Value in Health最新文献

Objectives: Incorporating patient-reported outcomes (PROs) to assess symptomatic adverse events (AEs) in cancer clinical trials (CTs) is important to characterize treatment tolerability. Cancer therapies approved over the past decade have expanded the types of expected toxicities. To inform future symptomatic AE PRO item selection, we identified the most common symptomatic adverse reactions from recently approved products.

Methods: We reviewed approvals from 2015 to 2021 for lung, breast, and hematologic cancer indications. Using United States Prescribing Information safety data, we recorded symptomatic adverse reactions reported in ≥20% of patients in the experimental arm of CTs supporting approvals. We calculated the proportion of arms reporting each symptomatic adverse reaction.

Results: In total, 130 experimental arms were included (lung = 30, breast = 10, hematologic = 90). For all cancer types, fatigue and diarrhea were reported in >50% of the arms. Nausea was reported in ≥50% of the arms for all except lung. Vomiting, decreased appetite, and alopecia, were reported in ≥50% of breast cancer arms. Rash, musculoskeletal pain, and cough were reported in >50% of leukemia/lymphoma arms. Cough was common (50%) in multiple myeloma arms.

Conclusions: Heterogeneity in symptomatic adverse reactions across CTs supports the use of item libraries when building a PRO strategy to assess tolerability. Fatigue, diarrhea, and nausea were the most frequent symptomatic adverse reactions reported in contemporary cancer CTs and could provide a starting point when selecting PRO symptomatic AE items. Additional symptomatic AE PRO items should be selected based on the mechanism of action, early clinical data, published literature, and patient and clinician input.

Objectives: Although substantial evidence exists on the costs and benefits of cancer care and screening programs for the general population, economic evidence of interventions addressing inequalities is less well known. This systematic review summarized economic evaluations of interventions addressing inequalities in cancer screening and care to inform decision makers on the value for money of such interventions.

Methods: Embase, MEDLINE, Cochrane Library, EconLit, and Scopus databases were searched for studies published from database inception to October 27, 2023. Studies were eligible for inclusion if they were economic evaluations of interventions to improve or address inequalities in cancer care among disadvantaged population groups. Study characteristics and cost-effectiveness results (US dollars 2023) were summarized. Study quality was assessed by 2 authors using the Drummond checklist.

Results: The searches yielded 2937 records, with 30 meeting the eligibility criteria for data extraction. In most of the studies (n = 27, 90%), interventions were considered cost-effective in addressing inequalities in cancer care and screening among disadvantaged populations. Notably, 60% of the studies were rated as high quality, 33.3% as good, and 6.7% as fair quality.

Conclusions: This systematic review identified cost-effective strategies addressing inequalities in cancer screening and care that have the potential to be replicated in other locations. The interventions were mainly focused on screening programs, and few addressed equity gaps around risk reduction and diagnostic and treatment outcomes. This underscores the need for targeted approaches to address inequalities in under-researched priority population groups along the cancer care continuum.

Objectives: This study examines the impact of slippage in hazard ratios (tending toward the null over subsequent datacuts) for overall survival for combination treatment with a PD-(L)-1 inhibitor and a tyrosine kinase inhibitor in advanced renal cell carcinoma.

Methods: Four trials' Kaplan-Meier curves were digitized over several datacuts and fitted with standard parametric curves. Accuracy and consistency of early data projections were calculated versus observed restricted mean survival time and fitted lifetime survival from the longest follow-up datacut. The change in economically justifiable price (eJP) was calculated fitting the same curve to both arms, using an assumed average utility of 0.7 and willingness-to-pay threshold of £30 000 per quality-adjusted life-year. The eJP represents the lifetime justifiable price increment for the new treatment, including differences in drug-, administration-, and disease-related costs.

