Food And Drug Administration Labeling Research Articles

(Even Off-Label) Cochlear Implantation in Single-Sided Deafness and Asymmetric Hearing Loss Results in Measurable Objective and Subjective Benefit.

To quantify objective and subjective outcomes in cochlear implant (CI) recipients with asymmetric hearing loss, including single-sided deafness (SSD) whose candidacy was determined on an ear-specific basis when word recognition was 50% or less. Retrospective case review. Tertiary referral center. The effectiveness of CI in cases of SSD and asymmetric hearing loss (AHL) has been described in terms of tinnitus suppression, improved speech recognition in quiet and noise, enhanced localization ability, and improved quality of life. However, CI is not yet routinely offered as a top option or standard of care for these individuals. Recent Food and Drug Administration (FDA) labeling limits aided word recognition in the ear to be implanted to only 5% in cases of AHL/SSD, which is significantly poorer than 40 to 50%, which is often referenced in cases of bilateral hearing loss. Anecdotal experience suggests that patients with much better preoperative word recognition than 5% can benefit from CI. We conducted a retrospective chart review of all adult CI candidates, with one ear exhibiting consonant-nucleus-consonant (CNC) word recognition scores at least 50% and one ear not meeting CI candidacy (i.e., CNC word recognition >50%). Outcome variables of interest included word and sentence recognition and subjective handicap questionnaires (hearing, tinnitus, dizziness) and the Speech Spatial Qualities questionnaire. Statistically and clinically significant improvement in speech understanding (word, sentence, sentence in noise) was noted for both the SSD and AHL groups in the implanted ear. There were statistically and clinically significant subjective improvements noted for both groups on the Hearing Handicap Inventory, the Tinnitus Handicap Inventory, and the Speech Spatial Qualities questionnaire by 1 month after activation. There were no significant differences between the AHL and SSD groups on either objective or subjective measures of the implanted ear. Individual word understanding improved for the majority of recipients across both groups and is not dependent on meeting the FDA criteria of less than 5%. Cochlear implantation is a viable option with measurable objective and perceived benefits for recipients with preoperative aided CNC word scores exceeding current FDA labeling. There is no significant difference between the AHL and SSD groups, suggesting that candidacy and outcome expectations should be set based on the ear to be implanted alone, without regard for the ability of the better hearing ear.

Machine learning-based quantitative prediction of drug exposure in drug-drug interactions using drug label information

Many machine learning techniques provide a simple prediction for drug-drug interactions (DDIs). However, a systematically constructed database with pharmacokinetic (PK) DDI information does not exist, nor is there a machine learning model that numerically predicts PK fold change (FC) with it. Therefore, we propose a PK DDI prediction (PK-DDIP) model for quantitative DDI prediction with high accuracy, while constructing a highly reliable PK-DDI database. Reliable information of 3,627 PK DDIs was constructed from 3,587 drugs using 38,711 Food and Drug Administration (FDA) drug labels. This PK-DDIP model predicted the FC of the area under the time-concentration curve (AUC) within ± 0.5959. The prediction proportions within 0.8–1.25-fold, 0.67–1.5-fold, and 0.5–2-fold of the AUC were 75.77, 86.68, and 94.76%, respectively. Two external validations confirmed good prediction performance for newly updated FDA labels and FC from patients’. This model enables potential DDI evaluation before clinical trials, which will save time and cost.

Risk for Postmarket Black Box Warnings in FDA-Approved Monoclonal Antibodies.

