Medical Decision Making最新文献

{"title":"Understanding Delayed Diabetes Diagnosis: An Agent-Based Model of Health-Seeking Behavior.","authors":"Firouzeh Rosa Taghikhah, Araz Jabbari, Kevin C Desouza, Arunima Malik, Hadi A Khorshidi","doi":"10.1177/0272989X251326908","DOIUrl":"10.1177/0272989X251326908","url":null,"abstract":"<p><p>BackgroundDiabetes is a rapidly growing global health issue, with the hidden burden of undiagnosed cases leading to severe complications and escalating health care costs.MethodsThis study investigated the potential of integrated behavioral frameworks to predict health-seeking behaviors and improve diabetes diagnosis timelines through the development of an agent-based model. Focusing on Narromine and Gilgandra in New South Wales, Australia, the model captured the integrative influence of 3 social theories-theory of planned behavior (TPB), health belief model (HBM), and goal framing theory (GFT)-on health care decisions across behavioral and nonbehavioral variables, providing a robust analysis of temporal diagnostic patterns, health care utilization, and costs.ResultsOur comparative experiments indicated that this multitheory framework improved predictive accuracy by 15% to 30% compared with single-theory models, effectively capturing the interplay of planned, belief-driven, and context-based health behaviors. Spatial-temporal analysis highlighted key regional and demographic variations in diagnosis behaviors. While early, planned medical visits were prevalent in regions with better access (Gilgandra), areas with limited infrastructure saw a reliance on hospital-based diagnoses (Narromine). Health care cost analysis demonstrated a nonlinear expenditure pattern, suggesting that these theories defy conventional linear cost trends. Scenario analysis demonstrated the impact of targeted interventions. Gender-specific awareness initiatives in Gilgandra reduced late-diagnosis rates among men by approximately 15%, while enhanced access to care in Narromine decreased hospital-based late diagnoses from a baseline of 80% to around 60%.ConclusionsThis study contributes an empirically grounded, policy-oriented decision support tool to inform targeted interventions, offering novel insights to improve diabetes management.HighlightsWe explored the delay in diabetes diagnosis, particularly within remote Australian communities, through looking into the health care-seeking behavior of individuals displaying diabetes symptoms.We developed an innovative agent-based model to craft a dynamic decision support tool for policy makers by providing unique insights into the health behaviors of diabetes patients.Our study contributes significantly to the understanding of public health management with particular concerns around diabetes, as well as equips the New South Wales Ministry of Health with impactful insights into the consequences of their decisions.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":" ","pages":"399-425"},"PeriodicalIF":3.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11992636/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143781313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Face Validity and Clinical Relevance of a Mathematical Population Cancer Epidemiology Model Using a Novel Advisory Group Approach.","authors":"Louise Davies, Sara Fernandes-Taylor, Natalia Arroyo, Yichi Zhang, Oguzhan Alagoz, David O Francis","doi":"10.1177/0272989X251327595","DOIUrl":"10.1177/0272989X251327595","url":null,"abstract":"&lt;p&gt;&lt;p&gt;BackgroundCancer simulation models can answer research and policy questions when prospective evidence is incomplete or not feasible. However, such models require incorporating unmeasureable inputs for which there is often not strong evidence, and model utility is limited if assumptions lack face validity or if the model is not clinically relevant. We systematically incorporated formal advisory input to mitigate these challenges as we developed a microsimulation model of papillary thyroid cancer (PApillary Thyroid CArcinoma Microsimulation model [PATCAM]).MethodsWe used a participatory action research approach incorporating focus group techniques and using principles of bidirectional learning.ResultsWe assembled a formal standing advisory group with representation by perspective (medical, patient, and payor), geography, and local practice culture to understand current and historical clinical beliefs and practices about thyroid cancer diagnosis and treatment. The group provided input on critical modeling assumptions and decisions: 1) the role of nodule size in biopsy decisions, 2) trends in provider biopsy behavior, 3) specialty propensity to biopsy, 4) population prevalence of thyroid cancer over time, 5) proportion of malignant tumors showing regression, and 6) cancer epidemiology and diagnostic practices by sex and age. Advisory group questions and concerns about model development will inform future research questions and strategies to communicate and disseminate model results.ConclusionsWe successfully used our advisory group to provide critical inputs on unmeasurable assumptions, increasing the face validity of our model. The use of a standing advisory group improved model transparency and contributed to future research plans and dissemination of model results so they can have maximum impact when guiding clinical decisions