Medical Decision Making最新文献

{"title":"Nurses' Anxiety Mediates the Relationship between Clinical Tolerance to Uncertainty and Antibiotic Initiation Decisions in Residential Aged-Care Facilities.","authors":"Saniya Singh, Chris Degeling, Peta Drury, Amy Montgomery, Peter Caputi, Frank P Deane","doi":"10.1177/0272989X241239871","DOIUrl":"10.1177/0272989X241239871","url":null,"abstract":"<p><strong>Highlights: </strong>The impact of non-clinical factors (e.g., resident and family preferences) on prescribing is well-established. There is a gap in the literature regarding the mechanisms through which these preferences are experienced as pressure by prescribers within the unique context of residential aged-care facilities (RACFs).A significant relationship was found between nurses' anxiety, clinical tolerance of uncertainty, and the perceived need for antibiotics and assessment.As such, there is a need to expand stewardship beyond education alone to include interventions that help nurses manage uncertainty and anxiety and include other stakeholders (e.g., family members) when making clinical decisions in the RACF setting.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11102643/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140295126","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":"Using Age-Specific Rates for Parametric Survival Function Estimation in Simulation Models.","authors":"Arantzazu Arrospide, Oliver Ibarrondo, Rubén Blasco-Aguado, Igor Larrañaga, Fernando Alarid-Escudero, Javier Mar","doi":"10.1177/0272989X241232967","DOIUrl":"10.1177/0272989X241232967","url":null,"abstract":"<p><strong>Purpose: </strong>To describe a procedure for incorporating parametric functions into individual-level simulation models to sample time to event when age-specific rates are available but not the individual data.</p><p><strong>Methods: </strong>Using age-specific event rates, regression analysis was used to parametrize parametric survival distributions (Weibull, Gompertz, log-normal, and log-logistic), select the best fit using the <i>R</i>² statistic, and apply the corresponding formula to assign random times to events in simulation models. We used stroke rates in the Spanish population to illustrate our procedure.</p><p><strong>Results: </strong>The 3 selected survival functions (Gompertz, Weibull, and log-normal) had a good fit to the data up to 85 y of age. We selected Gompertz distribution as the best-fitting distribution due to its goodness of fit.</p><p><strong>Conclusions: </strong>Our work provides a simple procedure for incorporating parametric risk functions into simulation models without individual-level data.</p><p><strong>Highlights: </strong>We describe the procedure for sampling times to event for individual-level simulation models as a function of age from parametric survival functions when age-specific rates are available but not the individual dataWe used linear regression to estimate age-specific hazard functions, obtaining estimates of parameter uncertainty.Our approach allows incorporating parameter (second-order) uncertainty in individual-level simulation models needed for probabilistic sensitivity analysis in the absence of individual-level survival data.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139974239","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":"Communicating the Imperfect Diagnostic Accuracy of COVID-19 Rapid Antigen Self-Tests: An Online Randomized Experiment","authors":"Huijun Li, Megha Kalra, Lin Zhu, Deonna M. Ackermann, Melody Taba, Carissa Bonner, Katy J.L. Bell","doi":"10.1177/0272989x241242131","DOIUrl":"https://doi.org/10.1177/0272989x241242131","url":null,"abstract":"ObjectiveTo investigate the potential impacts of optimizing coronavirus disease 2019 (COVID-19) rapid antigen test (RAT) self-testing diagnostic accuracy information.DesignOnline randomized experiment using hypothetical scenarios: in scenarios 1 to 3 (RAT result positive), the posttest probability was considered to be very high (likely true positives), and in scenarios 4 and 5 (RAT result negative), the posttest probability was considered to be moderately high (likely false negatives).SettingDecember 12 to 22, 2022, during the mixed-variant Omicron wave in Australia.ParticipantsAustralian adults. Intervention: diagnostic accuracy of a COVID-19 self-RAT presented in a health literacy-sensitive way; usual care: diagnostic accuracy information provided by the manufacturer; control: no diagnostic accuracy information.Main Outcome MeasureIntention to self-isolate.ResultsA total of 226 participants were randomized (control n = 75, usual care n = 76, intervention n = 75). More participants in the intervention group correctly interpreted the meaning of the diagnostic accuracy information ( P = 0.08 for understanding sensitivity, P &lt; 0.001 for understanding specificity). The proportion who would self-isolate was similar across scenarios 