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Diagnostic test evaluation methodology: A systematic review of methods employed to evaluate diagnostic tests in the absence of gold standard – An update

Chinyereugo m. umemneku chikere.

1 Institute of Health & Society, Faculty of Medical Sciences Newcastle University, Newcastle upon Tyne, England, United Kingdom

Kevin Wilson

2 School of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne, England, United Kingdom

Sara Graziadio

3 National Institute for Health Research, Newcastle In Vitro Diagnostics Co-operative, Newcastle upon Tyne Hospitals National Health Services Foundation Trust, Newcastle upon Tyne, England, United Kingdom

A. Joy Allen

4 National Institute for Health Research, Newcastle In Vitro Diagnostics Co-operative, Newcastle University, Newcastle upon Tyne, England, United Kingdom

Associated Data

All relevant data are within the manuscript and its supporting information files.

To systematically review methods developed and employed to evaluate the diagnostic accuracy of medical test when there is a missing or no gold standard.

Study design and settings

Articles that proposed or applied any methods to evaluate the diagnostic accuracy of medical test(s) in the absence of gold standard were reviewed. The protocol for this review was registered in PROSPERO (CRD42018089349).

Identified methods were classified into four main groups: methods employed when there is a missing gold standard; correction methods (which make adjustment for an imperfect reference standard with known diagnostic accuracy measures); methods employed to evaluate a medical test using multiple imperfect reference standards; and other methods, like agreement studies, and a mixed group of alternative study designs. Fifty-one statistical methods were identified from the review that were developed to evaluate medical test(s) when the true disease status of some participants is unverified with the gold standard. Seven correction methods were identified and four methods were identified to evaluate medical test(s) using multiple imperfect reference standards. Flow-diagrams were developed to guide the selection of appropriate methods.

Various methods have been proposed to evaluate medical test(s) in the absence of a gold standard for some or all participants in a diagnostic accuracy study. These methods depend on the availability of the gold standard, its’ application to the participants in the study and the availability of alternative reference standard(s). The clinical application of some of these methods, especially methods developed when there is missing gold standard is however limited. This may be due to the complexity of these methods and/or a disconnection between the fields of expertise of those who develop (e.g. mathematicians) and those who employ the methods (e.g. clinical researchers). This review aims to help close this gap with our classification and guidance tools.

Introduction

Before a new medical test can be introduced into clinical practice, it should be evaluated for analytical validity (does the test work in the laboratory?), clinical validity (does the test work in the patient population of interest?) and clinical utility (is the test useful–can it lead to improvement in health outcomes?) [ 1 , 2 ]. Clinical validity studies, also called diagnostic accuracy studies, evaluate the test’s accuracy in discriminating between patients with or without the target condition (disease) [ 3 ]. The characteristics of the test (e.g. sensitivity and specificity) may inform what role the index test (the new test under evaluation) plays in the diagnostic pathway; is it a triage, add-on or replacement test? [ 4 ] Sensitivity (the proportion of participants correctly identified by the index test as having the target condition e.g. those with the disease) and specificity (the proportion of participants correctly identified by the index as not having the target condition) [ 5 – 7 ] are basic measures of the diagnostic accuracy of a test. Other common measures are predictive values, likelihood values, overall accuracy [ 8 , 9 ], receiver operating characteristic (ROC) curve, area under the ROC curve (AUROC) [ 10 ], ROC surface, and volume under the ROC surface (VUS) [ 11 – 13 ]. These measures are obtained by comparing the index test results with the results of the best currently available test for diagnosing the same target condition in the same participants; both tests are supposedly applied to all participants of the study [ 14 ]. The test employed as the benchmark to evaluate the index test is called the reference standard [ 15 ]. The reference standard could be a gold standard (GS), with sensitivity and specificity equal to 100%. This means that the gold standard perfectly discriminates between participants with or without the target conditions and provides unbiased estimates of the diagnostic accuracy measure of the index test as describe in Fig 1 . The term “bias” in this review is defined as the difference between the estimated value and the true value of the parameter of interest [ 16 ].

It is also expected that when evaluating the diagnostic accuracy of a medical test, the participants undertake both the index and reference tests within a short time-period if not simultaneously. This is to avoid biases caused by changes in their true disease status, which can also affect the diagnostic accuracy of the index test.

In addition to the common aforementioned diagnostic accuracy measures, there are other ways to evaluate the test performance of an index test. These include studies of agreement or concordance [ 17 ] between the index test and the reference standard and test positivity (or negativity) rate; that is the proportion of diagnostic tests that are positive (or negative) to the target condition [ 18 ].

In practice, there are deviations from the classical method ( Fig 1 ). These deviations are:

• Scenarios where the gold standard is not applied to all participants in the study (i.e. there is a missing gold standard) because it is expensive, or invasive, or patients do not consent to it, or the clinicians decided not to give the gold test to some patients for medical reasons [ 19 , 20 ]. Evaluating the new test using data only from participants whose disease status was confirmed with the gold standard can produce work-up or verification bias [ 21 ].
• Scenarios where the reference standard is not a gold standard (i.e. it is an imperfect reference standard) because it has a misclassification error or because there is no generally accepted reference standard for the target condition. Using an imperfect reference standard produces reference standard bias [ 22 , 23 ].

Several methods have been developed and used to evaluate the test performance of a medical test in these two scenarios.

Reviews of some of these methods have been undertaken previously. The reviews by Zhou [ 24 ], Alonzo [ 25 ] and the report by Naaktgeboren et al [ 26 ] focused on methods when the gold standard or reference standard is not applied to all participants in the study; Van Smeden et al [ 27 ] and Collins and Huynh [ 28 ] focused on the latent class models (LCMs); and Hui and Zhou [ 29 ], Trikalinos and Balion [ 30 ] and Enoe et al [ 31 ] focused on methods employed when the reference standard is imperfect. Zaki et al [ 32 ] focused on the agreement between medical tests whose results are reported as a continuous response. Branscum et al [ 33 ] focused on Bayesian approaches; and the reviews by Walsh [ 23 ], Rutjes et al [ 14 ] and Reitsma et al [ 34 ] focused around methods for evaluating diagnostic tests when there is a missing or imperfect reference standard.

