients are unknown. This study estimates the cost-effectiveness of anti-B19V donor screening in the Netherlands.

STUDY DESIGN AND METHODS

The estimates needed for the cost-effectiveness model were: the occurrence of B19V in Dutch blood donors, the number of anti-B19V tested products required by hospitals, the likelihood of morbidity and mortality given B19V infection, treatment costs, and screening costs. These estimates were obtained from literature and observational data. When data were unavailable, structured expert judgment elicitation and statistical modeling were applied.

RESULTS

The costs of preventing one transfusion transmitted B19V infection are estimated at €68,942 (€42,045 - €102,080). On average, 1.25 cases of morbidity and 0.12 cases of mortality are prevented annually. Although the perceived risk of transfusion transmitted B19V infection was low, half of the treating physicians favored anti-B19V screening.

CONCLUSION

The estimated mortality and morbidity caused by B19V infection was low in the risk groups. The cost-effectiveness ratio is similar to other blood safety screening measures. No guidance exists to evaluate the acceptability of this ratio. The explicit overview of costs and effects may further guide the discussion of the desirability of B19V safe blood products.

A Conceptual Framework for Optimizing Blood Matching Strategies: Balancing Patient Complications Against Total Costs Incurred

Alloimmunization is currently the most frequent adverse blood transfusion event. Whilst completely matched donor blood would nullify the alloimmunization risk, this is practically infeasible. Current matching strategies therefore aim at matching a limited number of blood groups only, and have evolved over time by systematically including matching strategies for those blood groups for which (serious) alloimmunization complications most frequently occurred. An optimal matching strategy for controlling the risk of alloimmunization however, would balance alloimmunization complications and costs within the entire blood supply chain, whilst fulfilling all practical requirements and limitations. In this article the outline of an integrated blood management model is described and various potential challenges and prospects foreseen with the development of such a model are discussed.

Predicting anti-RhD titers in donors: Boostering response and decline rates are personal

Background

Anti-RhD immunised donors provide anti-RhD immunoglobulins used for the prevention of rhesus disease. These donors are periodically hyper-immunised (boostered) to retain a high titer level of anti-RhD.

Study design and methods

We analysed anti-RhD donor records from 1998 to 2016, consisting of 30,116 anti-RhD titers from 755 donors, encompassing 3,372 booster events. Various models were fit to these data to allow describing the anti-RhD titers over time.

Results

A random effects model with a log-linear anti-RhD titer decline over time and a saturating titer response to boostering is shown to fit the data well. This model contains two general model parameters, relating timing and maximum of the booster effect, as well as two parameters characterizing the individual donor, namely how fast the booster effect saturates with current titer and the anti-RhD decline rate. The average individual log₂ decline is 0.55 per year, i.e. a 32% decline in absolute titer, with half of the donors declining between 13% and 41% per year. Their anti-RhD titer peaks around 26 days following a booster event. Boostering response reduces with higher titers at boostering; at median titer (log₂ 11) the mean increase per booster is log₂ 0.38, that is from an absolute titer of 2048 to 2665 (+30%), with half of all donors increasing between 16% and 65% in their titer.

Conclusion

The model describes anti-RhD titer change per individual with only four parameters, two of which are donor specific. This information can be used to enhance the blood bank’s immunisation programme, by deriving individualized immunization policies in which boostering is adjusted to the anticipated anti-RhD decline, effectiveness of boostering and titer levels required.

Why was this transfusion given? Identifying clinical indications for blood transfusion in health care data

Background

To enhance the utility of transfusion data for research, ideally every transfusion should be linked to a primary clinical indication. In electronic patient records, many diagnostic and procedural codes are registered, but unfortunately, it is usually not specified which one is the reason for transfusion. Therefore, a method is needed to determine the most likely indication for transfusion in an automated way.

Study design and methods

An algorithm to identify the most likely transfusion indication was developed and evaluated against a gold standard based on the review of medical records for 234 cases by 2 experts. In a second step, information on misclassification was used to fine-tune the initial algorithm. The adapted algorithm predicts, out of all data available, the most likely indication for transfusion using information on medical specialism, surgical procedures, and diagnosis and procedure dates relative to the transfusion date.

Results

The adapted algorithm was able to predict 74.4% of indications in the sample correctly (extrapolated to the full data set 75.5%). A kappa score, which corrects for the number of options to choose from, was found of 0.63. This indicates that the algorithm performs substantially better than chance level.