1 to 3 (likely true positives). The proportion was higher in the intervention group than in the control for scenarios 4 and 5 (likely false negatives). These differences were not statistically significant. The largest potential effect was seen in scenario 5 (dinner party with confirmed cases, the person has symptoms, negative self-RAT result), with 63% of the intervention group and 49% of the control group indicating they would self-isolate (absolute difference 13.3%, 95% confidence interval: −2% to 30%, P = 0.10).ConclusionHealth literacy sensitive formatting supported participant understanding and recall of diagnostic accuracy information. This may increase community intentions to self-isolate when there is a likely false-negative self-RAT result. Trial registration: Australia New Zealand Clinical Trial Registry (ACTRN12622001517763)HighlightsCommunity-based diagnostic accuracy studies of COVID-19 self-RATs indicate substantially lower sensitivity (and higher risk of false-negative results) than the manufacturer-supplied information on most government public Web sites. This online randomized study found that a health literacy–sensitive presentation of the imperfect diagnostic accuracy COVID-19 self-RATs supported participant understanding and recall of diagnostic accuracy information. Health literacy–sensitive presentation may increase community intentions to self-isolate after a negative test result where the posttest probability is still moderately high (i.e., likely false-negative result). To prevent the onward spread of infection, efforts to improve communication about the high risk of false-negative results from COVID-19 self-RATs are urgently needed.","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140800984","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":"Collective Intelligence Increases Diagnostic Accuracy in a General Practice Setting","authors":"Matthew D. Blanchard, Stefan M. Herzog, Juliane E. Kämmer, Nikolas Zöller, Olga Kostopoulou, Ralf H. J. M. Kurvers","doi":"10.1177/0272989x241241001","DOIUrl":"https://doi.org/10.1177/0272989x241241001","url":null,"abstract":"BackgroundGeneral practitioners (GPs) work in an ill-defined environment where diagnostic errors are prevalent. Previous research indicates that aggregating independent diagnoses can improve diagnostic accuracy in a range of settings. We examined whether aggregating independent diagnoses can also improve diagnostic accuracy for GP decision making. In addition, we investigated the potential benefit of such an approach in combination with a decision support system (DSS).MethodsWe simulated virtual groups using data sets from 2 previously published studies. In study 1, 260 GPs independently diagnosed 9 patient cases in a vignette-based study. In study 2, 30 GPs independently diagnosed 12 patient actors in a patient-facing study. In both data sets, GPs provided diagnoses in a control condition and/or DSS condition(s). Each GP’s diagnosis, confidence rating, and years of experience were entered into a computer simulation. Virtual groups of varying sizes (range: 3–9) were created, and different collective intelligence rules (plurality, confidence, and seniority) were applied to determine each group’s final diagnosis. Diagnostic accuracy was used as the performance measure.ResultsAggregating independent diagnoses by weighing them equally (i.e., the plurality rule) substantially outperformed average individual accuracy, and this effect increased with increasing group size. Selecting diagnoses based on confidence only led to marginal improvements, while selecting based on seniority reduced accuracy. Combining the plurality rule with a DSS further boosted performance.DiscussionCombining independent diagnoses may substantially improve a GP’s diagnostic accuracy and subsequent patient outcomes. This approach did, however, not improve accuracy in all patient cases. Therefore, future work should focus on uncovering the conditions under which collective intelligence is most beneficial in general practice.HighlightsWe examined whether aggregating independent diagnoses of GPs can improve diagnostic accuracy. Using data sets of 2 previously published studies, we composed virtual groups of GPs and combined their independent diagnoses using 3 collective intelligence rules (plurality, confidence, and seniority). Aggregating independent diagnoses by weighing them equally substantially outperformed average individual GP accuracy, and this effect increased with increasing group size. Combining independent diagnoses may substantially improve GP’s diagnostic accuracy and subsequent patient outcomes.","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140594450","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":"Exploring Cultural and Religious Effects on HPV Vaccination Decision Making Using a Web-Based Decision Aid: A Quasi-experimental Study","authors":"Yulia Gendler, Ayala