and policy.HighlightsUnfamiliarity with simulation modeling poses a threat to its acceptability and adoption. The effectiveness of these models is contingent on end-users' willingness to accept and adopt model results. The effectiveness of the models is further limited if they lack face validity to potential users or do not have clinical relevance.Several approaches to overcoming validity challenges have been advanced, such as collaborative modeling, which involves developing multiple models independently using common data sources. However, when only a single model exists, another approach is needed. We used an Advisory Group and \"participatory modeling,\" which has been used in other settings but has not been previously reported in cancer modeling. We describe the methods used for and results of incorporating a formal advisory group into the development of a cancer microsimulation model.The use of a formal, standing advisory group (as opposed to one-off focus groups or interviews) strengthened our model by rigorously vetting modeling assumptions and model inputs with subject matter experts. The formal, ongoing structur","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":" ","pages":"385-398"},"PeriodicalIF":3.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Methodological Approaches for Incorporating Marginalized Populations into HPV Vaccine Modeling: A Systematic Review.","authors":"Jennifer C Spencer, Juan Yanguela, Lisa P Spees, Olufeyisayo O Odebunmi, Anna A Ilyasova, Caitlin B Biddell, Kristen Hassmiller Lich, Sarah D Mills, Colleen R Higgins, Sachiko Ozawa, Stephanie B Wheeler","doi":"10.1177/0272989X251325509","DOIUrl":"10.1177/0272989X251325509","url":null,"abstract":"<p><p><b>Background.</b> Delineation of historically marginalized populations in decision models can identify strategies to improve equity but requires assumptions in both model structure and stratification of input data. <b>Purpose.</b> We sought to characterize alternative methodological approaches for incorporating marginalized populations into human papillomavirus (HPV) vaccine decision-support models. <b>Data Sources.</b> We conducted a systematic search of PubMed, CINAHL, Scopus, and Embase from January 2006 through June 2022. <b>Study Selection.</b> We identified simulation models of HPV vaccination that refine any model input to specifically reflect a marginalized population. <b>Data Extraction.</b> We extracted data on key methodological decisions across modeling approaches to incorporate marginalized populations, including stratification of inputs, model structure, attribution of prevaccine disparities, calibration, validation, and sensitivity analyses. <b>Data Synthesis.</b> We identified 30 models that stratified inputs by sexual behavior (i.e., men who have sex with men), HIV infection status, race, ethnicity, income, rurality, or combinations of these. We identified 5 common approaches used to incorporate marginalized groups. These included models based primarily on differences in sexual behavior (k = 6), HPV cancer incidence (k = 10), cancer screening and care access (k = 4), and HPV natural history (through either direct incorporation of data [k = 10] or calibration [k = 5]). Few models evaluated sensitivity around their conceptualization of the marginalized group, and only 5 models validated outcomes for the marginalized group. <b>Limitations.</b> Evaluated studies reflected a variety of settings and research questions, making it difficult to evaluate the implications of differences across modeling approaches. <b>Conclusions.</b> Modelers should be explicit about the assumptions and theory driving their model structure and input parameters specific to key marginalized populations, such as the causes of prevaccination differences in outcomes. More emphasis is needed on model validation and rigorous sensitivity analysis.HighlightsWe identified 30 unique HPV vaccination models that incorporated marginalized populations, including populations living with HIV, low-income or rural populations, and individuals of a marginalized race, ethnicity, or sexual behavior.Methods for incorporating these populations, as well as the assumptions inherent in the modeling structure and parameter selections, varied substantially, with models explicitly or implicitly attributing prevaccine differences to alternative combinations of biological, behavioral, and societal mechanisms.Modelers seeking to incorporate marginalized populations should be transparent about assumptions underlying model structure and data and examine these assumptions in sensitivity analysis when possible.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":" ","pages":"358-369"},"PeriodicalIF":3.