The existing comprehensive reviews on this topic were published about 11 years ago [ 14 , 34 ]; knowledge, ideas, and research in this field has evolved significantly since then. Several new methods have been proposed and some existing methods have been modified. It is also possible that some previously identified methods may now be obsolete. Therefore, one of the aims of this systematic review is to review new and existing methods employed to evaluate the test performance of medical test(s) in the absence of gold standard for all or some of the participants in the study. It also aims to provide easy to use tools (flow-diagrams) for the selection of methods to consider when evaluating medical tests when sub-sample of the participants do not undergo the gold standard. The review builds upon the earlier reviews by Rutjes et al and Reitsma et al [ 14 , 34 ]. This review sought to identify methods developed to evaluate a medical test with continuous results in the presence of verification bias and when the diagnostic outcome (disease status) is classified into three or more groups (e.g. diseased, intermediate and non-diseased). This is a gap identified in the review conducted by Alonzo [ 25 ] in 2014.

The subsequent sections discuss the method employed to undertake the review, the results, the discussion of the findings and guidance to researchers involved in test accuracy studies.

Methodology

A protocol for this systematic review was developed, peer-reviewed and registered on PROSPERO (CRD42018089349).

Eligibility criteria

The review includes methodological articles (that is papers that proposed or developed a method) and application articles (that is papers where any of the proposed methods) were applied.

• Articles published in English language in a peer-reviewed journal.
• Articles that focus on evaluating the diagnostic accuracy of new (index) test when there is a missing gold standard, no gold standard or imperfect reference standard.
• Articles that assumed that the reference standard was a gold standard and the gold standard was applied to all participants in the study.
• Books, dissertations, thesis, conference abstracts, and articles not published in a peer reviewed journal.
• Systematic reviews and meta-analyses of the diagnostic accuracy of medical test(s) for a target condition (disease) in the absence of gold standard for some or all of the participants. However, individual articles included in these reviews that met the inclusion criteria were included.

Search strategies and selection of articles

The PRISMA statement [ 35 ] was used as a guideline when conducting this systematic review. The PRISMA checklist for this review, S1 Checklist , is included as one of the supplementary materials. The following bibliographic databases were searched: EMBASE, MEDLINE, SCOPUS, WILEY online library (which includes Cochrane library, EBM), PSYCINFO, Web of Science, and CINAHL. The details of the search strategies at reported in the S1 Appendix . The search dates were from January 2005 –February 2019. This is because, this review is an update of a review by Rutjes et al and Reitsma et al whose searched up to 2005. However, original methodological articles that proposed and described a method to evaluate medical test(s) when there is a missing or no gold standard published before 2005 were also included in the review. These original articles were identified by "snowballing" [ 36 ] from the references of some articles. All articles obtained from the electronic databases were imported to Endnote X8.0.2. The selection of articles to be included in this review were done by three people (CU, AJA, and KW). The sifting process was in two-stages: by title and abstract and then by full text against the inclusion and exclusion criteria. Any discrepancies between reviewers were resolved in a group meeting.

Data synthesis

A data collection form was developed for this review ( S1 Data ), which was piloted on seven studies and remodified to fit the purpose of this review. Information extracted from the included articles were synthesized narratively.

A total of 6127 articles were identified; 5472 articles were left after removing the duplicated articles; 5071 articles were excluded after sifting by title and abstract; 401 articles went forward to full text assessment; and a total of 209 articles were included in the review. The search and selection procedure are depicted using the PRISMA [ 35 ] flow-diagram ( Fig 2 ).

The articles included in this review used a wide variety of different study designs, like cross-sectional studies, retrospective studies, cohort studies, prospective studies and simulation studies.

The identified methods were categorized into four groups based on the availability and/or application of the gold standard to the participants in the study. These group are:

• Group 1: Methods employed when there is a missing gold standard.
• Group 2: Correction methods which adjust for using an imperfect reference standard whose diagnostic accuracy is known.
• Group 3: Methods employed when using multiple imperfect reference standards.
• Group 4: “other methods” . This group includes methods like study of agreement, test positivity rate, and considering alternative study design like validation.

Methods in groups 2, 3 and 4 are employed when there is no gold standard to evaluate the diagnostic accuracy of the index test; while methods in group 1 are employed when there is a gold standard to evaluate the diagnostic accuracy of the index test(s). However, the gold standard is applied to only a sub-sample of the participants.

A summary of all methods identified in the review, their key references and the clinical applications of these methods are reported on Table 1 .

LCA: latent class analysis; CRS is composite reference standard. ROC is receiver operating characteristics; NGS is no gold standard

Methods employed when gold standard is missing

Fifty-one statistical methods were identified from the review that were developed to evaluate the diagnostic accuracy of index test(s) when the true disease status of some participants is not verified with the gold standard. These methods are divided into two subgroups:

• Differential verification approach : Participants whose disease status was not verified with the gold standard could undergo another reference standard (that is imperfect or less invasive than the gold standard [ 84 ]) to ascertain their disease status. This is known as differential verification [ 200 ]. Differential verification has been explored Alonzo et al, De Groot et al and Naaktgeboren et al [ 200 – 202 ]. They discussed the bias associated with differential verification, and how results using this approach could be presented. There are three identified statistical methods in this group. They are: a Bayesian latent class approach proposed by De Groot et al [ 82 ], a Bayesian method proposed by Lu et al [ 203 ] and a ROC approach proposed by Glueck et al [ 16 ]. These three methods aim to simultaneously adjust for differential verification bias and reference standard bias that arises from using an alternative reference standard (i.e. imperfect reference standard) for participants whose true disease status was not verified with the gold standard.

