Immunohistochemistry for Diagnosing Melanoma in Older Adults.

Importance: Pathologic assessment to diagnose skin biopsies, especially for cutaneous melanoma, can be challenging, and immunohistochemistry (IHC) staining has the potential to aid decision-making. Currently, the temporal trends regarding the use of IHC for the examination of skin biopsies on a national level have not been described. Objective: To illustrate trends in the use of IHC for the examination of skin biopsies in melanoma diagnoses. Design, Setting, and Participants: A retrospective cross-sectional study was conducted to examine incident cases of melanoma diagnosed between January 2000 and December 2017. The analysis used the SEER-Medicare linked database, incorporating data from 17 population-based registries. The study focused on incident cases of in situ or malignant melanoma of the skin diagnosed in patients 65 years or older. Data were analyzed between August 2022 and November 2023. Main Outcomes and Measures: The main outcomes encompassed the identification of claims for IHC within the month of melanoma diagnoses and extending up to 14 days into the month following diagnosis. The SEER data on patients with melanoma comprised demographic, tumor, and area-level characteristics. Results: The final sample comprised 132 547 melanoma tumors in 116 117 distinct patients. Of the 132 547 melanoma diagnoses meeting inclusion criteria from 2000 to 2017, 43 396 cases had accompanying IHC claims (33%). Among these cases, 28 298 (65%) were diagnosed in male patients, 19 019 (44%) were diagnosed in patients aged 65 years to 74 years, 16 444 (38%) in patients aged 75 years to 84 years, and 7933 (18%) in patients aged 85 years and older. In 2000, 11% of melanoma cases had claims for IHC at or near the time of diagnosis. This proportion increased yearly, with 51% of melanoma cases having associated IHC claims in 2017. Increasing IHC use is observed for all stages of melanoma, including in situ melanoma. Claims for IHC in melanomas increased in all 17 SEER registries but at different rates. In 2017, the use of IHC for melanoma diagnosis ranged from 39% to 68% across registries. Conclusions and Relevance: Considering the dramatically rising and variable use of IHC in diagnosing melanoma by pathologists demonstrated in this retrospective cross-sectional study, further investigation is warranted to understand the clinical utility and discern when IHC most improves diagnostic accuracy or helps patients.

Racial and Ethnic Disparities in Receipt of Pediatric Mental Health Care.

BACKGROUND: Studies suggest increasing mental health care needs among children but limited capacity to meet those needs, potentially leaving some needs unmet. There are no recent national studies examining the receipt of mental health treatment among children. We sought to identify the correlates of treatment receipt in a nationally representative sample of children in the United States. METHODS: We conducted a cross-sectional analysis of the 2019 National Health Interview Survey. Parents reported on their child's sociodemographic characteristics, general health care engagement, mental health using the Strengths and Difficulties Questionnaire, and whether their child received therapy or medication in the prior year. Weighted logistic regressions tested associations among child characteristics and receipt of mental health treatment while controlling for parental report of child mental health symptoms. RESULTS: Among 7168 children surveyed, 1044 (15%) received mental health treatment, equating to over 7 million US children. Hispanic children (adjusted odds ratio [AOR]: 0.46 [95% confidence interval (CI): 0.34-0.62]) and non-Hispanic Black children (AOR: 0.35 [95% CI: 0.23-0.54]) had lower odds of receiving treatment compared to non-Hispanic White children, controlling for mental health symptoms. Children with a well-child visit in the last year (AOR: 2.05 [95% CI: 1.20-3.52]) and whose usual place of care was a doctor's office (AOR 2.10 [95% CI: 1.33-3.34]) had higher odds of treatment receipt. CONCLUSIONS: Racially and ethnically minoritized children and those without primary care access have disproportionately low levels of receipt of mental health treatment. Interventions to meet the needs of these groups should be prioritized to reduce mental health disparities.

Machine learning classification of diagnostic accuracy in pathologists interpreting breast biopsies.

