Diagnosis最新文献

{"title":"Challenges and barriers for the adoption of personalized medicine in Europe: the case of Oncotype DX Breast Recurrence Score^® test.","authors":"Denis Horgan, Paul Hofman, Patrizio Giacomini, France Dube, Jaya Singh, Daniel Schneider, Tanya Hills, Jennifer Faikish, Marc Van Den Bulcke, Umberto Malapelle, Maciej Gajewski, Vivek Subbiah","doi":"10.1515/dx-2024-0127","DOIUrl":"https://doi.org/10.1515/dx-2024-0127","url":null,"abstract":"<p><p>Personalized medicine, aiming to tailor treatments based on individual patient characteristics, holds immense potential in oncology. However, its widespread adoption in Europe faces numerous challenges, as illustrated by the case study of the Oncotype DX Breast Recurrence Score^® assay, a genomic test for breast cancer. This manuscript delineates the multifaceted obstacles encountered during the introduction of the Oncotype DX^®test (Oncotype DX Breast Recurrence Score test) in Europe from 2004 to 2018. In June 2018, the TAILORx results were published in the New England Journal of Medicine Sparano JA, Gray RJ, Makower DF, Pritchard KI, Albain KS, Hayes DF, et al. Adjuvant chemotherapy guided by a 21-gene expression assay in breast cancer. N Engl J Med 2018;379:111-21, Sparano JA, Gray RJ, Ravdin PM, Makower DF, Pritchard KI, Albain KS, et al. Clinical and genomic risk to guide the use of adjuvant therapy for breast cancer. N Engl J Med 2019;380:2395-405, and reported that among 6,711 women with hormone-receptor-positive, HER2-negative, node-negative breast cancer and a midrange recurrence score of 11-25 on the Oncotype DX assay, endocrine therapy was not inferior to chemoendocrine therapy, which provides evidence that adjuvant chemotherapy was not beneficial in these patients. Through a comprehensive analysis of clinical evidence, commercial presence, reimbursement mechanisms, guideline recommendations, regulatory pathways, and local experiences, this study sheds light on the intricate dynamics influencing the adoption of personalized medicine technologies. This article examines the various obstacles encountered during the introduction of the Oncotype DX Breast Cancer Assay in Europe from 2004 to 2018. By analyzing clinical evidence, commercial presence, reimbursement mechanisms, guideline recommendations, regulatory pathways, and local experiences, this study reveals the complex factors that influence the adoption of personalized medicine technologies. By highlighting these challenges, this article offers valuable insights into strategies to facilitate the integration of innovative diagnostic tools into clinical practice across Europe, ultimately leading to improved treatment decision-making for cancer patients.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142834578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Three-way comparison of different ESR measurement methods and analytical performance assessment of TEST1 automated ESR analyzer.","authors":"Kwanlada Chaiwong, Rujira Naksith, Waroonkarn Laiklang, Manissara Yeekaday, Suppakorn Wongkamchai, Orakan Limpornpukdee, Chutitorn Ketloy, Eakachai Prompetchara","doi":"10.1515/dx-2024-0158","DOIUrl":"https://doi.org/10.1515/dx-2024-0158","url":null,"abstract":"<p><strong>Objectives: </strong>Validation and performance assessment of novel ESR analyzer is required before implementation. The objective of this study was to assess the correlation between three ESR measurement methods. Full validation and performance assessment of an alternate method (TEST1) were also evaluated.</p><p><strong>Methods: </strong>Three-way correlation assessment for the Westergren (WG), modified Westregren (Mixrate), and alternate (TEST1) methods were performed. Analytical performance of TEST1 including precision, carryover, sample stability, potential interferences as well as effect of hematocrit (Hct) and mean corpuscular volume (MCV) were also determined.</p><p><strong>Results: </strong>Strong correlation between three ESR measurement methods were observed. Correlation coefficient (r) was 0.902, 0.977, and 0.949 for WG vs. TEST1, WG vs. Mixrate, and TEST1 vs. Mixrate, respectively with absolute bias <5 mm. For TEST1, precision and carryover were within the manufacturer's claim. Samples were stable upto 24 h and 48 h when they were stored at room temperature or 2-8 °C, respectively. No effect of trigyceride and cholesterol was observed. In low Hct samples, no significant different between the results obtained from Fabry's formula corrected WG values and from TEST1.</p><p><strong>Conclusions: </strong>Three-way comparison study yielded a strong correlation between methods. As part of the method validation before implementing a new analyzer, full validation of TEST1 showed that all validated parameters met the manufacturer's specifications. A negative bias was observed but remains within the acceptable criteria. Difference in values for samples with low hematocrit were noted, but these can be corrected by Fabry's formula applied to the values from WG method.