Results: Slippage in hazard ratios was observed in trials with longer follow-up, potentially influenced by subsequent PD-(L)-1 use after tyrosine kinase inhibitor monotherapy, early stoppage of PD-(L)-1, and development of resistance. Lognormal and log-logistic curves were more likely to overpredict the observed result; Gompertz and gamma underpredicted. Statistical measures of goodness of fit did not select the curves that resulted in the RMST closest to what was observed in the final data cut. Large differences in incremental mean life-years were observed between even the penultimate and final datacuts for most of the fitted curves, meaningfully affecting the eJP.

Conclusions: This work demonstrates the challenge in predicting treatment benefits with novel therapies using immature data. Incorporating information on the impact of subsequent treatment is likely to play a key role in improving predictions.

Objectives: Decision-analytic models assessing the value of emerging Alzheimer's disease (AD) treatments are challenged by limited evidence on short-term trial outcomes and uncertainty in extrapolating long-term patient-relevant outcomes. To improve understanding and foster transparency and credibility in modeling methods, we cross-compared AD decision models in a hypothetical context of disease-modifying treatment for mild cognitive impairment (MCI) due to AD.

Methods: A benchmark scenario (US setting) was used with target population MCI due to AD and a set of synthetically generated hypothetical trial efficacy estimates. Treatment costs were excluded. Model predictions (10-year horizon) were assessed and discussed during a 2-day workshop.

Results: Nine modeling groups provided model predictions. Implementation of treatment effectiveness varied across models based on trial efficacy outcome selection (clinical dementia rating - sum of boxes, clinical dementia rating - global, mini-mental state examination, functional activities questionnaire) and analysis method (observed severity transitions, change from baseline, progression hazard ratio, or calibration to these). Predicted mean time in MCI ranged from 2.6 to 5.2 years for control strategy and from 0.1 to 1.0 years for difference between intervention and control strategies. Predicted quality-adjusted life-year gains ranged from 0.0 to 0.6 and incremental costs (excluding treatment costs) from -US$66 897 to US$11 896.

Conclusions: Trial data can be implemented in different ways across health-economic models leading to large variation in model predictions. We recommend (1) addressing the choice of outcome measure and treatment effectiveness assumptions in sensitivity analysis, (2) a standardized reporting table for model predictions, and (3) exploring the use of registries for future AD treatments measuring long-term disease progression to reduce uncertainty of extrapolating short-term trial results by health-economic models.

Objectives: X-linked retinitis pigmentosa (XLRP) is a rare inherited retinal disease with no available treatment. Gene therapies in clinical trials will pose challenges for health technology assessment (HTA) if found to be safe and effective. We evaluated 2 of these challenges, namely acceptability and difficulties in assessing value beyond short-term patient health and healthcare savings and discounting in economic evaluation.

Methods: We conducted a narrative literature review on the socioeconomic burden of XLRP to identify relevant components of value for a hypothetical gene therapy from a societal perspective and to assess their relative importance. We compared the resulting value profile against the value frameworks of three European HTA agencies. We also reviewed their guidelines on discounting and potential discounting issues specific to XLRP.

Results: Much of the societal value of an XLRP gene therapy is likely to originate from productivity effects, carer spillovers, and value elements related to patient uncertainty. The evidence on these effects, however, is often limited, making it difficult for HTA agencies to assess them. Cost-effectiveness results are likely to be highly sensitive to the discount rate, and discounting will compound the effects of omitting important sources of value.

Conclusions: We have identified and detailed important components of societal value, key evidence gaps, and potential discounting issues for an XLRP gene therapy, which can inform future value assessments. Many of these may apply to gene therapies in other disease areas. Revisiting existing HTA approaches is recommended to ensure these are fit for purpose for such new classes of treatment.

Objectives: To identify the types of disease most likely to be affected by the Institute for Clinical and Economic Review's (ICER) shared savings assumptions.