OBJECTIVE: This study explores the feasibility of using machine learning to predict accurate versus inaccurate diagnoses made by pathologists based on their spatiotemporal viewing behavior when evaluating digital breast biopsy images. MATERIALS AND METHODS: The study gathered data from 140 pathologists of varying experience levels who each reviewed a set of 14 digital whole slide images of breast biopsy tissue. Pathologists' viewing behavior, including zooming and panning actions, was recorded during image evaluation. A total of 30 features were extracted from the viewing behavior data, and 4 machine learning algorithms were used to build classifiers for predicting diagnostic accuracy. RESULTS: The Random Forest classifier demonstrated the best overall performance, achieving a test accuracy of 0.81 and area under the receiver-operator characteristic curve of 0.86. Features related to attention distribution and focus on critical regions of interest were found to be important predictors of diagnostic accuracy. Further including case-level and pathologist-level information incrementally improved classifier performance. DISCUSSION: Results suggest that pathologists' viewing behavior during digital image evaluation can be leveraged to predict diagnostic accuracy, affording automated feedback and decision support systems based on viewing behavior to aid in training and, ultimately, clinical practice. They also carry implications for basic research examining the interplay between perception, thought, and action in diagnostic decision-making. CONCLUSION: The classifiers developed herein have potential applications in training and clinical settings to provide timely feedback and support to pathologists during diagnostic decision-making. Further research could explore the generalizability of these findings to other medical domains and varied levels of expertise.

Artificial Intelligence-Driven Mammography-Based Future Breast Cancer Risk Prediction: A Systematic Review.

PURPOSE: To summarize the literature regarding the performance of mammography-image based artificial intelligence (AI) algorithms, with and without additional clinical data, for future breast cancer risk prediction. MATERIALS AND METHODS: A systematic literature review was performed using six databases (medRixiv, bioRxiv, Embase, Engineer Village, IEEE Xplore, and PubMed) from 2012 through September 30, 2022. Studies were included if they used real-world screening mammography examinations to validate AI algorithms for future risk prediction based on images alone or in combination with clinical risk factors. The quality of studies was assessed, and predictive accuracy was recorded as the area under the receiver operating characteristic curve (AUC). RESULTS: Sixteen studies met inclusion and exclusion criteria, of which 14 studies provided AUC values. The median AUC performance of AI image-only models was 0.72 (range 0.62-0.90) compared with 0.61 for breast density or clinical risk factor-based tools (range 0.54-0.69). Of the seven studies that compared AI image-only performance directly to combined image + clinical risk factor performance, six demonstrated no significant improvement, and one study demonstrated increased improvement. CONCLUSIONS: Early efforts for predicting future breast cancer risk based on mammography images alone demonstrate comparable or better accuracy to traditional risk tools with little or no improvement when adding clinical risk factor data. Transitioning from clinical risk factor-based to AI image-based risk models may lead to more accurate, personalized risk-based screening approaches.

Pathologist Characteristics Associated With Rendering Higher-Grade Diagnoses for Melanocytic Lesions.