Correction methods

This group includes algebraic methods developed to correct the estimated sensitivity and specificity of the index test when the sensitivity and specificity of the imperfect reference standard is known. There are seven statistical methods in this group described in five different articles [ 91 – 95 ]. The methods by Emerson et al [ 95 ] does not estimate a single value for sensitivity or specificity, unlike the other correction methods [ 91 – 94 ] but produces an upper bound value and a lower bound value for the sensitivity and specificity of the index test. These bounded values are used to explain the uncertainty around the estimated sensitivity and specificity of the index test.

Methods with multiple imperfect reference standards

A gold standard or accurate information about the diagnostic accuracy of the imperfect reference standard are often not available to evaluate the index test. In these situations, multiple imperfect reference standards can be employed to evaluate the index test. Methods in this group include:

• Discrepancy analysis : this compares the index test with an imperfect reference standard. Participants with discordant results undergo another imperfect test, called the resolver test, to ascertain their disease status. Discrepancy analysis is typically not recommended because it produces biased estimates [ 100 , 204 ]. Modifications of this approach have been proposed [ 18 , 101 , 136 ]. In these, some of the participants with concordant responses (true positives and true negatives) are sampled to undertake the resolver test alongside participants with discordant responses (false negative–FN and false positive–FP). However, further research is needed to explore if these modified approaches are adequate to remove or reduce the potential bias.
• Latent class analysis (LCA) : The test performance of all the tests employed in the study are evaluated simultaneously using probabilistic models with the basic assumption that the disease status is latent or unobserved. There are frequentist LCAs and Bayesian LCAs. The frequentist LCAs use only the data from the participants in the study to estimate the diagnostic accuracy measures of the tests; while the Bayesian LCAs employ external information (e.g. expert opinion or estimates from previous research study) on the diagnostic accuracy measures of the tests evaluated in additional to the empirical data obtained from participants within the study. The LCAs assume that the tests (new test and reference standards) are either conditionally independent given the true disease status or the tests are conditionally dependent. To model the conditional dependence among the tests, various latent class model (LCM) with different dependence structure have been developed such as the Log-linear LCM [ 102 ], Probit LCM [ 103 ], extended log-linear and Probit LCM [ 108 ], Gaussian Random Effect LCM [ 105 ] and two-crossed random effect LCM [ 107 ] among others. However, some studies [ 205 ],[ 206 ] have shown that latent class models with different conditional dependence structures produce different estimates of sensitivities and specificities and each model still has a good fit. Thus, further research could be carried out to explore if each of the conditional dependence LCM are case specific.
• Construct composite reference standard : this method combines results from multiple imperfect tests (excluding the index test) with a predetermined rule to construct a reference standard that is used to evaluate the index test. By excluding the index test as part of the composite reference standard, incorporation bias can be avoided [ 131 ]. A novel method identified under the composite reference standard is the “dual composite reference standard” proposed by Tang et al [ 134 ].
• Panel or consensus diagnosis : this method uses the decision from a panel of experts to ascertain the disease status of each participant, which is then used to evaluate the index test.

Other methods

This group includes methods that fit the inclusion criteria but could not be placed into the other three groups. They include study of agreement, test positivity rate and the use of an alternative study design such as analytical validation. Study of agreement and test positivity rate are best used as exploratory tools alongside other methods [ 152 , 178 ] because they are not robust enough to assess the diagnostic ability of the medical test. Validation of a medical test cut across different disciplines in medicine such as psychology, laboratory or experimental medicine. With this approach, the medical test is assessed based on what it is designed to do [ 191 ]. Other designs include case-control designs (where the participants are known to have or not have the target condition) [ 207 , 208 ], laboratory based studies or experimental studies which are undertaken with the aim to evaluate the analytical sensitivity and specificity of the index test [ 190 , 209 , 210 ].

Guidance to researchers

The guidance flowchart ( Fig 5 ) is a modification and extension of the guidance for researchers flow-diagram developed by Reitsma et al [ 34 ].

Since, evaluating the accuracy measures of the index test is the focus of any diagnostic accuracy study, the flowchart starts with asking the first question “Is there a gold standard to evaluate the index test?” Following the responses from each question box (not bold); methods are suggested (bold boxes at the bottom of the flowchart) to guide clinical researchers, test evaluators, and researchers as to the different methods to consider.

Although, this review aims to provide up-to-date approaches that have been proposed or employed to evaluate the diagnostic accuracy of an index test in the absence of a gold standard for some or all of the participants in the accuracy study; some things researchers can consider when designing an accuracy study aside from the aim of their studies, are outlined in Box 1 ([ 26 , 211 – 218 ]).

Box 1: Suggestions when designing a diagnostic accuracy study.

• Design a protocol : The protocol describes every step of the study. It states the problem and how it will be addressed.
• Selection of participants from target population : The target population determines the criteria for including participants in the study. Also, the population is important in selecting the appropriate setting for the study.
• Selection of appropriate reference standard: The reference standard should diagnose same target condition as the index test. The choice of reference standard (gold or non-gold) determines the methods to apply when evaluating the index test (see Fig 5 ).
• Sample size : Having adequate sample size is necessary to make precise inference from the statistical analysis that will be carried out. Studies that discuss the appropriate sample size to consider when planning test accuracy are [ 211 – 215 ].
• Selection of accuracy measure to estimate : The researchers need to decide which accuracy measures they wish to estimate, and this is often determined by the test’s response (binary or continuous).
• Anticipate and eliminate possible bias : multiple forms of bias may exist [ 26 , 216 – 218 ]. Exploring how to avoid or adjust for these bias (if they are unavoidable) is important.
• Validation of results : Is validation of the results from the study on an independent sample feasible? Validation ensures an understanding of the reproducibility, strengths, and limitations of the study.

Some guidelines and tools have been developed to assist in designing, conducting and reporting diagnostic accuracy studies such as the STARD [ 219 – 223 ] guidelines, GATE [ 224 ] framework, QUADAS [ 225 ] tools; which can aid the design of a robust test accuracy study.