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142812334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harbingers of sepsis misdiagnosis among pediatric emergency department patients.","authors":"Jonathan G Sawicki, Jessica Graham, Gitte Larsen, Jennifer K Workman","doi":"10.1515/dx-2024-0119","DOIUrl":"https://doi.org/10.1515/dx-2024-0119","url":null,"abstract":"<p><strong>Objectives: </strong>To identify clinical presentations that acted as harbingers for future sepsis hospitalizations in pediatric patients evaluated in the emergency department (ED) using the Symptom Disease Pair Analysis of Diagnostic Error (SPADE) methodology.</p><p><strong>Methods: </strong>We identified patients in the Pediatric Health Information Systems (PHIS) database admitted for sepsis between January 1, 2004 and December 31, 2023 and limited the study cohort to those patients who had an ED treat-and-release visit in the 30 days prior to admission. Using the look-back approach of the SPADE methodology, we identified the most common clinical presentations at the initial ED visit and used an observed to expected (O:E) analysis to determine which presentations were overrepresented. We then employed a graphical, temporal analysis with a comparison group to identify which overrepresented presentations most likely represented harbingers for future sepsis hospitalization.</p><p><strong>Results: </strong>We identified 184,157 inpatient admissions for sepsis, of which 15,331 hospitalizations (8.3 %) were preceded by a treat-and-release ED visit in the prior 30 days. Based on the O:E and temporal analyses, the presentations of fever and dehydration were both overrepresented in the study cohort and temporally clustered close to sepsis hospitalization. ED treat-and-release visits for fever or dehydration preceded 1.2 % of all sepsis admissions.</p><p><strong>Conclusions: </strong>In pediatric patients presenting to the ED, fever and dehydration may represent harbingers for future sepsis hospitalization. The SPADE methodology could be applied to the PHIS database to develop diagnostic performance measures across a wide range of pediatric hospitals.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142812320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Medical language matters: impact of clinical summary composition on a generative artificial intelligence's diagnostic accuracy.","authors":"Cassandra Skittle, Eliana Bonifacino, Casey N McQuade","doi":"10.1515/dx-2024-0167","DOIUrl":"https://doi.org/10.1515/dx-2024-0167","url":null,"abstract":"<p><strong>Objectives: </strong>Evaluate the impact of problem representation (PR) characteristics on Generative Artificial Intelligence (GAI) diagnostic accuracy.</p><p><strong>Methods: </strong>Internal medicine attendings and residents from two academic medical centers were given a clinical vignette and instructed to write a PR. Deductive content analysis described the characteristics comprising each PR. Individual PRs were input into ChatGPT-4 (OpenAI, September 2023) which was prompted to generate a ranked three-item differential. The ranked differential and the top-ranked diagnosis were scored on a 3-part scale, ranging from incorrect, partially correct, to correct. Logistic regression evaluated individual PR characteristic's impact on ChatGPT accuracy.</p><p><strong>Results: </strong>For a three-item differential, accuracy was associated with including fewer comorbidities (OR 0.57, p=0.010), fewer past historical items (OR 0.60, p=0.019), and more physical examination items (OR 1.66, p=0.015). For ChatGPT's ability to rank the true diagnosis as the single-best diagnosis, utilizing temporal semantic qualifiers, more semantic qualifiers overall, and adhering to a typical 3-part PR format all correlated with diagnostic accuracy: OR 3.447, p=0.046; OR 1.300, p=0.005; OR 3.577, p=0.020, respectively.</p><p><strong>Conclusions: </strong>Several distinct PR factors improved ChatGPT diagnostic accuracy. These factors have previously been associated with expertise in creating PR. Future studies should explore how clinical input qualities affect GAI diagnostic accuracy prospectively.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142812324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Screening fasting glucose before the OGTT: near-patient glucometer- or laboratory-based measurement?","authors":"Giuseppe Lippi, Anna Ferrari, Sara Visconti, Loredana Martini, Davide Demonte, Claudia Lo Cascio, Barbara Capizzi","doi":"10.1515/dx-2024-0176","DOIUrl":"https://doi.org/10.1515/dx-2024-0176","url":null,"abstract":"<p><strong>Objectives: </strong>The measurement of fasting glucose is a common practice for lowering the risk of hyperglycemia before an oral glucose tolerance test (OGTT). In this study we analyze advantages and limitations of near-patient measurement of capillary fasting glucose with a portable glucometer or blood sampling and measurement of plasma glucose with laboratory instrumentation.