Importance: The incidence of melanoma diagnoses has been increasing in recent decades, and controlled studies have indicated high histopathologic discordance across the intermediate range of melanocytic lesions. The respective causes for these phenomena remain incompletely understood. Objective: To identify pathologist characteristics associated with tendencies to diagnose melanocytic lesions as higher grade vs lower grade or to diagnose invasive melanoma vs any less severe diagnosis. Design, Setting, and Participants: This exploratory study used data from 2 nationwide studies (the Melanoma Pathology [M-Path] study, conducted from July 2013 to May 2016, and the Reducing Errors in Melanocytic Interpretations [REMI] study, conducted from August 2018 to March 2021) in which participating pathologists who interpreted melanocytic lesions in their clinical practices interpreted study cases in glass slide format. Each pathologist was randomly assigned to interpret a set of study cases from a repository of skin biopsy samples of melanocytic lesions; each case was independently interpreted by multiple pathologists. Data were analyzed from July 2022 to February 2023. Main Outcomes and Measures: The association of pathologist characteristics with diagnosis of a study case as higher grade (including severely dysplastic and melanoma in situ) vs lower grade (including mild to moderately dysplastic nevi) and diagnosis of invasive melanoma vs any less severe diagnosis was assessed using logistic regression. Characteristics included demographics (age, gender, and geographic region), years of experience, academic affiliation, caseload of melanocytic lesions in their practice, specialty training, and history of malpractice suits. Results: A total of 338 pathologists were included: 113 general pathologists and 74 dermatopathologists from M-Path and 151 dermatopathologists from REMI. The predominant factor associated with rendering more severe diagnoses was specialist training in dermatopathology (board certification and/or fellowship training). Pathologists with this training were more likely to render higher-grade diagnoses (odds ratio [OR], 2.63; 95% CI, 2.10-3.30; P < .001) and to diagnose invasive melanoma (OR, 1.95; 95% CI, 1.53-2.49; P < .001) than pathologists without this training interpreting the same case. Nonmitogenic pT1a diagnoses (stage pT1a melanomas with no mitotic activity) accounted for the observed difference in diagnosis of invasive melanoma; when these lesions, which carry a low risk of metastasis, were grouped with the less severe diagnoses, there was no observed association (OR, 0.95; 95% CI, 0.74-1.23; P = .71). Among dermatopathologists, those with a higher caseload of melanocytic lesions in their practice were more likely to assign higher-grade diagnoses (OR for trend, 1.27; 95% CI, 1.04-1.56; P = .02). Conclusions and Relevance: The findings suggest that specialty training in dermatopathology is associated with a greater tendency to diagnose atypical melanocytic proliferations as pT1a melanomas. These low-risk melanomas constitute a growing proportion of melanomas diagnosed in the US.

Prevalence of Symptoms ≤12 Months After Acute Illness, by COVID-19 Testing Status Among Adults - United States, December 2020-March 2023.

To further the understanding of post-COVID conditions, and provide a more nuanced description of symptom progression, resolution, emergence, and reemergence after SARS-CoV-2 infection or COVID-like illness, analysts examined data from the Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE), a prospective multicenter cohort study. This report includes analysis of data on self-reported symptoms collected from 1,296 adults with COVID-like illness who were tested for SARS-CoV-2 using a Food and Drug Administration-approved polymerase chain reaction or antigen test at the time of enrollment and reported symptoms at 3-month intervals for 12 months. Prevalence of any symptom decreased substantially between baseline and the 3-month follow-up, from 98.4% to 48.2% for persons who received a positive SARS-CoV-2 test results (COVID test-positive participants) and from 88.2% to 36.6% for persons who received negative SARS-CoV-2 test results (COVID test-negative participants). Persistent symptoms decreased through 12 months; no difference between the groups was observed at 12 months (prevalence among COVID test-positive and COVID test-negative participants = 18.3% and 16.1%, respectively; p>0.05). Both groups reported symptoms that emerged or reemerged at 6, 9, and 12 months. Thus, these symptoms are not unique to COVID-19 or to post-COVID conditions. Awareness that symptoms might persist for up to 12 months, and that many symptoms might emerge or reemerge in the year after COVID-like illness, can assist health care providers in understanding the clinical signs and symptoms associated with post-COVID-like conditions.

Association Between SARS-CoV-2 Variants and Frequency of Acute Symptoms: Analysis of a Multi-institutional Prospective Cohort Study-December 20, 2020-June 20, 2022.

Background: While prior work examining severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern focused on hospitalization and death, less is known about differences in clinical presentation. We compared the prevalence of acute symptoms across pre-Delta, Delta, and Omicron. Methods: We conducted an analysis of the Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE), a cohort study enrolling symptomatic SARS-CoV-2-positive participants. We determined the association between the pre-Delta, Delta, and Omicron time periods and the prevalence of 21 coronavirus disease 2019 (COVID-19) acute symptoms. Results: We enrolled 4113 participants from December 2020 to June 2022. Pre-Delta vs Delta vs Omicron participants had increasing sore throat (40.9%, 54.6%, 70.6%; P < .001), cough (50.9%, 63.3%, 66.7%; P < .001), and runny noses (48.9%, 71.3%, 72.9%; P < .001). We observed reductions during Omicron in chest pain (31.1%, 24.2%, 20.9%; P < .001), shortness of breath (42.7%, 29.5%, 27.5%; P < .001), loss of taste (47.1%, 61.8%, 19.2%; P < .001), and loss of smell (47.5%, 55.6%, 20.0%; P < .001). After adjustment, those infected during Omicron had significantly higher odds of sore throat vs pre-Delta (odds ratio [OR], 2.76; 95% CI, 2.26-3.35) and Delta (OR, 1.96; 95% CI, 1.69-2.28). Conclusions: Participants infected during Omicron were more likely to report symptoms of common respiratory viruses, such as sore throat, and less likely to report loss of smell and taste. Trial registration: NCT04610515.