ObjectiveTo estimate the potential risk for a future postmarket black box warning (BBW) of US Food and Drug Administration (FDA)-approved monoclonal antibodies (mAbs) because of the importance for medical clinicians to understand mAb risks and benefits, including unknown future risks, especially for recently approved mAbs.MethodsThe complete dates of the study were March 16, 2020, through May 12, 2021. We searched the FDALabel database online and reviewed the scientific literature to determine current and previous FDA-approved mAbs as of March 2020. The BBWs and initial FDA-issued safety warnings were identified. The BBWs were categorized as premarket or postmarket. For mAbs with specific postmarket BBWs, previous FDA labels were evaluated to identify the presence or absence of an initial corresponding specific FDA warning.ResultsIn March 2020, a total of 83 mAbs had FDA approval; 33 had BBWs (27 premarket and 13 postmarket BBWs). Of these 33 mAbs, 55 individual specific BBWs existed (36 premarket and 19 postmarket specific warnings). On average, the specific BBWs occurred in the postmarket period at a rate of 3.4% (19/562) per year. Most (73.7%; 14/19) specific postmarket BBWs were preceded by an FDA warning in a median time of 3.61 (interquartile range, 1.36-5.78) years. Specific postmarket BBWs not preceded by a specific FDA product label warning occurred at an average rate of 0.9% (5/562) per year.ConclusionSpecific postmarket BBWs occurred in FDA-approved mAbs at a rate of 3.4% per year. Specific postmarket BBWs not preceded by a specific FDA product label warning had a rate of 0.9% per year.

Anticancer Drugs Approved by the US Food and Drug Administration From 2009 to 2020 According to Their Mechanism of Action

Both novel and next-in-class cancer drugs have a role in oncology, but the relative development of each is understudied. To characterize the mechanisms of action of anticancer drugs approved by the US Food and Drug Administration (FDA) between 2009 and 2020, noting how many approvals were based on a new mechanism of action vs next-in-class approvals. This cross-sectional study included all anticancer drugs approved by the FDA from January 2009 to December 2020. The mechanism of action of each drug was extracted from FDA labels. Supportive-care treatments were excluded. Name of drug approved, date of approval, indication, tumor type, mechanism of action, broad pharmaceutical class, and biological target. Approvals considering all tumor types and each tumor type separately were classified in 3 nonoverlapping categories: new mechanism of action, next in class, or subsequent approval. The number of all approvals each year; the number of approvals based on a new mechanism of action, either by drug (considering all tumor types) or by indication (considering tumor types separately); and the frequency of these numbers over time. Overall, 332 approvals were included. Between 2009 and 2020, there was an increase in the total number of approvals from 8 to 57. We found that 209 approvals (63%) were for a next-in-class indication in a new tumor type (84 [25%]) or a subsequent indication of the same drug in the same tumor type (195 [59%]). When considering each tumor type separately, 123 approvals (37%) were based on a new mechanism of action. In this study, approvals based on a new mechanism of action represented a minority of all approvals. Further consideration of incentives for drug development are needed to prioritize novel or highly innovative and transformative anticancer drugs.

BERT-Based Natural Language Processing of Drug Labeling Documents: A Case Study for Classifying Drug-Induced Liver Injury Risk.

Background & Aims: The United States Food and Drug Administration (FDA) regulates a broad range of consumer products, which account for about 25% of the United States market. The FDA regulatory activities often involve producing and reading of a large number of documents, which is time consuming and labor intensive. To support regulatory science at FDA, we evaluated artificial intelligence (AI)-based natural language processing (NLP) of regulatory documents for text classification and compared deep learning-based models with a conventional keywords-based model. Methods: FDA drug labeling documents were used as a representative regulatory data source to classify drug-induced liver injury (DILI) risk by employing the state-of-the-art language model BERT. The resulting NLP-DILI classification model was statistically validated with both internal and external validation procedures and applied to the labeling data from the European Medicines Agency (EMA) for cross-agency application. Results: The NLP-DILI model developed using FDA labeling documents and evaluated by cross-validations in this study showed remarkable performance in DILI classification with a recall of 1 and a precision of 0.78. When cross-agency data were used to validate the model, the performance remained comparable, demonstrating that the model was portable across agencies. Results also suggested that the model was able to capture the semantic meanings of sentences in drug labeling. Conclusion: Deep learning-based NLP models performed well in DILI classification of drug labeling documents and learned the meanings of complex text in drug labeling. This proof-of-concept work demonstrated that using AI technologies to assist regulatory activities is a promising approach to modernize and advance regulatory science.

Advances in Neurocardiology: Focus on Atrial Fibrillation.

Advances in Neurocardiology: Focus on Atrial Fibrillation.

