Systematic review and meta-analysis of preoperative predictors for early mortality following hip fracture surgery.

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.

Comparing quality of breast cancer care in the Netherlands and Norway by federated propensity score analytics.

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.

Suitability of Preference Methods Across the Medical Product Lifecycle: A Multicriteria Decision Analysis.

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.

Adherence to the Dutch Breast Cancer Guidelines for Surveillance in Breast Cancer Survivors: Real-World Data from a Pooled Multicenter Analysis.

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.

Comparing Modeling Approaches for Discrete Event Simulations With Competing Risks Based on Censored Individual Patient Data: A Simulation Study and Illustration in Colorectal Cancer.

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.

The ICEpop Capability Measure for Adults Instrument for Capabilities: Development of a Tariff for the Dutch General Population.

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.

Exploring the importance of controlling heteroskedasticity and heterogeneity in health valuation: a case study on Dutch EQ-5D-5L.

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.

The ICECAP-A instrument for capabilities: assessment of construct validity and test-retest reliability in a general Dutch population.

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.

Continuous vital sign monitoring using a wearable patch sensor in obese patients: a validation study in a clinical setting.

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.

Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model.

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.

Evaluating the Age-Based Recommendations for Long-Term Follow-Up in Breast Cancer.

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.

Applying Risk-Based Follow-Up Strategies on the Dutch Breast Cancer Population: Consequences for Care and Costs.

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.

Single tube liquid biopsy for advanced non-small cell lung cancer.

The need for a liquid biopsy in non-small cell lung cancer (NSCLC) patients is rapidly increasing. We studied the relation between overall survival (OS) and the presence of four cancer biomarkers from a single blood draw in advanced NSCLC patients: EpCAMhigh circulating tumor cells (CTC), EpCAMlow CTC, tumor-derived extracellular vesicles (tdEV) and cell-free circulating tumor DNA (ctDNA). EpCAMhigh CTC were detected with CellSearch, tdEV in the CellSearch images and EpCAMlow CTC with filtration after CellSearch. ctDNA was isolated from plasma and mutations present in the primary tumor were tracked with deep sequencing methods. In 97 patients, 21% had ≥2 EpCAMhigh CTC, 15% had ≥2 EpCAMlow CTC, 27% had ≥18 tdEV and 19% had ctDNA with ≥10% mutant allele frequency. Either one of these four biomarkers could be detected in 45% of the patients and all biomarkers were present in 2%. In 11 out of 16 patients (69%) mutations were detected in the ctDNA. Two or more unfavorable biomarkers were associated with poor OS. The presence of EpCAMhigh CTC and elevated levels of tdEV and ctDNA was associated with a poor OS; however, the presence of EpCAMlow CTC was not. This single tube approach enables simultaneous analysis of multiple biomarkers to explore their potential as a liquid biopsy.

Exacerbation action plans for patients with COPD and comorbidities: a randomised controlled trial.

This international randomised controlled trial evaluated whether COPD patients with comorbidities, trained in using patient-tailored multidisease exacerbation action plans, had fewer COPD exacerbation days than usual care (UC).COPD patients (Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification II-IV) with ≥1 comorbidity (ischaemic heart disease, heart failure, diabetes, anxiety, depression) were randomised to a patient-tailored self-management intervention (n=102) or UC (n=99). Daily symptom diaries were completed for 12 months. The primary outcome "COPD exacerbation days per patient per year" was assessed using intention-to-treat analyses.No significant difference was observed in the number of COPD exacerbation days per patient per year (self-management: median 9.6 (interquartile range (IQR) 0.7-31.1); UC: median 15.6 (IQR 3.0-40.3); incidence rate ratio (IRR) 0.87 (95% CI 0.54; 1.39); p=0.546). There was a significantly shorter duration per COPD exacerbation for self-management (self-management: median 8.1 (IQR 4.8-10.1) days; UC: median 9.5 (IQR 7.0-15.1) days; p=0.021), with no between-group differences in the total number of respiratory hospitalisations (IRR 0.76 (95% CI 0.42; 1.35); p=0.348), but a lower probability of ≥1 for respiratory-related hospitalisation compared to UC (relative risk 0.55 (95% CI 0.35; 0.87); p=0.008). No between-group differences were observed in all-cause hospitalisations (IRR 1.07 (95% CI 0.66; 1.72)) or mortality (self-management: n=4 (3.9%); UC: n=7 (7.1%); relative risk 0.55 (95% CI 0.17; 1.84)).Patient-tailored exacerbation action plans for COPD patients with comorbidities did not significantly reduce exacerbation days, but reduced the duration per COPD exacerbation and the risk of having at least one respiratory-related hospitalisation during follow-up, without excess all-cause mortality.

Does Inclusion of Interactions Result in Higher Precision of Estimated Health State Values?