Long COVID Clinical Phenotypes up to 6 Months After Infection Identified by Latent Class Analysis of Self-Reported Symptoms.

Background: The prevalence, incidence, and interrelationships of persistent symptoms after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection vary. There are limited data on specific phenotypes of persistent symptoms. Using latent class analysis (LCA) modeling, we sought to identify whether specific phenotypes of COVID-19 were present 3 months and 6 months post-infection. Methods: This was a multicenter study of symptomatic adults tested for SARS-CoV-2 with prospectively collected data on general symptoms and fatigue-related symptoms up to 6 months postdiagnosis. Using LCA, we identified symptomatically homogenous groups among COVID-positive and COVID-negative participants at each time period for both general and fatigue-related symptoms. Results: Among 5963 baseline participants (4504 COVID-positive and 1459 COVID-negative), 4056 had 3-month and 2856 had 6-month data at the time of analysis. We identified 4 distinct phenotypes of post-COVID conditions (PCCs) at 3 and 6 months for both general and fatigue-related symptoms; minimal-symptom groups represented 70% of participants at 3 and 6 months. When compared with the COVID-negative cohort, COVID-positive participants had higher occurrence of loss of taste/smell and cognition problems. There was substantial class-switching over time; those in 1 symptom class at 3 months were equally likely to remain or enter a new phenotype at 6 months. Conclusions: We identified distinct classes of PCC phenotypes for general and fatigue-related symptoms. Most participants had minimal or no symptoms at 3 and 6 months of follow-up. Significant proportions of participants changed symptom groups over time, suggesting that symptoms present during the acute illness may differ from prolonged symptoms and that PCCs may have a more dynamic nature than previously recognized. Clinical Trials Registration. NCT04610515.

The Relationship Between Homeownership and Health by Race/Ethnicity Since the Foreclosure Crisis: California Health Interview Survey 2011-2018.

BACKGROUND: US housing policy places a high priority on homeownership, providing large homeowner subsidies that are justified in part by homeownership's purported health benefits. However, studies conducted before, during, and immediately after the 2007-2010 foreclosure crisis found that while homeownership is associated with better health-related outcomes for White households, that association is weaker or non-existent for African-American and Latinx households. It is not known whether those associations persist in the period since the foreclosure crisis changed the US homeownership landscape. OBJECTIVE: To examine the relationship between homeownership and health and whether that relationship differs by race/ethnicity in the period since the foreclosure crisis. DESIGN: We conducted a cross-sectional analysis of 8 waves (2011-2018) of the California Health Interview Survey (n = 143,854, response rate 42.3 to 47.5%). PARTICIPANTS: We included all US citizen respondents ages 18 and older. MAIN MEASURES: The primary predictor variable was housing tenure (homeownership or renting). The primary outcomes were self-rated health, psychological distress, number of health conditions, and delays in receiving necessary medical care and/or medications. KEY RESULTS: Compared to renting, homeownership is associated with lower rates of reporting fair or poor health (OR = 0.86, P < 0.001), fewer health conditions (incidence rate ratio = 0.95, P = 0.03), and fewer delays in receiving medical care (OR = 0.81, P < 0.001) and medication (OR = 0.78, P < 0.001) for the overall study population. Overall, race/ethnicity was not a significant moderator of these associations in the post-crisis period. CONCLUSIONS: Homeownership has the potential to provide significant health-related benefits to minoritized communities, but this potential may be threatened by practices of racial exclusion and predatory inclusion. Further study is needed to elucidate health-promoting mechanisms within homeownership as well as potential harms of specific homeownership-promoting policies to develop healthier, more equitable housing policy.