This review sought to identify and review new and existing methods employed to evaluate the diagnostic accuracy of a medical test in the absence of gold standard. The identified methods are classified into four main groups based on the availability and/or the application of the gold standard on the participants in the study. The four groups are: methods employed when only a sub-sample of the participants have their disease status verified with the gold standard (group 1); correction methods (group 2); methods using multiple imperfect reference standards (group 3) and other methods (group 4) such as study of agreement, test positivity rate and alternative study designs like validation.

In this review additional statistical methods have been identified that were not included in the earlier reviews on this topic by Reitsma et al [ 34 ] and Alonzo [ 25 ]. A list of all the methods identified in this review are presented in the supplementary material ( S1 Supplementary Information ). This includes a brief description of the methods and a discussion of their strengths and weaknesses and any identified case studies where the methods have been clinically applied. Only a small number of the methods we have identified have applied clinically and published [ 38 , 63 ]. This may be due to the complexity of these methods (in terms of application and interpretation of results), and/or a disconnection between the fields of expertise of those who develop (e.g. mathematicians or statisticians) and those who employ the methods (e.g. clinical researchers). For example, the publication of such method in specialist statistical journals may not be readily accessible to clinical researchers designing the study. In order to close this gap, two flow-diagrams (Figs ​ (Figs3 3 and ​ and4) 4 ) were constructed in addition to the modified guidance flowchart, ( Fig 5 ) as guidance tools to aid clinical researchers and test evaluators in the choice of methods to consider when evaluating medical test in the absence of gold standard. Also, an R package ( bcROCsurface ) and an interactive web application (Shiny app) that estimates the ROC surface and VUS in the presence of verification bias have been developed by To Duc [ 78 ] to help bridge the gap.

One of the issues not addressed in this current review was on methods that evaluate the differences in diagnostic accuracy of two or more tests in the presence of verification bias. Some published articles that consider this issue are Nofuentes and Del Castillo [ 226 – 230 ], Marin-Jimenez and Nofuentes [ 231 ], Harel and Zhou [ 232 ] and Zhou and Castelluccio [ 233 ]. This review also did not consider methods employed to estimate the time-variant sensitivity and specificity of diagnostic test in absence of a gold standard. This issue has recently been addressed by Wang et al [ 234 ].

In terms of the methodology, a limitation of this review is the exclusion of books, dissertations, thesis, conference abstract and articles not published in English language (such as the review by Masaebi et al [ 235 ] which was published in 2019), which could imply that there could still be some methods not identified by this review.

Regarding the methods identified in this review, further research could be carried to explore the different modification to the discrepancy analysis approaches to understand if these modifications reduce or remove the potential bias. In addition, further research is needed to determine if the different methods developed to evaluate an index test in the presence of verification bias are robust methods. Given the large numbers of statistical methods that have been developed especially to evaluate medical tests when there is a missing gold standard and the complexity of some of these methods; more interactive web application (e.g. Shiny package in R [ 236 ]) could be developed to implement these methods in addition to the Shiny app developed by To Duc [ 78 ] and Lim et al [ 237 ]. The development of such interactive web tools will expedite the clinical applications of these developed methods and help bridge the gap between the method developers and the clinical researchers or tests evaluators who are the end users of these methods.

Various methods have been proposed and applied in the evaluation of medical tests when there is a missing gold standard result for some participants, or no gold standard at all. These methods depend on the availability of the gold standard, its application to all or subsample of participants in the study, the availability of alternative reference standard(s), and underlying assumption(s) made with respect to the index test(s) and / or participants in the study.

Knowing the appropriate method to employ when analysing the data from participants of a diagnostic accuracy studies in the absence of gold standard, help to make statistically robust inference on the accuracy of the index test. This, in addition to data on cost-effectiveness, utility and usability of the test will support clinicians, policy makers and stake holders to decide the adoption of the new test in practice or not.

Supporting information

S1 checklist, s1 appendix, s1 supplementary information, acknowledgments.

The authors will like to acknowledge Professor Patrick Bossuyt from the Department of Clinical Epidemiology and Biostatistics, Academic Medical centre, University of Amsterdam, the Netherlands, for giving the consent to update his review, reviewing the protocol and his continued advice throughout this work. Also we will like to acknowledge the authors of the previous review, Dr Anne Rutjes in University of Bern, Switzerland; Professor Johannes Reitsma in the Department of Epidemiology, Julius Center Research Program Methodology UMC Utrecht, The Netherlands; Professor Arri Coomarasamy in the College of Medical and Dental Sciences, University of Birmingham, UK; and Professor Khalid Saeed Khan in Queen Mary, University of London for the guidance flowchart which was modified and extended. AJA, SG, and LV are supported by the National Institute for Health Research (NIHR) Newcastle In Vitro Diagnostics Co-operative. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

Funding Statement

This work is supported by the Newcastle University Research Excellence; the School of Mathematics, Statistics and Physics Newcastle University; the Institute of Health & Society Newcastle University; and the National Institute for Health Research (NIHR) [NIHR Newcastle In Vitro Diagnostics Co-operative]. The view and opinions expressed are those of the authors and do not necessary reflect those of the NIHR Newcastle In Vitro Diagnostics Co-operative, Newcastle University and Newcastle upon Tyne NHS Foundation Trust, the NHS or Newcastle Research Academy. The views expressed are those of the authors and not necessarily those of the NIHR, the NHS or the Department of Health and Social Care. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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A Cost-Effectiveness Analysis Of Oropharyngeal Cancer Post-Treatment Surveillance Practices , Rema Shah

Machine Learning And Risk Prediction Tools In Neurosurgery: A Rapid Review , Josiah Sherman

Maternal And Donor Human Milk Support Robust Intestinal Epithelial Growth And Differentiation In A Fetal Intestinal Organoid Model , Lauren Smith