Conclusion

It is possible to use an automated algorithm to predict the indication for transfusion in terms of procedures and/or diagnoses. Before implementation of the algorithm in other data sets, the obtained results should be externally validated in an independent hospital data set.

The Impact of Decision Makers' Constraints on the Outcome of Value of Information Analysis

BACKGROUND

When proven effective, decision making regarding reimbursement of new health technology typically involves ethical, social, legal, and health economic aspects and constraints. Nevertheless, when applying standard value of information (VOI) analysis, the value of collecting additional evidence is typically estimated assuming that only cost-effectiveness outcomes guide such decisions.

OBJECTIVES

To illustrate how decision makers' constraints can be incorporated into VOI analyses and how these may influence VOI outcomes.

METHODS

A simulation study was performed to estimate the cost-effectiveness of a new hypothetical technology compared with usual care. Constraints were defined for the new technology on 1) the maximum acceptable rate of complications and 2) the maximum acceptable additional budget. The expected value of perfect information (EVPI) for the new technology was estimated in various scenarios, both with and without incorporating these constraints.

RESULTS

For a willingness-to-pay threshold of €20,000 per quality-adjusted life-year, the probability that the new technology was cost-effective equaled 57%, with an EVPI of €1868 per patient. Applying the complication rate constraint reduced the EVPI to €1137. Similarly, the EVPI reduced to €770 when applying the budget constraint. Applying both constraints simultaneously further reduced the EVPI to €318.

CONCLUSIONS

When decision makers explicitly apply additional constraints, beyond a willingness-to-pay threshold, to reimbursement decisions, these constraints can and should be incorporated into VOI analysis as well, because they may influence VOI outcomes. This requires continuous interaction between VOI analysts and decision makers and is expected to improve both the relevance and the acceptance of VOI outcomes.

Direct costs of transfusion reactions - an expert judgement approach

BACKGROUND AND OBJECTIVES

Despite increasingly meticulous haemovigilance reporting throughout the world, a systematic assessment of the cost of transfusion reactions is still lacking. This is partly caused by the fact that such an assessment requires a subjective expert assessment of the additional costs linked to the adverse reaction. Data on the cost of transfusion reactions could support decision-making regarding blood transfusion safety measures.

MATERIALS AND METHODS

Thirteen experts from nine hospitals were asked to estimate the additional care required following various types of transfusion reactions. Additional care was quantified as the proportion of reactions requiring care, and the amount of care required (e.g. hospitalization days, additional physician's time). Experts were also asked to provide, per type of transfusion reaction, an estimate of the proportion of transfusion reactions preventable. Structured quantitative expert elicitation methods were applied to obtain and combine expert estimates.

RESULTS

The estimated annual in-hospital cost of transfusion reactions in the Netherlands is €933 356 per year (€1.52 per transfusion). Two-thirds (64%) of these are incurred by non-serious transfusion reactions. Circulatory overload, TRALI and anaphylaxis clearly dominate the costs of serious adverse transfusion reactions (66% in total); non-haemolytic transfusion reactions incur 46% of the cost of non-serious transfusion reactions. Additional safety measures targeting circulatory overload and new antibody formation potentially offer the highest cost reduction.

CONCLUSION

In-hospital costs of transfusion reactions are substantial but contribute to less than 1% of the total cost of transfusion in the Netherlands. A considerable part of these costs (24%) might be preventable.

Impairment of the chondrogenic phase of endochondral ossification in vivo by inhibition of cyclooxygenase-2

Many studies have reported on the effects of cyclooxygenase-2 (COX-2) inhibition on osteogenesis. However, far less is known about the effects of COX-2 inhibition on chondrogenic differentiation. Previous studies conducted by our group show that COX-2 inhibition influences in vitro chondrogenic differentiation. Importantly, this might have consequences on endochondral ossification processes occurring in vivo, such as bone fracture healing, growth plate development and ectopic generation of cartilage. The goal of our study was to investigate, in vivo, the effect of COX-2 inhibition by celecoxib on the cartilaginous phase of three different endochondral ossification scenarios. 10 mg/kg/day celecoxib or placebo were orally administered for 25 d to skeletally-immature New Zealand White rabbits (n = 6 per group). Endochondral ossification during fracture healing of a non-critical size defect in the ulna, femoral growth plate and ectopically-induced cartilaginous tissue were examined by radiography, micro-computed tomography (µ-CT), histology and gene expression analysis. Celecoxib treatment resulted in delayed bone fracture healing, alterations in growth plate development and progression of mineralisation. In addition, chondrogenic differentiation of ectopically-induced cartilaginous tissue was severely impaired by celecoxib. In conclusion, we found that celecoxib impaired the chondrogenic phase of endochondral ossification.

