Search

Contains fulltext : 294867.pdf (Publisher’s version ) (Open Access), OBJECTIVE: Approximately one third of children with JIA receive biologic therapy, but evidence on biologic therapy withdrawal is lacking. This study aims to increase our understanding of whether and when pediatric rheumatologists postpone a decision to withdraw biologic therapy in children with clinically inactive non-systemic JIA. METHODS: A survey containing questions about background characteristics, treatment patterns, minimum treatment time with biologic therapy, and 16 different patient vignettes, was distributed among 83 pediatric rheumatologists in Canada and the Netherlands. For each vignette, respondents were asked whether they would withdraw biologic therapy at their minimum treatment time, and if not, how long they would continue biologic therapy. Statistical analysis included descriptive statistics, logistic and interval regression analysis. RESULTS: Thirty-three pediatric rheumatologists completed the survey (40% response rate). Pediatric rheumatologists are most likely to postpone the decision to withdraw biologic therapy when the child and/or parents express a preference for continuation (OR 6.3; p < 0.001), in case of a flare in the current treatment period (OR 3.9; p = 0.001), and in case of uveitis in the current treatment period (OR 3.9; p < 0.001). On average, biologic therapy withdrawal is initiated 6.7 months later when the child or parent prefer to continue treatment. CONCLUSION: Patient's and parents' preferences were the strongest driver of a decision to postpone biologic therapy withdrawal in children with clinically inactive non-systemic JIA and prolongs treatment duration. These findings highlight the potential benefit of a tool to support pediatric rheumatologists, patients and parents in decision making, and can help inform its design.

Purpose The estrogen (ER), progesterone (PR), and HER2 status are essential in guiding treatment decisions in breast cancer patients. In daily life, the ER/PR/HER2 status is expected to be commonly tested twice, i.e., at diagnosis using material from tumor needle biopsies, and after tumor resection using full tumor tissue material. This study explored the discordance of ER/PR/HER2 between tumor needle biopsies and full tumor resection material using real-world patient-level data from Dutch breast cancer patients. Methods Pathology reports of 11,054 breast cancer patients were derived from PALGA (Dutch Pathology Registry). Discordance was calculated for multiple combinations of the ER/PR/HER2 receptor status. The influence of patient and tumor characteristics on the probability of having discordant test results was analyzed using multiple logistic regression models (separately for ER, PR and HER2). Results For 1279 patients (14.4%), at least one of the receptors (ER/PR/HER2) was determined on both biopsy and tumor tissue material. The majority had concordant test results for ER (n=916; 94.8%), PR (n=1170; 86.7%), and HER2 (n=881; 98.1%). Patients having an ER- and HER2-positive but PR-negative biopsy classification, BR grade III, and <10% tumor tissue remaining after neoadjuvant therapy (NAT) have the highest probability of ER discordant test results (OR4.991; p=83.31%). The probability of discordance in PR is based on different sets of patient and tumor characteristics. Potential cost savings from omitting multiple tests if concordance can be perfectly predicted can be up to €205,000 yearly. Conclusions Double testing of ER/PR/HER2 is less common than expected. Discordance in ER/PR/HER2 test results between tumor needle biopsy taken at the time of diagnosis and tumor resection material is very low, especially in patients not receiving any form of neoadjuvant therapy. These results imply that a substantial number of tests can potentially be omitted in specific subgro

Contains fulltext : 200589.pdf (Publisher’s version ) (Closed access), BACKGROUND: Lung cancer screening can reduce cancer mortality. Most implementation studies focus only on low-dose computed tomography (LDCT) and clinical attributes of screening and do not include preferences of potential participants. In this study we evaluated the perceived value of screening programs based on LDCT, breath analysis (BA), or blood biomarkers (BB) according to the perspective of the target population. METHODS: A multi-criteria decision analysis framework was adopted. The weights of seven attributes of screening (sensitivity, specificity, radiation burden, duration of screening process, waiting time until results are communicated, location of screening, and mode of screening) were obtained from an earlier study that included a broad sample from the Netherlands. Performance data for the screening modalities was obtained from clinical trials and expert opinion. Parameter uncertainty about clinical performances was incorporated probabilistically, while heterogeneity in preferences was analyzed through subgroup analyses. RESULTS: The mean overall values were 0.58 (CI: 0.57 to 0.59), 0.57 (CI: 0.56 to 0.59), and 0.44 (CI: 0.43 to 0.45) for BB, BA, and LDCT, respectively. Seventy-seven per cent of respondents preferred BB or BA. For most subgroups, the overall values were similar to those of the entire sample. BA had the highest value for respondents who would have been eligible for earlier screening trials. DISCUSSION: BB and BA seem valuable to participants because they can be applied in a primary care setting. Although LDCT still seems preferable given its strong and positive evidence base, it is important to take non-clinical attributes into account to maximize attendance.