Methods: For diseases with treatments that were Food and Drug Administration approved between 2019 and 2023, annual direct and indirect economic burden and characteristics of each disease were extracted from peer-reviewed literature. ICER's shared savings methodology was applied 2 ways: 50/50 shared savings and $150 000 cost-offset cap. The primary outcome was the difference in eligible cost savings provided by a hypothetical disease cure under ICER's 2 shared savings methods. Characteristics of diseases most impacted by these 2 methods were evaluated descriptively.

Results: Food and Drug Administration approved 260 therapies for 89 unique diseases between 2019 and 2023. Shared savings reduced value of a hypothetical cure for hemophilia A most (50/50 method: -$367 670 per year; cap method: -$585 340 per year), followed by acute hepatic porphyria (50/50 method: -$333 948; cap method: -$517 896) and paroxysmal nocturnal hemoglobinuria (50/50 method: -$291 997; cap method: -$433 993). Compared with diseases with annual burdens <$150 000, those ≥$150 000 had earlier disease onset by 22.0 years (age 12.3 vs 34.3), lower life expectancy by 10.6 years (55.8 vs 66.4 years), and lower disease prevalence (4.7 vs 1981.5 per 100 000). Shared savings' impact on health-benefit price benchmarks was projected to be larger for diseases with shorter life expectancy (ρ = -0.319; p =.005), worse quality of life (ρ = -0.263; P =.020), and lower prevalence (ρ = -0.418; P < .001).

Conclusions: ICER's shared savings assumptions would most likely have the largest negative impact on health-benefit price benchmarks for rare, severe, and pediatric diseases.

Objectives: To develop the Dysmenorrhea-related Impact on Functioning Scale (DIFS) to assess the impact of dysmenorrhea on functioning in cisgender women and transgender men and to evaluate its measurement properties.

Methods: Mixed and online design study conducted with adolescents and adult cisgender women and transgender men with dysmenorrhea. We developed the DIFS based on the International Classification of Functioning, Disability, and Health. Content validity was assessed with experts and people with dysmenorrhea. Item Response Theory developed the DIFS total score. Structural validity was assessed by exploratory and confirmatory factor analysis and internal consistency by Cronbach's α and McDonald's Ω. Construct validity and test-retest reliability were assessed by correlation between DIFS and World Health Organization Disability Assessment Schedule and intraclass correlation coefficient, respectively. Measurement error was also assessed.

Results: A total of 3335 people participated in the study. The DIFS is a 15-item instrument divided into "Bodily Functions" and "Daily Activities and Social Participation" sections and "Functioning" as a general factor. Internal consistency (α and Ω > 0.7) and test-retest reliability (intraclass correlation coefficient > 0.9) were adequate. No systematic error was found. Correlation was positive and strong between World Health Organization Disability Assessment Schedule and "Functioning" (r = 0.62, P ≤ .05). For the DIFS total score, higher scores indicate a greater impact of dysmenorrhea on functioning, and 44 points is the cutoff point for classifying the person with a significant impact of dysmenorrhea on functioning.

Conclusions: DIFS showed excellent measurement properties for assessing the impact of dysmenorrhea on functioning for cisgender women and transgender men.

Objectives: To investigate heterogeneity in the cost-effectiveness of high-flow nasal cannula (HFNC) therapy compared with continuous positive airway pressure (CPAP) for acutely ill children requiring noninvasive respiratory support.

Methods: Using data from the First-line Support for Assistance in Breathing in Children trial, we explore heterogeneity at the patient and subgroup levels using 2 causal forest approaches and a seemingly unrelated regression approach for comparison. First-line Support for Assistance in Breathing in Children is a noninferiority randomized controlled trial (ISRCTN60048867) involving 24 UK pediatric intensive care units. The Step-up trial focuses on acutely ill children aged 0 to 15 years, requiring noninvasive respiratory support. A total of 600 children were randomly assigned to HFNC and CPAP groups in a 1:1 allocation ratio, with 94 patients excluded because of data unavailability.