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11992634/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143634897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Motivated Interpretations of Survival Rates in Icon Arrays: An Issue of Frequency Format?","authors":"Jeremy D Strueder, Inkyung Park, Siobhan M McDonnell, Mir A Basir, Paul D Windschitl","doi":"10.1177/0272989X251332315","DOIUrl":"https://doi.org/10.1177/0272989X251332315","url":null,"abstract":"<p><p>BackgroundIcon arrays, which visually depict frequencies, are commonly recommended for communicating risk information such as survival rates. However, they have been found to be ineffective at buffering against motivated reasoning that can lead to undue optimism. To determine whether the impersonal frequency format of icon arrays (reporting a number affected out of a reference class) makes them vulnerable to motivated reasoning, a novel intervention is tested as a means for reducing undue optimism.MethodsFemale US participants from Amazon's MTurk (<i>N</i> = 399) imagined a scenario in which their infant would be born extremely preterm. They were presented with icon array information about the survival chances (15-in-100 or 45-in-100) of prematurely born infants with intensive care. For the key intervention, some participants were asked a reflection question immediately after seeing the icon array, which prompted them to indicate what the information meant for their own infant's percent-chance of survival (i.e., they converted a frequency about a reference class to a probability value about the personal outcome of interest). For other participants, the reflection question merely asked about frequency. The main dependent measure came next and assessed gut-level optimism.ResultsPeople's gut-level beliefs about their infant's chances of survival were optimistically biased; the intervention did not reduce this. These gut-level beliefs, rather than the objective survival rate information conveyed through icon arrays, were predictive of subsequent treatment choices.ConclusionsThe results suggest that the inability of icon arrays to buffer against motivated reasoning is not due to their frequency format. Moreover, the findings highlight the usefulness of measuring gut-level interpretations of likelihood, which can reveal significant insights into the psychological mechanisms driving patient-treatment choices.HighlightsIcon arrays, which visually depict frequencies, are commonly recommended as best-practice for communicating risk information in health contexts.However, recent work has found that they are ineffective at reducing the extent to which people engage in motivated reasoning when processing likelihood information.We find that the frequency format of icon arrays-depicting a rate for outcomes in a group of people rather than a case-specific probability-is not a primary reason why they are ineffective at reducing optimism biasWe also find that measures of gut-level beliefs of likelihood are particularly well suited for detecting optimism bias, yet also predict subsequent treatment decisions.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":" ","pages":"272989X251332315"},"PeriodicalIF":3.1,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144025059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cancer Patients' Experiences of Burden when Involved in Treatment Decision Making.","authors":"Fiorella L Huijgens, Marij A Hillen, Mette J Huisinga, André N Vis, Corinne N Tillier, Hester S A Oldenburg, Gwen M P Diepenhorst, Inge Henselmans","doi":"10.1177/0272989X251334979","DOIUrl":"https://doi.org/10.1177/0272989X251334979","url":null,"abstract":"<p><p>PurposePatients are increasingly involved in decision making by their clinicians. Yet, there are concerns that involvement in decision making may cause emotional distress in patients. Little research has examined the nature of the burden experienced by patients confronted with a life-changing treatment decision. Therefore, we explored the nature and manifestations of burden experienced by patients with early-stage breast and prostate cancer regarding their involvement in decision making. We further aimed to identify patient-perceived causes and potential solutions for their experienced burden.MethodsWe used semi-structured interviews to explore the perspectives of patients with early-stage breast and prostate cancer. Patients (<i>N</i> = 24) were eligible if they were diagnosed in the past 6 mo and reported some degree of burden regarding their involvement in decision making. Two researchers independently inductively coded the interviews using thematic analysis.ResultsPatients described being burdened by the decision in various ways and at various moments in the decision-making process. Patients attributed their decision-related burden mainly to uncertainty, fear of making the wrong decision, insufficient guidance by their clinician, and feeling an overwhelming sense of responsibility for their treatment decision. Patients indicated various factors that mitigated their burden or facilitated decision making, including having sufficient time, the opportunity to discuss the choice with experts and/or family, and receiving advice or confirmation from family or the clinician.ConclusionThese findings suggest that decision-related burden could be caused by the uncertainty and anxiety patients experience and by a nonpreferred division of roles within the decision-making process.ImplicationsAccordingly, acknowledging patients' feelings by discussing the presence of uncertainty and distress might normalize the burden for patients. Moreover, clinicians could explore and adjust to patients' role preference in decision making and discuss what would facilitate the decision process for patients.HighlightsPatients experience emotional, cognitive, and physical burden from their involvement in decision making.Some of the burden appears to result from the way clinicians involve patients in decision making.In addition to information about options, benefits, and harms, patients require active support in their decision-making process.Clinicians could aim to avoid overfocus on patient autonomy and instead establish authentic, shared decisions, with a role for some clinician control if needed.