Blau","doi":"10.1177/0272989x241240466","DOIUrl":"https://doi.org/10.1177/0272989x241240466","url":null,"abstract":"BackgroundHuman papillomavirus (HPV) poses a significant public health concern, as it is linked to various serious health conditions such as cancer and genital warts. Despite the vaccine’s safety, efficacy, and availability through national school programs, HPV vaccination rates remain low in Israel, particularly within the ultra-Orthodox community due to religious and cultural barriers. Decision aids have shown promise in facilitating shared decision making and promoting informed choices in health care. This study aimed to assess the impact of a novel Web-based decision aid on HPV vaccination intentions, knowledge, decision self-efficacy, and decisional conflict among Israeli parents and young adults, with a specific focus on exploring differences between religious groups.MethodsTwo Web-based decision aids were developed for parents of children aged 10 to 17 y ( n = 120) and young adults aged 18 to 26 y ( n = 160). A quasi-experimental study was conducted among Hebrew-speaking parents and young adults eligible for HPV vaccination. Participants completed pre- and postintervention questionnaires assessing vaccination intentions, knowledge about HPV, decision self-efficacy, and decisional conflict.ResultsThe decision aid significantly improved intentions toward HPV vaccination among most religious groups, except the Jewish ultra-Orthodox community. Ultra-Orthodox participants exhibited reluctance to vaccinate themselves or their children (odds ratio [OR] = 0.23, P &lt; 0.001 for parents’ group; OR = 0.43, P &lt; 0.001 for young adults’ group). Parental preference for vaccinating girls over boys (OR = 2.66, P &lt; 0.001) and increased inclination for vaccination among Muslim-Arabs were observed (OR = 3.12, P &lt; 0.001). Knowledge levels improved among ultra-Orthodox participants but not decisional conflict and self-efficacy.ConclusionsThe Web-based decision aid positively influenced the quality of HPV vaccination decision making among various religious groups in Israel, except for the ultra-Orthodox community. Culturally tailored approaches that address specific community concerns are essential for informed decision making.HighlightsHuman papillomavirus (HPV) vaccination rates in Israel are substantially lower than those of other routine vaccinations, particularly among religious and ultra-Orthodox communities, largely due to sociocultural beliefs and misinformation. A newly developed Web-based decision aid was implemented in a study involving parents and young adults to evaluate its impact on vaccination intent, knowledge about HPV, decision self-efficacy, and decisional conflict. While the decision aid significantly enhanced vaccination intention, knowledge, and perceived behavioral control among various religious groups, it did not yield the same outcomes within the ultra-Orthodox Jewish community. This study highlights the vital role of cultural adaptation in HPV vaccine decision aids within Israel, revealing significant disparities in vaccinat","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140594079","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":"Exploring Structural Uncertainty in Cost-Effectiveness Modeling of Gestational Diabetes Screening: An Application Example from Norway","authors":"Pia S. Henkel, Emily A. Burger, Line Sletner, Kine Pedersen","doi":"10.1177/0272989x241241339","DOIUrl":"https://doi.org/10.1177/0272989x241241339","url":null,"abstract":"BackgroundScreening pregnant women for gestational diabetes mellitus (GDM) has recently been expanded in Norway, although screening eligibility criteria continue to be debated. We aimed to compare the cost-effectiveness of alternative GDM screening strategies and explored structural uncertainty and the value of future research in determining the most cost-effective eligibility criteria for GDM screening in Norway.DesignWe developed a probabilistic decision tree to estimate the total costs and health benefits (i.e., quality-adjusted life-years; QALYs) associated with 4 GDM screening strategies (universal, current guidelines, high-risk, and no screening). We identified the most cost-effective strategy as the strategy with the highest incremental cost-effectiveness ratio below a Norwegian benchmark for cost-effectiveness ($28,400/QALY). We excluded inconclusive evidence on the effects of screening on later maternal type 2 diabetes mellitus (T2DM) in the primary analysis but included this outcome in a secondary analysis using 2 different sources of evidence (i.e., Cochrane or US Preventive Services Task Force). To quantify decision uncertainty, we conducted scenario analysis and value-of-information analyses.ResultsCurrent screening recommendations were considered inefficient in all analyses, while universal screening was most cost-effective in our primary analysis ($26,014/QALY