Insight into "Calculated Risk": An Application to the Prioritization of Emerging Infectious Diseases for Blood Transfusion Safety

Increasing identification of transmissions of emerging infectious diseases (EIDs) by blood transfusion raised the question which of these EIDs poses the highest risk to blood safety. For a number of the EIDs that are perceived to be a threat to blood safety, evidence on actual disease or transmission characteristics is lacking, which might render measures against such EIDs disputable. On the other hand, the fact that we call them "emerging" implies almost by definition that we are uncertain about at least some of their characteristics. So what is the relative importance of various disease and transmission characteristics, and how are these influenced by the degree of uncertainty associated with their actual values? We identified the likelihood of transmission by blood transfusion, the presence of an asymptomatic phase of infection, prevalence of infection, and the disease impact as the main characteristics of the perceived risk of disease transmission by blood transfusion. A group of experts in the field of infectious diseases and blood transfusion ranked sets of (hypothetical) diseases with varying degrees of uncertainty associated with their disease characteristics, and used probabilistic inversion to obtain probability distributions for the weight of each of these risk characteristics. These distribution weights can be used to rank both existing and newly emerging infectious diseases with (partially) known characteristics. Analyses show that in case there is a lack of data concerning disease characteristics, it is the uncertainty concerning the asymptomatic phase and the disease impact that are the most important drivers of the perceived risk. On the other hand, if disease characteristics are well established, it is the prevalence of infection and the transmissibility of the disease by blood transfusion that will drive the perceived risk. The risk prioritization model derived provides an easy to obtain and rational expert assessment of the relative importance of an (emerging) infectious disease, requiring only a limited amount of information. Such a model might be used to justify a rational and proportional response to an emerging infectious disease, especially in situations where little or no specific information is available.

Validation of multisource electronic health record data: an application to blood transfusion data

Background

Although data from electronic health records (EHR) are often used for research purposes, systematic validation of these data prior to their use is not standard practice. Existing validation frameworks discuss validity concepts without translating these into practical implementation steps or addressing the potential influence of linking multiple sources. Therefore we developed a practical approach for validating routinely collected data from multiple sources and to apply it to a blood transfusion data warehouse to evaluate the usability in practice.

Methods

The approach consists of identifying existing validation frameworks for EHR data or linked data, selecting validity concepts from these frameworks and establishing quantifiable validity outcomes for each concept. The approach distinguishes external validation concepts (e.g. concordance with external reports, previous literature and expert feedback) and internal consistency concepts which use expected associations within the dataset itself (e.g. completeness, uniformity and plausibility). In an example case, the selected concepts were applied to a transfusion dataset and specified in more detail.

Results

Application of the approach to a transfusion dataset resulted in a structured overview of data validity aspects. This allowed improvement of these aspects through further processing of the data and in some cases adjustment of the data extraction. For example, the proportion of transfused products that could not be linked to the corresponding issued products initially was 2.2% but could be improved by adjusting data extraction criteria to 0.17%.

Conclusions

This stepwise approach for validating linked multisource data provides a basis for evaluating data quality and enhancing interpretation. When the process of data validation is adopted more broadly, this contributes to increased transparency and greater reliability of research based on routinely collected electronic health records.

Electronic supplementary material

The online version of this article (doi:10.1186/s12911-017-0504-7) contains supplementary material, which is available to authorized users.

Development of a web-based application and multicountry analysis framework for assessing interdicted infections and cost-utility of screening donated blood for HIV, HCV and HBV

BACKGROUND AND OBJECTIVES

Most countries test donations for HIV, HCV and HBV using serology with or without nucleic acid testing (NAT). Cost-utility analyses provide information on the relative value of different screening options. The aim of this project was to develop an open access risk assessment and cost-utility analysis web-tool for assessing HIV, HCV and HBV screening options (http://www.isbtweb.org/working-parties/transfusion-transmitted-infectious-diseases/). An analysis for six countries (Brazil, Ghana, the Netherlands, South Africa, Thailand and USA) was conducted.

MATERIALS AND METHODS

Four strategies; (1) antibody assays (Abs) for HIV and HCV + HBsAg, (2) antibody assays that include antigens for HIV and HCV (Combo) + HBsAg, (3) NAT in minipools of variable size (MP NAT) and (4) individual donation (ID) NAT can be evaluated using the tool. Country-specific data on donors, donation testing results, recipient outcomes and costs are entered using the online interface. Results obtained include the number infections interdicted using each screening options, and the (incremental and average) cost-utility of the options.