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":" ","pages":"272989X251334979"},"PeriodicalIF":3.1,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144022508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stress-testing US colorectal cancer screening guidelines: Decennial colonoscopy from age 45 is robust to natural history uncertainty and colonoscopy sensitivity assumptions.","authors":"Pedro Nascimento de Lima, Christopher Maerzluft, Jonathan Ozik, Nicholson Collier, Carolyn M Rutter","doi":"10.1177/0272989X251334373","DOIUrl":"https://doi.org/10.1177/0272989X251334373","url":null,"abstract":"<p><p>PurposeThe 2023 American College of Physicians (ACP) guidelines for colorectal cancer (CRC) screening are at odds with the United States Preventive Task Force (USPSTF) guidelines, with the former recommending screening starting at age 50 y and the latter at age 45 y. This article \"stress tests\" CRC colonoscopy screening strategies to investigate their robustness to uncertainties stemming from the natural history of disease and sensitivity of colonoscopy.MethodsThis study uses the CRC-SPIN microsimulation model to project the life-years gained (LYG) under several colonoscopy CRC screening strategies. The model was extended to include birth cohort effects on adenoma risk. We estimated natural history parameters under 2 different assumptions about the youngest age of adenoma initiation. For each, we generated 500 parameter sets to reflect uncertainty in the natural history parameters. We simulated 26 colonoscopy screening strategies and examined 4 different colonoscopy sensitivity assumptions, encompassing the range of sensitivities consistent with prior tandem colonoscopy studies. Across this set of scenarios, we identify efficient screening strategies and report posterior credible intervals for benefits of screening (LYG), burden (number of colonoscopies), and incremental burden-effectiveness ratios.ResultsProjected absolute screening benefits varied widely based on assumptions, but strategies starting at age 45 y were consistently in the efficiency frontier. Strategies in which screening starts at age 50 y with 10-y intervals were never efficient, saving fewer life-years than starting screening at age 45 y and performing colonoscopies every 15 y while requiring more colonoscopies per person.ConclusionsDecennial colonoscopy screening initiation at age 45 y remained a robust recommendation. Colonoscopy screening with a 10-y interval starting at age 50 y did not result in an efficient use of colonoscopies in any of the scenarios evaluated.HighlightsColorectal cancer colonoscopy screening strategies initiated at age 45 y were projected to yield more life-years gained while requiring the least number of colonoscopies across different model assumptions about disease natural history and colonoscopy sensitivity.Colonoscopy screening starting at age 50 y with a 10-y interval consistently underperformed strategies that started at age 45 y.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":" ","pages":"272989X251334373"},"PeriodicalIF":3.1,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144025061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Linking Patient Perceptions of Shared Decision Making to Satisfaction in Lung Cancer Screening Decisions.","authors":"Stephanie A Robinson, Anna M Barker, Gemmae M Fix, Marla L Clayman, Abigail N Herbst, Julie C White, Renda Soylemez Wiener","doi":"10.1177/0272989X251333451","DOIUrl":"https://doi.org/10.1177/0272989X251333451","url":null,"abstract":"<p><p>IntroductionLung cancer is especially prevalent among US veterans, and lung cancer mortality can be reduced through lung cancer screening (LCS). LCS guidelines recommend shared decision making (SDM) to help patients weigh the benefits and harms of LCS and make informed, values-based decisions about screening. Yet some question whether SDM affects patient outcomes. This study evaluated US veterans' perceptions of LCS SDM quality and its relationship with satisfaction in LCS decisions.MethodsWe administered surveys via mail and phone to veterans in the VA New England Healthcare Network after recent LCS conversations. SDM quality was measured using CollaboRATE, with top scores indicating high quality. Decision satisfaction was assessed using the Satisfaction with Decision scale. Generalized linear models analyzed associations between perceived SDM quality and decision satisfaction, adjusting for demographics, health, and overall care satisfaction.ResultsAmong 1,033 patients who received surveys, 320 responded (31.0%), with 220 recalling the LCS conversation. Among those who answered the CollaboRATE questions, 34.0% (73/215) perceived SDM to be high quality (\"top scorers\"). Perceived high-quality SDM was significantly associated with greater decision satisfaction compared with lower perceived SDM quality (adjusted mean satisfaction on a 30-point scale = 26.75 v. 24.23; <i>P</i> < 0.001). A greater proportion of patients who received, versus did not receive, patient education materials rated SDM as