Potential Implications of Expanded US Food and Drug Administration Labeling for Sacubitril/Valsartan in the US

The US Food and Drug Administration (FDA) expanded labeling for sacubitril/valsartan for use in individuals with chronic heart failure (HF) with left ventricular ejection fraction (LVEF) lower than normal. The population-level implications of implementation of sacubitril/valsartan at higher LVEF ranges is unknown. While the Prospective Comparison of ARNI With ARB Global Outcomes in HF With Preserved Ejection Fraction (PARAGON-HF) trial did not meet its primary end point, the trial may provide useful information in projecting expected clinical events among treated individuals. To quantify newly eligible treatment candidates for sacubitril/valsartan under the expanded FDA labeling and to apply treatment effects and the number needed to treat (NNT) to prevent 1 worsening HF event derived from subgroups of the PARAGON-HF trial who fall under the revised FDA label. Newly eligible treatment candidates were estimated by mapping the LVEF distribution from 559 520 adult patients hospitalized between 2014 and 2019 in the Get With The Guidelines-Heart Failure registry to adults self-identifying with HF in the National Health and Nutrition Examination Survey (2015 to 2018). The NNT with 3 years of treatment for 3 end points of interest (total HF hospitalizations, total HF hospitalizations and cardiovascular death, and total HF hospitalizations and urgent HF visits and cardiovascular death) were estimated from the PARAGON-HF trial. Data were analyzed from February to June 2021. Number of worsening HF events prevented or postponed if eligible patients were treated with sacubitril/valsartan for 3 years. Of an estimated 4 682 098 adults, the mean (SE) age was 66.3 (0.8) years, 1 995 037 (42.6%) were women, and 748 045 (16.0%) were Black. The potential number of adults projected to be newly eligible varied by the definition of FDA labeling of lower than normal LVEF from 643 161 (95% CI, 534 433-751 888; LVEF of 41% to 50%) to 1 838 756 (95% CI, 1 527 911-2 149 601; LVEF of 41% to 60%). In the PARAGON-HF trial, the NNT to prevent a worsening HF event (range, 7 to 12 patients) was consistent irrespective of specific LVEF range selected. Comprehensive implementation of sacubitril/valsartan among newly eligible patients was empirically estimated to prevent up to 69 268 (95% CI, 57 558-80 978) worsening HF events (LVEF of 41% to 50%) to 182 592 (95% CI, 151 725-213 460) worsening HF events (LVEF of 41% to 60%). The expanded FDA labeling is positioned to substantially increase the potential HF population eligible for sacubitril/valsartan by up to 1.8 million individuals and has the potential to prevent or postpone as many as 180 000 worsening HF events, depending on the definition of normal LVEF.

Enrollment disparities in cancer clinical trials leading to FDA approvals between 2008 and 2020.

e18501 Background: Cancer clinical trials based in the United States (US) have lacked adequate representation of racial and ethnic minorities, the elderly, and women. Pivotal clinical trials leading to United States Food and Drug Administration (FDA) approval are often multi-national trials and may also lack generalizability to underrepresented populations in the United States. We determined the racial, ethnic, age, and sex enrollment in pivotal trials relative to the US cancer population. Methods: We reviewed the FDA’s Drug Approvals and Databases for novel and new use drug approvals for breast, colorectal, lung, and prostate cancer indications from 2008 through 2020. Drugs@FDA was searched for drug approval summaries and FDA labels to identify clinical trials used to justify clinical efficacy that led to FDA approval. For eligible trials, enrollment data were obtained from FDA approval summaries, FDA labels, ClinicalTrials.gov, and corresponding journal manuscripts. Enrollment Fraction (EF) was calculated as enrollment in identified clinical trials divided by 2017 SEER cancer prevalence. All data sources were publicly available. Results: From 2008 through 2020, 60 drugs received novel or new use drug approval for breast, colorectal, lung, or prostate cancer indications based on 66 clinical trials with a total enrollment of 36,830. North America accounted for 9,259 (31%) enrollees of the 73% of trials reporting location of enrollment. Racial demographics were reported in 78% of manuscripts, 66% of ClinicalTrials.gov pages, and 98% of FDA labels or approval summaries. Compared with a 0.4% enrollment fraction among White patients, lower enrollment fractions were noted in Hispanic (0.2%, odds ratio [OR] vs White, 0.46; 95% confidence interval [CI], 0.43 to 0.49, P< 0.001) and Black (0.1%, OR 0.29; 95% CI 0.28 to 0.31, P< 0.001) patients. Elderly patients (age ≥ 65 years) were less likely than younger patients to be enrollees (EF 0.3% vs 0.9%, OR 0.27; 95% CI 0.26 to 0.27, P< 0.001) despite accounting for 61.3% of cancer prevalence. For colorectal and lung cancer trials, females were less likely than males (EF 0.7% vs 1.1%, OR 0.66; 95% CI 0.63 to 0.68, P< 0.001) to be enrolled. Conclusions: Black, Hispanic, elderly, and female patients were less likely to enroll in cancer clinical trials leading to FDA approvals from 2008 to 2020. Race and geographic enrollment data were inconsistently reported in journal manuscripts and ClinicalTrials.gov. The lack of appropriate representation of specific patient populations in these key clinical trials limits their generalizability. Future efforts must be made to ensure equitable access, representation, and reporting of enrollees that adequately represent the US population of patients with cancer.