Implementing the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis: Long-term effect of a simple educational intervention.

Background: A standardized pathology management tool for melanocytic skin lesions may improve patient care by simplifying interpretation and categorization of the diverse terminology currently extant. Objective: To assess an online educational intervention that teaches dermatopathologists to use the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MPATH-Dx), a schema collapsing multiple diagnostic terms into 5 classes ranging from benign to invasive melanoma. Methods: Practicing dermatopathologists (N = 149) from 40 US states participated in a 2-year educational intervention study (71% response rate). The intervention involved a brief tutorial followed by practice on 28 melanocytic lesions, with the goal of teaching pathologists how to correctly use the MPATH-Dx schema; competence using the MPATH-Dx tool 12-24 months postintervention was assessed. Participants' self-reported confidence using the MPATH-Dx tool was assessed preintervention and postintervention. Results: At preintervention, confidence using the MPATH-Dx tool was already high, despite 68% lacking prior familiarity with it, and confidence increased postintervention (P = .0003). During the intervention, participants used the MPATH-Dx tool correctly for 90% of their interpretations; postintervention, participants used the MPATH-Dx tool correctly for 88% of their interpretations. Limitations: Future research should examine implementing a standardized pathology assessment schema in actual clinical practice. Conclusion: Dermatopathologists can be taught to confidently and competently use the MPATH-Dx schema with a simple educational tutorial followed by practice.

Pathologist pupil dilation reflects experience level and difficulty in diagnosing medical images.

Purpose: Digital whole slide imaging allows pathologists to view slides on a computer screen instead of under a microscope. Digital viewing allows for real-time monitoring of pathologists' search behavior and neurophysiological responses during the diagnostic process. One particular neurophysiological measure, pupil diameter, could provide a basis for evaluating clinical competence during training or developing tools that support the diagnostic process. Prior research shows that pupil diameter is sensitive to cognitive load and arousal, and it switches between exploration and exploitation of a visual image. Different categories of lesions in pathology pose different levels of challenge, as indicated by diagnostic disagreement among pathologists. If pupil diameter is sensitive to the perceived difficulty in diagnosing biopsies, eye-tracking could potentially be used to identify biopsies that may benefit from a second opinion. Approach: We measured case onset baseline-corrected (phasic) and uncorrected (tonic) pupil diameter in 90 pathologists who each viewed and diagnosed 14 digital breast biopsy cases that cover the diagnostic spectrum from benign to invasive breast cancer. Pupil data were extracted from the beginning of viewing and interpreting of each individual case. After removing 122 trials ( < 10 % ) with poor eye-tracking quality, 1138 trials remained. We used multiple linear regression with robust standard error estimates to account for dependent observations within pathologists. Results: We found a positive association between the magnitude of phasic dilation and subject-centered difficulty ratings and between the magnitude of tonic dilation and untransformed difficulty ratings. When controlling for case diagnostic category, only the tonic-difficulty relationship persisted. Conclusions: Results suggest that tonic pupil dilation may indicate overall arousal differences between pathologists as they interpret biopsy cases and could signal a need for additional training, experience, or automated decision aids. Phasic dilation is sensitive to characteristics of biopsies that tend to elicit higher difficulty ratings and could indicate a need for a second opinion.

Association of Cost-Driven Residential Moves With Health-Related Outcomes Among California Renters.

