Dr. Ko joined Stanford Medicine in 2012 and serves as Director and Chief of Medical Dermatology for Stanford Health Care (SHC) while also spearheading the dermatology department's efforts around network development, digital health, quality/safety/performance improvement, and value-based care. He is active in a number of leadership roles within the organization including co-chairing the Clinic Advisory Council, a forum of medical and executive leaders of Stanford Health Care’s Ambulatory clinics, and as a Service Medical Director.
His passion for melanoma, early cancer detection, and improving care delivery drives his efforts and research around leveraging advances in machine learning and artifical intelligence to increase the breadth of populations that can be reached. He developed and runs a digital care delivery program at SHC, providing virtual visits for patients and remote consultations for referring clinicians. He conducts research on and engages in collaborations around interventions that layer advances in machine learning on digital health capabilities to enhance access, quality and value of dermatologic care. He chairs the American Academy of Dermatology's Task Force Committee on Augmented Intelligence.
Dr. Ko has also been driven to find new treatments for alopecia areata, an immune-mediated condition that can progress to total hair loss through various clinical trials and translational research efforts. He sits on the clinical research advisory board of the National Alopecia Areata Foundation and is founder and co-director of the Skin Interventional and Innovation Research Group (SIIRG) which conducts clinical and translational research on skin disease.
He graduated magna cum laude from Harvard University and worked in investment banking; mergers and acquisitions at JP Morgan before going on to earn a combined medical and business degree at Tufts University. During medical school, he was a member of the Alpha Omega Alpha honor society. Dr. Ko then performed his residency at the Harvard Dermatology Residency Training Program where he served as chief resident.
- Skin Cancer
- Alopecia Areata
- Screening for melanoma in high risk patients (family history, red hair, many moles)
- Laser Therapy of Medical Skin Conditions
- Artificial Intelligence and Machine Learning
Clinical Associate Professor, Dermatology
Medical Director and Chief, Medical Dermatology, Stanford Health Care (2012 - Present)
Co-Chair, Clinic Advisory Council, Stanford Health Care (2018 - Present)
Director of Network Development and Digital Health, Stanford Department of Dermatology (2012 - Present)
Physician Leader, Safety, Quality and Performance Improvement, Stanford Department of Dermatology (2017 - Present)
Director of Value Based Care, Stanford Department of Dermatology (2020 - Present)
Medical Director, Service Excellence, Stanford Health Care (2018 - Present)
Member, Ambulatory Value Optimization Committee, Stanford Health Care (2018 - Present)
Member, Access Management Guidance Team, Stanford Health Care (2018 - Present)
Member, Clinic Advisory Council, Stanford Hospital and Clinics (2015 - Present)
Physician Lead and Co-Chair, Clinic Performance Team 4, Stanford Hospital and Clinics (2015 - 2018)
Boards, Advisory Committees, Professional Organizations
Chair, American Academy of Dermatology Task Force on Augmented Intelligence (2019 - Present)
Research Advisory Council, National Alopecia Areata Foundation (2016 - Present)
Board Certification: Dermatology, American Board of Dermatology (2012)
Chief Resident, Harvard Combined Dermatology Residency Training Program (2012)
Residency: Massachusetts General Hospital (2012) MA
BA, Harvard University, Magna Cum Laude (2002)
MD, MBA, Tufts University School of Medicine, Alpha Omega Alpha (2008)
A Study to Evaluate Upadacitinib in Adolescent and Adult Subjects With Moderate to Severe Atopic Dermatitis (Measure Up 2)
The objective of this study is to assess the efficacy and safety of upadacitinib for the treatment of adolescent and adult participants with moderate to severe AD who are candidates for systemic therapy.
A Study to Evaluate Upadacitinib in Combination With Topical Corticosteroids in Adolescent and Adult Participants With Moderate to Severe Atopic Dermatitis
The objective of this study is to assess the efficacy and safety of upadacitinib combined with topical corticosteroids (TCS) for the treatment of adolescent and adult participants with moderate to severe Atopic dermatitis (AD) who are candidates for systemic therapy.