gained) and remained most cost-effective when we assumed a preventive effect of GDM treatment on T2DM. When we assumed no preventive effect, high-risk screening was preferred ($19,115/QALY gained). When we assumed GDM screening does not prevent perinatal death in scenario analysis, all strategies except no screening exceeded the cost-effectiveness benchmark. In most analyses, decision uncertainty was high.ConclusionsThe most cost-effective screening strategy, ranging from no screening to universal screening, depended on the source and inclusion of GDM treatment effects on perinatal death and T2DM. Further research on these long-term outcomes could reduce decision uncertainty.HighlightsThis article analyses the cost-effectiveness of 4 alternative gestational diabetes mellitus (GDM) screening strategies in Norway: universal screening, current (broad) screening, high-risk screening, and no screening. The current Norwegian screening recommendations were considered inefficient under all analyses. The most cost-effective screening strategy ranged from no screening to universal screening depending on the source and inclusion of GDM treatment effects on later maternal diabetes and perinatal death. The parameters related to later maternal diabetes and perinatal death accounted for most of the decision uncertainty.","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140593916","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":"Creating a Multiply Imputed Value Set for the EQ-5D-5L in Canada: State-Level Misspecification Terms Are Needed to Characterize Parameter Uncertainty Correctly","authors":"Teresa C. O. Tsui, Kelvin K. W. Chan, Feng Xie, Eleanor M. Pullenayegum","doi":"10.1177/0272989x241241328","DOIUrl":"https://doi.org/10.1177/0272989x241241328","url":null,"abstract":"BackgroundParameter uncertainty in EQ-5D-5L value sets often exceeds the instrument’s minimum important difference, yet this is routinely ignored. Multiple imputation (MI) accounts for parameter uncertainty in the value set; however, no valuation study has implemented this methodology. Our objective was to create a Canadian MI value set for the EQ-5D-5L, thus enabling users to account for parameter uncertainty in the value set.MethodsUsing the Canadian EQ-5D-5L valuation study ( N = 1,073), we first refit the original model followed by models with state-level misspecification. Models were compared based on the adequacy of 95% credible interval (CrI) coverage for out-of-sample predictions. Using the best-fitting model, we took 100 draws from the posterior distribution to create 100 imputed value sets. We examined how much the standard error of the estimated mean health utilities increased after accounting for parameter uncertainty in the value set by using the MI and original value sets to score 2 data sets: 1) a sample of 1,208 individuals from the Canadian general public and 2) a sample of 401 women with breast cancer.ResultsThe selected model with state-level misspecification outperformed the original model (95% CrI coverage: 94.2% v. 11.6%). We observed wider standard errors for the estimated mean utilities on using the MI value set for both the Canadian general public (MI: 0.0091; original: 0.0035) and patients with breast cancer (MI: 0.0169; original: 0.0066).Discussion and ConclusionsWe provide 1) the first MI value sets for the EQ-5D-5L and 2) code to construct MI value sets while accounting for state-level model misspecification. Our study suggests that ignoring parameter uncertainty in value sets leads to falsely narrow SEs.HighlightsValue sets for health state utility instruments are estimated subject to parameter uncertainty; this parameter uncertainty may exceed the minimum important difference of the instrument, yet it is not fully captured using current methods. This study creates the first multiply imputed value set for a multiattribute utility instrument, the EQ-5D-5L, to fully capture this parameter uncertainty. We apply the multiply imputed value set to 2 data sets from 1) the Canadian general public and 2) women with invasive breast cancer. Scoring the EQ-5D-5L using a multiply imputed value set led to wider standard error estimates, suggesting that the current practice of ignoring parameter uncertainty in the value set leads to falsely low standard errors. Our work will be of interest to methodologists and developers of the EQ-5D-5L and users of the EQ-5D-5L, such as health economists, researchers, and policy makers.","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140594117","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":"Capturing Valuation Study Sampling Uncertainty in the Estimation of Health State Utility Values Using the EQ-5D-3L","authors":"Spyridon Poulimenos, Jeff Round, Gianluca Baio","doi":"10.1177/0272989x241239899","DOIUrl":"https://doi.org/10.1177/0272989x241239899","url":null,"abstract":"ObjectivesUtility scores associated with preference-based