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Jorien Veldwijk,1–3 Catharina GM Groothuis-Oudshoorn,4 Ulrik Kihlbom,2,5,6 Sophie Langenskiöld,2,5,6 Evelien Dekker,7 Frank GJ Kallenberg,7 G Ardine de Wit,3,8 Mattijs S Lambooij3 1Erasmus School of Health Policy and Management, Erasmus University, Rotterdam, the Netherlands; 2Centre for Research Ethics & Bioethics, Uppsala University, Uppsala, Sweden; 3Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands; 4Health Technology and Services Research, University of Twente, Enschede, the Netherlands; 5Department of Health Economics, Uppsala University, Uppsala, Sweden; 6Department of Learning, Informatics, Management and Ethics, Karolinska Institute, Stockholm, Sweden; 7Department of Gastroenterology and Hepatology, Academic Medical Center, Amsterdam, the Netherlands; 8Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands Purpose: The purpose of this study was to investigate to what extent the outcomes of a discrete choice experiment (DCE) differ based on respondents’ psychological distance to the decision at hand.Methods: A DCE questionnaire regarding individuals’ preferences for genetic screening for colorectal cancer (CRC) within the Dutch national CRC screening program was created. The DCE contained nine D-efficient designed choice tasks and was distributed among two populations that differ in their psychological distance to the decision at hand: 1) a representative sample of the Dutch general population aged 55–65 years, and 2) a sample of Dutch individuals who attended an information appointment regarding colonoscopies following the detection of blood in their stool sample in the CRC screening program. The DCE consisted of four attributes related to the decision whether to participate in genetic screening for CRC: 1) risk of being genetically predisposed, 2) risk of developing CRC, 3) frequency of follow-up colonoscopies, and 4) survival. Direct attribute ranking, dominant decision-making behavior, and relative importance scores (based on panel MIXL) were compared between the two populations. Attribute level estimates were compared with the Swait and Louviere test.Results: The proportion of respondents who both ranked survival as the most important attribute, and showed dominant decision-making behavior for this attribute, was significantly higher in the screened population compared to the general population. The relative importance scores of the attributes significantly differed between populations. Finally, the Swait and Louviere test also revealed significant differences in attribute level estimates in both the populations.Conclusion: The study outcomes differed between populations depending on their psychological distance to the decision. This study shows the importance of adequate sample selection; therefore, it is advocated to increase attention to study sample selection and reporting in DCE studies. Keywords: discrete choice experiment, preferences, stated preferences, sample, psychological distance, genetic screening

Xin Yi Wong,1 Catharina GM Groothuis-Oudshoorn,2 Chuen Seng Tan,3 Janine A van Til,2 Mikael Hartman,3,4 Kok Joon Chong,5 Maarten J IJzerman,2,6,7 Hwee-Lin Wee1,3 1Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore, Republic of Singapore; 2Department of Health Technology and Services Research, Faculty of Behavioural, Management and Social Sciences, Technical Medical Centre, University of Twente, Enschede, The Netherlands; 3Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore; 4Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Republic of Singapore; 5Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Republic of Singapore; 6Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia; 7Victorian Comprehensive Cancer Centre, Melbourne, Australia Background: Single-nucleotide polymorphism (SNP) gene test is a potential tool for improving the accuracy of breast cancer risk prediction. We seek to measure women’s preferences and marginal willingness-to-pay (mWTP) for this new technology. Materials and methods: We administered a discrete choice experiment (DCE) to English-speaking Singaporean women aged 40–69 years without any history of breast cancer, enrolled via door-to-door recruitment with quota sampling by age and ethnicity. DCE attributes comprise: 1) sample type (buccal swab and dried blood spot), 2) person conducting pretest discussion (specialist doctor, non-specialist doctor, and nurse educator), 3) test location (private family clinic, public primary-care clinic, and hospital), and 4) out-of-pocket cost (S$50, S$175, and S$300). Mixed logit model was used to estimate the effect of attribute levels on women’s preferences and mWTP. Interactions between significant attributes and respondent characteristics were investigated. Predicted uptake rates for various gene testing scenarios were studied. Results: A total of 300 women aged 52.6±7.6 years completed the survey (100 Chinese, Malay, and Indian women, respectively). Sample type (P=0.046), person conducting pretest discussion, and out-of-pocket cost (P

Kirsten Koehorst-ter Huurne,1 Catharina GM Groothuis-Oudshoorn,2 Paul DLPM vanderValk,1 Kris LL Movig,3 Job van der Palen,4,5 Marjolein Brusse-Keizer4 1Department of Pulmonary Medicine, Medisch Spectrum Twente, Enschede, the Netherlands; 2Department of Health Technology and Services Research, University of Twente, Enschede, the Netherlands; 3Department of Clinical Pharmacy, Medisch Spectrum Twente, Enschede, the Netherlands; 4Medical School Twente, Medisch Spectrum Twente, Enschede, the Netherlands; 5Department of Research Methodology, Measurement, and Data Analysis, University of Twente, Enschede, the Netherlands Aim: The aim of this study was to analyze the association between therapy adherence to inhaled corticosteroids (ICSs) and tiotropium on the one hand and morbidity and mortality in COPD on the other hand. Methods: Therapy adherence to ICSs and tiotropium over a 3-year period of, respectively, 635 and 505 patients was collected from pharmacy records. It was expressed as percentage and deemed optimal at ≥75–≤125%, suboptimal at ≥50%–125% (overuse). The association between adherence and time to first hospital admission for an acute exacerbation of chronic obstructive pulmonary disease (AECOPD), community acquired pneumonia (CAP), and mortality was analyzed, with optimal use as the reference category. Results: Suboptimal use and underuse of ICSs and tiotropium were associated with a substantial increase in mortality risk: hazard ratio (HR) of ICSs was 2.9 (95% CI 1.7–5.1) and 5.3 (95% CI 3.3–8.5) and HR of tiotropium was 3.9 (95% CI 2.1–7.5) and 6.4 (95% CI 3.8–10.8) for suboptimal use and underuse, respectively. Suboptimal use and overuse of tiotropium were also associated with an increased risk of CAP, HR 2.2 (95% CI 1.2–4.0) and HR 2.3 (95% CI 1.2–4.7), respectively. Nonadherence to tiotropium was also associated with an increased risk of severe AECOPD: suboptimal use HR 3.0 (95% CI 2.01–4.5), underuse HR 1.9 (95% CI 1.2–3.1), and overuse HR 1.84 (95% CI 1.1–3.1). Nonadherence to ICSs was not related to time to first AECOPD or first CAP. Conclusion: Poor adherence to ICSs and tiotropium was associated with a higher mortality risk. Furthermore, nonadherence to tiotropium was associated with a higher morbidity. The question remains whether improving adherence can reduce morbidity and mortality. Keywords: COPD, adherence, morbidity, mortality, pneumonia, exacerbation, hospitalization