SAR231893-LPS15497- "Dupilumab Effect on Sleep in AD Patients"
Primary Objective: To evaluate the effect of dupilumab on sleep quality in adult patients with moderate to severe atopic dermatitis (AD) Secondary Objectives: To evaluate the effect of dupilumab on objective and subjective quantitative sleep parameters, AD related outcomes, and daytime consequences of sleep deprivation To continue to assess the safety and tolerability throughout the study
A Study of ATI-502 Topical Solution for the Treatment of Atopic Dermatitis
This is an open label, multicenter study designed to evaluate the safety and tolerability of ATI-502 Topical Solution in male and female subjects with moderate or severe atopic dermatitis (AD). Subjects will be required to apply ATI-502 study medication to their identified AD treatment areas. All subjects will be required to complete a safety follow up visit 4 weeks post last study medication application
Stanford is currently not accepting patients for this trial.
A Study of Baricitinib (LY3009104) in Participants With Severe or Very Severe Alopecia Areata
This study is designed to select up to two doses of baricitinib (referred to as low dose and high dose) and assess their efficacy and safety for the treatment of severe or very severe alopecia areata.
Stanford is currently not accepting patients for this trial.
A Study of Lebrikizumab (LY3650150) in Patients With Moderate-to-Severe Atopic Dermatitis
The purpose of this study is to evaluate the safety and efficacy of lebrikizumab compared with placebo in patients with moderate-to-severe atopic dermatitis.
Stanford is currently not accepting patients for this trial.
Effect of Dupilumab (Anti-IL4Rα) on the Host-Microbe Interface in Atopic Dermatitis
The purpose of this study is to understand the effect that T helper 2 (Th2) blockade has on well-described pathophysiological features of Atopic Dermatitis (AD), for example: barrier, epidermal activation, dysbiosis and epidermal lipids.
Stanford is currently not accepting patients for this trial. For more information, please contact Kristoffer Thordarson, 650-441-9974.
Extension Study to Evaluate Safety and Efficacy of CTP-543 in Adults With Alopecia Areata
The overall objectives of the study are to evaluate long-term safety of CTP-543 and to assess long-term effects of CTP-543 on treating hair loss in adult patients with chronic, moderate to severe alopecia areata.
Stanford is currently not accepting patients for this trial.
Study to Evaluate the Safety and Efficacy of CTP-543 in Adult Patients With Moderate to Severe Alopecia Areata
This study will evaluate the safety and efficacy of CTP-543 in adult patients with chronic, moderate to severe alopecia areata.
Stanford is currently not accepting patients for this trial. For more information, please contact Michelle Kim, 650-498-4880.
Tofacitinib for the Treatment of Alopecia Areata and Its Variants
The purpose of this study is to investigate the ability of tofacitinib citrate, a Janus kinase inhibitor, to generate hair regrowth in patients with moderate to severe alopecia areata and its variants.
Stanford is currently not accepting patients for this trial.
Patient Perspectives on the Use of Artificial Intelligence for Skin Cancer Screening: A Qualitative Study.