</p><p><strong>Methods: </strong>The final study population consisted of 241 subjects (mean age: 36 ± 8 years; 97.9 % pregnant women) referred to our local phlebotomy center for an OGTT. Fasting glucose was measured in capillary blood using a near-patient glucometer (glucometer-based strategy) and in plasma with laboratory instrumentation using the hexokinase reference assay (laboratory-based strategy).</p><p><strong>Results: </strong>The mean turnaround time from sample collection to obtaining the glucose value was longer with the laboratory-based strategy (32 min 8 vs. 8 s). The imprecision of the glucometer was higher than that of the laboratory assay (3.4 vs. 0.8 %). A negative bias of -3.3 % in fasting glucose was found with the glucometer compared to the laboratory measurement. The diagnostic accuracy, sensitivity and specificity of the glucometer for detecting fasting glucose values ≥7.0 mmol/L were 99.2 , 50.0 and 100.0 % compared to the laboratory assay. The glucometer-based strategy had an incremental cost of 0.17€ per patient compared to the laboratory-based strategy.</p><p><strong>Conclusions: </strong>Screening fasting glucose in capillary blood with a near-patient glucometer instead of measuring fasting plasma glucose with laboratory instrumentation allows faster patient management in the phlebotomy center but is associated with higher imprecision, inaccuracy, costs and avoidable finger pricks.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142794437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond thinking fast and slow: a Bayesian intuitionist model of clinical reasoning in real-world practice.","authors":"Isaac K S Ng, Wilson G W Goh, Tow Keang Lim","doi":"10.1515/dx-2024-0169","DOIUrl":"https://doi.org/10.1515/dx-2024-0169","url":null,"abstract":"<p><p>Clinical reasoning is a quintessential aspect of medical training and practice, and is a topic that has been studied and written about extensively over the past few decades. However, the predominant conceptualisation of clinical reasoning has insofar been extrapolated from cognitive psychological theories that have been developed in other areas of human decision-making. Till date, the prevailing model of understanding clinical reasoning has remained as the dual process theory which views cognition as a dichotomous two-system construct, where intuitive thinking is fast, efficient, automatic but error-prone, and analytical thinking is slow, effortful, logical, deliberate and likely more accurate. Nonetheless, we find that the dual process model has significant flaws, not only in its fundamental construct validity, but also in its lack of practicality and applicability in naturistic clinical decision-making. Instead, we herein offer an alternative Bayesian-centric, intuitionist approach to clinical reasoning that we believe is more representative of real-world clinical decision-making, and suggest pedagogical and practice-based strategies to optimise and strengthen clinical thinking in this model to improve its accuracy in actual practice.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142794414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing a framework for understanding diagnostic reconciliation based on evidence review, stakeholder engagement, and practice evaluation.","authors":"Sandra Algarin Perneth, Gilberto Perez Rodriguez Garcia, Juan P Brito, Tejal Gandhi, Carma L Bylund, Ian G Hargraves, Naykky Singh Ospina","doi":"10.1515/dx-2024-0132","DOIUrl":"https://doi.org/10.1515/dx-2024-0132","url":null,"abstract":"<p><strong>Objectives: </strong>Diagnostic reconciliation is the collaborative process between patients and clinicians to create and reconcile evidence-based, feasible, and desirable care plans. However, the specific components of this process remain unclear. The objective of this study was to develop the first comprehensive framework to elucidate the diagnostic reconciliation process.</p><p><strong>Methods: </strong>We followed a multi-step and iterative approach to develop the framework, including a focused systematic review of diagnostic conversations, quantitative evaluation of recordings of real-life clinical visits recordings, and stakeholder engagement (e.g., patients, clinicians, researchers).</p><p><strong>Results: </strong>We identified 17 potential components to the process of diagnostic reconciliation through literature review and stakeholder engagement. After review of 56 clinical visits and further stakeholder engagement, we developed a final framework including four categories: 1) understanding the need for a test/referral, 2) logistics of test/referral scheduling, 3) test/referral information, and 4) test/referral results.