A limited number of clinical studies have examined the effect of poststroke rehabilitation with robotic devices on hemiparetic arm function. We systematically reviewed the literature to assess the effect of robot-aided therapy on stroke patients' upper-limb motor control and functional abilities. Eight clinical trials were identified and reviewed. For four of these studies, we also pooled short-term mean changes in Fugl-Meyer scores before and after robot-aided therapy. We found that robot-aided therapy of the proximal upper limb improves short-and long-term motor control of the paretic shoulder and elbow in subacute and chronic patients; however, we found no consistent influence on functional abilities. In addition, robotaided therapy appears to improve motor control more than conventional therapy. [ABSTRACT FROM AUTHOR]

Background: Individual risk prediction of 5-year locoregional recurrence (LRR) and contralateral breast cancer (CBC) supports decisions regarding personalised surveillance. The previously developed INFLUENCE tool was rebuild, including a recent population and patients who received neoadjuvant systemic therapy (NST)., Methods: Women, surgically treated for nonmetastatic breast cancer, diagnosed between 2012 and 2016, were selected from the Netherlands Cancer Registry. Cox regression with restricted cubic splines was compared to Random Survival Forest (RSF) to predict five-year LRR and CBC risks. Separate models were developed for NST patients. Discrimination and calibration were assessed by 100x bootstrap resampling., Results: In the non-NST and NST group, 49,631 and 10,154 patients were included, respectively. Age, mode of detection, histology, sublocalisation, grade, pT, pN, hormonal receptor status ± endocrine treatment, HER2 status ± targeted treatment, surgery ± immediate reconstruction ± radiation therapy, and chemotherapy were significant predictors for LRR and/or CBC in non-NST patients. For NST patients this was similar, but excluding (y)pT and (y)pN status, and including presence of ductal carcinoma in situ, axillary lymph node dissection and pathologic complete response. For non-NST patients, the Cox and RSF models were integrated in the online tool with 5-year AUCs of 0.77 (95%CI:0.77-0.77) and 0.68 (95%CI:0.67-0.68)] for LRR and CBC prediction, respectively. For NST patients, the RSF model performed best (AUCs 0.77 (95%CI:0.76-0.78) and 0.73 (95%CI:0.69-0.76) for LRR and CBC, respectively). Regarding calibration, observed-predicted differences were all <1 %., Conclusion: This INFLUENCE 3.0 models showed moderate performance in LRR and CBC prediction. The models have been made available as online tool to enable clinical decision support regarding personalised follow-up., Competing Interests: Declaration of coompeting interest Tom A. Hueting declares employment at Evidencio. The other authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Previously, we showed that quantification of lymphoma-associated miRNAs miR-155-5p, -127-3p and let-7a-5p levels in plasma extracellular vesicles (EVs) report treatment response in patients with classic Hodgkin lymphoma (cHL). Prior to clinical implementation, quality control (QC) steps and validation are required to meet international regulatory standards. Most published EV-based diagnostic assays have yet to meet these requirements. In order to advance the assay towards regulatory compliance (e.g., IVDR 2017/746), we incorporated three QC steps in our experimental EV-miRNA quantitative real-time reverse-transcription PCR (q-RT-PCR) assay in an ISO-13485 certified quality-management system (QMS). Liposomes encapsulated with a synthetic (nematode-derived) miRNA spike-in controlled for EV isolation by automated size-exclusion chromatography (SEC). Additional miRNA spike-ins controlled for RNA isolation and cDNA conversion efficiency. After deciding on quality criteria, in total 107 out of 120 samples from 46 patients passed QC. Generalized linear mixed-effect modelling with bootstrapping determined the diagnostic performance of the quality-controlled data at an area under the curve (AUC) of 0.84 (confidence interval [CI]: 0.76-0.92) compared to an AUC of 0.87 (CI: 0.80-0.94) of the experimental assay. After the inclusion of QC steps, the accuracy of the assay was determined to be 78.5% in predicting active disease status in cHL patients during treatment. We demonstrate that a quality-controlled plasma EV-miRNA assay is technically robust, taking EV-miRNA as liquid biopsy assay an important step closer to clinical evaluation., Competing Interests: D.M.P. is co‐founder, shareholder and CSO of Exbiome BV, receives funding from the Stichting MRD in Hodgkin Lymphoma, has served as an advisor for Takeda and received research funding (Intl. Scholars Award in hemato‐oncology) from Gilead and is a consultant for Y2Y. D.M.P. is an inventor on a patent related to EV‐RNA diagnostics submitted by Johns Hopkins University. The other authors declare no conflicts of interest. ExBiome measured the plasma samples and developed the QMS‐compliant assay but was not part of the analyses that determined the clinical performance of the data and was not given access to clinical data and context of the samples., (© 2024 The Author(s). Journal of Extracellular Biology published by Wiley Periodicals LLC on behalf of International Society for Extracellular Vesicles.)

Hip fractures are a global health problem with a high postoperative mortality rate. Preoperative predictors for early mortality could be used to optimise and personalise healthcare strategies. This study aimed to identify predictors for early mortality following hip fracture surgery. Cohort studies examining independent preoperative predictors for mortality following hip fracture surgery were identified through a systematic search on Scopus and PubMed. Predictors for 30-day mortality were the primary outcome, and predictors for mortality within 1 year were secondary outcomes. Primary outcomes were analysed with random-effects meta-analyses. Confidence in the cumulative evidence was assessed using the GRADE criteria. Secondary outcomes were synthesised narratively. Thirty-three cohort studies involving 462,699 patients were meta-analysed. Five high-quality evidence predictors for 30-day mortality were identified: age per year (OR: 1.06, 95% CI: 1.04-1.07), ASA score ≥ 3 (OR: 2.69, 95% CI: 2.12-3.42), male gender (OR: 2.00, 95% CI: 1.85-2.18), institutional residence (OR: 1.81, 95% CI: 1.31-2.49), and metastatic cancer (OR: 2.83, 95% CI: 2.58-3.10). Additionally, six moderate-quality evidence predictors were identified: chronic renal failure, dementia, diabetes, low haemoglobin, heart failures, and a history of any malignancy. Weak evidence was found for non-metastatic cancer. This review found relevant preoperative predictors which could be used to identify patients who are at high risk of 30-day mortality following hip fracture surgery. For some predictors, the prognostic value could be increased by further subcategorising the conditions by severity., (© 2023. The Author(s).)