RESULTS

In each of the six countries evaluated, the use of antibody assays is cost effective or even cost saving. NAT has varying cost-utility depending on the setting, and where adopted, the incremental cost-utility exceeds any previously defined or proposed threshold in each country.

CONCLUSION

The web-tool allows an assessment of infectious units interdicted and value for money of different testing strategies. Regardless of gross national income (GNI) per capita, countries appear willing to dedicate healthcare resources to blood supply safety in excess of that for other sectors of health care.

Protocol for a national blood transfusion data warehouse from donor to recipient

INTRODUCTION

Blood transfusion has health-related, economical and safety implications. In order to optimise the transfusion chain, comprehensive research data are needed. The Dutch Transfusion Data warehouse (DTD) project aims to establish a data warehouse where data from donors and transfusion recipients are linked. This paper describes the design of the data warehouse, challenges and illustrative applications.

STUDY DESIGN AND METHODS

Quantitative data on blood donors (eg, age, blood group, antibodies) and products (type of product, processing, storage time) are obtained from the national blood bank. These are linked to data on the transfusion recipients (eg, transfusions administered, patient diagnosis, surgical procedures, laboratory parameters), which are extracted from hospital electronic health records.

APPLICATIONS

Expected scientific contributions are illustrated for 4 applications: determine risk factors, predict blood use, benchmark blood use and optimise process efficiency. For each application, examples of research questions are given and analyses planned.

CONCLUSIONS

The DTD project aims to build a national, continuously updated transfusion data warehouse. These data have a wide range of applications, on the donor/production side, recipient studies on blood usage and benchmarking and donor-recipient studies, which ultimately can contribute to the efficiency and safety of blood transfusion.

Modelling lifelong effects of different prophylactic treatment strategies for severe haemophilia A

BACKGROUND

Lifelong prophylactic replacement therapy with clotting factor concentrates is recommended for severe haemophilia. The prophylactic dose determines both clinical outcome and treatment cost. In the absence of clinical studies, computer simulation was used to explore lifelong effects and clotting factor consumption for various prophylactic dose levels, and optimize strategies for switching between prophylactic and on-demand treatment.

DESIGN AND METHODS

Individual patients' lifetime joint bleeds, radiological arthropathy (Pettersson score, 0-78) and consumption were simulated for each treatment strategy. Treatment effectiveness (expressed as % of patients maintaining a lifetime Pettersson score ≤14) and clotting factor consumption were modelled for lifelong prophylaxis at dose levels 1000-4500 IU kg(-1) year(-1) , for on-demand treatment and for switching strategies. Treatment efficiency (consumption per unit of effectiveness) was used to compare strategies.

RESULTS

Compared to lifelong on-demand treatment, lifelong prophylaxis at 1000 IU kg(-1) year(-1) increased effectiveness from 21 to 36%, at an additional consumption of 0.9 × 10(6) IU kg(-1) . For lifelong prophylaxis, each additional 1000 IU kg(-1) year(-1) resulted in a proportional increase in consumption by ±5 × 10(6) IU kg(-1) but a less than proportional reduction in arthropathy by ±50%; consequently, increasing consumption progressively diminished treatment efficiency. Switching strategies slightly reduce effectiveness and consumption. Optimum switching criteria were similar across prophylactic dose levels.

CONCLUSION

According to the simulation model, low-dose prophylaxis (1000 IU kg(-1) year(-1) ) improved outcome at a limited increase in consumption compared to on-demand treatment. Increasing prophylactic dose further improved health outcomes, but at decreasing efficiency. Optimal prophylactic dose should therefore be selected balancing acceptable health impact and available budget.

A novel approach to detect test-seeking behaviour in the blood donor population: making the invisible visible

BACKGROUND AND OBJECTIVES

Individuals may donate blood in order to determine their infection status after exposure to an increased infection risk. Such test-seeking behaviour decreases transfusion safety. Instances of test seeking are difficult to substantiate as donors are unlikely to admit to such behaviour. However, manifestation in a population of repeat donors may be determined using statistical inference.

MATERIALS AND METHODS

Test-seeking donors would be highly motivated to donate following infection risk, influencing the timing of their donation. Donation intervals within 2005-2014 of all Dutch blood donors who acquired syphilis (N = 50), HIV (N = 13), HTLV (N = 4) or HCV (N = 2) were compared to donation intervals of uninfected blood donors (N = 7 327 836) using the Anderson-Darling test. We adjusted for length bias as well as for age, gender and donation type of the infected. Additionally, the power of the proposed method was investigated by simulation.