Importance: Unaffordable housing is associated with adverse health-related outcomes, but little is known about the associations between moving due to unaffordable housing and health-related outcomes. Objective: To characterize the association of recent cost-driven residential moves with health-related outcomes. Design, Setting, and Participants: This cross-sectional study involved a weighted multivariable regression analysis of California Health Interview Survey data from January 1, 2011, to December 31, 2017. A population-based sample of 52 646 adult renters and other nonhomeowners in California were included. Data were analyzed from March 2, 2021, to January 6, 2023. Exposure: Cost-driven moves in the past 3 years relative to no move and to non-cost-driven moves. Main Outcomes and Measures: Five outcomes were assessed: psychological distress (low, moderate, or severe, as categorized by the 6-item Kessler Psychological Distress Scale), emergency department [ED] visits in the past year (any vs none), preventive care visits in the past year (any vs none), general health (poor or fair vs good, very good, or excellent), and walking for leisure in the past 7 days (in minutes). Results: Among 52 646 adult renters and other nonhomeowners, 50.3% were female, 85.2% were younger than 60 years, 45.3% were Hispanic, and 55.1% had income lower than 200% of the federal poverty level. Overall, 8.9% of renters reported making a recent cost-driven move, with higher prevalence among Hispanic (9.9%) and non-Hispanic Black (11.3%) renters compared with non-Hispanic White renters (7.2%). In multivariable models, compared with not moving, cost-driven moving was associated with a 4.2 (95% CI, 2.6-5.7) percentage point higher probability of experiencing moderate psychological distress; a 3.2 (95% CI, 1.9-4.5) percentage point higher probability of experiencing severe psychological distress; a 2.5 (95% CI, 0-4.9) percentage point higher probability of ED visits; a 5.1 (95% CI, 1.6-8.6) percentage point lower probability of having preventive care visits; a 3.7 (95% CI, 1.2-6.2) percentage point lower probability of having good, very good, or excellent general health; and 16.8 (95% CI, 6.9-26.6) fewer minutes of walking for leisure. General health, psychological distress, and walking for leisure were also worse with cost-driven moves relative to non-cost-driven moves, with a 3.2 (95% CI, 1.7-4.7) percentage point higher probability of experiencing moderate psychological distress; a 2.5 (95% CI, 1.2-3.9) percentage point higher probability of experiencing severe psychological distress; a 4.6 (95% CI, 2.1-7.2) percentage point lower probability of having good, very good, or excellent general health; and 13.0 (95% CI, 4.0-21.9) fewer minutes of walking for leisure. However, the incidence of preventive care and ED visits did not differ between those who made cost-driven vs non-cost-driven moves. Conclusions and Relevance: In this study, cost-driven moves were associated with adverse health-related outcomes relative to not moving and to non-cost-driven moves. These findings suggest that policies to improve housing affordability, prevent displacement, and increase access to health care for groups vulnerable to cost-driven moves may have the potential to improve population health equity, especially during the current national housing affordability crisis.

From Image to Diagnosis: Characterizing Sources of Error in Histopathologic Interpretation.

An accurate histopathologic diagnosis on surgical biopsy material is necessary for the clinical management of patients and has important implications for research, clinical trial design/enrollment, and public health education. This study used a mixed methods approach to isolate sources of diagnostic error while residents and attending pathologists interpreted digitized breast biopsy slides. Ninety participants, including pathology residents and attending physicians at major United States medical centers reviewed a set of 14 digitized whole-slide images of breast biopsies. Each case had a consensus-defined diagnosis and critical region of interest (cROI) representing the most significant pathology on the slide. Participants were asked to view unmarked digitized slides, draw their participant region of interest (pROI), describe its features, and render a diagnosis. Participants' review behavior was tracked using case viewer software and an eye-tracking device. Diagnostic accuracy was calculated in comparison to the consensus diagnosis. We measured the frequency of errors emerging during 4 interpretive phases: (1) detecting the cROI, (2) recognizing its relevance, (3) using the correct terminology to describe findings in the pROI, and (4) making a diagnostic decision. According to eye-tracking data, trainees and attending pathologists were very likely (∼94% of the time) to find the cROI when inspecting a slide. However, trainees were less likely to consider the cROI relevant to their diagnosis. Pathology trainees (41% of cases) were more likely to use incorrect terminology to describe pROI features than attending pathologists (21% of cases). Failure to accurately describe features was the only factor strongly associated with an incorrect diagnosis. Identifying where errors emerge in the interpretive and/or descriptive process and working on building organ-specific feature recognition and verbal fluency in describing those features are critical steps for achieving competency in diagnostic decision making.