Background: For hip fracture patients with a limited life expectancy, operative and palliative non-operative management (P-NOM) can yield similar quality of life outcomes. However, evidence on when to abstain from surgery is lacking. The aim of this study was to quantify the influence of patient characteristics on surgeons' decisions to recommend P-NOM. Methods: Dutch surgical residents and orthopaedic trauma surgeons were enrolled in a conjoint analysis and structured expert judgement (SEJ). The participants assessed 16 patient cases comprising 10 clinically relevant characteristics. For each case, they recommended either surgery or P-NOM and estimated the 30-day postoperative mortality risk. Treatment recommendations were analysed using Bayesian logistic regression, and perceived risks were pooled with equal and performance-based weights using Cooke's Classical Model. Results: The conjoint analysis and SEJ were completed by 14 and 9 participants, respectively. Participants were more likely to recommend P-NOM to patients with metastatic carcinomas (OR: 4.42, CrI: 2.14-8.95), severe heart failure (OR: 4.05, CrI: 1.89-8.29), end-stage renal failure (OR: 3.54, CrI: 1.76-7.35) and dementia (OR: 3.35, CrI: 1.70-7.06). The patient receiving the most P-NOM recommendations (12/14) had a pooled perceived risk of 30-day mortality between 50.8 and 62.7%. Conclusions: Overall, comorbidities had the strongest influence on participants' decisions to recommend P-NOM. Nevertheless, practice variation and heterogeneity in risk perceptions were substantial. Hence, more decision support for considering P-NOM is needed.

Background and Objective: There has been an increase in the study and use of stated-preference methods to inform medicine development decisions. The objective of this study was to identify prioritized topics and questions relating to health preferences based on the perspective of members of the preference research community., Methods: Preference research stakeholders from industry, academia, consultancy, health technology assessment/regulatory, and patient organizations were recruited using professional networks and preference-targeted e-mail listservs and surveyed about their perspectives on 19 topics and questions for future studies that would increase acceptance of preference methods and their results by decision makers. The online survey consisted of an initial importance prioritization task, a best-worst scaling case 1 instrument, and open-ended questions. Rating counts were used for analysis. The best-worst scaling used a balanced incomplete block design., Results: One hundred and one participants responded to the survey invitation with 66 completing the best-worst scaling. The most important research topics related to the synthesis of preferences across studies, transferability across populations or related diseases, and method topics including comparison of methods and non-discrete choice experiment methods. Prioritization differences were found between respondents whose primary affiliation was academia versus other stakeholders. Academic researchers prioritized methodological/less studied topics; other stakeholders prioritized applied research topics relating to consistency of practice., Conclusions: As the field of health preference research grows, there is a need to revisit and communicate previous work on preference selection and study design to ensure that new stakeholders are aware of this work and to update these works where necessary. These findings might encourage discussion and alignment among different stakeholders who might hold different research priorities. Research on the application of previous preference research to new contexts will also help increase the acceptance of health preference information by decision makers., (© 2023. The Author(s).)

Introduction: Discrete choice experiments (DCE) are commonly used to elicit patient preferences and to determine the relative importance of attributes but can be complex and costly to administer. Simpler methods that measure relative importance exist, such as swing weighting with direct rating (SW-DR), but there is little empirical evidence comparing the two. This study aimed to directly compare attribute relative importance rankings and weights elicited using a DCE and SW-DR., Methods: A total of 307 patients with non-small-cell lung cancer in Italy and Belgium completed an online survey assessing preferences for cancer treatment using DCE and SW-DR. The relative importance of the attributes was determined using a random parameter logit model for the DCE and rank order centroid method (ROC) for SW-DR. Differences in relative importance ranking and weights between the methods were assessed using Cohen's weighted kappa and Dirichlet regression. Feedback on ease of understanding and answering the 2 tasks was also collected., Results: Most respondents (>65%) found both tasks (very) easy to understand and answer. The same attribute, survival, was ranked most important irrespective of the methods applied. The overall ranking of the attributes on an aggregate level differed significantly between DCE and SW-ROC ( P  < 0.01). Greater differences in attribute weights between attributes were reported in DCE compared with SW-DR ( P  < 0.01). Agreement between the individual-level attribute ranking across methods was moderate (weighted Kappa 0.53-0.55)., Conclusion: Significant differences in attribute importance between DCE and SW-DR were found. Respondents reported both methods being relatively easy to understand and answer. Further studies confirming these findings are warranted. Such studies will help to provide accurate guidance for methods selection when studying relative attribute importance across a wide array of preference-relevant decisions., Highlights: Both DCEs and SW tasks can be used to determine attribute relative importance rankings and weights; however, little evidence exists empirically comparing these methods in terms of outcomes or respondent usability.Most respondents found the DCE and SW tasks very easy or easy to understand and answer.A direct comparison of DCE and SW found significant differences in attribute importance rankings and weights as well as a greater spread in the DCE-derived attribute relative importance weights., Competing Interests: The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: J. Veldwijk, I. P. Smith, S. Oliveri, S. Petrocchi, L. Lanzoni, Isabelle Huys, Rosanne Janssens, Ardine de Wit, and C. G. M. Groothuis-Oudshoorn declare no conflict of interest. M. Y. Smith is a full-time employee of Alexion AstraZeneca Rare Disease and is a shareholder in the company. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study formed part of the PREFER project. The Patient Preferences in Benefit-Risk Assessments during the Drug Life Cycle (PREFER) project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 115966. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and EFPIA. The PREFER project aims to strengthen patient-centric decision-making through evidence-based recommendations guiding stakeholders on how and when patient preference studies should inform medical product development and evaluation. Financial support for this study was provided entirely by a grant from Innovative Medicines Initiative 2 Joint Undertaking under grant No. 11966. The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report.

Purpose: The aim of the study was to benchmark and compare breast cancer care quality indicators (QIs) between Norway and the Netherlands using federated analytics preventing transfer of patient-level data., Methods: Breast cancer patients (2017-2018) were retrieved from the Netherlands Cancer Registry and the Cancer Registry of Norway. Five European Society of Breast Cancer Specialists (EUSOMA) QIs were assessed: two on magnetic resonance imaging (MRI), two on surgical approaches, and one on postoperative radiotherapy. The QI outcomes were calculated using 'Vantage 6' federated Propensity Score Stratification (PSS). Likelihood of receiving a treatment was expressed in odds ratios (OR)., Results: In total, 39,163 patients were included (32,786 from the Netherlands and 6377 from Norway). PSS scores were comparable to the crude outcomes of the QIs. The Netherlands scored higher on the QI 'proportions of patients preoperatively examined with breast MRI' [37% vs.17.5%; OR 2.8 (95% CI 2.7-2.9)], the 'proportions of patients receiving primary systemic therapy examined with breast MRI' [83.3% vs. 70.8%; OR 2.3 (95% CI 1.3-3.3)], and 'proportion of patients receiving a single breast operation' [95.2% vs. 91.5%; OR 1.8 (95% CI 1.4-2.2)]. Country scores for 'immediate breast reconstruction' and 'postoperative radiotherapy after breast-conserving surgery' were comparable. The EUSOMA standard was achieved in both countries for 4/5 indicators., Conclusion: Both countries achieved high scores on the QIs. Differences were observed in the use of MRI and proportion of patients receiving single surgery. The federated approach supports future possibilities on benchmark QIs without transfer of privacy-sensitive data., (© 2023. The Author(s).)