high quality (44.4% v. 27.7%, <i>P</i> = 0.018).LimitationsThe sample was primarily White, male, and all US veterans, limiting generalizability to other LCS-eligible cohorts. The cross-sectional design prevents causal inferences and long-term follow-up.ConclusionsHigher perceived SDM quality was associated with greater patient satisfaction with the LCS decision. Improving SDM processes can enhance patient engagement and may improve LCS adherence and health outcomes.HighlightsHigher perceived shared decision making (SDM) quality in lung cancer screening (LCS) discussions leads to greater patient satisfaction with screening decisions.While the use of patient education materials was linked to higher perceived SDM quality, less than half of patients who received materials rated SDM as high quality. There remains room for improved design and delivery to ensure materials effectively support the SDM process and guidance to providers on how to effectively incorporate patient educational materials to support, rather than replace, high-quality SDM conversations.Enhancing SDM processes and aligning them with patient preferences can support patient satisfaction with their decision, which may have downstream benefits to patient engagement, adherence, and improved outcomes.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":" ","pages":"272989X251333451"},"PeriodicalIF":3.1,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144041791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The \"Stock of Time\" Method: A New Approach to Calculate Indirect Costs and Benefits in Economic Evaluations.","authors":"Lucy Kok, Carl Koopmans","doi":"10.1177/0272989X251333787","DOIUrl":"https://doi.org/10.1177/0272989X251333787","url":null,"abstract":"<p><p>BackgroundHealth interventions affect people's welfare directly by impacting people's health but also indirectly via a change in consumption and leisure time caused by the change in health. This study discusses 2 ongoing issues in the economic evaluation of health interventions. The first is how to value a change in the amount of leisure time of a patient. The second issue concerns the valuation of a change in production.MethodsWe present a theoretical model that assumes that individual utility depends on health, consumption, and leisure time. We assume that the total stock of time consists of 3 components: leisure time, working time, and recovery time. The model takes a societal perspective and assumes that individuals optimize their utility, conditional on time and budget restrictions.ResultsFor the first issue, the model indicates that the value of a change in the stock of time available for leisure and work has to be added to the direct effects of a health intervention, instead of only a change in work hours. For the second issue, the model indicates that in case of a change in longevity, only the change in taxes paid may be counted because the income change is included in the value of the change in quality-adjusted life-years. A numerical example shows that this approach may counterbalance the potential overestimation of the welfare effects of treatments with the human capital method and underestimation related to the friction cost method.ConclusionWe propose a new method that includes the welfare effects of health interventions due to a change in the amount of leisure time and avoids double counting of welfare changes, which are included in the direct effects.HighlightsWe present a theoretical model and use it to analyze 2 issues in the economic evaluation of health interventions: the inclusion of leisure time and the valuation of production.The model indicates that the effects of health changes on the amount of both work and leisure hours need to be taken into account in economic evaluation.As to the valuation of production, the model indicates that in case of a change in longevity, only the change in taxes may be counted.We propose the \"stock of time\" method to value changes in working hours and leisure hours, which may counterbalance potential overestimates and underestimates in established methods.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":" ","pages":"272989X251333787"},"PeriodicalIF":3.1,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144036584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Co-designing a Structured Expert Elicitation with Clinicians to Enhance Health Care Decision Making in Exercise Oncology.","authors":"Yufan Wang, Alexandra L McCarthy, Haitham Tuffaha","doi":"10.1177/0272989X251332967","DOIUrl":"https://doi.org/10.1177/0272989X251332967","url":null,"abstract":"<p><p>BackgroundWhile structured expert elicitation (SEE) is gaining traction in health technology assessment in situations in which data are scarce, its application in practice remains limited. Co-designing a practical and fit-for-purpose SEE with experts could enhance its acceptability and feasibility in clinical research.ObjectivesAn SEE was co-designed with clinicians to elicit expert opinions on 3 uncertain quantities of interest (QoIs) for a decision-analytic model in exercise oncology.MethodsA series of co-design meetings was convened to design 6 elicitation stages. Individual elicitation was conducted using the variable interval method (VIM), via videoconferencing. Linear pooling was adopted to generate group estimates. Semi-structured