Remdesivir: Preliminary Data and Clinical Use Versus Recommended Use.

* Abbreviations: COVID-19 — : coronavirus disease 2019 FDA — : Food and Drug Administration Remdesivir inhibits viral replication of severe acute respiratory coronavirus 2 in vitro and has been shown to reduce time to recovery in adults with coronavirus disease 2019 (COVID-19). It is currently the only antiviral approved by the Food and Drug Administration (FDA) for the treatment of COVID-19.1–4 Although remdesivir is being used in children with COVID-19, it is not approved for patients <12 years of age. Fortunately, if treatment with remdesivir of COVID-19 meets key assumptions, the drug may qualify for the extrapolation pathway, whereby efficacy data in adults can be used to support efficacy in children. However, safety data cannot be extrapolated; population-specific safety data are needed to support FDA labeling for pediatric use. Thus, we read with anticipation the safety data on compassionate use of remdesivir in 77 children with severe COVID-19 presented by Goldman et al5 in this issue of Pediatrics . Goldman et al5 describe low rates of adverse events, including elevated liver aminotransferase levels and anemia, similar to the safety profile seen in adults receiving remdesivir. In light of these data, we will consider whether the concept of extrapolation could be used to support efficacy of remdesivir in children … Address correspondence to Danny K. Benjamin, MD, PhD, Duke Clinical Research Institute, Durham Centre, Suite 800, 300 W Morgan St., Durham, NC 27701. E-mail: danny.benjamin{at}duke.edu

Hypothalamic-Pituitary-Adrenal Axis Pediatric Safety Studies Submitted to the FDA.

Corticosteroid use has been associated with hypothalamic-pituitary-adrenal (HPA) axis suppression which can predispose the pediatric patient to multiple immune- and growth-related adverse effects. The objectives of this review were to identify the pediatric drug development programs involving corticosteroids and the associated pediatric HPA axis suppression studies submitted to the US Food and Drug Administration (FDA), capture FDA guidance topic related recommendations, and determine the consistency of HPA axis data in prescription corticosteroid labeling. A review of FDA submissions from January 2002 to July 2018 involving corticosteroid products and HPA axis testing in pediatric patients was conducted. The adrenal function testing methods, number of pediatric HPA axis dedicated studies, duration of these studies, and the labeling outcomes were assessed. Of the 437 total drug products that were submitted to FDA, only 36 products were corticosteroids or a corticosteroid combination product yielding a total of 83 pediatric clinical studies. Twenty-four of the 36 products included 37 HPA axis suppression dedicated studies which employed different measurement methods. The pediatric HPA axis suppression trial data collected did not necessitate any new actionable recommendations in the FDA labeling. Future pediatric drug development program goals would be to determine whether HPA axis suppression studies should be conducted, establish optimal testing methods if HPA axis testing is performed, continue to update guidances for industry, and actionable labeling recommendations. However, regulatory policy related to conducting pediatric HPA axis studies requires additional scientific research and discussion by the pediatric drug development community.

Moving on With Monoamine Oxidase Inhibitors.