Zoom behavior during visual search modulates pupil diameter and reflects adaptive control states.

Adaptive gain theory proposes that the dynamic shifts between exploration and exploitation control states are modulated by the locus coeruleus-norepinephrine system and reflected in tonic and phasic pupil diameter. This study tested predictions of this theory in the context of a societally important visual search task: the review and interpretation of digital whole slide images of breast biopsies by physicians (pathologists). As these medical images are searched, pathologists encounter difficult visual features and intermittently zoom in to examine features of interest. We propose that tonic and phasic pupil diameter changes during image review may correspond to perceived difficulty and dynamic shifts between exploration and exploitation control states. To examine this possibility, we monitored visual search behavior and tonic and phasic pupil diameter while pathologists (N = 89) interpreted 14 digital images of breast biopsy tissue (1,246 total images reviewed). After viewing the images, pathologists provided a diagnosis and rated the level of difficulty of the image. Analyses of tonic pupil diameter examined whether pupil dilation was associated with pathologists' difficulty ratings, diagnostic accuracy, and experience level. To examine phasic pupil diameter, we parsed continuous visual search data into discrete zoom-in and zoom-out events, including shifts from low to high magnification (e.g., 1× to 10×) and the reverse. Analyses examined whether zoom-in and zoom-out events were associated with phasic pupil diameter change. Results demonstrated that tonic pupil diameter was associated with image difficulty ratings and zoom level, and phasic pupil diameter showed constriction upon zoom-in events, and dilation immediately preceding a zoom-out event. Results are interpreted in the context of adaptive gain theory, information gain theory, and the monitoring and assessment of physicians' diagnostic interpretive processes.

Variability Among Breast Cancer Risk Classification Models When Applied at the Level of the Individual Woman.

BACKGROUND: Breast cancer risk models guide screening and chemoprevention decisions, but the extent and effect of variability among models, particularly at the individual level, is uncertain. OBJECTIVE: To quantify the accuracy and disagreement between commonly used risk models in categorizing individual women as average vs. high risk for developing invasive breast cancer. DESIGN: Comparison of three risk prediction models: Breast Cancer Risk Assessment Tool (BCRAT), Breast Cancer Surveillance Consortium (BCSC) model, and International Breast Intervention Study (IBIS) model. SUBJECTS: Women 40 to 74 years of age presenting for screening mammography at a multisite health system between 2011 and 2015, with 5-year follow-up for cancer outcome. MAIN MEASURES: Comparison of model discrimination and calibration at the population level and inter-model agreement for 5-year breast cancer risk at the individual level using two cutoffs (≥ 1.67% and ≥ 3.0%). KEY RESULTS: A total of 31,115 women were included. When using the ≥ 1.67% threshold, more than 21% of women were classified as high risk for developing breast cancer in the next 5 years by one model, but average risk by another model. When using the ≥ 3.0% threshold, more than 5% of women had disagreements in risk severity between models. Almost half of the women (46.6%) were classified as high risk by at least one of the three models (e.g., if all three models were applied) for the threshold of ≥ 1.67%, and 11.1% were classified as high risk for ≥ 3.0%. All three models had similar accuracy at the population level. CONCLUSIONS: Breast cancer risk estimates for individual women vary substantially, depending on which risk assessment model is used. The choice of cutoff used to define high risk can lead to adverse effects for screening, preventive care, and quality of life for misidentified individuals. Clinicians need to be aware of the high false-positive and false-negative rates and variation between models when talking with patients.

Diagnostic error, uncertainty, and overdiagnosis in melanoma.

Diagnostic error can be defined as deviation from a gold standard diagnosis, typically defined in terms of expert opinion, although sometimes in terms of unexpected events that might occur in follow-up (such as progression and death from disease). Although diagnostic error does exist for melanoma, deviations from gold standard diagnosis, certainly among appropriately trained and experienced practitioners, are likely to be the result of uncertainty and lack of specific criteria, and differences of opinion, rather than lack of diagnostic skills. In this review, the concept of diagnostic error will be considered in relation to diagnostic uncertainty, and the concept of overdiagnosis in melanoma will be presented and discussed.