Importance: The use of artificial intelligence (AI) is expanding throughout the field of medicine. In dermatology, researchers are evaluating the potential for direct-to-patient and clinician decision-support AI tools to classify skin lesions. Although AI is poised to change how patients engage in health care, patient perspectives remain poorly understood.Objective: To explore how patients conceptualize AI and perceive the use of AI for skin cancer screening.Design, Setting, and Participants: A qualitative study using a grounded theory approach to semistructured interview analysis was conducted in general dermatology clinics at the Brigham and Women's Hospital and melanoma clinics at the Dana-Farber Cancer Institute. Forty-eight patients were enrolled. Each interview was independently coded by 2 researchers with interrater reliability measurement; reconciled codes were used to assess code frequency. The study was conducted from May 6 to July 8, 2019.Main Outcomes and Measures: Artificial intelligence concept, perceived benefits and risks of AI, strengths and weaknesses of AI, AI implementation, response to conflict between human and AI clinical decision-making, and recommendation for or against AI.Results: Of 48 patients enrolled, 26 participants (54%) were women; mean (SD) age was 53.3 (21.7) years. Sixteen patients (33%) had a history of melanoma, 16 patients (33%) had a history of nonmelanoma skin cancer only, and 16 patients (33%) had no history of skin cancer. Twenty-four patients were interviewed about a direct-to-patient AI tool and 24 patients were interviewed about a clinician decision-support AI tool. Interrater reliability ratings for the 2 coding teams were kappa=0.94 and kappa=0.89. Patients primarily conceptualized AI in terms of cognition. Increased diagnostic speed (29 participants [60%]) and health care access (29 [60%]) were the most commonly perceived benefits of AI for skin cancer screening; increased patient anxiety was the most commonly perceived risk (19 [40%]). Patients perceived both more accurate diagnosis (33 [69%]) and less accurate diagnosis (41 [85%]) to be the greatest strength and weakness of AI, respectively. The dominant theme that emerged was the importance of symbiosis between humans and AI (45 [94%]). Seeking biopsy was the most common response to conflict between human and AI clinical decision-making (32 [67%]). Overall, 36 patients (75%) would recommend AI to family members and friends.Conclusions and Relevance: In this qualitative study, patients appeared to be receptive to the use of AI for skin cancer screening if implemented in a manner that preserves the integrity of the human physician-patient relationship.
View details for DOI 10.1001/jamadermatol.2019.5014
View details for PubMedID 32159733
Inflammatory alopecia in patients on dupilumab: a retrospective cohort study at an academic institution.
Journal of the European Academy of Dermatology and Venereology : JEADV
Dupilumab targets IL-4Ralpha and is used for moderate-to-severe atopic dermatitis (AD). Prior reports have described new alopecia areata (AA),1 flaring of prior AA,2 as well as improvement or resolution of AA3 in patients treated with dupilumab. We conducted a retrospective cohort study to describe the natural history of prior or new inflammatory alopecia in patients on dupilumab.
View details for DOI 10.1111/jdv.16094
View details for PubMedID 31737955
The Alopecia Areata Investigator's Global Assessment (AA-IGA) scale: A measure for evaluating clinically meaningful success in clinical trials
MOSBY-ELSEVIER. 2019: AB283
View details for Web of Science ID 000482195002305
- Marking the Path Toward Artificial Intelligence-Based Image Classification in Dermatology. JAMA dermatology 2019
- Assessment of the Development of New Regional Dermatoses in Patients Treated for Atopic Dermatitis With Dupilumab JAMA DERMATOLOGY 2019; 155 (7): 850–52
Artificial intelligence and dermatology: opportunities, challenges, and future directions.
Seminars in cutaneous medicine and surgery
2019; 38 (1): E31–37
The application of artificial intelligence (AI) to medicine has considerable potential within dermatology, where the majority of diagnoses are based on visual pattern recognition. Opportunities for AI in dermatology include the potential to automate repetitive tasks; optimize time-consuming tasks; extend limited medical resources; improve interobserver reliability issues; and expand the diagnostic toolbox of dermatologists. To achieve the full potential of AI, however, developers must aim to create algorithms representing diverse patient populations; ensure algorithm output is ultimately interpretable; validate algorithm performance prospectively; preserve human-patient interaction when necessary; and demonstrate validity in the eyes of regulatory bodies.
View details for PubMedID 31051021
- Commentary: Position Statement on Augmented Intelligence (AuI). Journal of the American Academy of Dermatology 2019
Implementation and evaluation of Stanford Health Care store-and-forward teledermatology consultation workflow built within an existing electronic health record system.
