Lipoprotein(a), C-Reactive Protein, and Cardiovascular Risk in Primary and Secondary Prevention Populations.

Importance: Elevated lipoprotein(a) (Lp[a]) is a putative causal risk factor for atherosclerotic cardiovascular disease (ASCVD). There are conflicting data as to whether Lp(a) may increase cardiovascular risk only in the presence of concomitant inflammation. Objective: To investigate whether Lp(a) is associated with cardiovascular risk independent of high-sensitivity C-reactive protein (hs-CRP) in both primary and secondary prevention populations. Design, Setting, and Participants: This cohort study uses data from 3 distinct cohorts, 1 population-based cohort and 2 randomized clinical trials. Participants included individuals from the UK Biobank (data from 2006-2010) without prevalent ASCVD, participants in the FOURIER (TIMI 59) trial (data from 2013-2017) who had baseline Lp(a) and hs-CRP data, and participants in the SAVOR-TIMI 53 trial (data from 2010-2013) who had prevalent ASCVD and baseline values for Lp(a) and hs-CRP. The data analysis took place from November 2022 to November 2023. Exposure: Baseline plasma Lp(a), considered either as a continuous variable or dichotomized at 125 nmol/L. Main Outcomes and Measures: Risk of major adverse cardiovascular events (MACE) (composite of cardiovascular death, myocardial infarction [MI], or ischemic stroke), the individual MACE components, and peripheral artery disease (PAD). Results: Among 357 220 individuals in the UK Biobank without prevalent ASCVD, 232 699 (65%) had low hs-CRP (<2 mg/L), and 124 521 (35%) had high hs-CRP (≥2 mg/L) values. In a Cox proportional hazard model adjusted for ASCVD risk factors, higher Lp(a) was associated with increased cardiovascular risk regardless of baseline hs-CRP value for MACE (hs-CRP ≥2 mg/L: hazard ratio [HR] per 50-nmol/L higher Lp[a], 1.05; 95% CI, 1.04-1.07; P < .001; for hs-CRP <2 mg/L: HR, 1.05; 95% CI, 1.04-1.07; P < .001; P = .80 for interaction), as well as MI, ischemic stroke, and PAD individually. Among 34 020 individuals in the FOURIER and SAVOR trials with baseline cardiometabolic disease, there were 17 643 (52%) with low and 16 377 (48%) with high baseline hs-CRP values. In Cox proportional hazard models using aggregated data from FOURIER and SAVOR, higher baseline Lp(a) was associated with increased cardiovascular risk regardless of baseline hs-CRP for MACE (hs-CRP ≥2 mg/L: HR per 50-nmol/L higher Lp[a], 1.02; 95% CI, 1.00-1.05; P = .04; hs-CRP <2 mg/L: HR, 1.05; 95% CI, 1.02-1.08; P < .001; P = .16 for interaction), MI, and PAD. Conclusions and Relevance: In this study, higher levels of Lp(a) were associated with MACE, MI, and PAD in both primary and secondary prevention populations regardless of baseline hs-CRP value.

Integrative proteomic analyses across common cardiac diseases yield new mechanistic insights and enhanced prediction.

Cardiac diseases represent common highly morbid conditions for which underlying molecular mechanisms remain incompletely understood. Here, we leveraged 1,459 protein measurements in 44,313 UK Biobank participants to characterize the circulating proteome associated with incident coronary artery disease, heart failure, atrial fibrillation, and aortic stenosis. Multivariable-adjusted Cox regression identified 820 protein-disease associations-including 441 proteins-at Bonferroni-adjusted P <8.6×10 -6 . Cis -Mendelian randomization suggested causal roles that aligned with epidemiological findings for 6% of proteins identified in primary analyses, prioritizing novel therapeutic targets for different cardiac diseases (e.g., interleukin-4 receptor for heart failure and spondin-1 for atrial fibrillation). Interaction analyses identified seven protein-disease associations that differed Bonferroni-significantly by sex. Models incorporating proteomic data (vs. clinical risk factors alone) improved prediction for coronary artery disease, heart failure, and atrial fibrillation. These results lay a foundation for future investigations to uncover novel disease mechanisms and assess the clinical utility of protein-based prevention strategies for cardiac diseases.