RESULTS

Among the Dutch donors who acquired infection, we found only a non-significant overrepresentation of short donation intervals (P = 0·54). However, we show by simulation that both relatively short and long donation intervals among infected donors can reveal test seeking. The power of the method is >90% if among 69 infected donors >35 (51%) are test seeking, or if among 320 infected donors >90 (30%) are test seeking.

CONCLUSION

We show how statistical analysis may be used to reveal the extent of test seeking in repeat blood donor populations. In the Dutch setting, indications for test-seeking behaviour were not statistically significant. This may, however, be due to the low number of infected individuals.

A consensus-based tool for ranking the risk of blood-transmissible infections

BACKGROUND

Emerging infectious diseases (EIDs) pose a threat to blood transfusion safety. Despite a lack of evidence, safety interventions may be required. However, what should decision makers base their decisions on? A model was developed that allows valuing the perceived risk of an EID for blood safety as derived from a group of experts. The model requires estimates of four disease characteristics and the accuracy of these estimates.

STUDY DESIGN AND METHODS

Sixteen selected experts ranked 24 hypothetical diseases, each comprising a quantitative estimate of four characteristics: transfusion transmissibility, proportion of asymptomatic infectious phase, prevalence of infection, and disease impact. Each of the characteristics was expressed at one of six predefined levels with varying ranges of uncertainty. The model was derived using probabilistic inversion and was applied to value the perceived risk of most currently known EIDs relevant to blood transfusion.

RESULTS

The model demonstrated that transmissibility and prevalence are the most important risk drivers. However, disease impact and likelihood of transmission during the asymptomatic phase of infection are more important when the disease characteristics are unknown. In the ranking of currently known EIDs, diseases that have been identified previously as posing a serious risk to blood transfusion appear at the top of the list.

CONCLUSION

With the current model, the perceived risk of EIDs for transfusion safety can be determined for both known and unknown diseases, even when little information is available. Extension of the expert base, further model development and validation, and continuous updating of the model are recommended.

Prediction of the anti-RhD donor population size for managerial decision-making

BACKGROUND

Rhesus D (RhD)-negative women pregnant with a RhD-positive child receive prophylactic injections to prevent haemolytic disease of the newborn. Because of the success of the prophylaxis, the number of naturally immunized women has decreased, thereby also decreasing the number of potential donors who provide the plasma from which the prophylaxis is made. As the current donor pool is ageing, the availability of the prophylaxis is threatened.

OBJECTIVES

Objectives are to investigate whether the anti-D population and the changes therein can be described by a relatively simple model, to determine the impact of ageing of the anti-D donors on the decline of the population and how many new donors should be recruited to meet future supply demand.

METHODS

Data on Dutch anti-D donors in 1994-2013 were used to simulate the donor population size and age composition for various donor recruitment scenarios.

RESULTS

With a continuous influx of 27 new donors per year and a donor stopping rate of 10% per year, the population size will stabilize at 195 donors, with 2·3% of donors stopping annually due to reaching the donor age limit. A formula is derived to estimate which donor recruitment and retention efforts are required to maintain a prespecified donor pool.

CONCLUSION

A relatively simple model can already describe and predict the size of the anti-D donor population and the impact of ageing accurately.

Modelling the risk of transfusion transmission from travelling donors

Background

The EUFRAT (European Up-Front Risk Assessment Tool) was developed as an online risk assessment tool (http://eufrattool.ecdc.europa.eu) to help decision-makers assess the transmission risk of emerging infectious diseases (EID) through blood transfusion. The aim of this study is to extend the methodology developed in the EUFRAT project to quantify the transfusion transmission (TT) risk from travelling donors.

Methods

A generic model for estimating the TT risk from a group of travelling donors that visited an EID risk area was developed. In addition, the new model distinguishes projected future transmissions from those that have already occurred. As an illustration the model was applied to the outbreaks of chikungunya in Italy in 2007 and Q fever in the Netherlands in 2007–2009.

Results

Formulas for calculating the travelling donors’ TT risk were derived. For the chikungunya outbreak in Italy an early intervention (at the end of week 7 after the start of the outbreak, so after only 19 % of all cases) would have been required to prevent only 41 % of all expected transmissions at that time. For Q fever, in which the transmission of chronic Q fever is considered, even at the end of the third annual outbreak’s peak 47 % of all (chronic) Q fever transmissions could still be prevented.