Journal of telemedicine and telecare
Introduction Teledermatology services that function separately from patients' primary electronic health record (EHR) can lead to fragmented care, poor provider communication, privacy concerns and billing challenges. This study addresses these challenges by developing PhotoCareMD, a store-and-forward (SAF) teledermatology consultation workflow built entirely within an existing Epic-based EHR. Methods Thirty-six primary care physicians (PCPs) from eight outpatient clinics submitted 215 electronic consults (eConsults) for 211 patients to a Stanford Health Care dermatologist via PhotoCareMD. Comparisons were made with in-person referrals for this same dermatologist prior to initiation of PhotoCareMD. Results Compared to traditional in-person dermatology clinic visits, eConsults decreased the time to diagnosis and treatment from 23 days to 16 hours. The majority (73%) of eConsults were resolved electronically. In-person referrals from PhotoCareMD (27%) had a 50% lower cancellation rate compared with traditional referrals (11% versus 22%). The average in-person visit and documentation was 25 minutes compared with 8 minutes for an eConsult. PhotoCareMD saved 13 additional clinic hours to be made available to the dermatologist over the course of the pilot. At four patients per hour, this opens 52 dermatology clinic slots. Over 96% of patients had a favourable experience and 95% felt this service saved them time. Among PCPs, 100% would recommend PhotoCareMD to their colleagues and 95% said PhotoCareMD was a helpful educational tool. Discussion An internal SAF teledermatology workflow can be effectively implemented to increase access to and quality of dermatologic care. Our workflow can serve as a successful model for other hospitals and specialties.
View details for DOI 10.1177/1357633X18799805
View details for PubMedID 30301409
Challenges and recommendations for epigenomics in precision health
2017; 35 (12): 1128–32
View details for PubMedID 29220033
Dermatologist-level classification of skin cancer with deep neural networks.
2017; 542 (7639): 115-118
Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of skin lesions using images is a challenging task owing to the fine-grained variability in the appearance of skin lesions. Deep convolutional neural networks (CNNs) show potential for general and highly variable tasks across many fine-grained object categories. Here we demonstrate classification of skin lesions using a single CNN, trained end-to-end from images directly, using only pixels and disease labels as inputs. We train a CNN using a dataset of 129,450 clinical images-two orders of magnitude larger than previous datasets-consisting of 2,032 different diseases. We test its performance against 21 board-certified dermatologists on biopsy-proven clinical images with two critical binary classification use cases: keratinocyte carcinomas versus benign seborrheic keratoses; and malignant melanomas versus benign nevi. The first case represents the identification of the most common cancers, the second represents the identification of the deadliest skin cancer. The CNN achieves performance on par with all tested experts across both tasks, demonstrating an artificial intelligence capable of classifying skin cancer with a level of competence comparable to dermatologists. Outfitted with deep neural networks, mobile devices can potentially extend the reach of dermatologists outside of the clinic. It is projected that 6.3 billion smartphone subscriptions will exist by the year 2021 (ref. 13) and can therefore potentially provide low-cost universal access to vital diagnostic care.
View details for DOI 10.1038/nature21056
View details for PubMedID 28117445
Crowdsourcing dermatology: DataDerm, big data analytics, and machine learning technology.
Journal of the American Academy of Dermatology
View details for PubMedID 29042152
Safety and efficacy of the JAK inhibitor tofacitinib citrate in patients with alopecia areata.
2016; 1 (15)
Alopecia areata (AA) is an autoimmune disease characterized by hair loss mediated by CD8(+) T cells. There are no reliably effective therapies for AA. Based on recent developments in the understanding of the pathomechanism of AA, JAK inhibitors appear to be a therapeutic option; however, their efficacy for the treatment of AA has not been systematically examined.This was a 2-center, open-label, single-arm trial using the pan-JAK inhibitor, tofacitinib citrate, for AA with >50% scalp hair loss, alopecia totalis (AT), and alopecia universalis (AU). Tofacitinib (5 mg) was given twice daily for 3 months. Endpoints included regrowth of scalp hair, as assessed by the severity of alopecia tool (SALT), duration of hair growth after completion of therapy, and disease transcriptome.Of 66 subjects treated, 32% experienced 50% or greater improvement in SALT score. AA and ophiasis subtypes were more responsive than AT and AU subtypes. Shorter duration of disease and histological peribulbar inflammation on pretreatment scalp biopsies were associated with improvement in SALT score. Drug cessation resulted in disease relapse in 8.5 weeks. Adverse events were limited to grade I and II infections. An AA responsiveness to JAK/STAT inhibitors score was developed to segregate responders and nonresponders, and the previously developed AA disease activity index score tracked response to treatment.At the dose and duration studied, tofacitinib is a safe and effective treatment for severe AA, though it does not result in a durable response. Transcriptome changes reveal unexpected molecular complexity within the disease.ClinicalTrials.gov NCT02197455 and NCT02312882.This work was supported by the US Department of Veterans Affairs Office of Research and Development, National Institute of Arthritis and Musculoskeletal and Skin Diseases National Institutes of Health grant R01 AR47223 and U01 AR67173, the National Psoriasis Foundation, the Swedish Society of Medicine, the Fernström Foundation, the Locks of Love Foundation, the National Alopecia Areata Foundation, and the Ranjini and Ajay Poddar Resource Fund for Dermatologic Diseases Research.