Evaluation of Point-of-Care Decision Support for Adult Acne Treatment by Primary Care Clinicians.

Importance: Acne is a common reason for referral to dermatologists from primary care clinicians. We previously modeled the impact of algorithm-based acne care in reducing dermatology referrals, missed appointments, and treatment delays. Objective: To prospectively evaluate the downstream outcomes following a real-time, algorithm-based electronic decision-support tool on the treatment of patients referred for acne. Design, Setting, and Participants: This prospective cohort study included 260 treatment-naive patients referred to a dermatologist for the chief concern of acne, as well as the referring primary care clinicians, at 33 primary care sites affiliated with Brigham and Women's Hospital from March 2017 to March 2018. Interventions: We developed and implemented a decision-support tool into the electronic medical record system at an academic medical center. The algorithm identified patients referred to a dermatologist who had not previously been treated for acne and offered guideline-based recommendations for treatment via a real-time notification. Main Outcomes and Measures: Treatment modification by referring clinicians. Results: Of 260 patients referred for acne, 209 (80.4%) were women, 146 (56.1%) were non-Hispanic white, and 236 (90.8%) listed English as the preferred language. Patients had a median (quartile 1-quartile 3) age of 28.8 years (24.4-35.1 years) and 185 of 260 had private insurance (71.1%). In total, the algorithm was associated with cancellation of the initial referral in 35 of 260 (13.5%) instances and treatment initiation by the referring clinician in 51 of 260 (19.6%) instances. Conclusions and Relevance: This decision-support algorithm was associated with a modest reduction in rates of acne-related referrals to dermatologists, and an increased likelihood of treatment initiation by the referring clinician.

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 κ = 0.94 and κ = 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.

A State-of-the-Art Review Highlighting Medical Overuse in Dermatology, 2017-2018: A Systematic Review.

Importance: Emerging efforts to recognize and combat medical overuse are important solutions to mitigate patient morbidity from unnecessary health care interventions. Objectives: To identify and highlight important original investigations on medical overuse in dermatology from 2017 to 2018. Evidence Review: The PubMed and Embase databases coupled with articles published in 8 major dermatology and medical journals from January 1, 2017, to December 31, 2018, were searched to identify articles related to medical overuse in dermatology. Findings: Of 1941 candidate articles identified through the database search and 41 through the manual journal review, 38 were deemed relevant to medical overuse in dermatology by 2 independent reviewers. Twenty-eight of these articles were determined to be high priority based on scoring for quality of methods, magnitude of clinical effect, and number of patients potentially affected. After expert reviewer scoring, 10 articles were selected for analysis based on highest scores and greatest clinical significance. Selected articles covered topics such as dermatology consultation for cellulitis, management of dysplastic nevi, prognostic utility of sentinel lymph node biopsy, laboratory monitoring for terbinafine and isotretinoin, and safe medication prescribing. For cellulitis management, dermatology consultation is important for reducing misdiagnosis, unnecessary hospitalization, and inappropriate use of antibiotics. Findings related to common dermatologic procedures revealed that clinical observation is safe for dysplastic nevi and that sentinel lymph node biopsy may not have prognostic utility over Breslow thickness. In monitoring for terbinafine and isotretinoin, patient education on clinical symptoms is likely more effective than standard laboratory test result monitoring. Finally, dermatologists should reconsider the use of cyclosporine in patients with Stevens-Johnson syndrome and toxic epidermal necrolysis and reevaluate the use of perioperative narcotics for patients. Conclusions and Relevance: This review notes actionable, evidence-based practices to reduce medical overuse in dermatology. This work may help to facilitate management changes to emphasize high-value care in dermatology while promoting awareness and further evaluation of overuse in medicine.