Moving on With Monoamine Oxidase Inhibitors.

Labeling of Cannabidiol Products: A Public Health Perspective.

Introduction: Interest in the therapeutic use of cannabidiol (CBD) has reached a fever-pitch in recent months, as CBD-containing products appear everywhere from online retailers to grocery stores and gas stations. The widespread availability of hemp-derived CBD products is confounding given that CBD is a U.S. Food and Drug Administration (FDA)-approved drug, and thus precluded from being added to food and beverages, or included in dietary supplements. The use by manufacturers of disease-related claims on marketing materials and product labels, along with the federal legalization of hemp in December 2018, has created political pressure on FDA to promulgate regulations. Conclusions: Accurate and informative labeling of hemp and hemp-derived CBD products is an important public health issue. FDA-regulated product labels are considered an essential tool for protecting consumers and enabling informed decision-making. Untruthful or unsubstantiated health-related claims, and unallowed Drug Claims, in marketing materials and on labels of CBD products may create harm by enticing consumers to forgo more evidence-based medical interventions. Furthermore, missing or inaccurate labeling of the amount of CBD, delta-9 tetrahydrocannabinol (THC), and potentially harmful contaminants such as pesticides, naturally-occurring yeast and mold or heavy metals may result in harm and/or lack of efficacy. Manufacturers of these products may reasonably be expected to understand and adhere to FDA regulations for labeling and marketing of food, dietary supplements and drugs, both over-the-counter (OTC) and prescription, even though FDA has interpreted federal law as excluding them from these categories. As manufacturers prepare for forthcoming regulations, a better understanding of the basic framework for FDA labeling and marketing regulations for food, dietary supplements and drugs is warranted.

2020 Update on sunscreen compliance with American Academy of Dermatology recommendations

2020 Update on sunscreen compliance with American Academy of Dermatology recommendations

Timing of US Food and Drug Administration (FDA) cancer drug approvals relative to publication of clinical trial results.

2071 Background: Publication of clinical trial results in peer reviewed literature is essential to inform clinicians regarding the use of new anti-cancer treatments, which often have a low therapeutic ratio and require careful assessment of risks and benefits. Publication of registration trials should precede FDA approval to facilitate evaluation and implementation of new therapies. The timing of trial publication relative to FDA drug approvals has not been systematically investigated. Methods: We collected all FDA drug approvals for a cancer indication between 2000-19. Trials were identified using FDA labels as well as drugs and publications indexed on HemOnc.org. Approvals for generics/biosimilars, non-oncology indications and label revisions without supportive evidence were excluded. Dates of approval, the approval pathway, approval type (new vs expansion), and the first full publication related to the registration were recorded. Trials and approvals were matched using available metadata. We calculated the proportion of drugs approved prior to publication overall and for those receiving accelerated approval (AA). We used logistic regression to compare rates of pre-publication approval by approval pathway and by new vs expanded approval. Results: Among a total of 378 drug approvals, 139 (37%) had pre-publication approval. Of these, the median overall time from approval to publication was 140 days (IQR 64-281 days). For those with approval after publication, median time from publication to approval was 157 days (IQR 72-359 days). The number of drugs approved pre-publication rose by 27% between the first and last quarters of the study period, though, the proportion decreased as more anti-cancer drugs have been approved in recent years (Table). More drugs were approved pre-publication through AA than regular approval (46% vs 34%, OR 1.66 [95% CI 1.03-2.70], p=0.04) and as new approvals vs. expanded approvals (45% vs 32%, OR 1.76 [95% CI 1.15-2.70], p=0.01). Conclusions: A substantial minority of FDA approvals occur before trial results are published, with the odds being higher for drugs receiving AA and for new approvals. Since clinicians rely upon published results to inform risk/benefit decisions, efforts are needed to ensure trial results are published by the time of FDA approval of new cancer drugs and indications. [Table: see text]

Mismatch between mortality burden and number of FDA registration trials in highly lethal cancers.