Constructing A Fetal Human Liver Atlas: Insights Into Liver Development , Zihan Su

Somatic Mutations In Aging, Paroxysmal Nocturnal Hemoglobinuria, And Myeloid Neoplasms , Tho Tran

Illness Perception And The Impact Of A Definitive Diagnosis On Women With Ischemia And No Obstructive Coronary Artery Disease: A Qualitative Study , Leslie Yingzhijie Tseng

Advances In Keratin 17 As A Cancer Biomarker: A Systematic Review , Robert Tseng

Regionalization Strategy To Optimize Inpatient Bed Utilization And Reduce Emergency Department Crowding , Ragini Luthra Vaidya

Survival Outcomes In T3 Laryngeal Cancer Based On Staging Features At Diagnosis , Vickie Jiaying Wang

Analysis Of Revertant Mosaicism And Cellular Competition In Ichthyosis With Confetti , Diana Yanez

A Hero's Journey: Experiences Using A Therapeutic Comicbook In A Children’s Psychiatric Inpatient Unit , Idil Yazgan

Prevalence Of Metabolic Comorbidities And Viral Infections In Monoclonal Gammopathy , Mansen Yu

Automated Detection Of Recurrent Gastrointestinal Bleeding Using Large Language Models , Neil Zheng

Vascular Risk Factor Treatment And Control For Stroke Prevention , Tianna Zhou

Theses/Dissertations from 2023 2023

Radiomics: A Methodological Guide And Its Applications To Acute Ischemic Stroke , Emily Avery

Characterization Of Cutaneous Immune-Related Adverse Events Due To Immune Checkpoint Inhibitors , Annika Belzer

An Investigation Of Novel Point Of Care 1-Tesla Mri Of Infants’ Brains In The Neonatal Icu , Elisa Rachel Berson

Understanding Perceptions Of New-Onset Type 1 Diabetes Education In A Pediatric Tertiary Care Center , Gabriel BetancurVelez

Effectiveness Of Acitretin For Skin Cancer Prevention In Immunosuppressed And Non-Immunosuppressed Patients , Shaman Bhullar

Adherence To Tumor Board Recommendations In Patients With Hepatocellular Carcinoma , Yueming Cao

Clinical Trials Related To The Spine & Shoulder/elbow: Rates, Predictors, & Reasons For Termination , Dennis Louis Caruana

Improving Delivery Of Immunomodulator Mpla With Biodegradable Nanoparticles , Jungsoo Chang

Sex Differences In Patients With Deep Vein Thrombosis , Shin Mei Chan

Incorporating Genomic Analysis In The Clinical Practice Of Hepatology , David Hun Chung

Emergency Medicine Resident Perceptions Of A Medical Wilderness Adventure Race (medwar) , Lake Crawford

Surgical Outcomes Following Posterior Spinal Fusion For Adolescent Idiopathic Scoliosis , Wyatt Benajmin David

Representing Cells As Sentences Enables Natural Language Processing For Single Cell Transcriptomics , Rahul M. Dhodapkar

Life Vs. Liberty And The Pursuit Of Happiness: Short-Term Involuntary Commitment Laws In All 50 US States , Sofia Dibich

Healthcare Disparities In Preoperative Risk Management For Total Joint Arthroplasty , Chloe Connolly Dlott

Toll-Like Receptors 2/4 Directly Co-Stimulate Arginase-1 Induction Critical For Macrophage-Mediated Renal Tubule Regeneration , Natnael Beyene Doilicho

Associations Of Atopic Dermatitis With Neuropsychiatric Comorbidities , Ryan Fan

International Academic Partnerships In Orthopaedic Surgery , Michael Jesse Flores

Young Adults With Adhd And Their Involvement In Online Communities: A Qualitative Study , Callie Marie Ginapp

Becoming A Doctor, Becoming A Monster: Medical Socialization And Desensitization In Nazi Germany And 21st Century USA , SimoneElise Stern Hasselmo

Comparative Efficacy Of Pharmacological Interventions For Borderline Personality Disorder: A Network Meta-Analysis , Olivia Dixon Herrington

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Home > FACULTIES > Pathology > PATHOL-ETD

Pathology Theses and Dissertations

This collection contains theses and dissertations from the Department of Pathology, collected from the Scholarship@Western Electronic Thesis and Dissertation Repository

Theses/Dissertations from 2023 2023

Investigation of Novel Pan-RAF Inhibitors in Anaplastic Thyroid Cancer , Sarah EB Ryan

Theses/Dissertations from 2022 2022

Evaluating the utility of S100A7 in identifying oral dysplastic lesions that will progress to oral squamous cell carcinoma , Jeff Soparlo

Theses/Dissertations from 2021 2021

Investigating The Impact Of The COVID-19 Pandemic On Maternal Perceived Stress, Postpartum Depressive Symptoms, And Pregnancy Outcomes In London, Ontario: A One Health Approach , Mei Yuan

Theses/Dissertations from 2020 2020

Evidence of an Antigen Presenting Cell Phenotype in Granular Cell Tumours , Benjamin J W A Rogala

Theses/Dissertations from 2019 2019

Junctophilin-2 Protects Cardiomyocytes against Palmitate-induced Injury , Xiaoyun Ji

Evaluating the Utility of Protein Biomarker, S100A7, and Diagnostic Test, Straticyte, in Predicting the Progression of Oral Dysplasia , Lachlan McLean

Alpha-Synuclein Toxicity is Caused by Mitochondrial Dysfunction , Michael G. Tauro

Theses/Dissertations from 2018 2018

Non-Cancerous Abnormalities That Could Mimic Prostate Cancer Like Signal in Multi-Parametric MRI Images , Mena Gaed

Mitochondrial permeability regulates cardiac endothelial cell necroptosis and cardiac allograft rejection , Ingrid Gan

Kallikrein-Related Peptidases are Dysregulated in Pleomorphic Adenoma , Matthew D. Morrison