Results: The primary outcome is the incremental net monetary benefit (INB) of HFNC compared with CPAP, using a willingness-to-pay threshold of £20 000 per quality-adjusted life year gain. INB is derived from total costs and quality-adjusted life years at 6 months. Subgroup analysis showed that some subgroups, such as male children, those aged less than 12 months, and those without severe respiratory distress at randomization, had more favorable INB results. Patient-level analysis revealed heterogeneity in INB estimates, particularly driven by the cost component, with greater uncertainty for those with higher INBs.

Conclusions: The estimated overall INB of HFNC is significantly larger for specific patient subgroups, suggesting that the cost-effectiveness of HFNC can be heterogeneous, which highlights the importance of considering patient characteristics in evaluating the cost-effectiveness of HFNC.

Objectives: Decision models for economic evaluation are increasingly including health-related quality of life (HRQoL) for informal/unpaid carers, but these estimates often come from poor quality data and typically rely on cross-sectional analysis. We aimed to identify within-person effects using longitudinal analysis of 13 waves of Understanding Society (the UK Household Longitudinal Survey).

Methods: We analyzed data for coresident carer and care-recipient dyads, where the carer reported "looking after or giving special help to" the care recipient in any of the 13 waves. We used fixed-effects models to study the effects of caring for the care recipient (the "caregiving" effect) using volume of care (hours per week) and continuous duration of caregiving (years) and caring about the care recipient (the "family" effect) using the care recipient's HRQoL on the carer's HRQoL. HRQoL was measured using the Short Form 6 Dimension, calculated from the Short Form 12.

Results: We found consistent evidence for the family effect: improving care recipient's HRQoL by 0.1 would improve carer's HRQoL by approximately 0.012. We also consistently found evidence of a small but statistically significant decrement to carer's HRQoL for each additional year of caring. These findings were robust to scenario analyses. Evidence for the relationship between volume of care and carer's HRQoL was less clear.

Conclusions: We propose that our estimates can be used to populate economic models to predict changes in carers' HRQoL over time and allow disutilities to be estimated separately for the family and caregiving effect.

Objectives: To systematically review published evidence on cancer drug wastage and the effectiveness of mitigation methods.

Methods: Search keywords for Scopus, PubMed, and EMBASE were developed using the Pearl Growing technique. Relevant articles were identified in a two-step process: first based on titles/abstracts, then on full article reviews. Among the identified English peer-reviewed articles, those considering adults ≥18 years and relevant cancer drug wastage outcomes were included. Key concepts and measures for drug wastage and its mitigation were tabulated. Trends in publication numbers were analyzed using Mann-Kendall tests. Costs were converted first to 2024 local currencies using country-wise consumer price indexes, and then to 2024 USD using exchange rates.

Results: Among 6,298 unique articles, 94 met the inclusion criteria. Seventy-four (79%) of these were published since 2015, highlighting increasing attention to cancer drug wastage. Twenty-three articles (24%) explicitly reported drug wastage amounts, whereas fifty-two articles (55%) considered the mitigation methods. Most articles focused on high-income countries (n=67), single hospital settings (n=45), and retrospective study designs (n=55). Wastage mitigation techniques included vial-sharing (n=21), dose-rounding (n=17), closed-system transfer device (n=9), centralized drug preparation (n=7), and vial size optimization (n=7). A trend towards higher median wastage cost was evident in US settings ($135.35/patient-month) compared to other countries ($37.71/patient-month)), while mitigation methods across countries were not statistically significant.

Conclusions: High cancer drug costs highlight the importance of minimizing drug wastage to reduce healthcare expenditure. Our review demonstrates that wastage varies by healthcare setting and mitigation technique. Future studies would benefit from reporting standards for cancer drug wastage that include reporting wastage (both in mg and cost, preferably in terms of Purchase Power Parity), as well as cohort size, considered vial sizes, considered dosages, and employed mitigation methods separately for each drug. This approach would account for variability in cancer drug wastage and help identify optimal mitigation practices tailored to the health system context.