View details for PubMedID 27699252
Implementation and evaluation of Stanford Health Care direct-care teledermatology program.
SAGE open medicine
2016; 4: 2050312116659089-?
Teledermatology has proven to be an effective means of providing dermatologic care. The existing research has primarily evaluated its usefulness in a consultative model. Few academic centers have evaluated a patient-initiated model, and direct-to-consumer services remain the subject of controversy. Stanford Health Care recently launched a direct-care, patient-initiated teledermatology pilot program. This article evaluates the viability and patient satisfaction with this service.During the pilot period, patients were able to seek remote dermatologic care using an eVisit tool in their MyHealth account. Patients initiated the consultation, answered questions regarding their complaint, and uploaded a picture if relevant. A Stanford dermatologist reviewed each eVisit and responded with an assessment and plan. The dermatologist noted whether they were able to make a diagnosis and their level of confidence in it. After the study, 10 patients participated in a focus group to provide feedback on the service.In all, 38 patients sought care during the pilot period. A dermatologist was able to make a diagnosis in 36 of 38 (95%) cases, with an average confidence level of 7.9 of 10. The average time to consultation was 0.8 days. Patients indicated high levels of satisfaction with the service although they had suggestions for improvement.Patients provided clinically useful images and information in a direct-care teledermatology model. Such services allow dermatology providers to increase access while maintaining high-quality care in an academic medical center. Further research is needed on standalone services that cannot integrate encounters with the patient's existing medical record.
View details for DOI 10.1177/2050312116659089
View details for PubMedID 27493756
View details for PubMedCentralID PMC4959300
A new era: melanoma genetics and therapeutics
JOURNAL OF PATHOLOGY
2011; 223 (2): 241-250
We have recently witnessed an explosion in our understanding of melanoma. Knowledge of the molecular basis of melanoma and the successes of targeted therapies have pushed melanoma care to the precipice of a new era. Identification of significant pathways and oncogenes has translated to the development of targeted therapies, some of which have produced major clinical responses. In this review, we provide an overview of selected key pathways and melanoma oncogenes as well as the targeted agents and therapeutic approaches whose successes suggest the promise of a new era in melanoma and cancer therapy. Despite these advances, the conversion of transient remissions to stable cures remains a vital challenge. Continued progress towards a better understanding about the complexity and redundancy responsible for melanoma progression may provide direction for anti-cancer drug development.
View details for DOI 10.1002/path.2804
View details for Web of Science ID 000285554600013
View details for PubMedID 21125678
Pathways to Melanoma
SEMINARS IN CUTANEOUS MEDICINE AND SURGERY
2010; 29 (4): 210-217
Melanoma is one of the most aggressive and yet poorly understood of human malignancies. Advances in genomics has allowed a more nuanced understanding of the disease, moving beyond the traditional dysplastic nevus-to-melanoma model and identifying multiple divergent oncogenic pathways leading to melanoma. An understanding of the molecular mechanisms driving melanoma has opened the doors for the development of targeted therapeutic approaches. As we enter the era of personalized medicine, it will be critical for clinicians to both appreciate and be able to determine the molecular profile of their patients' melanoma because this profile will guide risk stratification, genetic counseling, and treatment customization. A review of the divergent pathways of melanoma development is presented here, with a particular emphasis on recently identified mutations, and their implications for patient care.