Objectives: Care for JIA patients has been transformed in the biologics era; however, biologics carry important (although rare) risks and are costly. Flares after biological withdrawal are seen frequently, yet there is little clinical guidance to identify which patients in clinical remission can safely have their biologic discontinued (by stopping or tapering). We examined what characteristics of the child or their context are important to pediatric rheumatologists when making the decision to discuss withdrawal of biologics., Methods: We conducted a survey including a best-worst scaling (BWS) exercise in pediatric rheumatologists who are part of the UCAN CAN-DU network to assess the relative importance of 14 previously identified characteristics. A balanced incomplete block design was used to generate choice tasks. Respondents evaluated 14 choice sets of 5 characteristics of a child with JIA and identified for each set which was the most and least important in the decision to offer withdrawal. Results were analyzed using conditional logit regression., Results: Fifty-one (out of 79) pediatric rheumatologists participated (response rate 65%). The three most important characteristics were how challenging it was to achieve remission, history of established joint damage, and time spent in remission. The three least important characteristics were history of temporomandibular joint involvement, accessibility of biologics, and the patient's age., Conclusions: These findings give quantitative insight about factors important to pediatric rheumatologists' decision-making about biologic withdrawal. In addition to high quality clinical evidence, further research is needed to understand the perspective of patients and families to inform shared decision-making about biologic withdrawal for JIA patients with clinically inactive disease. Key Points ● What is already known on this topic-there is limited clinical guidance for pediatric rheumatologists in making decisions about biologic withdrawal for patients with juvenile idiopathic arthritis who are in clinical remission. ● What this study adds-this study quantitatively examined what characteristic of the child in clinical remission, or of their context, are most important to pediatric rheumatologists in deciding whether to offer withdrawal of biologics. ● How this study might affect research, practice or policy-understanding of these characteristics can provide useful information to other pediatric rheumatologists in making their decisions, and may guide areas to focus on for future research., (© 2023. The Author(s), under exclusive licence to International League of Associations for Rheumatology (ILAR).)

The AHFS 90 was developed for the prediction of early mortality in patients ≥ 90 years undergoing hip fracture surgery. The AHFS 90 has a good accuracy and in most risk categories a good calibration. In our study population, the AHFS 90 yielded a maximum prediction of early mortality of 64.5%., Purpose: Identifying hip fracture patients with a high risk of early mortality after surgery could help make treatment decisions and information about the prognosis. This study aims to develop and validate a risk score for predicting early mortality in patients ≥ 90 years undergoing hip fracture surgery (AHFS 90 )., Methods: Patients ≥ 90 years, surgically treated for a hip fracture, were included. A selection of possible predictors for mortality was made. Missing data were subjected to multiple imputations using chained equations. Logistic regression was performed to develop the AHFS 90 , which was internally and externally validated. Calibration was assessed using a calibration plot and comparing observed and predicted risks., Results: One hundred and two of the 922 patients (11.1%) died ≤ 30 days following hip fracture surgery. The AHFS 90 includes age, gender, dementia, living in a nursing home, ASA score, and hemoglobin level as predictors for early mortality. The AHFS 90 had good accuracy (area under the curve 0.72 for geographic cross validation). Predicted risks correspond with observed risks of early mortality in four risk categories. In two risk categories, the AHFS 90 overestimates the risk. In one risk category, no mortality was observed; therefore, no analysis was possible. The AHFS 90 had a maximal prediction of early mortality of 64.5% in this study population., Conclusion: The AHFS 90 accurately predicts early mortality after hip fracture surgery in patients ≥ 90 years of age. Predicted risks correspond to observed risks in most risk categories. In our study population, the AHFS 90 yielded a maximum prediction of early mortality of 64.5%., (© 2023. The Author(s).)

Objectives: This study aimed to understand the importance of criteria describing methods (eg, duration, costs, validity, and outcomes) according to decision makers for each decision point in the medical product lifecycle (MPLC) and to determine the suitability of a discrete choice experiment, swing weighting, probabilistic threshold technique, and best-worst scale cases 1 and 2 at each decision point in the MPLC., Methods: Applying multicriteria decision analysis, an online survey was sent to MPLC decision makers (ie, industry, regulatory, and health technology assessment representatives). They ranked and weighted 19 methods criteria from an existing performance matrix about their respective decisions across the MPLC. All criteria were given a relative weight based on the ranking and rating in the survey after which an overall suitability score was calculated for each preference elicitation method per decision point. Sensitivity analyses were conducted to reflect uncertainty in the performance matrix., Results: Fifty-nine industry, 29 regulatory, and 5 health technology assessment representatives completed the surveys. Overall, "estimating trade-offs between treatment characteristics" and "estimating weights for treatment characteristics" were highly important criteria throughout all MPLC decision points, whereas other criteria were most important only for specific MPLC stages. Swing weighting and probabilistic threshold technique received significantly higher suitability scores across decision points than other methods. Sensitivity analyses showed substantial impact of uncertainty in the performance matrix., Conclusion: Although discrete choice experiment is the most applied preference elicitation method, other methods should also be considered to address the needs of decision makers. Development of evidence-based guidance documents for designing, conducting, and analyzing such methods could enhance their use., (Copyright © 2022. Published by Elsevier Inc.)

Introduction: New glucose-monitoring technologies have different cost-benefit profiles compared with traditional finger-prick tests, resulting in a preference-sensitive situation for patients. This study aimed to assess the relative value adults with diabetes assign to device attributes in two countries., Research Design and Methods: Adults with type 1 or 2 diabetes from the Netherlands (n=226) and Poland (n=261) completed an online discrete choice experiment. Respondents choose between hypothetical glucose monitors described using seven attributes: precision, effort to check, number of finger pricks required, risk of skin irritation, information provided, alarm function and out-of-pocket costs. Panel mixed logit models were used to determine attribute relative importance and to calculate expected uptake rates and willingness to pay (WTP)., Results: The most important attribute for both countries was monthly out-of-pocket costs. Polish respondents were more likely than Dutch respondents to choose a glucose-monitoring device over a standard finger prick and had higher WTP for a device. Dutch respondents had higher WTP for device improvements in an effort to check and reduce the number of finger pricks a device requires., Conclusion: Costs are the primary concern of patients in both countries when choosing a glucose monitor and would likely hamper real-world uptake. The costs-benefit profiles of such devices should be critically reviewed., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Our aim was to determine the agreement of heart rate (HR) and respiratory rate (RR) measurements by the Philips Biosensor with a reference monitor (General Electric Carescape B650) in severely obese patients during and after bariatric surgery. Additionally, sensor reliability was assessed. Ninety-four severely obese patients were monitored with both the Biosensor and reference monitor during and after bariatric surgery. Agreement was defined as the mean absolute difference between both monitoring devices. Bland Altman plots and Clarke Error Grid analysis (CEG) were used to visualise differences. Sensor reliability was reflected by the amount, duration and causes of data loss. The mean absolute difference for HR was 1.26 beats per minute (bpm) (SD 0.84) during surgery and 1.84 bpm (SD 1.22) during recovery, and never exceeded the 8 bpm limit of agreement. The mean absolute difference for RR was 1.78 breaths per minute (brpm) (SD 1.90) during surgery and 4.24 brpm (SD 2.75) during recovery. The Biosensor's RR measurements exceeded the 2 brpm limit of agreement in 58% of the compared measurements. Averaging 15 min of measurements for both devices improved agreement. CEG showed that 99% of averaged RR measurements resulted in adequate treatment. Data loss was limited to 4.5% of the total duration of measurements for RR. No clear causes for data loss were found. The Biosensor is suitable for remote monitoring of HR, but not RR in morbidly obese patients. Future research should focus on improving RR measurements, the interpretation of continuous data, and development of smart alarm systems., (© 2021. The Author(s), under exclusive licence to Springer Nature B.V.)