Increased Mitochondrial Calpain-1 Is an Important Mechanism Contributing to Mitochondrial ROS Generation in Cardiac Diseases , Rui Ni

Elucidating mechanisms of innate and acquired resistance to PI3Ka inhibition in head and neck squamous cell carcinoma , Kara M. Ruicci

The Effects of Child Restraint System Use and Motor Vehicle Collision Severity on Injury Patterns and Severity in Children 8 Years Old and Younger. , Peyton A. Schroeder

Role of Long Noncoding RNAs in Diabetic Complications , Anu Alice Thomas

Effect of Estrogen and Glucocorticoid Signaling on Th2 cells – Implications for Severe Asthma , Meerah Vijeyakumaran

Theses/Dissertations from 2017 2017

CRISPR Screen for Identification of Kinases that Mediate Prostate Cancer Cell Invasion , Hamad Aldhafeeri

Immunological Impact of CLI-095 on Dendritic Cell Maturation and Hypoxia-re-oxygenation induced inflammatory injury , Hajed Obaid Alharbi

ERK5 Expression in Brain Tumours , Reem Ansari

Expression of Human Tissue Kallikreins (KLKs) in Polymorphous Low Grade Adenocarcinoma (PLGA) , Jacqueline M. Cox

A Clinico-Pathological Study of the Structural and Functional Changes in the Retina and Optic Nerve Following Diabetic Retinopathy Treatments , Richard Filek

Mechanisms underlying chemotherapy-induced vascular proliferation in ovarian cancer , Zeynep Gülsüm Kahramanoğlu

The Effect of Glucocorticosteroids on Th2 cells , Tharsan Kanagalingam

Hsp90 and its Co-chaperones Modify TDP-43 Localization, Aggregation, and Toxicity , Lilian T. Lin

Characterization of Hemangioma-initiating Stem Cells , Natalie Montwill

Postnatal β1 Integrin Deficiency in Pancreatic Beta-Cells Impairs Function and Survival , Jason E. Peart

Up-regulation of junctophilin-2 prevents ER stress and apoptosis in hypoxia/reoxygenation-stimulated H9c2 cells , Zijun Su

Theses/Dissertations from 2016 2016

Body and Organ Measurements in Infants and Neonates: An Autopsy Study , Audrey-Ann M. Evetts

The Long Non-coding RNA Malat1 Regulates Inflammatory Cytokine Production in Chronic Diabetic Complications , Andrew D. Gordon

Expression of Kallikrein-Related Peptidases (KLKs) in Adenoid Cystic Carcinoma , Zachary R. Kerr

Mechanisms regulating stem cell phenotype in infantile hemangioma , Niamh Richmond

Etiology of Motor Vehicle Collision Fatalities in Urban and Rural Canada , James R. Roos

Identification of a Nuclear Localization Signal (NLS) within the Pleckstrin Homology (PH) domain of Rho Guanine Nucleotide Exchange Factor (RGNEF) , Michael V. Tavolieri

Development and Performance Evaluation of an Antibody-Based Technology for Detection of E. coli O157 in Meat Samples and Its Potential Evolution Using Antibody Engineering , Yadira Tejeda Saldaña

Regulation of Phosphatase and Tensin Homolog Expression and Activity by Transforming Growth-Factor Beta in the Trabecular Meshwork Cells: Implications for Primary Open Angle Glaucoma , Nikoleta Tellios

Theses/Dissertations from 2015 2015

Phase II Clinical Trial of Concurrent Neoadjuvant Chemotherapy With Radiotherapy in Locally Advanced Breast Cancer , Muriel Brackstone

Expression Of Human Kallikrein Protein And mRNA In Maxillofacial Cysts And Tumours , Karl Kevin Cuddy

Chromatin Structure and Differential Accessibility of Homologous Human Mitotic Metaphase Chromosomes , Wahab A. Khan

β-adrenergic receptor-dependent and -independent effects of propranolol in infantile hemangioma , Jina J.Y. Kum

CD4+ T-cell Mediated Microvascular Endothelial Cell Death and Chronic Cardiac Allograft Rejection Involves Necroptosis , Cecilia YT Kwok

Epithelial to mesenchymal transition in the metastatic progression of gastroenteropancreatic neuroendocrine tumours , Stephanie Mok

Protective Effect of Modified Human Fibroblast Growth Factor on Diabetic Nephropathy , Ana M. Pena Diaz

Diabetic Bone Marrow & Stem Cell Dysfunction , Meghan A. Piccinin

Investigation of Pancreatic β-Cell Insulin Receptor Regulation of β-Cell Growth, Function, and Survival Via a Temporal Conditional Knockout , Liangyi Zhou

Theses/Dissertations from 2014 2014

The Role Of The RNA-Binding Protein Rho Guanine Nucleotide Exchange Factor In The Cellular Stress Response , Kevin WH Cheung

Exposure to Environmental Contaminants and Stress as Determinants of Health in Three Communities: Walpole Island and Attawapiskat First Nations and Naivasha, Kenya , Deirdre Phaedra Henley

miRNA Regulation of Programmed Cell Death-1 in T Cells: Potential Prognostic and Therapeutic Markers in Melanoma , Nathan J. Johnston

Cell Death Regulates Injury and Inflammation During Renal Allograft Transplantation , Arthur Lau

Role of SIRT1 in Vascular Complications of Diabetes , Rokhsana Mortuza

RIPK3 Regulates Microvascular Endothelial Cell Necroptosis and Cardiac Allograft Rejection , Alexander William Pavlosky

The Role of Integrins in Support of Pancreatic Function, Survival and Maturation , Matthew Riopel

Polycomb Repressive Complex 2 Regulates miR-200b in Retinal Endothelial Cells: Possible Implications in Diabetic Retinopathy , Michael A. Ruiz

Association of Head and Cervical Injuries in Pediatric Occupants Involved in Motor Vehicle Collisions , Shayan Shekari