View details for DOI 10.1016/j.sder.2010.10.004
View details for Web of Science ID 000287382200003
View details for PubMedID 21277534
Paying for Enhanced Service Comparing Patients' Experiences in a Concierge and General Medicine Practice
PATIENT-PATIENT CENTERED OUTCOMES RESEARCH
2009; 2 (2): 95-103
Concierge medical practice is a relatively new and somewhat controversial development in primary-care practice. These practices promise patients more personalized care and dedicated service, in exchange for an annual membership fee paid by patients. The experiences of patients using these practices remain largely undocumented.To assess the experiences of patients in a concierge medicine practice compared with those in a general medicine practice.Stratified random samples of patients empanelled to each of the four doctors who practice at both a general medicine and a concierge medicine practice separately situated at an academic medical center were drawn. Patients were eligible for the study if they had a visit with the physician between January and May 2006. The study questionnaire (Consumer Assessment of Healthcare Providers and Systems Clinician and Group Survey, supplemented with items from the Ambulatory Care Experiences Survey) was administered by mail to 100 general medicine patients per physician (n = 400) and all eligible concierge medicine patients (n = 201). Patients who completed the survey and affirmed the study physician as their primary-care physician formed the analytic sample (n = 344) that was used to compare the experiences of concierge medicine and general medicine patients. Models controlled for respondent characteristics and accounted for patient clustering within physicians using physician fixed effects.Patients' experiences with organizational features of care, comprising care co-ordination (p < 0.01), access to care (p < 0.001) and interactions with office staff (p < 0.001), favored concierge medicine over general medicine practice. The quality of physician-patient interactions did not differ significantly between the two groups. However, the patients of the concierge medicine practice were more likely to report that their physician spends sufficient time in clinical encounters than patients of the general medicine practice (p < 0.003).The results suggest patients of the concierge medicine practice experienced and reported enhanced service, greater access to care, and better care co-ordination than those of the general medicine practice. This suggests that further study to understand the etiology of these differences may be beneficial in enhancing patients' experience in traditional primary-care practices.
View details for DOI 10.2165/01312067-200902020-00005
View details for Web of Science ID 000208001400005
View details for PubMedID 22273085
Induction and exacerbation of psoriasis with TNF-blockade therapy: A review and analysis of 127 cases
JOURNAL OF DERMATOLOGICAL TREATMENT
2009; 20 (2): 100-108
There are reports of rare adverse effects of tumor necrosis factor (TNF) inhibitors, including infections, malignancies, and induction of autoimmune conditions. Intriguing, are cases of induction or exacerbation of psoriasis in conjunction with TNF inhibitor therapy, given that they are approved for treatment of the same condition. Objective: Published cases of psoriasis occurring during anti-TNF therapy were analyzed, including overviews of proposed etiologies and treatment recommendations.A literature search using Ovid MEDLINE and PubMed was performed for articles published between January 1990 and September 2007 to collect reported cases of psoriasis in patients receiving therapy with TNF blocking agents.A total of 127 cases were identified: 70 in patients on infliximab (55.1%), 35 with etanercept (27.6%), and 22 with adalimumab (17.3%). Females comprised 58% of cases; mean age of reported patients was 45.8 years, and the time from initiation of treatment to onset of lesions averaged 10.5 months. These patients suffered from a number of primary conditions, with rheumatoid arthritis, ankylosing spondylitis, and Crohn's disease accounting for the vast majority. Palmoplantar pustular psoriasis was observed in 40.5% of the cases, with plaque-type psoriasis in 33.1%, and other types comprising the remainder. Topical corticosteroids were the most commonly employed treatment modality but led to resolution in only 26.8% of cases in which they were employed solely. Switching to a different anti-TNF agent led to resolution in 15.4% of cases. Cessation of anti-TNF therapy with systemic therapy led to resolution in 64.3% of cases.More information and cases are needed. Biopsies of TNF-blockade-induced lesions may reveal what cytokines and cell types drive the development of these lesions. Additionally, there is a need to develop an algorithm to treat this paradoxical side effect of therapy with TNF-blockers.