Background: Regular follow-up after treatment for breast cancer is crucial to detect potential recurrences and second contralateral breast cancer in an early stage. However, information about follow-up patterns in the Netherlands is scarce., Patients and Methods: Details concerning diagnostic procedures and policlinic visits in the first 5 years following a breast cancer diagnosis were gathered between 2009 and 2019 for 9916 patients from 4 large Dutch hospitals. This information was used to analyze the adherence of breast cancer surveillance to guidelines in the Netherlands. Multivariable logistic regression was used to relate the average number of a patient's imaging procedures to their demographics, tumor-treatment characteristics, and individual locoregional recurrence risk (LRR), estimated by a risk-prediction tool, called INFLUENCE., Results: The average number of policlinic contacts per patient decreased from 4.4 in the first to 2.0 in the fifth follow-up year. In each of the 5 follow-up years, the share of patients without imaging procedures was relatively high, ranging between 31.4% and 33.6%. Observed guidelines deviations were highly significant (P < .001). A higher age, lower UICC stage, and having undergone radio- or chemotherapy were significantly associated with a higher chance of receiving an imaging procedure. The estimated average LRR-risk was 3.5% in patients without any follow-up imaging compared with 2.3% in patients with the recommended number of 5 imagings., Conclusion: Compared to guidelines, more policlinic visits were made, although at inadequate intervals, and fewer imaging procedures were performed. The frequency of imaging procedures did not correlate with the patients' individual risk profiles for LRR., (© The Author(s) 2022. Published by Oxford University Press.)

Background: Respondents in a health valuation study may have different sources of error (i.e., heteroskedasticity), tastes (differences in the relative effects of each attribute level), and scales (differences in the absolute effects of all attributes). Although prior studies have compared values by preference-elicitation tasks (e.g., paired comparison [PC] and best-worst scaling case 2 [BWS]), no study has yet controlled for heteroskedasticity and heterogeneity (taste and scale) simultaneously in health valuation., Methods: Preferences on EQ-5D-5L profiles were elicited from a random sample of 380 adults from the general population of the Netherlands, using 24 PC and 25 BWS case 2 tasks. To control for heteroskedasticity and heterogeneity (taste and scale) simultaneously, we estimated Dutch EQ-5D-5L values using conditional, heteroskedastic, and scale-adjusted latent class (SALC) logit models by maximum likelihood., Results: After controlling for heteroskedasticity, the PC and BWS values were highly correlated (Pearson's correlation: 0.9167, CI: 0.9109-0.9222) and largely agreed (Lin's concordance: 0.7658, CI: 0.7542-0.7769) on a pits scale. In terms of preference heterogeneity, some respondents (mostly young men) failed to account for any of the EQ-5D-5L attributes (i.e., garbage class), and others had a lower scale (59%; p-value: 0.123). Overall, the SALC model produced a consistent Dutch EQ-5D-5L value set on a pits scale, like the original study (Pearson's correlation:0.7295; Lin's concordance: 0.6904)., Conclusions: This paper shows the merits of simultaneously controlling for heteroskedasticity and heterogeneity in health valuation. In this case, the SALC model dispensed with a garbage class automatically and adjusted the scale for those who failed the PC dominant task. Future analysis may include more behavioral variables to better control heteroskedasticity and heterogeneity in health valuation., Highlights: The Dutch EQ-5D-5L values based on paired comparison [PC] and best-worst scaling [BWS] responses were highly correlated and largely agreed after controlling for heteroskedasticity. Controlling for taste and scale heterogeneity simultaneously enhanced the Dutch EQ-5D-5Lvalues by automatically dispensing with a garbage class and adjusting the scale for those who failed the dominant task. After controlling for heteroskedasticity and heterogeneity, this study produced Dutch EQ-5D-5L values on a pits scale moderately concordant with the original values., (© 2022. The Author(s).)

Purpose: The ICEpop CAPability measure for Adults (ICECAP-A) assesses five capabilities that are important to one's well-being. The instrument might be an important addition to generic health questionnaires when evaluating quality of life extending beyond health. This study aimed to conduct a psychometric assessment of the Dutch translation of the ICECAP-A., Methods: Construct validity of the instrument was assessed in two ways. First, by measuring correlations with the EQ-5D-5L questionnaire and a measure of self-efficacy and, second, by investigating the ability to distinguish between groups known to differ on the construct the ICECAP-A means to capture. Additionally, test-retest reliability was evaluated., Results: In total, 1002 participants representative of the general Dutch population completed an online survey. For test-retest reliability, 252 participants completed the same questionnaire 2 weeks later. The ICECAP-A indicated moderate to strong correlations with the EQ-5D-5L and a strong correlation with self-efficacy. Furthermore, it was capable of differentiating known groups. Moreover, results indicated adequate test-retest reliability with an intraclass correlation coefficient of 0.79., Conclusion: In summary, results suggest adequate test-retest reliability and construct validity and indicate that the ICECAP-A might be of added value, especially when considering areas outside of the traditional health intervention model., (© 2021. The Author(s).)