interviews were conducted after the elicitation exercise to gather the experts' first-hand experience of the elicitation process and to identify areas for improvement. Qualitative data were transcribed and content analyzed.ResultsTwelve experts participated in the co-designed SEE. Three beta distributions were derived and estimated from the experts' responses: the relative risk reduction of cardiovascular events of exercise for women who survived early-stage endometrial cancer (Mean: 0.362, SD: 0.15), the probability that a clinician would refer a patient to the exercise program (Mean: 0.457, SD: 0.218), and the probability that a cancer patient would use such a health service upon referral (Mean: 0.446, SD: 0.203). Most of the experts' first-hand experience of the co-designed SEE was positive. The qualitative feedback highlighted critical aspects of the elicitation process that should be designed and executed with caution when targeting clinicians with no prior experience of SEE.ConclusionsThis is the first expert elicitation conducted in exercise oncology. Engaging diverse stakeholders through co-design meetings and incorporating qualitative feedback proved effective and practical in introducing expert elicitation into clinical research.HighlightsRecent SEE guidelines aim to facilitate the conduct of expert elicitation in model-based economic evaluation, but its application in practice remains limited.Engaging experts in the design of SEE could enhance its acceptability and feasibility in clinical research.This is the first co-designed expert elicitation involving clinicians in the field of exercise oncology.This practical approach to conducting SEE could promote a wider adoption to inform health care policy decisions when the evidence is lacking or uncertain.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":" ","pages":"272989X251332967"},"PeriodicalIF":3.1,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144019947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing the Harms and Benefits of Cervical Screening in a Partially Vaccinated Population in Ontario, Canada: A Modeling Study.","authors":"Daniël D de Bondt, Erik E L Jansen, Christine Stogios, Bronwen R McCurdy, Rachel Kupets, Joan Murphy, Dustin Costescu, Linda Rabeneck, Rebecca Truscott, Jan A C Hontelez, Inge M C M de Kok","doi":"10.1177/0272989X251332597","DOIUrl":"https://doi.org/10.1177/0272989X251332597","url":null,"abstract":"<p><p>ObjectivesIn Ontario, Canada, the first cohorts who were offered school-based human papillomavirus (HPV) vaccination are now eligible for cervical screening. We determined which screening strategies for these populations would result in optimal harms-benefits ratios of screening.MethodsWe used the hybrid microsimulation model STDSIM- MISCAN-Cervix to determine the harms and cancers prevented of 309 different primary HPV screening strategies, varying by screening ages and triage methods. In addition, we performed an unstratified (i.e., uniform screening protocols) and stratified (i.e., screening protocols by vaccination status) analysis. Harms induced were quantified as a weighted combination of the number of primary HPV-based screens and colposcopy referrals at 1:10. A harms-benefit acceptability threshold of number of harms induced for each cancer prevented was set at the estimated ratio under current screening recommendations in unvaccinated cohorts in Ontario.ResultsFor the unstratified scenario, 5 lifetime screens with HPV16/18 genotyping was optimal. For the stratified scenario, the optimal scenario was 3 lifetime screens with HPV16/18/31/33/45/52/58 genotyping for vaccinated individuals versus 6 lifetime screens with HPV16/18 genotyping for unvaccinated individuals.ConclusionsWe determined the optimal cervical screening strategy in Ontario over the next decades. To maintain an optimal harms-benefits balance of screening, the Ontario Cervical Screening Program could adjust screening recommendations in the future to reduce the number of lifetime screens and extend screening intervals to account for vaccinated cohorts. Stratified screening by vaccination status could further improve this balance on an individual level.HighlightsPeople in cohorts who were offered HPV vaccination as part of Ontario's school-based program may achieve a better harms-benefits balance if cervical screening recommendations are updated to a less intensive protocol in future. This holds for the cohorts as a whole (i.e., unstratified screening) as well as for both vaccinated and unvaccinated individuals in these cohorts.Instead of using a cost-effectiveness threshold, it is possible to determine optimal screening protocols by calculating an acceptability threshold using alternative harms-benefits measures based on existing policy.Using univariate harms measures such as primary HPV screening tests or colposcopies per 1,000 people can yield biases in optimizing cervical screening programs. Alternatively, combining both primary screens and colposcopy referrals could provide a more accurate harms measure and result in optimal strategies with a better balance between harms and benefits.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":" ","pages":"272989X251332597"},"PeriodicalIF":3.1,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144056317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}