Search

Abstract Background The attainment of global health security goals and universal health coverage will remain a mirage unless African health systems are adequately funded to improve resilience to public health emergencies. The COVID-19 pandemic exposed the global inequity in accessing medical countermeasures, leaving African countries far behind. As we anticipate the next pandemic, improving investments in health systems to adequately finance pandemic prevention, preparedness, and response (PPPR) promptly, ensuring equity and access to medical countermeasures, is crucial. In this article, we analyze the African and global pandemic financing initiatives and put ways forward for policymakers and the global health community to consider. Methods This article is based on a rapid literature review and desk review of various PPPR financing mechanisms in Africa and globally. Consultation of leaders and experts in the area and scrutinization of various related meeting reports and decisions have been carried out. Main text The African Union (AU) has demonstrated various innovative financing mechanisms to mitigate the impacts of public health emergencies in the continent. To improve equal access to the COVID-19 medical countermeasures, the AU launched Africa Medical Supplies Platform (AMSP) and Africa Vaccine Acquisition Trust (AVAT). These financing initiatives were instrumental in mitigating the impacts of COVID-19 and their lessons can be capitalized as we make efforts for PPPR. The COVID-19 Response Fund, subsequently converted into the African Epidemics Fund (AEF), is another innovative financing mechanism to ensure sustainable and self-reliant PPPR efforts. The global initiatives for financing PPPR include the Pandemic Emergency Financing Facility (PEF) and the Pandemic Fund. The PEF was criticized for its inadequacy in building resilient health systems, primarily because the fund ignored the prevention and preparedness items. The Pandemic Fund is also being criticized for its suboptimal emphasis on the response aspect of the pandemic and non-inclusive governance structure. Conclusions To ensure optimal financing for PPPR, we call upon the global health community and decision-makers to focus on the harmonization of financing efforts for PPPR, make regional financing mechanisms central to global PPPR financing efforts, and ensure the inclusivity of international finance governance systems.

No abstract available.

Abstract Background Early in the COVID-19 pandemic, countries adopted non-pharmaceutical interventions (NPIs) such as lockdowns to limit SARS-CoV-2 transmission. Social contact studies help measure the effectiveness of NPIs and estimate parameters for modelling SARS-CoV-2 transmission. However, few contact studies have been conducted in Africa. Methods We analysed nationally representative cross-sectional survey data from 19 African Union Member States, collected by the Partnership for Evidence-based Responses to COVID-19 (PERC) via telephone interviews at two time points (August 2020 and February 2021). Adult respondents reported contacts made in the previous day by age group, demographic characteristics, and their attitudes towards COVID-19. We described mean and median contacts across these characteristics and related contacts to Google Mobility reports and the Oxford Government Response Stringency Index for each country at the two time points. Results Mean reported contacts varied across countries with the lowest reported in Ethiopia (9, SD=16, median = 4, IQR = 8) in August 2020 and the highest in Sudan (50, SD=53, median = 33, IQR = 40) in February 2021. Contacts of people aged 18–55 represented 50% of total contacts, with most contacts in household and work or study settings for both surveys. Mean contacts increased for Ethiopia, Ghana, Liberia, Nigeria, Sudan, and Uganda and decreased for Cameroon, the Democratic Republic of Congo (DRC), and Tunisia between the two time points. Men had more contacts than women and contacts were consistent across urban or rural settings (except in Cameroon and Kenya, where urban respondents had more contacts than rural ones, and in Senegal and Zambia, where the opposite was the case). There were no strong and consistent variations in the number of mean or median contacts by education level, self-reported health, perceived self-reported risk of infection, vaccine acceptance, mask ownership, and perceived risk of COVID-19 to health. Mean contacts were correlated with Google mobility (coefficient 0.57, p=0.051 and coefficient 0.28, p=0.291 in August 2020 and February 2021, respectively) and Stringency Index (coefficient −0.12, p = 0.304 and coefficient −0.33, p=0.005 in August 2020 and February 2021, respectively). Conclusions These are the first COVID-19 social contact data collected for 16 of the 19 countries surveyed. We find a high reported number of daily contacts in all countries and substantial variations in mean contacts across countries and by gender. Increased stringency and decreased mobility were associated with a reduction in the number of contacts. These data may be useful to understand transmission patterns, model infection transmission, and for pandemic planning.