2072 Background: Treatment successes in cancer are achieved through new drugs tested in clinical trials. However, drug discovery has been disparate across cancer types for various reasons. We sought to investigate if the number of trials used to support United States Food and Drug Administration (FDA) drug approvals is proportional to the incidence and mortality burden of highly lethal cancers, i.e. those with an expected relative mortality of &gt;5% per Cancer Statistics, 2020 (Siegel et al.). Methods: All FDA labels for 258 antineoplastic cancer drugs approved as of January 2020 were reviewed for citations of registration trials supporting initial approval and additional indications. Trials were identified by matching described characteristics (e.g., patients enrolled, clinical trial NCT codes) to publications indexed on HemOnc.org. Trials were labeled by cancer type studied and type of trial (randomized vs non-randomized). Results: We identified 559 registration trials in total. Results for the six highly lethal cancers are shown in the table. The percent of registration trials was roughly proportional to incidence, but not mortality burden. For example, despite the 22% expected mortality burden of lung cancer, it had a share of only 11% of registration trials whereas breast cancer has an expected 7% mortality burden, with a share of 14% of registration trials. Chronic myeloid leukemia is expected to cause 1,130 deaths in 2020 (0.2%) and has had 20 registration trials (3.6%). The highly lethal cancers had a higher rate of randomized trials supporting approval than other cancers (84% vs 56%, p&lt;0.001 [Chi-square]). Conclusions: While the findings may in part be due to disease biology (e.g., pancreatic ductal adenocarcinoma has proven resistant to many novel therapies), our evaluation highlights a potential mismatch between resources and needs. Randomized trials were more often used to support new drug approvals in highly lethal cancers. These findings will be important in regulatory policy. [Table: see text]

The Clinical Pharmacology Sections in Drug Package Inserts: Do We Need to Reexamine the Basis?

The Clinical Pharmacology Sections in Drug Package Inserts: Do We Need to Reexamine the Basis?

Pharmacogenetics in Practice: Estimating the Clinical Actionability of Pharmacogenetic Testing in Perioperative and Ambulatory Settings.

Most literature describing pharmacogenetic implementations are within academic medical centers and use single‐gene tests. Our objective was to describe the results and lessons learned from a multisite pharmacogenetic pilot that utilized panel‐based testing in academic and nonacademic settings. This was a retrospective analysis of 667 patients from a pilot in 4 perioperative and 5 outpatient cardiology clinics. Recommendations related to 12 genes and 65 drugs were classified as actionable or not actionable. They were ascertained from Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines and US Food and Drug Administration (FDA) labeling. Patients displayed a high prevalence of actionable results (88%, 99%) and use of medications (28%, 46%) with FDA or CPIC recommendations, respectively. Sixteen percent of patients had an actionable result for a current medication per CPIC compared with 5% per FDA labeling. A systematic approach by a health system may be beneficial given the quantity and diversity of patients affected.

Suicidality, Depression, and the FDA: Health Inequities and the Ethical Conduct of Research.

Persons with mental health disorders, including suicidality, are underrepresented in clinical trials, undermining the generalizability of results and possibly contributing to health inequities. This report (1) documents the exclusion of persons with suicidality in trials used to secure US Food and Drug Administration (FDA) approval for antidepressants, (2) describes barriers to inclusion, and (3) identifies possible steps for overcoming barriers. Inclusion and exclusion criteria for efficacy trials for depression or major depressive disorder described on FDA labels for 14 antidepressants approved from 1991 through 2013 were studied by reading the FDA labels, publications described on labels, and ClinicalTrials.gov entries for registered trials. Labels for drugs approved in or before 1998 were obtained through a Freedom of Information Act request filed June 26, 2018. For drugs approved after 1998, labels are on the FDA website. Publications based on the trials described on FDA labels were identified through a PubMed search on October 23, 2018, using each drug name and trial or study as the keywords and setting no date limit. For drugs approved from 1991 to 2000, of 36 publications identified, 26 did not mention suicidality, 7 excluded persons with suicidality but did not describe assessing suicidality with an instrument, 2 excluded persons with suicidality and described assessing suicidality using at least 1 instrument, and 1 included persons with suicidality. For drugs approved from 2000 through 2013, of 28 publications identified, 4 did not mention suicidality, 12 reported excluding persons with suicidality but did not describe assessing suicidality with an instrument, 12 excluded persons with suicidality and described assessing suicidality using at least one instrument, and none included persons with suicidality. More stringent criteria for assessing and excluding based on suicidality very likely were applied for drugs approved post-2000. The exclusion of persons with suicidality from antidepressant trials is common, creating uncertainty about medication safety and efficacy in parts of the target population. Information about study populations can be beneficial for prescribing clinicians, but it is not always readily available.