Objectives: The ICEpop Capability Measure for Adults (ICECAP-A) assesses 5 capabilities (stability, attachment, autonomy, achievement, and enjoyment) that are important to one's quality of life and might be an important addition to generic health questionnaires currently used in economic evaluations. This study aimed to develop a Dutch tariff of the Dutch translation of the ICECAP-A., Methods: The methods used are similar to those used in the development of the UK tariff. A profile case best-worst scaling task was presented to 1002 participants from the general Dutch population. A scale-adjusted latent class analysis was performed to test for preferences of ICECAP-A capabilities and scale heterogeneity., Results: A 3-preference class 2-scale class model with worst choice as scale predictor was considered optimal and was used to calculate the resulting tariff. Results indicated that the capabilities stability, attachment, and enjoyment were considered more important aspects of quality of life than autonomy and achievement. Additionally, improving capabilities from low to moderate levels had a larger effect on quality of life than improving capabilities that were already at a higher level., Conclusions: The ICECAP-A tariffs found in this study could be used in economic evaluations of healthcare interventions in The Netherlands., (Copyright © 2021 International Society for Pharmacoeconomics and Outcomes Research, Inc. Published by Elsevier Inc. Published by Elsevier Inc. All rights reserved.)

Objectives: This study aimed to provide detailed guidance on modeling approaches for implementing competing events in discrete event simulations based on censored individual patient data (IPD)., Methods: The event-specific distributions (ESDs) approach sampled times from event-specific time-to-event distributions and simulated the first event to occur. The unimodal distribution and regression approach sampled a time from a combined unimodal time-to-event distribution, representing all events, and used a (multinomial) logistic regression model to select the event to be simulated. A simulation study assessed performance in terms of relative absolute event incidence difference and relative entropy of time-to-event distributions for different types and levels of right censoring, numbers of events, distribution overlap, and sample sizes. Differences in cost-effectiveness estimates were illustrated in a colorectal cancer case study., Results: Increased levels of censoring negatively affected the modeling approaches' performance. A lower number of competing events and higher overlap of distributions improved performance. When IPD were censored at random times, ESD performed best. When censoring occurred owing to a maximum follow-up time for 2 events, ESD performed better for a low level of censoring (ie, 10%). For 3 or 4 competing events, ESD better represented the probabilities of events, whereas unimodal distribution and regression better represented the time to events. Differences in cost-effectiveness estimates, both compared with no censoring and between approaches, increased with increasing censoring levels., Conclusions: Modelers should be aware of the different modeling approaches available and that selection between approaches may be informed by data characteristics. Performing and reporting extensive validation efforts remains essential to ensure IPD are appropriately represented., (Copyright © 2021 International Society for Pharmacoeconomics and Outcomes Research, Inc. Published by Elsevier Inc. Published by Elsevier Inc. All rights reserved.)

The goal of this study was to describe the variation in hospital-based diagnostic care activities for patients with symptomatology suspect for breast cancer in The Netherlands. Two cohorts were included: the 'benign' cohort (30,334 women suspected of, but without breast cancer) and the 'malignant' cohort (2236 breast cancer patients). Hospital-based financial data was combined with tumor data (malignant cohort) from The Netherlands Cancer Registry. Patterns within diagnostic pathways were analyzed. Factors influencing the number of visits and number of diagnostic care activities until diagnosis were identified in the malignant cohort with multivariable Cox and Poisson regression models. Compared to patients with benign diagnosis, patients with malignant disease received their diagnosis less frequently in one day, after an equal average number of hospital visits and higher average number of diagnostic activities. Factors increasing the number of diagnostic care activities were the following: lower age and higher cM-and cN-stages. Factors increasing the number of days until (malignant) diagnosis were as follows: higher BIRADS-score, screen-detected and higher cN-and cT-stages. Hospital of diagnosis influenced both number of activities and days to diagnosis. The diagnostic care pathway of patients with malignant disease required more time and diagnostic activities than benign disease and depends on hospital, tumor and patient characteristics.

Purpose: To extend the functionality of the existing INFLUENCE nomogram for locoregional recurrence (LRR) of breast cancer toward the prediction of secondary primary tumors (SP) and distant metastases (DM) using updated follow-up data and the best suitable statistical approaches., Methods: Data on women diagnosed with non-metastatic invasive breast cancer were derived from the Netherlands Cancer Registry (n = 13,494). To provide flexible time-dependent individual risk predictions for LRR, SP, and DM, three statistical approaches were assessed; a Cox proportional hazard approach (COX), a parametric spline approach (PAR), and a random survival forest (RSF). These approaches were evaluated on their discrimination using the Area Under the Curve (AUC) statistic and on calibration using the Integrated Calibration Index (ICI). To correct for optimism, the performance measures were assessed by drawing 200 bootstrap samples., Results: Age, tumor grade, pT, pN, multifocality, type of surgery, hormonal receptor status, HER2-status, and adjuvant therapy were included as predictors. While all three approaches showed adequate calibration, the RSF approach offers the best optimism-corrected 5-year AUC for LRR (0.75, 95%CI: 0.74-0.76) and SP (0.67, 95%CI: 0.65-0.68). For the prediction of DM, all three approaches showed equivalent discrimination (5-year AUC: 0.77-0.78), while COX seems to have an advantage concerning calibration (ICI < 0.01). Finally, an online calculator of INFLUENCE 2.0 was created., Conclusions: INFLUENCE 2.0 is a flexible model to predict time-dependent individual risks of LRR, SP and DM at a 5-year scale; it can support clinical decision-making regarding personalized follow-up strategies for curatively treated non-metastatic breast cancer patients., (© 2021. The Author(s).)

As ongoing trials study the safety of an active surveillance strategy for low-risk ductal carcinoma in situ (DCIS), there is a need to explain why particular choices regarding treatment strategies are made by eligible women as well as their oncologists, what factors enter the decision process, and how much each factor affects their choice. To measure preferences for treatment and surveillance strategies, women with newly-diagnosed, primary low-risk DCIS enrolled in the Dutch CONTROL DCIS Registration and LORD trial, and oncologists participating in the Dutch Health Professionals Study were invited to complete a discrete choice experiment (DCE). The relative importance of treatment strategy-related attributes (locoregional intervention, 10-year risk of ipsilateral invasive breast cancer (iIBC), and follow-up interval) were discerned using conditional logit models. A total of n = 172 patients and n = 30 oncologists completed the DCE. Patient respondents had very strong preferences for an active surveillance strategy with no surgery, irrespective of the 10-year risk of iIBC. Extensiveness of the locoregional treatment was consistently shown to be an important factor for patients and oncologists in deciding upon treatment strategies. Risk of iIBC was least important to patients and most important to oncologists. There was a stronger inclination toward a twice-yearly follow-up for both groups compared to annual follow-up.