Context: In advanced prostate cancer (PC), there is increasing investigation of circulating biomarkers, including quantitation and characterization of circulating tumour cells and cell-free nucleic acids, for therapeutic monitoring and as prognostic and predictive biomarkers. However, there is a lack of consensus and standardisation regarding analyses, reporting, and integration of results into specific clinical contexts. A consensus meeting on circulating biomarkers was held to address these topics. Objective: To present a report of the consensus statement on circulating biomarkers in advanced PC. Evidence acquisition: Four important areas of controversy in the field of circulating biomarkers in PC management were identified: known clinical utility of circulating biomarkers; unmet clinical needs for circulating biomarkers in PC care; most pressing blood-based molecular assays required; and essential steps for developing circulating biomarker assays. A panel of 18 international PC experts in the field of circulating biomarkers developed the programme and consensus questions. The panel voted publicly but anonymously on 50 predefined questions developed following a modified Delphi process. Evidence synthesis: Voting was based solely on panellist opinions of the predefined topics and therefore not on a standard literature review or meta-analysis. The outcomes of the voting had varying degrees of support, as reflected in the wording of this article and in the detailed voting results provided in the Supplementary material. Conclusions: The expert voting results presented can guide the future development of circulating biomarkers for PC care. Notably, the consensus meeting highlighted the importance of reproducibility and variability studies, among other significant areas in need of trials specifically designed to address them. Patient summary: A panel of international experts met to discuss and vote on the use of different blood-based prostate cancer tests, and how they

Background Establishing the underlying cause of anaemia in general practice is a diagnostic challenge. Currently, general practitioners individually determine which laboratory tests to request (routine work-up) in order to diagnose the underlying cause. However, an extensive work-up (consisting of 14 tests) increases the proportion of patients correctly diagnosed. This study investigates the cost-effectiveness of this extensive work-up. Methods A decision-analytic model was developed, incorporating all societal costs from the moment a patient presents to a general pra

Background: For rational decision making, assessing the cost-effectiveness and budget impact of new drugs and comparing the costs of drugs already on the market is required. In addition to value frameworks, such as the American Society of Clinical Oncology Value Framework and the European Society of Medical Oncology–Magnitude of Clinical benefit Scale, this also requires a transparent overview of actual drug prices. While list prices are available, evidence on treatment cost is not. This paper aims to synthesise evidence on the reimbursement and costs of high-cost breast cancer drugs in The Netherlands (NL). Methods: A literature review was performed to identify currently reimbursed breast cancer drugs in the NL. Treatment costs were determined by multiplying list prices with the average length of treatment and dosing schedule. Results: Comparing list prices to the estimated treatment cost resulted in substantial differences in the ranking of costliness of the drugs. The average mean treatment length was unknown for 11/31 breast cancer drugs (26.2%). The differences in the 15 highest-cost drugs were largest for Bevacizumab, Lapatinib and everolimus, with list prices of €541, €158, €1,168 and estimated treatment cost of €174,400, €18,682 and €31,207, respectively. The lowest-cost (patented) targeted drug is €1,818 more expensive than the highest-cost (off-patent) generic drug according to the estimated drug treatment cost. Conclusions: A lack of evidence on the reimbursement and cost of high-cost breast cancer drugs complicates rapid and transparent evidence synthesis, necessary to focus strategies aiming to limit the increasing healthcare costs. Interestingly, the findings show that off-patent generics (such as paclitaxel or doxorubicin), although substantially cheaper than patented drugs, are still relatively costly. Extending standardisation and increasing European and national regulations on presenting information on costs per cancer drug is highly recommended.

Item does not contain fulltext, BACKGROUND: Because early detection of lung cancer can substantially improve survival, there is increasing attention for lung cancer screening. OBJECTIVES: To estimate public preferences for lung cancer screening and to identify subgroups in preferences. METHODS: Seven important attributes were selected using the literature, interviews, and a panel session. Preferences were elicited using a swing weighting questionnaire. The resulting attribute weights indicate the relative importance of swings from the worst to the best level between attributes. Hierarchical clustering was used to identify subgroups with different attribute weights. RESULTS: One thousand thirty-four respondents from a representative Dutch panel aged between 40 and 80 years were included. The identified attributes were location of screening (weight = 0.18 +/- 0.16), mode of screening (weight = 0.17 +/- 0.14), sensitivity (weight = 0.16 +/- 0.13) and specificity (weight = 0.13 +/- 0.12) of the screening modality, waiting time until results (weight = 0.13 +/- 0.12), radiation burden (weight = 0.13 +/- 0.12), and duration of screening procedure (weight = 0.10 +/- 0.09). Most respondents preferred breath analysis (45%) to giving blood samples (31%) or going through a scanner (24%) as screening modality; 59% preferred screening at the general practitioner's office instead of at the hospital. There was a significant difference in education between the five identified preference subgroups (P < 0.01). CONCLUSIONS: There is considerable variation in how people value attributes of lung cancer screening. Different screening policies and implementation strategies may be appropriate for particular preference subgroups. Our results indicate that people prefer breath analysis and that they are more likely to attend screening modalities that can be used at a primary care facility.