Green microalgae can accumulate neutral lipids, as part of a general lipid remodeling mechanism under stress such as nitrogen starvation. Lobosphaera incisa is of special interest because of its unique TAG acyl chain composition, especially 20:4 (n-6) can reach up to 21% of dry weight after nitrogen starvation. In order to identify factors that may influence the accumulation of polyunsaturated fatty acids (PUFAs), we identified recently a linoleate 13-lipoxygenase (LiLOX). It shares highest identity with plastidic enzymes from vascular plants and is induced upon nitrogen starvation. Here, we confirmed the localization of LiLOX in the stroma of plastids via transient expression in epithelial onion cells. In order to further characterize this enzyme, we focused on the identification of the endogenous substrate of LiLOX. In this regard, an ex vivo enzymatic assay, coupled with non-targeted analysis via mass spectrometry allowed the identification of MGDG, DGDG and PC as three substrate candidates, later confirmed via in vitro assays. Further investigation revealed that LiLOX has preferences towards the lipid class MGDG, which seems in agreement with its localization in the galactolipid rich plastid. Altogether, this study shows the first characterization of plastidic LOX from green algae, showing preference for MGDGs. However, lipidomics analysis did neither reveal an endogenous LiLOX product nor the final end product of MGDG oxidation. Nevertheless, the latter is a key to understanding the role of this enzyme and since its expression is highest during the degradation of the plastidic membrane, it is tempting to assume its involvement in this process.

In older patients with acute myeloid leukemia, the more frequent presence of biologically inherent therapy-resistant disease and increased comorbidities translate to poor overall survival and therapeutic challenges. Optimal front-line therapies for older patients with acute myeloid leukemia remain controversial. We retrospectively evaluated survival outcomes in 980 elderly (≥70 years) acute myeloid leukemia patients from a single institution between 1995 and 2016. Four treatment categories were compared: high-intensity (daunorubicin/cytarabine or equivalent), hypomethylating agent, low-intensity (low-dose cytarabine or similar without hypomethylating agents), and supportive care therapy (including hydroxyurea). At a median follow up of 20.5 months, the median overall survival for the entire cohort was 7.1 months. Multivariate analysis identified secondary acute myeloid leukemia, poor-risk cytogenetics, performance status, front-line therapy, age, white blood cell count, platelet count, and hemoglobin level at diagnosis as having an impact on survival. High-intensity therapy was used in 360 patients (36.7%), hypomethylating agent in 255 (26.0%), low-intensity therapy in 91 (9.3%), and supportive care in 274 (28.0%). Pairwise comparisons between hypomethylating agent therapy and the three other treatment groups demonstrated statistically significant superior median overall survival with hypomethylating agent [14.4 months) vs. high-intensity therapy 10.8 months, hazard ratio 1.35, 95% confidence interval (CI): 1.10-1.65; P =0.004], low-intensity therapy (5.9 months, hazard ratio 2.01, 95%CI: 1.53-2.62; P

Optimal management of pregnancies at 39 weeks gestational age is unknown. Therefore, we sought to perform a comparative effectiveness analysis of elective induction of labor (eIOL) at 39 weeks among nulliparous women with non-anomalous singleton, vertex fetuses as compared to expectant management (EM) which included IOL for medical or obstetric indications or at 41 weeks in undelivered mothers.A Monte Carlo micro-simulation model was constructed modeling two mutually exclusive health states: eIOL at 39 weeks, or EM with IOL for standard medical or obstetrical indications or at 41 weeks if undelivered. Health state distribution probabilities included maternal and perinatal outcomes and were informed by a review of the literature and data derived from the Consortium of Safe Labor. Analyses investigating preferences for maternal versus infant health were performed using weighted utilities. Primary outcome was determining which management strategy posed less maternal and neonatal risk. Secondary outcomes were rates of cesarean deliveries, maternal morbidity and mortality, stillbirth, neonatal morbidity and mortality, and preferences regarding the importance of maternal and perinatal health.A management strategy of eIOL at 39 weeks resulted in less maternal and neonatal risk as compared to EM with IOL at 41 weeks among undelivered patients. Cesarean section rates were higher in the EM arm (35.9% versus 13.9%, p