health-related quality-of-life instruments such as the EQ-5D-3L are reported as point estimates. In this study, we develop methods for capturing the uncertainty associated with the valuation study of the UK EQ-5D-3L that arises from the variability inherent in the underlying data, which is tacitly ignored by point estimates. We derive a new tariff that properly accounts for this and assigns a specific closed-form distribution to the utility of each of the 243 health states of the EQ-5D-3L.MethodsUsing the UK EQ-5D-3L valuation study, we used a Bayesian approach to obtain the posterior distributions of the derived utility scores. We constructed a hierarchical model that accounts for model misspecification and the responses of the survey participants to obtain Markov chain Monte Carlo (MCMC) samples from the posteriors. The posterior distributions were approximated by mixtures of normal distributions under the Kullback–Leibler (KL) divergence as the criterion for the assessment of the approximation. We considered the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm to estimate the parameters of the mixture distributions.ResultsWe derived an MCMC sample of total size 4,000 × 243. No evidence of nonconvergence was found. Our model was robust to changes in priors and starting values. The posterior utility distributions of the EQ-5D-3L states were summarized as 3-component mixtures of normal distributions, and the corresponding KL divergence values were low.ConclusionsOur method accounts for layers of uncertainty in valuation studies, which are otherwise ignored. Our techniques can be applied to other instruments and countries’ populations.HighlightsGuidelines for health technology assessments typically require that uncertainty be accounted for in economic evaluations, but the parameter uncertainty of the regression model used in the valuation study of the health instrument is often tacitly ignored. We consider the UK valuation study of the EQ-5D-3L and construct a Bayesian model that accounts for layers of uncertainty that would otherwise be disregarded, and we derive closed-form utility distributions. The derived tariff can be used by researchers in economic evaluations, as it allows analysts to directly sample a utility value from its corresponding distribution, which reflects the associated uncertainty of the utility score.","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140594116","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":"Use of Persuasive Language in Communication of Risk during Prostate Cancer Treatment Consultations.","authors":"Aurash Naser-Tavakolian, Rebecca Gale, Michael Luu, John M Masterson, Abhishek Venkataramana, Dmitry Khodyakov, Jennifer T Anger, Edwin Posadas, Howard Sandler, Stephen J Freedland, Brennan Spiegel, Timothy J Daskivich","doi":"10.1177/0272989X241228612","DOIUrl":"10.1177/0272989X241228612","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Physician treatment preference may influence how risks are communicated in prostate cancer consultations. We identified persuasive language used when describing cancer prognosis, life expectancy, and side effects in relation to a physician's recommendation for aggressive (surgery/radiation) or nonaggressive (active surveillance/watchful waiting) treatment.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A qualitative analysis was performed on transcribed treatment consultations of 40 men with low- and intermediate-risk prostate cancer across 10 multidisciplinary providers. Quotes pertaining to cancer prognosis, life expectancy, and side effects were randomized. Coders predicted physician treatment recommendations from isolated blinded quotes. Testing characteristics of consensus predictions against the physician's treatment recommendation were reported. Coders then identified persuasive strategies favoring aggressive/nonaggressive treatment for each quote. Frequencies of persuasive strategies favoring aggressive/nonaggressive treatment were reported. Logistic regression quantified associations between persuasive strategies and physician treatment recommendations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 496 quotes about cancer prognosis (&lt;i&gt;n&lt;/i&gt; = 127), life expectancy (&lt;i&gt;n&lt;/i&gt; = 51), and side effects (&lt;i&gt;n&lt;/i&gt; = 318) were identified. The accuracy of predicting treatment recommendation based on individual quotes containing persuasive language (&lt;i&gt;n&lt;/i&gt; = 256/496, 52%) was 91%. When favoring aggressive treatment, persuasive language downplayed side effect risks and amplified cancer risk (recurrence, progression, or mortality). Significant predictors (&lt;i&gt;P&lt;/i&gt; &lt; 0.05) of aggressive treatment recommendation included favorable side effect interpretation, downplaying side effects, and long time horizon for cancer risk due to longevity. When favoring nonaggressive treatment, persuasive language amplified side effect risks and downplayed cancer risk. Significant predictors of nonaggressive treatment recommendation included unfavorable side effect interpretation, favorable interpretation of cancer risk, and short time horizon for cancer risk due to longevity.