Development of Non-Covalent Functionalization of Carbon Nanotubes for siRNA Delivery , King Sun Siu

The Expression and Potential Significance of Human Kallikreins 6, 7, 8, 10, 13, and 14 in the Epithelium of Selected Odontogenic Cysts and Tumors of Variably Aggressive Biological Behaviour , Rebecca Woodford

Theses/Dissertations from 2013 2013

Targeted siRNA Delivery Methods for RNAi-Based Therapies , Di Chen

Elucidating the Role of Menin During Islet Cell Development in the Human Fetal Pancreas , Jessica L. Dubrick

Vascular Stem Cells in Diabetic Complications , Emily C. Keats

Theses/Dissertations from 2012 2012

Immunohistochemical Studies of Expression and Correlation of Osteopontin, CD44, and Integrin αVβ3 in Selected Benign and Malignant Salivary Gland Tumours , Tommy Fok

The role of non-canonical Wnt/planar cell polarity signalling in breast cancer progression , Connor D. MacMillan

Elucidating the Function of Transplanted Islets of Langerhans and Predicting Their Ability to Reverse Diabetes , Andrew R. Pepper

Role of ERK5 in Diabetic Vascular Complications , Yuexiu Wu

Regulation of NK cell-mediated tubular epithelial cell death and kidney ischemia-reperfusion injury by the NKR-P1B receptor and Clr-b , James Yip

Theses/Dissertations from 2011 2011

A Model System for Rapid Identification and Functional Testing of Genes Involved in Early Breast Cancer Progression , Lesley H. Souter

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Edinburgh Medical School is one of two schools at the College of Medicine and Veterinary Medicine at the University of Edinburgh. The Edinburgh Medical School integrates research and teaching across our three Deaneries: Biomedical Sciences, Clinical Sciences and Molecular,Genetic and Population Health Sciences.

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Investigating colonic macrophage heterogeneity in steady-state, inflammation, and resolution , social behaviour in two rat models of syngap1 haploinsufficiency , multimodal decoding of the human and mouse mesenchymal lineage in biliary fibrosis , establishing the mechanistic basis of action for novel siderophore-based antibiotics in gram-negative bacteria , planar cell polarity pathway as a master regulator of biliary morphogenesis , anatomical, biomechanical and histological evaluation of the glenoid labrum , circuitry and function of layer 1 interneurons in the medial entorhinal cortex , exploiting large-scale exome sequence data to study the genotype-phenotype relationship , characterising disease heterogeneity in crohn's disease and ulcerative colitis: leveraging longitudinal biomarker profiles , influence of glucocorticoid bioavailability on atherogenesis , manganese-enhanced magnetic resonance imaging in cardiometabolic disorders , visual experience dependent control of nmdar subunit composition and neuronal gene expression: a critical role for the glun2a c-terminal domain , using data to understand outcomes for cancer surgery in low- and middle-income countries , modulation of tissue glucocorticoid exposure by cleavage of corticosteroid binding globulin in humans , investigating the role of macrophage-epithelial cell interaction in salivary gland regeneration , determining the endometrial phenotype of women with abnormal uterine bleeding , investigating the role of microglial senescence in central nervous system injury and regeneration , characterisation of the pro-regenerative extracellular matrix in the zebrafish spinal cord , different mutations in the beta-tubulin tubb4b result in a novel spectrum of dominant-negative ciliopathies , investigating the modulators of positional identity in human neuromesodermal progenitor differentiation in vitro .

Assessing DxGPT: Diagnosing Rare Diseases with Various Large Language Models

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Diagnosing rare diseases is a significant challenge in healthcare, with patients often experiencing long delays and misdiagnoses. The large number of rare diseases and the difficulty for doctors to be familiar with all of them contribute to this problem. Artificial intelligence, particularly large language models (LLMs), has shown promise in improving the diagnostic process by leveraging their extensive knowledge to help doctors navigate the complexities of diagnosing rare diseases.

Foundation 29 presents a comprehensive evaluation of DxGPT, a web-based platform designed to assist healthcare professionals in the diagnostic process for rare diseases. The platform currently utilizes GPT-4, but this study also compares its performance with other large language models, including Claude 3, Gemini 1.5 Pro, Llama, Mistral, Mixtral, and Cohere Command R+. It is crucial to emphasize that DxGPT is not a medical device but rather a decision support tool that aims to aid in clinical reasoning.

This study extends beyond initial synthetic patient cases, incorporating real-world data from the RAMEDIS and Peking Union Medical College Hospital (PUMCH) datasets. The analysis followed two main metrics: Strict Accuracy (P1), how often the first diagnostic suggestion agreed with the real diagnosis, and Top-5 Accuracy (P1 + P5), how often the right diagnosis was in the top five suggestions. The results show a complex picture of diagnostic accuracy, with performance varying significantly across models and datasets:

On the synthetic dataset, closed models like GPT-4, Claude, and Gemini exhibited relatively high accuracy. Open models like Llama 3 and Mixtral performed reasonably well, though lagging behind.

On the RAMEDIS rare disease cases, Claude 3 Opus model demonstrated 55% Strict Accuracy and 70% Top-5 Accuracy, outperforming other closed models. Open models like Llama 3 and Mixtral showed moderate accuracy.

The PUMCH dataset proved challenging for all models, with the highest Strict Accuracy at 59.46% (GPT-4 Turbo 1106) and Top-5 Accuracy at 64.86%.