Objective: To assess the adherence to antiretroviral therapy (ART) in the human immunodeficiency virus (HIV)-infected population in India. Design: Systematic review and meta-analysis. Materials and Methods: The Medline and Cochrane library database were searched. Any prospective or retrospective study enrolling a minimum of 10 subjects with a primary objective of assessing ART adherence in the HIV population in India was included. Data were extracted on adherence definition, adherence estimates, study design, study population characteristics, recall period and assessment method. For metaanalysis, the pooled proportion was calculated as a back-transform of the weighted mean of the transformed proportions (calculated according to the Freeman-Tukey variant of the arcsine square root) using the random effects model. Results: There were seven cross-sectional studies and one retrospective study enrolling 1666 participants. Publication bias was significant (P = 0.003). Pooled results showed an ART adherence rate of 70% (95% confidence interval: 59-81%, I 2 = 96.3%). Sensitivity analyses based on study design, adherence assessment method and study region did not influence adherence estimates. Fifty percent (4/8) of the studies reported cost of medication as the most common obstacle for ART adherence. Twenty-five percent (2/8) reported lack of access to medication as the reason for non-adherence and 12% (1/8) cited adverse events as the most prevalent reason for non-adherence. The overall methodological quality of the included studies was poor. Conclusion: Pooled results show that overall ART adherence in India is below the required levels to have an optimal treatment effect. The quality of studies is poor and cannot be used to guide policies to improve ART adherence.

Dual Processing Theories (DPT) assume that human cognition is governed by two distinct types of processes typically referred to as type 1 (intuitive) and type 2 (deliberative). Based on DPT we have derived a Dual Processing Model (DPM) to describe and explain therapeutic medical decision-making. The DPM model indicates that doctors decide to treat when treatment benefits outweigh its harms, which occurs when the probability of the disease is greater than the so called "threshold probability" at which treatment benefits are equal to treatment harms. Here we extend our work to include a wider class of decision problems that involve diagnostic testing. We illustrate applicability of the proposed model in a typical clinical scenario considering the management of a patient with prostate cancer. To that end, we calculate and compare two types of decision-thresholds: one that adheres to expected utility theory (EUT) and the second according to DPM. Our results showed that the decisions to administer a diagnostic test could be better explained using the DPM threshold. This is because such decisions depend on objective evidence of test/treatment benefits and harms as well as type 1 cognition of benefits and harms, which are not considered under EUT. Given that type 1 processes are unique to each decision-maker, this means that the DPM threshold will vary among different individuals. We also showed that when type 1 processes exclusively dominate decisions, ordering a diagnostic test does not affect a decision; the decision is based on the assessment of benefits and harms of treatment. These findings could explain variations in the treatment and diagnostic patterns documented in today's clinical practice.

Decision-making relies on both analytical and emotional thinking. Cognitive reasoning styles (e.g. maximizing and satisficing tendencies) heavily influence analytical processes, while affective processes are often dependent on regret. The relationship between regret and cognitive reasoning styles has not been well studied in physicians, and is the focus of this paper.A regret questionnaire and 6 scales measuring individual differences in cognitive styles (maximizing-satisficing tendencies; analytical vs. intuitive reasoning; need for cognition; intolerance toward ambiguity; objectivism; and cognitive reflection) were administered through a web-based survey to physicians of the University of South Florida. Bonferroni's adjustment was applied to the overall correlation analysis. The correlation analysis was also performed without Bonferroni's correction, given the strong theoretical rationale indicating the need for a separate hypothesis. We also conducted a multivariate regression analysis to identify the unique influence of predictors on regret.165 trainees and 56 attending physicians (age range 25 to 69) participated in the survey. After bivariate analysis we found that maximizing tendency positively correlated with regret with respect to both decision difficulty (r=0.673; p