Conclusions

The updated model allows estimation of the infection transmission risk from travelling donors. In combination with the distinction between past and future transmissions, these estimates provide valuable information to support decisions concerning communication with the public and/or the implementation of safety interventions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-016-1452-z) contains supplementary material, which is available to authorized users.

Impact of using different blood donor subpopulations and models on the estimation of transfusion transmission residual risk of human immunodeficiency virus, hepatitis B virus, and hepatitis C virus in Zimbabwe

BACKGROUND

Various models for estimating the residual risk (RR) of transmission of infections by blood transfusion have been published mainly based on data from high-income countries. However, to obtain the data required for such an assessment remains challenging for most developing settings. The National Blood Service Zimbabwe (NBSZ) adapted a published incidence-window period (IWP) model, which has less demanding data requirements. In this study we assess the impact of various definitions of blood donor subpopulations and models on RR estimates. We compared the outcomes of two published models and an adapted NBSZ model.

STUDY DESIGN AND METHODS

The Schreiber IWP model (Model 1), an amended version (Model 2), and an adapted NBSZ model (Model 3) were applied. Variably the three models include prevalence, incidence, preseroconversion intervals, mean lifetime risk, and person-years at risk. Annual mean RR estimates and 95% confidence intervals for each of the three models for human immunodeficiency virus (HIV), hepatitis B virus (HBV), and hepatitis C virus (HCV) were determined using NBSZ blood donor data from 2002 through 2011.

RESULTS

The annual mean RR estimates for Models 1 through 3 were 1 in 6542, 5805, and 6418, respectively for HIV; 1 in 1978, 2027, and 1628 for HBV; and 1 in 9588, 15,126, and 7750, for HCV.

CONCLUSIONS

The adapted NBSZ model provided comparable results to the published methods and these highlight the high occurrence of HBV in Zimbabwe. The adapted NBSZ model could be used as an alternative to estimate RRs when in settings where two repeat donations are not available.

Estimating the risk of dengue transmission from Dutch blood donors travelling to Suriname and the Dutch Caribbean

BACKGROUND

The risk of dengue transmitted by travellers is known. Methods to estimate the transmission by transfusion (TT) risk from blood donors travelling to risk areas are available, for instance, the European Up-Front Risk Assessment Tool (EUFRAT). This study aimed to validate the estimated risk from travelling donors obtained from EUFRAT.

METHODS

Surveillance data on notified dengue cases in Suriname and the Dutch Caribbean islands (Aruba, Curaçao, St. Maarten, Bonaire, St. Eustatius and Saba) in 2001-2011 was used to calculate local incidence rates. Information on travel and donation behaviour of Dutch donors was collected. With the EUFRAT model, the TT risks from Dutch travelling donors were calculated. Model estimates were compared with the number of infections in Dutch travellers found by laboratory tests in the Netherlands.

RESULTS

The expected cumulative number of donors becoming infected during travels to Suriname and the Dutch Caribbean from 2001 to 2011 was estimated at 5 (95% CI, 2-11) and 86 (45-179), respectively. The infection risk inferred from the laboratory-based study was 19 (9-61) and 28 (14-92). Given the independence of the data sources, these estimates are remarkably close. The model estimated that 0·02 (0·001-0·06) and 0·40 (0·01-1·4) recipients would have been infected by these travelling donors.

CONCLUSIONS

The EUFRAT model provided an estimate close to actual observed number of dengue infections. The dengue TT risk among Dutch travelling donors can be estimated using basic transmission, travel and donation information. The TT risk from Dutch donors travelling to Suriname and the Dutch Caribbean is small.

Aiming for a representative sample: Simulating random versus purposive strategies for hospital selection

Background

A ubiquitous issue in research is that of selecting a representative sample from the study population. While random sampling strategies are the gold standard, in practice, random sampling of participants is not always feasible nor necessarily the optimal choice. In our case, a selection must be made of 12 hospitals (out of 89 Dutch hospitals in total). With this selection of 12 hospitals, it should be possible to estimate blood use in the remaining hospitals as well. In this paper, we evaluate both random and purposive strategies for the case of estimating blood use in Dutch hospitals.