Minimally-invasive tools to assess tumour presence and burden may improve clinical management. FDG-PET (metabolic) imaging is the current gold standard for interim response assessment in patients with classical Hodgkin Lymphoma (cHL), but this technique cannot be repeated frequently. Here we show that microRNAs (miRNA) associated with tumour-secreted extracellular vesicles (EVs) in the circulation of cHL patients may improve response assessment. Small RNA sequencing and qRT-PCR reveal that the relative abundance of cHL-expressed miRNAs, miR-127-3p, miR-155-5p, miR-21-5p, miR-24-3p and let-7a-5p is up to hundred-fold increased in plasma EVs of cHL patients pre-treatment when compared to complete metabolic responders (CMR). Notably, in partial responders (PR) or treatment-refractory cases ( n  = 10) the EV-miRNA levels remain elevated. In comparison, tumour specific copy number variations (CNV) were detected in cell-free DNA of 8 out of 10 newly diagnosed cHL patients but not in patients with PR. Combining EV-miR-127-3p and/or EV-let-7a-5p levels, with serum TARC (a validated protein cHL biomarker), increases the accuracy for predicting PET-status ( n  = 129) to an area under the curve of 0.93 (CI: 0.87-0.99), 93.5% sensitivity, 83.8/85.0% specificity and a negative predictive value of 96%. Thus the level of tumour-associated miRNAs in plasma EVs is predictive of metabolic tumour activity in cHL patients. Our findings suggest that plasma EV-miRNA are useful for detection of small residual lesions and may be applied as serial response prediction tool., Competing Interests: Dirk Michiel Pegtel and Michael Hackenberg are co‐founders of Exbiome BV. Dirk Michiel Pegtel is CSO of ExBiome BV and has received travel compensation from Takeda., (© 2021 The Authors. Journal of Extracellular Vesicles published by Wiley Periodicals, LLC on behalf of the International Society for Extracellular Vesicles.)

Introduction: One of the challenges faced by hospitals during the coronavirus disease 2019 (COVID-19) pandemic is resource shortages in intensive care units (ICUs). In times of scarcity, patient prioritization based on non-medical considerations might be necessary., Objective: The aim of this study was to pilot test a survey to elicit public opinions on the relative importance of non-medical considerations in priority setting when admitting patients to the ICU in times of crisis., Methods: A discrete-choice experiment was used to collect social preferences for priority setting when admitting patients to the ICU during the COVID-19 pandemic. The six attributes were patient age, profession, guardianship, risk-conscious behavior on a societal level, health-conscious behavior, and expected ICU length of stay. The data were analyzed using a mixed multinomial logit model. Interactions between the age and profession of the respondents and the age and profession of the patient profiles were considered., Results: The mean (± standard deviation) age of respondents was 35.9 ± 14.5 years. In all, 70% of respondents indicated that medical and/or non-medical considerations should play a role in prioritizing patients for the ICU, whereas 15% agreed with a "first come, first served" strategy and the remaining 15% had no opinion. Respondents deemed risk-conscious behavior on a societal level to be the most important non-medical factor that should be used to prioritize patients in phase three of the framework, garnering an attribute importance (AI) of 31.2%, followed by patient age (AI 16.3%) and health-conscious behavior (AI 16.0%). ICU length of stay had the lowest impact on patient prioritization for ICU admittance (AI 10.9%). Younger and older respondents attached more importance to age than respondents in the middle age group and indicated a stronger preference to prioritize patients in their own age group (p = 0.042)., Conclusion: The results of our study demonstrate the relative importance members of the public attach to responsible societal behavior during the COVID-19 pandemic. In the next phase of the study, we will elicit the perspectives of a representative sample of the Dutch population. Changes to the task design and attribute operationalization could improve the external validity of the study findings, and optimization of the experimental design will improve the internal validity of the study.

Background: Depression and anxiety occur frequently postpartum, calling for early detection and treatment. Evidence on risk factors may support early detection, but is inconclusive. Our aim was to identify risk factors for postpartum depression and anxiety, before, during and after pregnancy., Methods: We used data from 1406 mothers of the intervention arm of the Post-Up study. Risk factors were collected at 3 weeks and 12 months postpartum. Depression and anxiety symptoms were measured in the first month postpartum by the Edinburgh Postnatal Depression Scale (EPDS) and 6-item State-Trait Anxiety Inventory (STAI-6), respectively. We used stepwise logistic regression to identify relevant risk factors., Results: Of the mothers, 8.0% had EPDS-scores ≥9 and 14.7% STAI-6-scores ≥42. Factors associated with higher risk of depression were: foreign language spoken at home, history of depression, low maternal self-efficacy and poor current health of the mother. No initiation of breastfeeding was associated with lower risk of depression, no breastfeeding at 3 weeks postpartum increased the risk. Factors associated with higher risk of anxiety were: higher educational level, history of depression, preterm birth, negative experience of delivery and first week postpartum, excessive infant crying, low maternal self-efficacy, low partner support and poor current maternal health., Limitations: Use of a self-report instrument, potential bias by postpartum mood status, and no inclusion of emerging depression cases after one month postpartum., Conclusions: The shared and separate risk factors for postpartum depression and anxiety may help professionals in identifying mothers at increased risk and provide opportunities for preventive interventions and treatment., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Four machine learning models were developed and compared to predict the risk of a future major osteoporotic fracture (MOF), defined as hip, wrist, spine and humerus fractures, in patients with a prior fracture. We developed a user-friendly tool for risk calculation of subsequent MOF in osteopenia patients, using the best performing model., Introduction: Major osteoporotic fractures (MOFs), defined as hip, wrist, spine and humerus fractures, can have serious consequences regarding morbidity and mortality. Machine learning provides new opportunities for fracture prediction and may aid in targeting preventive interventions to patients at risk of MOF. The primary objective is to develop and compare several models, capable of predicting the risk of MOF as a function of time in patients seen at the fracture and osteoporosis outpatient clinic (FO-clinic) after sustaining a fracture., Methods: Patients aged > 50 years visiting an FO-clinic were included in this retrospective study. We compared discriminative ability (concordance index) for predicting the risk on MOF with a Cox regression, random survival forests (RSF) and an artificial neural network (ANN)-DeepSurv model. Missing data was imputed using multiple imputations by chained equations (MICE) or RSF's imputation function. Analyses were performed for the total cohort and a subset of osteopenia patients without vertebral fracture., Results: A total of 7578 patients were included, 805 (11%) patients sustained a subsequent MOF. The highest concordance-index in the total dataset was 0.697 (0.664-0.730) for Cox regression; no significant difference was determined between the models. In the osteopenia subset, Cox regression outperformed RSF (p = 0.043 and p = 0.023) and ANN-DeepSurv (p = 0.043) with a c-index of 0.625 (0.562-0.689). Cox regression was used to develop a MOF risk calculator on this subset., Conclusion: We show that predicting the risk of MOF in patients who already sustained a fracture can be done with adequate discriminative performance. We developed a user-friendly tool for risk calculation of subsequent MOF in patients with osteopenia.