Revision of the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis Classification Schema for Melanocytic Lesions: A Consensus Statement.

Importance: A standardized pathology classification system for melanocytic lesions is needed to aid both pathologists and clinicians in cataloging currently existing diverse terminologies and in the diagnosis and treatment of patients. The Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MPATH-Dx) has been developed for this purpose. Objective: To revise the MPATH-Dx version 1.0 classification tool, using feedback from dermatopathologists participating in the National Institutes of Health-funded Reducing Errors in Melanocytic Interpretations (REMI) Study and from members of the International Melanoma Pathology Study Group (IMPSG). Evidence Review: Practicing dermatopathologists recruited from 40 US states participated in the 2-year REMI study and provided feedback on the MPATH-Dx version 1.0 tool. Independently, member dermatopathologists participating in an IMPSG workshop dedicated to the MPATH-Dx schema provided additional input for refining the MPATH-Dx tool. A reference panel of 3 dermatopathologists, the original authors of the MPATH-Dx version 1.0 tool, integrated all feedback into an updated and refined MPATH-Dx version 2.0. Findings: The new MPATH-Dx version 2.0 schema simplifies the original 5-class hierarchy into 4 classes to improve diagnostic concordance and to provide more explicit guidance in the treatment of patients. This new version also has clearly defined histopathological criteria for classification of classes I and II lesions; has specific provisions for the most frequently encountered low-cumulative sun damage pathway of melanoma progression, as well as other, less common World Health Organization pathways to melanoma; provides guidance for classifying intermediate class II tumors vs melanoma; and recognizes a subset of pT1a melanomas with very low risk and possible eventual reclassification as neoplasms lacking criteria for melanoma. Conclusions and Relevance: The implementation of the newly revised MPATH-Dx version 2.0 schema into clinical practice is anticipated to provide a robust tool and adjunct for standardized diagnostic reporting of melanocytic lesions and management of patients to the benefit of both health care practitioners and patients.

Severe Fatigue and Persistent Symptoms at 3 Months Following Severe Acute Respiratory Syndrome Coronavirus 2 Infections During the Pre-Delta, Delta, and Omicron Time Periods: A Multicenter Prospective Cohort Study.

BACKGROUND: Most research on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants focuses on initial symptomatology with limited longer-term data. We characterized prevalences of prolonged symptoms 3 months post-SARS-CoV-2 infection across 3 variant time-periods (pre-Delta, Delta, and Omicron). METHODS: This multicenter prospective cohort study of adults with acute illness tested for SARS-CoV-2 compared fatigue severity, fatigue symptoms, organ system-based symptoms, and ≥3 symptoms across variants among participants with a positive ("COVID-positive") or negative SARS-CoV-2 test ("COVID-negative") at 3 months after SARS-CoV-2 testing. Variant periods were defined by dates with ≥50% dominant strain. We performed multivariable logistic regression modeling to estimate independent effects of variants adjusting for sociodemographics, baseline health, and vaccine status. RESULTS: The study included 2402 COVID-positive and 821 COVID-negative participants. Among COVID-positives, 463 (19.3%) were pre-Delta, 1198 (49.9%) Delta, and 741 (30.8%) Omicron. The pre-Delta COVID-positive cohort exhibited more prolonged severe fatigue (16.7% vs 11.5% vs 12.3%; P = .017) and presence of ≥3 prolonged symptoms (28.4% vs 21.7% vs 16.0%; P < .001) compared with the Delta and Omicron cohorts. No differences were seen in the COVID-negatives across time-periods. In multivariable models adjusted for vaccination, severe fatigue and odds of having ≥3 symptoms were no longer significant across variants. CONCLUSIONS: Prolonged symptoms following SARS-CoV-2 infection were more common among participants infected during pre-Delta than with Delta and Omicron; however, these differences were no longer significant after adjusting for vaccination status, suggesting a beneficial effect of vaccination on risk of long-term symptoms. Clinical Trials Registration. NCT04610515.