Methods

Available population-wide data on hospital blood use and number of hospital beds are used to simulate five sampling strategies: (1) select only the largest hospitals, (2) select the largest and the smallest hospitals (‘maximum variation’), (3) select hospitals randomly, (4) select hospitals from as many different geographic regions as possible, (5) select hospitals from only two regions. Simulations of each strategy result in different selections of hospitals, that are each used to estimate blood use in the remaining hospitals. The estimates are compared to the actual population values; the subsequent prediction errors are used to indicate the quality of the sampling strategy.

Results

The strategy leading to the lowest prediction error in the case study was maximum variation sampling, followed by random, regional variation and two-region sampling, with sampling the largest hospitals resulting in the worst performance. Maximum variation sampling led to a hospital level prediction error of 15 %, whereas random sampling led to a prediction error of 19 % (95 % CI 17 %-26 %). While lowering the sample size reduced the differences between maximum variation and the random strategies, increasing sample size to n = 18 did not change the ranking of the strategies and led to only slightly better predictions.

Conclusions

The optimal strategy for estimating blood use was maximum variation sampling. When proxy data are available, it is possible to evaluate random and purposive sampling strategies using simulations before the start of the study. The results enable researchers to make a more educated choice of an appropriate sampling strategy.

Electronic supplementary material

The online version of this article (doi:10.1186/s12874-015-0089-8) contains supplementary material, which is available to authorized users.

Two decades of risk factors and transfusion-transmissible infections in Dutch blood donors

BACKGROUND

Risk behavior-based donor selection procedures are widely used to mitigate the risk of transfusion-transmissible infections (TTIs), but their effectiveness is disputed in countries with low residual risks of TTIs.

STUDY DESIGN AND METHODS

In 1995 to 2014, Dutch blood donors infected with hepatitis B virus (HBV), hepatitis C virus (HCV), human immunodeficiency virus (HIV), human T-lymphotropic virus (HTLV), or syphilis were interviewed by trained medical counselors to identify risk factors associated with TTIs. Trends in the prevalence and incidence of TTIs were analyzed using binomial regression models.

RESULTS

A total of 972 new donors and 381 repeat donors had TTIs. New donors had higher rates of TTIs compared to repeat donors. Although the HBV and HCV prevalence gradually decreased over time, the incidence of all five TTIs remained stable during the past two decades. In new donors the TTIs had the following risk profiles: "blood-blood contact" for HCV, "unprotected sex" for HIV and syphilis, and "country of birth" for HBV and HTLV. In infected repeat donors, sexual risk factors predominated for all TTIs. At posttest counseling, 28% of infected repeat donors admitted to risk factors leading to permanent donor exclusion if revealed during the donor selection procedure (predominantly male-to-male sex and recent diagnosis of syphilis).

CONCLUSION

The prevalence and incidence of TTIs among Dutch blood donors are six- to 60-fold lower than in the general Dutch population, illustrating the effectiveness of donor selection procedures. However, at least a quarter of infected donors appeared noncompliant to the donor health questionnaire (DHQ), suggesting that DHQs, or the way donor questioning is implemented, can be improved.

Estimating unknown parameters in haemophilia using expert judgement elicitation

The increasing attention to healthcare costs and treatment efficiency has led to an increasing demand for quantitative data concerning patient and treatment characteristics in haemophilia. However, most of these data are difficult to obtain. The aim of this study was to use expert judgement elicitation (EJE) to estimate currently unavailable key parameters for treatment models in severe haemophilia A. Using a formal expert elicitation procedure, 19 international experts provided information on (i) natural bleeding frequency according to age and onset of bleeding, (ii) treatment of bleeds, (iii) time needed to control bleeding after starting secondary prophylaxis, (iv) dose requirements for secondary prophylaxis according to onset of bleeding, and (v) life-expectancy. For each parameter experts provided their quantitative estimates (median, P10, P90), which were combined using a graphical method. In addition, information was obtained concerning key decision parameters of haemophilia treatment. There was most agreement between experts regarding bleeding frequencies for patients treated on demand with an average onset of joint bleeding (1.7 years): median 12 joint bleeds per year (95% confidence interval 0.9-36) for patients ≤ 18, and 11 (0.8-61) for adult patients. Less agreement was observed concerning estimated effective dose for secondary prophylaxis in adults: median 2000 IU every other day The majority (63%) of experts expected that a single minor joint bleed could cause irreversible damage, and would accept up to three minor joint bleeds or one trauma related joint bleed annually on prophylaxis. Expert judgement elicitation allowed structured capturing of quantitative expert estimates. It generated novel data to be used in computer modelling, clinical care, and trial design.