BackgroundRandomized controlled trials (RCTs) are considered the gold standard for assessing the efficacy of new treatments compared to standard treatments. However, the reasoning behind treatment selection in RCTs is often unclear. Here, we focus on a cohort of RCTs in multiple myeloma (MM) to understand the patterns of competing treatment selections.MethodsWe used social network analysis (SNA) to study relationships between treatment regimens in MM RCTs and to examine the topology of RCT treatment networks. All trials considering induction or autologous stem cell transplant among patients with MM were eligible for our analysis. Medline and abstracts from the annual proceedings of the American Society of Hematology and American Society for Clinical Oncology, as well as all references from relevant publications were searched. We extracted data on treatment regimens, year of publication, funding type, and number of patients enrolled. The SNA metrics used are related to node and network level centrality and to node positioning characterization.Results135 RCTs enrolling a total of 36,869 patients were included. The density of the RCT network was low indicating little cohesion among treatments. Network Betweenness was also low signifying that the network does not facilitate exchange of information. The maximum geodesic distance was equal to 4, indicating that all connected treatments could reach each other in four "steps" within the same pathway of development. The distance between many important treatment regimens was greater than 1, indicating that no RCTs have compared these regimens.ConclusionOur findings show that research programs in myeloma, which is a relatively small field, are surprisingly decentralized with a lack of connectivity among various research pathways. As a result there is much crucial research left unexplored. Using SNA to visually and analytically examine treatment networks prior to designing a clinical trial can lead to better designed studies.

To assess if commercially sponsored trials are associated with higher success rates than publicly-sponsored trials.We undertook a systematic review of all consecutive, published and unpublished phase III cancer randomized controlled trials (RCTs) conducted by GlaxoSmithKline (GSK) and the NCIC Clinical Trials Group (CTG). We included all phase III cancer RCTs assessing treatment superiority from 1980 to 2010. Three metrics were assessed to determine treatment successes: (1) the proportion of statistically significant trials favouring the experimental treatment, (2) the proportion of the trials in which new treatments were considered superior according to the investigators, and (3) quantitative synthesis of data for primary outcomes as defined in each trial.GSK conducted 40 cancer RCTs accruing 19,889 patients and CTG conducted 77 trials enrolling 33,260 patients. 42% (99%CI 24 to 60) of the results were statistically significant favouring experimental treatments in GSK compared to 25% (99%CI 13 to 37) in the CTG cohort (RR = 1.68; p = 0.04). Investigators concluded that new treatments were superior to standard treatments in 80% of GSK compared to 44% of CTG trials (RR = 1.81; p

Prognostic models are often used to estimate the length of patient survival. The Cox proportional hazards model has traditionally been applied to assess the accuracy of prognostic models. However, it may be suboptimal due to the inflexibility to model the baseline survival function and when the proportional hazards assumption is violated. The aim of this study was to use internal validation to compare the predictive power of a flexible Royston-Parmar family of survival functions with the Cox proportional hazards model. We applied the Palliative Performance Scale on a dataset of 590 hospice patients at the time of hospice admission. The retrospective data were obtained from the Lifepath Hospice and Palliative Care center in Hillsborough County, Florida, USA. The criteria used to evaluate and compare the models' predictive performance were the explained variation statistic R(2), scaled Brier score, and the discrimination slope. The explained variation statistic demonstrated that overall the Royston-Parmar family of survival functions provided a better fit (R(2) =0.298; 95% CI: 0.236-0.358) than the Cox model (R(2) =0.156; 95% CI: 0.111-0.203). The scaled Brier scores and discrimination slopes were consistently higher under the Royston-Parmar model. Researchers involved in prognosticating patient survival are encouraged to consider the Royston-Parmar model as an alternative to Cox.