Contains fulltext : 182686.pdf (Publisher’s version ) (Open Access), The need for patient engagement has been recognized by regulatory agencies, but there is no consensus about how to operationalize this. One approach is the formal elicitation and use of patient preferences for weighing clinical outcomes. The aim of this study was to demonstrate how patient preferences can be used to weigh clinical outcomes when both preferences and clinical outcomes are uncertain by applying a probabilistic value-based multi-criteria decision analysis (MCDA) method. Probability distributions were used to model random variation and parameter uncertainty in preferences, and parameter uncertainty in clinical outcomes. The posterior value distributions and rank probabilities for each treatment were obtained using Monte-Carlo simulations. The probability of achieving the first rank is the probability that a treatment represents the highest value to patients. We illustrated our methodology for a simplified case on six HIV treatments. Preferences were modeled with normal distributions and clinical outcomes were modeled with beta distributions. The treatment value distributions showed the rank order of treatments according to patients and illustrate the remaining decision uncertainty. This study demonstrated how patient preference data can be used to weigh clinical evidence using MCDA. The model takes into account uncertainty in preferences and clinical outcomes. The model can support decision makers during the aggregation step of the MCDA process and provides a first step toward preference-based personalized medicine, yet requires further testing regarding its appropriate use in real-world settings.

Item does not contain fulltext, BACKGROUND: To increase the adherence of health professionals and cancer survivors to evidence-based physical exercise, effective implementation strategies (ISTs) are required. OBJECTIVES: To examine to what extent these ISTs provide value for money and which IST has the highest expected value. METHODS: The net benefit framework of health economic evaluations is used to conduct a value-of-implementation analysis of nine ISTs. Seven are directed to health professionals and two to cancer survivors. The analysis consists of four steps: 1) analyzing the expected value of perfect implementation (EVPIM); 2) assessing the estimated costs of the various ISTs; 3) comparing the ISTs' costs with the EVPIM; and 4) assessing the total net benefit (TNB) of the ISTs. These steps are followed to identify which strategy has the greatest value. RESULTS: The EVPIM for physical exercise in the Netherlands is euro293 million. The total costs for the ISTs range from euro34,000 for printed educational materials for professionals to euro120 million for financial incentives for patients, and thus all are cost-effective. The TNB of the ISTs that are directed to professionals ranges from euro5.7 million for printed educational materials to euro30.9 million for reminder systems. Of the strategies that are directed to patients, only the motivational program had a positive net benefit of euro100.4 million. CONCLUSIONS: All the ISTs for cancer survivors, except for financial incentives, had a positive TNB. The largest improvements in adherence were created by a motivational program for patients, followed by a reminder system for professionals.

Providing health services with the greatest possible value to patients and society given the constraints imposed by patient characteristics, health care system characteristics, budgets, and so forth relies heavily on the design of structures and processes. Such problems are complex and require a rigorous and systematic approach to identify the best solution. Constrained optimization is a set of methods designed to identify efficiently and systematically the best solution (the optimal solution) to a problem characterized by a number of potential solutions in the presence of identified constraints. This report identifies 1) key concepts and the main steps in building an optimization model; 2) the types of problems for which optimal solutions can be determined in real-world health applications; and 3) the appropriate optimization methods for these problems. We first present a simple graphical model based on the treatment of “regular” and “severe” patients, which maximizes the overall health benefit subject to time and budget constraints. We then relate it back to how optimization is relevant in health services research for addressing present day challenges. We also explain how these mathematical optimization methods relate to simulation methods, to standard health economic analysis techniques, and to the emergent fields of analytics and machine learning.

Item does not contain fulltext, While acute musculoskeletal pain is a frequent complaint, its management is often neglected. An implementation of a nurse-initiated pain protocol based on the algorithm of a Dutch pain management guideline in the emergency department might improve this. A pre-post intervention study was performed as part of the prospective PROTACT follow-up study. During the pre- (15 months, n = 504) and post-period (6 months, n = 156) patients' self-reported pain intensity and pain treatment were registered. Analgesic provision in patients with moderate to severe pain (NRS >/=4) improved from 46.8% to 68.0%. Over 10% of the patients refused analgesics, resulting into an actual analgesic administration increase from 36.3% to 46.1%. Median time to analgesic decreased from 10 to 7 min (P < 0.05), whereas time to opioids decreased from 37 to 15 min (P < 0.01). Mean pain relief significantly increased to 1.56 NRS-points, in patients who received analgesic treatment even up to 2.02 points. The protocol appeared to lead to an increase in analgesic administration, shorter time to analgesics and a higher clinically relevant pain relief. Despite improvements, suffering moderate to severe pain at ED discharge was still common. Protocol adherence needs to be studied in order to optimize pain management.