View details for DOI 10.1080/09546630802441234
View details for Web of Science ID 000264554200008
View details for PubMedID 18923992
Prospective assessment of computer-aided detection in interpretation of screening mammography
AMERICAN JOURNAL OF ROENTGENOLOGY
2006; 187 (6): 1483-1491
The purpose of this study was to prospectively assess the usefulness of computer-aided detection (CAD) in the interpretation of screening mammography and to provide the true sensitivity and specificity of this technique in a clinical setting.Over a 26-month period, 5,016 screening mammograms were interpreted without, and subsequently with, the assistance of the iCAD MammoReader detection system. Data collected for actionable findings included dominant feature (calcification, mass, asymmetry, architectural distortion), detection method (radiologist only, CAD only, or both radiologist and CAD), BI-RADS assessment code, associated histopathology for those undergoing biopsy, and tumor stage for malignant lesions. The study population was cross-checked against an independent reference standard to identify false-negative cases.Of the 5,016 cases, the recall rate increased from 12% to 14% with the addition of CAD. Of the 107 (2%) patients who underwent biopsy, 101 (94%) were prompted by the radiologist and six (6%) were prompted by CAD. Of the 124 biopsies performed on actionable findings in the 107 patients, findings in 79 (64%) were benign and in 45 (36%) were in situ or invasive carcinoma. Three study participants who were not recalled by the radiologist with the assistance of CAD developed cancer within 1 year of the screening mammogram and were considered to be false-negative cases. The radiologist detected 43 (90%) of the 48 total malignancies and 45 (94%) of the 48 malignancies with the assistance of CAD. CAD missed eight cancers that were detected by the radiologist, which presented as architectural distortions (n = 3), irregular masses (n = 4), and a circumscribed mass (n = 1). CAD detected two in situ cancers as a faint cluster of calcifications that had not been perceived by the radiologist and one mass that was dismissed by the radiologist, accounting for at least a 4.7% increase in cancer detection rate. Sensitivity of screening mammography with the use of CAD (94%) represented an absolute and relative 4% increase over the sensitivity of the radiologist alone (90%). Specificity of screening mammography with and without the use of CAD was 99%.Routine use of CAD while interpreting screening mammograms significantly increases recall rates, has no significant effect on positive predictive value for biopsy, and can increase cancer detection rate by at least 4.7% and sensitivity by at least 4%. This study provides "true" values for sensitivity and specificity for use of CAD in interpretation of screening mammography as measured prospectively in the context of a working clinical setting.
View details for DOI 10.2214/AJR.05.1582
View details for Web of Science ID 000242289200017
View details for PubMedID 17114541
- Dupilumab Treatment of Nummular Dermatitis: A Retrospective Cohort Study. Journal of the American Academy of Dermatology 2020
- Dupilumab for occupational irritant hand dermatitis in a nonatopic individual: A case report. JAAD case reports 2020; 6 (4): 296–98
Repeat patch testing in a patient with allergic contact dermatitis improved on dupilumab.
JAAD case reports
2019; 5 (4): 336–38
View details for PubMedID 30989102
- Artificial intelligence and dermatology: opportunities, challenges, and future directions SEMINARS IN CUTANEOUS MEDICINE AND SURGERY 2019; 38 (1): E31–E37
Assessment of the Development of New Regional Dermatoses in Patients Treated for Atopic Dermatitis With Dupilumab.
View details for PubMedID 31042259
Rebound effect associated with JAK inhibitor use in the treatment of alopecia areata.
Journal of the European Academy of Dermatology and Venereology : JEADV
Alopecia areata (AA) is a common autoimmune disease driven by Th1 cytokines characterized by non-scarring hair loss.1,2 Mouse models have demonstrated that IFN-gamma-producing NKG2D+ CD8+ cytotoxic T lymphocytes (CTLs) are essential for disease pathogenesis, along with JAK-STAT dependent cytokines IFN-gamma and IL-15, which induce autoreactive T cell activation.1,3 This article is protected by copyright. All rights reserved.