Controlled clinical trials are widely considered to be the vehicle to treatment discovery in cancer that leads to significant improvements in health outcomes including an increase in life expectancy. We have previously shown that the pattern of therapeutic discovery in randomized controlled trials (RCTs) can be described by a power law distribution. However, the mechanism generating this pattern is unknown. Here, we propose an explanation in terms of the social relations between researchers in RCTs. We use social network analysis to study the impact of interactions between RCTs on treatment success. Our dataset consists of 280 phase III RCTs conducted by the NCI from 1955 to 2006. The RCT networks are formed through trial interactions formed i) at random, ii) based on common characteristics, or iii) based on treatment success. We analyze treatment success in terms of survival hazard ratio as a function of the network structures. Our results show that the discovery process displays power law if there are preferential interactions between trials that may stem from researchers' tendency to interact selectively with established and successful peers. Furthermore, the RCT networks are "small worlds": trials are connected through a small number of ties, yet there is much clustering among subsets of trials. We also find that treatment success (improved survival) is proportional to the network centrality measures of closeness and betweenness. Negative correlation exists between survival and the extent to which trials operate within a limited scope of information. Finally, the trials testing curative treatments in solid tumors showed the highest centrality and the most influential group was the ECOG. We conclude that the chances of discovering life-saving treatments are directly related to the richness of social interactions between researchers inherent in a preferential interaction model.

BACKGROUND: JAMA introduced a requirement for independent statistical analysis for industry-funded trials in July 2005. We wanted to see whether this policy affected the number of industry-funded trials published by JAMA. METHODS AND FINDINGS: We undertook a retrospective, before-and-after study of published papers. Two investigators independently extracted data from all issues of JAMA published between 1 July 2002 and 30 June 2008 (i.e., three years before and after the policy). They were not blinded to publication date. The randomized controlled trials (RCTs) were classified as industry funded (IF), joint industry/non-commercial funding (J), industry supported (IS) (when manufacturers provided materials only), non-commercial (N) or funding not stated (NS). Findings were compared and discrepancies resolved by discussion or further analysis of the reports. RCTs published in The Lancet and NEJM over the same period were used as a control group. Between July 2002 and July 2008, JAMA published 1,314 papers, of which 311 were RCTs. The number of industry studies (IF, J or IS) fell significantly after the policy (p = 0.02) especially for categories J and IS. However, over the same period, the number of industry studies rose in both The Lancet and NEJM. CONCLUSIONS: After the requirement for independent statistical analysis for industry-funded studies, JAMA published significantly fewer RCTs and significantly fewer industry-funded RCTs. This pattern was not seen in the control journals. This suggests the JAMA policy affected the number of submissions, the acceptance rate, or both. Without analysing the submissions, we cannot check these hypotheses but, assuming the number of published papers is related to the number submitted, our findings suggest that JAMA's policy may have resulted in a significant reduction in the number of industry-sponsored trials it received and published.

Ioannidis estimated that most published research findings are false, but he did not indicate when, if at all, potentially false research results may be considered as acceptable to society. We combined our two previously published models to calculate the probability above which research findings may become acceptable. A new model indicates that the probability above which research results should be accepted depends on the expected payback from the research (the benefits) and the inadvertent consequences (the harms). This probability may dramatically change depending on our willingness to tolerate error in accepting false research findings. Our acceptance of research findings changes as a function of what we call "acceptable regret," i.e., our tolerance of making a wrong decision in accepting the research hypothesis. We illustrate our findings by providing a new framework for early stopping rules in clinical research (i.e., when should we accept early findings from a clinical trial indicating the benefits as true?). Obtaining absolute "truth" in research is impossible, and so society has to decide when less-than-perfect results may become acceptable.