BACKGROUND: Most preference-based instruments producing overall values for health states are devised on the simplifying assumption that the overall effect of distinct health-related quality of life domains (attributes) of the instrument equals the sum of the attributes. Nevertheless, health attributes are often inter-related and depend on each other. OBJECTIVES: To investigate whether inclusion of second-order interactions in the three-level EuroQol five-dimensional questionnaire (EQ-5D-3L) value function would result in better fit and lead to different health state values than a model with main effects only. METHODS: Using an efficient design, 400 pairs of EQ-5D-3L health states were generated in a pairwise choice format. We analyzed responses of 4000 people from the general population using a conditional logit model, and we tested goodness of fit using pseudo R2, Akaike information criterion, differences in log-likelihood, and likelihood ratio. We compared accuracies of models' predictions based on root mean square error and mean absolute error. RESULTS: The interaction-effects model showed systematically lower values than the main-effects model. Inclusion of interactions resulted only in a slightly better model fit. Interactions comprising mobility and self-care were the most salient. CONCLUSIONS: For the EQ-5D-3L, a value function based on interactions produces systematically lower values than a main-effects model, meaning that the effect of two or more health problems combined is stronger than the sum of the individual main effects.

Assessing Lung Cancer Screening Programs under Uncertainty in a Heterogeneous Population.

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.

Choice Defines Value: A Predictive Modeling Competition in Health Preference Research.

OBJECTIVE: To identify which specifications and approaches to model selection better predict health preferences, the International Academy of Health Preference Research (IAHPR) hosted a predictive modeling competition including 18 teams from around the world. METHODS: In April 2016, an exploratory survey was fielded: 4074 US respondents completed 20 out of 1560 paired comparisons by choosing between two health descriptions (e.g., longer life span vs. better health). The exploratory data were distributed to all teams. By July, eight teams had submitted their predictions for 1600 additional pairs and described their analytical approach. After these predictions had been posted online, a confirmatory survey was fielded (4148 additional respondents). RESULTS: The victorious team, "Discreetly Charming Econometricians," led by Michal Jakubczyk, achieved the smallest χ2, 4391.54 (a predefined criterion). Its primary scientific findings were that different models performed better with different pairs, that the value of life span is not constant proportional, and that logit models have poor predictive validity in health valuation. CONCLUSIONS: The results demonstrated the diversity and potential of new analytical approaches in health preference research and highlighted the importance of predictive validity in health valuation.

A preference-based item response theory model to measure health: concept and mathematics of the multi-attribute preference response model.

BACKGROUND: A new patient-reported health measurement model has been developed to quantify descriptions of health states. Known as the multi-attribute preference response (MAPR) model, it is based on item response theory. The response task in the MAPR is for a patient to judge whether hypothetical health-state descriptions are better or worse than his/her own health status. METHODS: In its most simple form MAPR is a Rasch model where for each respondent on the same unidimensional health scale values are estimated of their own health status and values of the hypothetical comparator health states. These values reflect the quality or severity of the health states. Alternatively, the respondents are offered health-state descriptions that are based on a classification system (e.g., multi-attribute) with a fixed number of health attributes, each with a limited number of levels. In the latter variant, the weights of the levels of the attributes in the descriptive system, which represents the range of the health states, are estimated. The results of a small empirical study are presented to illustrate the procedures of the MAPR model and possible extensions of the model are discussed. RESULTS: The small study that we conducted to illustrate the procedure and results of our proposed method to measure the quality of health states and patients' own health status showed confirming results. CONCLUSIONS: This paper introduces the typical MAPR model and shows how it extends the basic Rasch model with a regression function for the attributes of the health-state classification system.

Public Preferences for Lung Cancer Screening Policies.

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.

Valuing Treatments for Parkinson Disease Incorporating Process Utility: Performance of Best-Worst Scaling, Time Trade-Off, and Visual Analogue Scales.

OBJECTIVE: The objective of this study was to compare treatment profiles including both health outcomes and process characteristics in Parkinson disease using best-worst scaling (BWS), time trade-off (TTO), and visual analogue scales (VAS). METHODS: From the model comprising of seven attributes with three levels, six unique profiles were selected representing process-related factors and health outcomes in Parkinson disease. A Web-based survey (N = 613) was conducted in a general population to estimate process-related utilities using profile-based BWS (case 2), multiprofile-based BWS (case 3), TTO, and VAS. The rank order of the six profiles was compared, convergent validity among methods was assessed, and individual analysis focused on the differentiation between pairs of profiles with methods used. RESULTS: The aggregated health-state utilities for the six treatment profiles were highly comparable for all methods and no rank reversals were identified. On the individual level, the convergent validity between all methods was strong; however, respondents differentiated less in the utility of closely related treatment profiles with a VAS or TTO than with BWS. For TTO and VAS, this resulted in nonsignificant differences in mean utilities for closely related treatment profiles. CONCLUSIONS: This study suggests that all methods are equally able to measure process-related utility when the aim is to estimate the overall value of treatments. On an individual level, such as in shared decision making, BWS allows for better prioritization of treatment alternatives, especially if they are closely related. The decision-making problem and the need for explicit trade-off between attributes should determine the choice for a method.