View details for DOI 10.1111/jdv.15383
View details for PubMedID 30520145
Automated Classification of Skin Lesions: From Pixels to Practice.
The Journal of investigative dermatology
2018; 138 (10): 2108–10
The letters "Interpretation of the Outputs of Deep Learning Model trained with Skin Cancer Dataset" and "Automated Dermatological Diagnosis: Hype or Reality?" highlight the opportunities, hurdles, and possible pitfalls with the development of tools that allow for automated skin lesion classification. The potential clinical impact of these advances relies on their scalability, accuracy, and generalizability across a range of diagnostic scenarios.
View details for PubMedID 30244720
The importance of eyebrows in the treatment of alopecia areata: An online questionnaire
MOSBY-ELSEVIER. 2018: AB288
View details for Web of Science ID 000440565902156
A case and review of congenital leukonychia.
Dermatology online journal
2016; 22 (10)
Leukonychia refers to a white discoloration of the nails. Although several conditions may cause white nails, a rare, isolated, congenital form of the disease is hypothesized to stem from disordered keratinization of the nail plate. Herein, we report a case of a 41-year-old woman with congenital leukonychia and review prior cases.
View details for PubMedID 28329587
- Validation of a Skin-Lesion Image-Matching Algorithm Based on Computer Vision Technology TELEMEDICINE AND E-HEALTH 2016; 22 (1): 45-50
- Randomized Controlled Trial of Cryotherapy With Liquid Nitrogen vs Topical Salicylic Acid vs Wait-and-See for Cutaneous Warts ARCHIVES OF DERMATOLOGY 2012; 148 (7): 840-842
A Randomized, Prospective Trial Evaluating Surgeon Preference in Selection of Absorbable Suture Material
JOURNAL OF DRUGS IN DERMATOLOGY
2012; 11 (2): 196-201
This study is the first double-blinded, randomized comparison of two absorbable sutures. To better understand product characteristics and surgeon preference, we conducted a study of two similar-appearing FDA-approved sutures, glyconate and poliglecaprone 25. Four dermatologic surgeons were enlisted. A total of 48 patients with 53 surgical sites were examined. One half of each surgical wound was closed with one type of suture and the other half with the other type. Each half was evaluated for product characteristics. There was no statistically significant difference in surgeon preference for glyconate versus poliglecaprone 25 (P=0.64). Of the cohort preferring poliglecaprone 25, there was a correlation with speed of closure (P=0.06). Of the surgeons that preferred glyconate, we found significantly better visibility (P=0.03), reduced suture breakage during knot tying (P=0.05), and correlation with better handling properties (P=0.06) associated with that preference. The data from this study will enable products to be designed towards these needs and allow surgeons to select sutures that more precisely fit their particular requirements.
View details for Web of Science ID 000299965700009
View details for PubMedID 22270202
Skin and bone: the pathogenetic relationship between psoriasis and psoriatic arthritis
GIORNALE ITALIANO DI DERMATOLOGIA E VENEREOLOGIA
2010; 145 (3): 393-406
Our current understanding of the relationship between psoriasis and psoriatic arthritis remains incomplete, though the evidence from the clinical setting, response to therapeutics, epidemiology, genetics, imaging, and immunopathologic models suggest that they make likely share a common pathogenesis. Psoriatic disease can no longer be thought of as a condition limited to skin and joints. Rather, it must be considered a multi-faceted disorder in which systemic inflammation plays a central role. There is now convincing evidence that individuals with psoriasis have a higher prevalence of co-morbid disease, particularly cardiovascular risk factors, metabolic disorders, and other immune-mediated inflammatory diseases. The cutaneous manifestations of psoriasis place dermatologists in a crucial and privileged role--one that affords us the potential for early detection of associated co-morbid conditions through screening and perhaps impact disease course and clinical outcomes.
View details for Web of Science ID 000279937700007
View details for PubMedID 20461047