Introduction: To evaluate how often men with metastatic prostate cancer (mPC) receive standard of care treatment with androgen deprivation therapy (ADT)., Methods: Men aged ≥20 years with newly diagnosed mPC (stage IV) between 2010 and 2018 were identified using California Cancer Registry data. Receipt of hormonal therapy as initial cancer treatment was examined by patient/tumor characteristics at time of diagnosis. Chi-square tests and logistic regression, adjusted for covariates, were performed to assess association between receipt of hormonal therapy and patient/tumor characteristics., Results: We identified 13,680 men with newly diagnosed mPC, of which 3637 had local metastasis (N1) only while 9596 had distant metastasis (M1) with or without N1 disease. 21.8 % (n = 2980) of men did not receive ADT. The highest rate of receiving ADT was among men between ages 75-84 (81.6%) and the lowest rate was in men over 85 (76.0%). Asian men had the largest proportion receiving ADT (n = 962, 81.5%) with remaining subgroups having similar proportion of men receiving ADT (76.8% to 77.2%). Once adjusted for covariates, regression results showed men with a higher Gleason score (8-10) were more likely to receive ADT (OR 2.04, 1.82-2.27, p = < 0.001) as well as men with distant sites of metastatic disease (OR 4.02, 3.62-4.46, p = < 0.001). Men residing in neighborhoods with the lowest socioeconomic status were least likely to receive ADT (OR 0.79, 0.68-0.93, p = 0.0032). No differences in receipt of ADT were observed by race/ethnicity., Discussion: Despite significant advancements in the treatment of mPC in recent years, over one-fifth of patients did not receive ADT, which is the backbone for all new systemic therapies. This dataset might help address some of the prostate cancer care disparities in California., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Linkage studies have successfully mapped loci underlying monogenic disorders, but mostly failed when applied to common diseases. Conversely, genome-wide association studies (GWASs) have identified replicable associations between thousands of SNPs and complex traits, yet capture less than half of the total heritability. In the present study we reconcile these two approaches by showing that linkage signals of height and body mass index (BMI) from 119,000 sibling pairs colocalize with GWAS-identified loci. Concordant with polygenicity, we observed the following: a genome-wide inflation of linkage test statistics; that GWAS results predict linkage signals; and that adjusting phenotypes for polygenic scores reduces linkage signals. Finally, we developed a method using recombination rate-stratified, identity-by-descent sharing between siblings to unbiasedly estimate heritability of height (0.76 ± 0.05) and BMI (0.55 ± 0.07). Our results imply that substantial heritability remains unaccounted for by GWAS-identified loci and this residual genetic variation is polygenic and enriched near these loci., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Several phase III trials have altered the management of oncogenic driven non-small cell lung cancer (NSCLC) including those harboring EGFR and ALK mutations. However, several of these pivotal trials deviated from standard-of-care practices for either baseline imaging or surveillance imaging. This occurred despite sponsor acknowledgement in a clinical trial protocol that historical trials utilized imaging modalities that potentially under-staged patients. Inadequate baseline imaging for adjuvant trials instead of PET/CT may not identify individuals with metastatic disease, and thereby subject such individuals with metastatic disease to inferior treatment if randomized to the control arm. Similarly, more frequent surveillance imaging than what is considered standard-of-care may identify disease progression earlier than what is expected in real-world clinical practice and therefore embellish the magnitude of benefit between a targeted therapy and the control arm. While targeted therapies have provided clinical benefit for individuals with oncogenic driven NSCLC, physicians and patients must be cognizant that clinical trial deviations from standard-of-care imaging practices may have embellished the magnitude of benefit for several of these therapies., Competing Interests: Declaration of Competing Interest D.J.B. has the following disclosures: Consulting or Advisory Role: AIMED BIO, Astellas, Eisai, Seagen. Speakers’ Bureau: Merck. Travel and Accommodations: Merck, Seagen. V.P. receives research funding from Arnold Ventures through a grant made to UCSF, and royalties for books and writing from Johns Hopkins Press, MedPage, and the Free Press. He declares consultancy roles with UnitedHealthcare and OptumRX; He hosts the podcasts, Plenary Session, VPZD, Sensible Medicine, writes the newsletters, Sensible