Purpose: To evaluate the effect of breast MRI on overall survival (OS) and disease-free survival (DFS) of patients with invasive breast cancer in the Netherlands., Methods: We selected all women from the Netherlands Cancer Registry diagnosed with invasive breast cancer (a) between 2011 and 2013 for the OS-cohort and (b) in the first quarter of 2012 for the DFS-cohort. The study population was subdivided into an MRI and non-MRI group. In addition, subgroups were created according to breast cancer subtype: invasive carcinoma of no special type (NST) versus invasive lobular carcinoma (ILC). OS and DFS were compared between the MRI and non-MRI group using the Kaplan-Meier method and the log-rank test. Cox proportional hazard regression analysis was performed to estimate hazard ratios (HR) with a 95% confidence interval (CI). To account for missing data, multiple imputation was performed., Results: Of the 31,756 patients included in the OS-cohort (70% non-MRI and 30% MRI), 27,752 (87%) were diagnosed with invasive carcinoma NST and 4004 (13%) with ILC. Of the 2464 patients included in the DFS-cohort (72% non-MRI and 28% MRI), 2161 (88%) were diagnosed with invasive carcinoma NST and 303 (12%) with ILC. The distribution of breast MRI use was significantly lower over different age categories, from 49.0% aged < 50 to 16.5% aged > 70. Multivariable Cox regression showed that breast MRI was not significantly associated with OS overall (HR 0.91, 95%-CI 0.74-1.11, p = 0.35), nor in the different histological subtypes. Multivariable Cox regression analysis showed that breast MRI was also not significantly associated with DFS (HR 1.16, 95%-CI 0.81-1.67), nor in the different histological subtypes., Conclusion: Use of breast MRI was not significantly associated with an improved OS or DFS in patients treated with primary surgery.

Objectives: An important aim of follow-up after primary breast cancer treatment is early detection of locoregional recurrences (LRR). This study compares 2 personalized follow-up scheme simulations based on LRR risk predictions provided by a time-dependent prognostic model for breast cancer LRR and quantifies their possible follow-up efficiency., Methods: Surgically treated early patients with breast cancer between 2003 and 2008 were selected from the Netherlands Cancer Registry. The INFLUENCE nomogram was used to estimate the 5-year annual LRR. Applying 2 thresholds, they were defined according to Youden's J-statistic and a predefined follow-up sensitivity of 95%, respectively. These patient's risk estimations served as the basis for scheduling follow-up visits; 2 personalized follow-up schemes were simulated. The number of potentially saved follow-up visits and corresponding cost savings for each follow-up scheme were compared with the current Dutch breast cancer guideline recommendation and the observed utilization of follow-up on a training and testing cohort., Results: Using LRR risk-predictions for 30 379 Dutch patients with breast cancer from 2003 to 2006 (training cohort), 2 thresholds were calculated. The threshold according to Youden's approach yielded a follow-up sensitivity of 62.5% and a potential saving of 62.1% of follow-up visits and €24.8 million in 5 years. When the threshold corresponding to 95% follow-up sensitivity was used, 17% of follow-up visits and €7 million were saved compared with the guidelines. Similar results were obtained by applying these thresholds to the testing cohort of 11 462 patients from 2007 to 2008. Compared with the observed utilization of follow-up, the potential cost-savings decline moderately., Conclusions: Personalized follow-up schemes based on the INFLUENCE nomogram's individual risk estimations for breast cancer LRR could decrease the number of follow-up visits if one accepts a limited risk of delayed LRR detection., (Copyright © 2020 ISPOR–The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. All rights reserved.)

Background: After 5 years of annual follow-up following breast cancer, Dutch guidelines are age based: annual follow-up for women <60 years, 60-75 years biennial, and none for >75 years. We determined how the risk of recurrence corresponds to these consensus-based recommendations and to the risk of primary breast cancer in the general screening population., Subjects, Materials, and Methods: Women with early-stage breast cancer in 2003/2005 were selected from the Netherlands Cancer Registry (n = 18,568). Cumulative incidence functions were estimated for follow-up years 5-10 for locoregional recurrences (LRRs) and second primary tumors (SPs). Risks were compared with the screening population without history of breast cancer. Alternative cutoffs for age were determined by log-rank tests., Results: The cumulative risk for LRR/SP was lower in women <60 years (5.9%, 95% confidence interval [CI] 5.3-6.6) who are under annual follow-up than for women 60-75 (6.3%, 95% CI 5.6-7.1) receiving biennial visits. All risks were higher than the 5-year risk of a primary tumor in the screening population (ranging from 1.4% to 1.9%). Age cutoffs <50, 50-69, and > 69 revealed better risk differentiation and would provide more risk-based schedules. Still, other factors, including systemic treatments, had an even greater impact on recurrence risks., Conclusion: The current consensus-based recommendations use suboptimal age cutoffs. The proposed alternative cutoffs will lead to a more balanced risk-based follow-up and thereby more efficient allocation of resources. However, more factors should be taken into account for truly individualizing follow-up based on risk for recurrence., Implications for Practice: The current age-based recommendations for breast cancer follow-up after 5 years are suboptimal and do not reflect the actual risk of recurrent disease. This results in situations in which women with higher risks actually receive less follow-up than those with a lower risk of recurrence. Alternative cutoffs could be a start toward risk-based follow-up and thereby more efficient allocation of resources. However, age, or any single risk factor, is not able to capture the risk differences and therefore is not sufficient for determining follow-up. More risk factors should be taken into account for truly individualizing follow-up based on the risk for recurrence., (© 2020 The Authors. The Oncologist published by Wiley Periodicals LLC on behalf of AlphaMed Press.)

Objective: As part of the Models of Child Health Appraised (MOCHA) project, this study aimed to answer the following research questions: 1) How do European citizens perceive the quality of primary health care provided for children? And 2) What are their priorities with respect to quality assessment of primary health care aimed at satisfying children's needs?, Methods: Nine potential attributes of quality of primary care were operationalized in 40 quality aspects. An online survey was used to elicit opinions in a representative sample of citizens of Germany, the Netherlands, Poland, Spain, and the United Kingdom. Data collection comprised: background characteristics; perceived quality of primary health care for children; and priority setting of quality aspects. Descriptive analysis was performed and differences between groups were tested using Chi-Square test and ANOVA., Results: Valid results were obtained from 2403 respondents. Mean satisfaction with quality of primary care ranged from 5.5 (Poland) to 7.2 (Spain). On average, between 56% (Poland) and 70% (Netherlands) of respondents had a positive perception of the primary health care system for children in their country. The ability of a child to limit their parents' access to the child's medical records was judged most negatively in all countries (average agreement score 28%, range 12-36%). The right of a child to a confidential consultation was judged most differently between countries (average agreement score 61%, range 40-75%). Overall top-10 priorities in ensuring high quality primary care were: timeliness (accessibility); skills/competences, management, facilities (appropriateness); no costs (affordability); information, dignity/respect (continuity); and swift referrals, collaboration (coordination)., Discussion: Between countries, significant differences exist in the perceived quality of primary care and priorities with regard to quality assessment. Taking into account the citizens' perspective in decision-making means that aspects with low perceived quality that are highly prioritized warrant further action., Competing Interests: The authors have declared that no competing interest exist.