These findings demonstrate the potential of DxGPT and LLMs in improving diagnostic methods for rare diseases. However, they also emphasize the need for further validation, particularly in real-world clinical settings, and comparison with human expert diagnoses. Successful integration of AI into medical diagnostics will require collaboration between researchers, clinicians, and regulatory bodies to ensure safety, efficacy, and ethical deployment.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

Foundation 29 received a grant from Takeda to develop pilot #1 for Global Rare Disease Commission https://www.globalrarediseasecommission.com/Report/ . Pilot #1 is about exploring how to use artificial intelligence for RD diagnosis. Produced work is publically available at www.dx29.ai . Foundation 29 received a grant from GW Pharma to develop www.dx29.ai . This an open source tool and free of charge tool for physicians to accelerate time to diagnosis for patients with rare diseses. Produced work is publically available at www.dx29.ai . Foundation 29 received a grant from UCB Pharma to develop https://dxgpt.app/ . This an open source tool based on GPT-4 Azure OpenAI model and is free of charge tool for physicians and patients to accelerate time to diagnosis for patients with rare diseses. Produced work is publically available at https://dxgpt.app/ and https://github.com/foundation29org/dxgpt_testing . Foundation 29 received a grant from Italfarmaco to develop https://dxgpt.app/ . This an open source tool based on GPT-4 Azure OpenAI model and is free of charge tool for physicians and patients to accelerate time to diagnosis for patients with rare diseses. Produced work is publically available at https://dxgpt.app/ and https://github.com/foundation29org/dxgpt_testing . These grants are not related to any of these pharma's products. This study was funded by all these 4 grants as part of DxGPT development.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

https://huggingface.co/datasets/chenxz/RareBench

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

juanjodoolmo{at}foundation29.org

Data Availability

All data produced are available online at: https://huggingface.co/datasets/chenxz/RareBench and https://github.com/foundation29org/dxgpt_testing

https://github.com/foundation29org/dxgpt_testing

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Ivan Specht decided to employ his love of math during pandemic, which led to contact-tracing app, papers, future path

Part of the commencement 2024 series.

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Ivan Specht started at Harvard on track to study pure mathematics. But when COVID-19 sent everyone home, he began wishing the math he was doing had more relevance to what was happening in the world.

Specht, a New York City native, expanded his coursework, arming himself with statistical modeling classes, and began to “fiddle around” with simulating ways diseases spread through populations. He got hooked. During the pandemic, he became one of only two undergraduates to serve on Harvard’s testing and tracing committee, eventually developing a prototype contact-tracing app called CrimsonShield.

Specht took his curiosity for understanding disease propagation to the lab of computational geneticist Pardis Sabeti , professor in Organismic and Evolutionary Biology at Harvard and member of the Broad Institute, known for her work sequencing the Ebola virus in 2014 . Specht, now a senior, has since co-authored several studies around new statistical methods for analyzing the spread of infectious diseases, with plans to continue that work in graduate school.

“Ivan is absolutely brilliant and a joy to work with, and his research accomplishments already as an undergraduate are simply astounding,” Sabeti said. “He is operating at the level of a seasoned postdoc.”

His senior thesis, “Reconstructing Viral Epidemics: A Random Tree Approach,” described a statistical model aimed at tackling one of the most intractable problems that plague infectious disease researchers: determining who transmitted a given pathogen to whom during a viral outbreak. Specht was co-advised by computer science Professor Michael Mitzenmacher, who guided the statistical and computational sections of his thesis, particularly in deriving genomic frequencies within a host using probabilistic methods.

Specht said the pandemic made clear that testing technology could provide valuable information about who got sick, and even what genetic variant of a pathogen made them sick. But mapping paths of transmission was much more challenging because that process was completely invisible. Such information, however, could provide crucial new details into how and where transmission occurred and be used to test things such as vaccine efficacy or the effects of closing schools. 

Specht’s work exploited the fact that viruses leave clues about their transmission path in their phylogenetic trees, or lines of evolutionary descent from a common ancestor. “It turns out that genome sequences of viruses provide key insight into that underlying network,” said the joint mathematics and statistics concentrator.

Uncovering this transmission network goes to the heart of how single-stranded RNA pathogens survive: Once they infect their host, they mutate, producing variants that are marked by slightly different genetic barcodes. Specht’s statistical model determines how the virus spreads by tracking the frequencies of different viral variants observed within a host.  

As the centerpiece of his thesis, he reconstructed a dataset of about 45,000 SARS-CoV-2 genomes across Massachusetts, providing insights into how outbreaks unfolded across the state.

Specht will take his passion for epidemiological modeling to graduate school at Stanford University, with an eye toward helping both researchers and communities understand and respond to public health crises.

A graphic designer with experience in scientific data visualization, Specht is focused not only on understanding outbreaks, but also creating clear illustrations of them. For example, his thesis contains a creative visual representation of those 45,000 Massachusetts genomes, with colored dots representing cases, positioned nearby other “dots” they are likely to have infected.

Specht’s interest in graphics began in middle school when, as an enthusiast of trains and mass transit, he started designing imagined subway maps for cities that lack actual subways, like Austin, Texas . At Harvard, he designed an interactive “subway map” depicting a viral outbreak.

As a member of the Sabeti lab, Specht taught an infectious disease modeling course to master’s and Ph.D. students at University of Sierra Leone last summer. His outbreak analysis tool is also now being used in an ongoing study of Lassa fever in that region. And he co-authored two chapters of a textbook on outbreak science in collaboration with the Moore Foundation.

Over the past three years, Specht has been lead author of a paper in Scientific Reports and another in Cell Patterns , and co-author on two others, including a cover story in Cell . His first lead-author paper, “The case for altruism in institutional diagnostic testing,” showed that organizations like Harvard should allocate COVID-19 testing capacity to their surrounding communities, rather than monopolize it for themselves. That work was featured in The New York Times .

During his time at Harvard, Specht lived in Quincy House and was design editor of the Harvard Advocate, the University’s undergraduate literary magazine. In his free time he also composes music, and he still considers himself a mass transit enthusiast.

In the acknowledgements section of his thesis, he credited Sabeti with opening his eyes to the “many fascinating problems at the intersection of math, statistics, and computational biology.”

“I could fill this entire thesis with reasons I am grateful for Professor Sabeti, but I think they can be summarized by the sense of wonder and inspiration I feel every time I set foot in her lab.”

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