Medicine, the Drug Development Letter and VP's Observations and Thoughts, and runs a YouTube channel, which collectively earn revenue on the platforms: Patreon, YouTube and Substack., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Importance: There is an increasing number of cancer 'survivors' and increasing research into supportive care. However, it is unknown how patterns of attention and citation differ between supportive and non-supportive cancer care research. We sought to estimate the engagement of high-impact studies of supportive compared to non-supportive cancer care papers., Methods: In a cross-sectional review of top oncology journals (2016-2023), we reviewed studies examining supportive care strategies and a frequency-matched random sampling of studies on non-supportive interventions. We compared data on social engagement metrics, as represented by Altmetric scores and citations and funding status, by supportive care or non-supportive care articles., Results: We found overall Altmetric scores were no different between articles that did not test supportive care and those that did, with a numerically higher score for supportive care articles (86.0 vs 102; p=0.416). Other bibliometric statistics (such as the number of blogs, number of X users, and the number of X posts) obtained from Altmetric did not differ significantly between the two groups. Non-supportive cancer care papers had a significantly higher number of citations than supportive cancer care papers (45.6 in supportive care vs 141 in non-supportive care papers; p<0.001). A greater proportion of non-supportive cancer care papers were also supported by pharmaceutical companies compared to supportive cancer care papers (54.2 % vs 15.3 %; p<0.001)., Conclusion: Though social media engagement is similar between supportive and non-supportive cancer care papers in high-impact journals, there is a significant difference in support from pharmaceutical companies and the number of citations., Competing Interests: Declaration of Competing Interest V.P. receives research funding from Arnold Ventures through a grant made to UCSF, and royalties for books and writing from Johns Hopkins Press, MedPage, and the Free Press. He declares consultancy roles with UnitedHealthcare and OptumRX; He hosts the podcasts, Plenary Session, VPZD, Sensible Medicine, writes the newsletters, Sensible Medicine, the Drug Development Letter and VP's Observations and Thoughts, and runs the YouTube channel Vinay Prasad MD MPH, which collectively earn revenue on the platforms: Patreon, YouTube and Substack. DB receives Consulting or Advisory Role: Astellas, Eisai, Seagen. Speakers' Bureau: Merck. Travel and Accommodations: Merck. AH and SR have no disclosures to report., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objectives: Patient preferences have the potential to influence the development of new treatments for locally advanced/metastatic urothelial carcinoma (la/mUC), and therefore we explored how patients with la/mUC value different attributes of first-line treatments., Methods: An online preference survey and multidimensional thresholding (MDT) exercise were developed following a targeted literature review and qualitative interviews with physicians, patients with la/mUC, and their caregivers. Treatment attributes included two benefits (overall response rate [ORR], pain related to bladder cancer [scored 0-100; 100 being the worst pain possible]) and four treatment-related risks (peripheral neuropathy, severe side effects, mild to moderate nausea, mild to moderate skin reactions). A Dirichlet regression was used to estimate average preference weights. Marginal utility and the reduction in ORR that patients would accept in exchange for a 10-point decrease or a 10% decrease in other attributes were calculated., Results: A total of 100 patients were recruited and self-completed the survey and MDT. Mean patient age was 64.9 years (standard deviation, 7.6), 54% were female, and 38% identified as white. All included treatment attributes had a statistically significant impact on preferences. Changes in ORR had the largest impact, followed by cancer-related pain and treatment-related risks. Patients were willing to accept an 8.4% decrease in ORR to reduce their pain level by 10 points or a 7.8% decrease in ORR to reduce the risk of peripheral neuropathy by 10%. For a 10% decrease in severe side effects, mild to moderate nausea, or skin reaction, patients would accept decreases in ORR of 5.5%, 3.7%, or 3.4%, respectively., Conclusions: Of the attributes tested, changes in ORR were most important to patients. Patients made tradeoffs between treatment attributes indicating that a lower ORR may be acceptable for an improvement in other attributes such as reduced cancer-related pain or the risk of treatment-related adverse events., (© 2024. The Author(s).)