Modeling the transmission risk of emerging infectious diseases through blood transfusion

BACKGROUND

A timely risk assessment is desired to guide decisions on preventive transfusion safety measures during emerging infectious disease (EID) outbreaks. The European Up-Front Risk Assessment Tool (EUFRAT) model was developed to provide quantitative transmission risk estimates of EIDs through blood transfusion.

STUDY DESIGN AND METHODS

The generic model comprises five sequential steps to estimate the infection risks in the blood transfusion chain: 1) the prevalence of infection in the donor population, 2) the risk of obtaining infected donations, 3) infected components, 4) infected blood products, and 5) the risk of transmitting the infection to recipients. The model uses inputs from epidemiologic characteristics of an EID and transfusion practice. The model was applied to data from a recent chikungunya outbreak in Italy.

RESULTS

Based on data from the outbreak peak, an estimated prevalence of 1.07 (95% confidence interval [CI], 0.38-2.03) per 100,000 donors would lead to 0.04 infected donations (95% CI, 0.01-0.10), 0.13 infected blood components, 0.13 infected end products, and 0.0001 severe infections in recipients. This estimated risk can be reduced by increasing the duration of quarantine of the donated blood and becomes zero after 7 or more days of quarantine. The model also estimated the probability of a donor returning from the outbreak area and subsequently donating infected blood in his home country to be 0.30 (95% CI, 0.01-0.65) per 100,000.

CONCLUSION

The model can be used to quantify EID outbreak risks to blood transfusion recipients and the effect of targeted safety interventions and as such support public health decision-making.

Validity of assessing inhibitor development in haemophilia PUPs using registry data: the EUHASS project

Inhibitory antibodies to exogenous FVIII/FIX are a major complication of haemophilia treatment. Up to 30% of previously untreated patients (PUPs) with severe haemophilia A develop inhibitors, most likely during the initial 50 exposure days to concentrate. In addition to classical cohort studies, a European monitoring system (EUHASS) has been set up to evaluate inhibitor development in PUPs. The present study addresses the reliability of estimating the cumulative incidence of inhibitor development in this registry. Data from the retrospective CANAL cohort study, including 288 PUPs with severe haemophilia A and complete treatment records until the 50th exposure to FVIII, were used to simulate the consequences of several cross-sectional sampling techniques on the estimated incidence of inhibitors. Both mathematical calculus and computer modelling were applied to study the effects of sample size and the introduction of a new product. For existing concentrates, both longitudinal cohort study methods and the EUHASS method yielded similar estimates of the cumulative incidence of inhibitor cases over a 5-year time period: 27.9% (95% CI: 21-36) vs. 29.4% (22-38). For a newly introduced concentrate, a reliable estimate of inhibitor incidence with the EUHASS method could only be made after 3-4 years, even in large datasets. The results from EUHASS in inhibitor incidence in PUPs are expected to be valid. After introduction of a new concentrate, the inhibitor incidence on this concentrate can only be reliably determined after an observation period of several years.

A modeling approach to evaluate long-term outcome of prophylactic and on demand treatment strategies for severe hemophilia A

BACKGROUND

Severe hemophilia requires life-long treatment with expensive clotting factor concentrates; studies comparing effects of different therapeutic strategies over decades are very difficult to perform. A simulation model was developed to evaluate the long-term outcome of on demand, prophylactic and mixed treatment strategies for patients with severe hemophilia A.

DESIGN AND METHODS

A computer model was developed based on individual patients' data from a Dutch cohort study in which intermediate dose prophylaxis was used and a French cohort study in which on demand treatment was used, and multivariate regression analyses. This model simulated individual patients' life expectancy, onset of bleeding, life-time joint bleeds, radiological outcome and concentrate use according to the different treatment strategies.

RESULTS

According to the model, life-time on demand treatment would result in an average of 1,494 joint bleeds during the hemophiliac's life, and consumption of 4.9 million IU of factor VIII concentrate. In contrast, life-time intermediate dose prophylaxis resulted in a mean of 357 joint bleeds and factor consumption of 8.3 million IU. A multiple switch strategy (between prophylactic and on demand treatment based on bleeding pattern) resulted in a mean number of 395 joint bleeds and factor consumption of 6.6 million IU. The estimated proportion of patients with Pettersson scores over 28 points was 32% for both the prophylactic and the multiple switching strategies, compared to 76% for continuous on demand treatment.

CONCLUSIONS

The present model allows evaluation of the impact of various treatment strategies on patients' joint bleeds and clotting factor consumption. It may be expanded with additional data to allow more precise estimates and include economic evaluations of treatment strategies.