</p><p><strong>Conclusions: </strong>The proposed framework lays the foundation for evaluation and improvement of diagnostic conversations in practice. Clinicians can enhance patient-centered diagnosis by co-creating diagnostic plans of care in practice and using the components described in the novel diagnostic reconciliation framework.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142794421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The foundations of the diagnostic error movement: a tribute to Eta Berner, PhD.","authors":"Mark L Graber","doi":"10.1515/dx-2024-0182","DOIUrl":"https://doi.org/10.1515/dx-2024-0182","url":null,"abstract":"","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142794442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of meta-memory techniques in generating effective differential diagnoses in a pediatric core clerkship.","authors":"Khadijah Tiamiyu, Amit Pahwa, Megan Gates, Amanda Bertram, Emily Murphy","doi":"10.1515/dx-2024-0133","DOIUrl":"https://doi.org/10.1515/dx-2024-0133","url":null,"abstract":"<p><strong>Objectives: </strong>We primarily assessed differences in differential diagnosis (DDx) efficacy of initial and refined top diagnoses (tDDx) and \"can't miss\" DDx (CMDx) between 3 MMTs (Constellations, Mental CT, and VINDICATES).</p><p><strong>Methods: </strong>Pediatric clerkship students participated in two 1-h case-based sessions. The case was presented in three aliquots. Students were randomly assigned to MMT groups. Assigned MMTs were used to generate the initial tDDx and CMDx following aliquot 1. tDDx and CMDx were refined following both aliquots 2 and 3. Group DDx responses and student affective data were collected via survey. DDx efficacy was defined using pooled faculty responses and scoring was done by consensus.</p><p><strong>Results: </strong>There was no significant difference in scores between MMT groups, except the second iteration of CMDx in Case A (Constellations 50 % [interquartile range, IQR, 50-100], Mental CT 50 % [50-100], VINDICATES 0 % [0-50], p=0.02). Students' self-reported confidence in generating (p<0.001) and refining (p<0.001) their DDx significantly increased after the curriculum.</p><p><strong>Conclusions: </strong>Although prior studies identified a differential effect of MMTs on DDx generation, we did not observe a difference in initial or refined DDx efficacy between MMTs. .</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142767237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic scope: the AI can't see what the mind doesn't know.","authors":"Gary E Weissman, Laura Zwaan, Sigall K Bell","doi":"10.1515/dx-2024-0151","DOIUrl":"https://doi.org/10.1515/dx-2024-0151","url":null,"abstract":"<p><strong>Background: </strong>Diagnostic scope is the range of diagnoses found in a clinical setting. Although the diagnostic scope is an essential feature of training and evaluating artificial intelligence (AI) systems to promote diagnostic excellence, its impact on AI systems and the diagnostic process remains under-explored.</p><p><strong>Content: </strong>We define the concept of diagnostic scope, discuss its nuanced role in building safe and effective AI-based diagnostic decision support systems, review current challenges to measurement and use, and highlight knowledge gaps for future research.</p><p><strong>Summary: </strong>The diagnostic scope parallels the differential diagnosis although the latter is at the level of an encounter and the former is at the level of a clinical setting. Therefore, diagnostic scope will vary by local characteristics including geography, population, and resources. The true, observed, and considered scope in each setting may also diverge, both posing challenges for clinicians, patients, and AI developers, while also highlighting opportunities to improve safety. Further work is needed to systematically define and measure diagnostic scope in terms that are accurate, equitable, and meaningful at the bedside. AI tools tailored to a particular setting, such as a primary care clinic or intensive care unit, will each require specifying and measuring the appropriate diagnostic scope.</p><p><strong>Outlook: </strong>AI tools will promote diagnostic excellence if they are aligned with patient and clinician needs and trained on an accurately measured diagnostic scope. A careful understanding and rigorous evaluation of the diagnostic scope in each clinical setting will promote optimal care through human-AI collaborations in the diagnostic process.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142767289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}