Pharmacogenomic information from CPIC and DPWG guidelines and its application on drug labels.

There are several hurdles to overcome before implementing pharmacogenomics (PGx) in precision medicine. One of the hurdles is unawareness of PGx by clinicians due to insufficient pharmacogenomic information on drug labels. Therefore, it might be important to implement PGx that reflects pharmacogenomic information on drug labels, standard of prescription for clinicians. This study aimed to evaluate the level at which PGx was being used in clinical practice by comparing the Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group guidelines and drug labels of the US Food and Drug Administration (FDA) and the Korea Ministry of Food and Drug Safety (MFDS). Two PGx guidelines and drugs labels were scrutinized, and the concordance of the pharmacogenomic information between guidelines and drug labels was confirmed. The concordance of the label between FDA and MFDS was analyzed. In FDA labels, the number of concordant drug with guidelines was 24, while 13 drugs were concordant with MFDS labels. The number of drugs categorized as contraindication, change dose, and biomarker testing required was 7, 12 and 12 for the FDA and 8, 5 and 4 for the MFDS, respectively. The pharmacogenomic information of 9 drugs approved by both FDA and MFDS was identical. In conclusion, pharmacogenomic information on clinical implementation guidelines was limited on both FDA and MFDS labels because of various reasons including the characteristics of the guidelines and the drug labels. Therefore, more effort from pharmaceutical companies, academia and regulatory affairs needs to be made to implement pharmacogenomic information on drug labels.

PSY52 PATIENT-REPORTED OUTCOME MEASURES IN ATOPIC DERMATITIS AND CHRONIC HAND ECZEMA IN ADULTS

Patient-reported outcome measures (PROMs) provide an important complement to physician-assessed clinical outcome measures in dermatologic diseases such as atopic dermatitis (AD) and chronic hand eczema (CHE). AD and CHE are chronic and relapsing inflammatory skin conditions that often co-occur. While both diseases result in various signs and symptoms that are burdensome and can negatively affect patients’ lives, there may be distinct differences in the signs, symptoms, burden, and health-related quality of life (HRQOL) impact of these diseases. The objective of this study was to identify and evaluate PROMs used in studies of AD and CHE. The aim was to explore the assessment of key symptoms and impacts, and identify any gaps in the measures in use. A structured review of the PubMed database was conducted to identify PROMs used or developed for use in AD or CHE. The Dermatology Life Quality Index (DLQI), the Pruritus/Itch Numeric Rating Scale (NRS), the Patient-Oriented Eczema Measure (POEM), and the Quality of Life in Hand Eczema Questionnaire (QOLHEQ) were identified and reviewed in detail. With these measures, the AD and CHE symptoms and impacts most commonly evaluated in the literature include dermatology-related HRQOL in the domains of symptoms and feelings, daily activities, leisure, work and school, personal relationships, and adverse effects; pruritus; sleep disturbance; AD-specific symptoms (dryness, itching, flaking, cracking, bleeding, and weeping/oozing); and CHE-specific symptoms (pain, itch, fissuring, redness, bleeding, and dryness). A review of regulatory labels of drugs approved for AD by the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) found that, among the four measures reviewed, the Pruritus NRS was included in the FDA and EMA labels for dupilumab, the DLQI was included in the EMA labels for dupilumab and tacrolimus, and the POEM was included in the EMA label for dupilumab. Key symptoms of AD (e.g. itching, flaking, cracking) and CHE (e.g. pain, itching, fissuring) are increasingly being assessed with PROMs; however, primary endpoints in clinical trials are often based on clinician-reported outcome measures. As therapeutic strategies in dermatology are targeted at specific dermatologic symptoms and diseases affecting specific sites (e.g. CHE), future research should explore patients’ experiences with these symptoms and sites and the changes with treatment that are most meaningful to them.