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Physicians use persuasive language favoring their preferred treatment, regardless of whether their recommendation is appropriate.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Implications: &lt;/strong&gt;Clinicians should quantify risk so patients can judge potential harm without solely relying on persuasive language.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Highlights: &lt;/strong&gt;Physicians use persuasive language favoring their treatment recommendation when communicating risks of prostate cancer treatment, which may influence a patient's treatment choice.Coders predicted physician treatment recommendations based on isolated, randomized quotes about cancer prognosis, life expectancy, and side effects with 91% accuracy.Qualitative analysis revealed that when favoring nonaggressive treatment, physicians used p","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11102816/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139724726","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":"Causal Estimation of Long-term Intervention Cost-effectiveness Using Genetic Instrumental Variables: An Application to Cancer.","authors":"Padraig Dixon, Richard M Martin, Sean Harrison","doi":"10.1177/0272989X241232607","DOIUrl":"10.1177/0272989X241232607","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;This article demonstrates a means of assessing long-term intervention cost-effectiveness in the absence of data from randomized controlled trials and without recourse to Markov simulation or similar types of cohort simulation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Using a Mendelian randomization study design, we developed causal estimates of the genetically predicted effect of bladder, breast, colorectal, lung, multiple myeloma, ovarian, prostate, and thyroid cancers on health care costs and quality-adjusted life-years (QALYs) using outcome data drawn from the UK Biobank cohort. We then used these estimates in a simulation model to estimate the cost-effectiveness of a hypothetical population-wide preventative intervention based on a repurposed class of antidiabetic drugs known as sodium-glucose cotransporter-2 (SGLT2) inhibitors very recently shown to reduce the odds of incident prostate cancer.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Genetic liability to prostate cancer and breast cancer had material causal impacts on either or both health care costs and QALYs. Mendelian randomization results for the less common cancers were associated with considerable uncertainty. SGLT2 inhibition was unlikely to be a cost-effective preventative intervention for prostate cancer, although this conclusion depended on the price at which these drugs would be offered for a novel anticancer indication.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Implications: &lt;/strong&gt;Our new causal estimates of cancer exposures on health economic outcomes may be used as inputs into decision-analytic models of cancer interventions such as screening programs or simulations of longer-term outcomes associated with therapies investigated in randomized controlled trials with short follow-ups. Our method allowed us to rapidly and efficiently estimate the cost-effectiveness of a hypothetical population-scale anticancer intervention to inform and complement other means of assessing long-term intervention value.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Highlights: &lt;/strong&gt;The article demonstrates a novel method of assessing long-term intervention cost-effectiveness without relying on randomized controlled trials or cohort simulations.Mendelian randomization was used to estimate the causal effects of certain cancers on health care costs and quality-adjusted life-years (QALYs) using data from the UK Biobank cohort.Given causal data on the association of different cancer exposures on costs and QALYs, it was possible to simulate the cost-effectiveness of an anticancer intervention.Genetic liability to prostate cancer and breast cancer significantly affected health care costs and QALYs, but the hypothetical intervention using SGLT2 inhibitors for prostate cancer may not be cost-effective, depending on the drug's price for the new anticancer indication. The methods we propose and implement can be used to efficiently estimate intervention cost-effectiveness and to inform decision making in all manner of preventative and therapeutic con","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10988994/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139998105","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}