Non-small cell lung cancer (NSCLC) is the most common form of lung cancer in the United States. Immunotherapies and cytotoxic chemotherapies used to treat advanced NSCLC carry a substantial risk of adverse events (AEs), but real-world data on the incidence and costs associated with the unique AE profiles of these treatments are sparse.To examine the AE incidence and costs among patients initiating non–driver mutation-targeted first-line therapy for metastatic NSCLC (mNSCLC) in clinical practice.This was a retrospective administrative claims study conducted among commercial and Medicare Advantage health plan members who initiated first-line, nontargeted systemic anti-NSCLC therapy between January 1, 2008, and February 28, 2018. Patients were assigned to mutually exclusive treatment cohorts  and were observed from the index date (start of first-line therapy) through the earliest of health plan disenrollment, death, or March 31, 2018. AE incidence rates and associated health care costs were measured from the index date through the earliest of the start of a new therapy, 180 days after the end of first-line therapy, or the end of the study period. The factors influencing whether patients incurred high AE-related health care costs were assessed using multivariable models adjusted for patient demographic and clinical characteristics.P < 0.001). In the multivariable analysis, the odds of incurring any AE costs were similar for the IO and IO-CHEM cohorts compared with the CHEM cohort . Among patients who incurred AE costs, those in the IO cohort were less likely than those in the CHEM cohort to have high costs ; the difference between the IO-CHEM and CHEM cohorts was not statistically significant.The final study population  included 8,818 in the CHEM cohort, 482 in the IO cohort, and 412 in the IO-CHEM cohort. Overall, 74.4% had at least 1 AE during follow-up. The AE incidence rate was lowest for the IO cohort, with incidence rate ratios (95% CI) of 1.4 (1.3-1.6) for the CHEM cohort and 1.4 (1.2-1.6) for the IO-CHEM cohort. Mean AE-related costs were lowest for the IO cohort  and highest for the CHEM cohort ($23,009; Among real-world patients initiating nontargeted first-line therapy for mNSCLC, those receiving immunotherapy experienced fewer AEs and had lower total AE-related costs than those treated with cytotoxic chemotherapy. Immunotherapy-treated patients were no more likely than chemotherapy-treated patients to incur AE-related costs and were less likely to have high AE costs if they incurred any at all. These findings indicate that immunotherapy-related AEs are not a differentiating factor in cost of care for this patient population in clinical practice. What is already known about this subjectImmunotherapies and cytotoxic chemotherapies used to treat metastatic non-small cell lung cancer (mNSCLC) are associated with improved survival but also carry a substantial risk of adverse events (AEs).Real-world data on the AE incidence and AE-related costs of current mNSCLC treatments are sparse.What this study addsPatients with first-line immunotherapy-treated mNSCLC had less frequent AEs, lower total AE costs, and lower odds of incurring high AE costs than those treated with cytotoxic chemotherapy.Patients with previous infections or neurological disorders had a higher likelihood of incurring high AE costs during first-line therapy.1 It is also among the costliest cancers; total expenditures associated with lung cancer care in 2018 were estimated at more than $14 billion nationally, and the total cost of treatment has been found to surpass $100,000 per patient.3Lung cancer is the leading cause of cancer mortality in the United States, with an estimated 228,150 new diagnoses and 142,670 deaths in 2019.4 While platinum-based chemotherapy was long the primary option for first-line treatment of advanced NSCLC, the arsenal of available treatments expanded substantially with the development of drugs targeted toward specific driver mutations or the programmed cell death receptor-1 (PD-1) and programmed cell death-ligand 1 (PD-L1) pathways.5 Today, NSCLC treatment options for patients with metastatic tumors overexpressing PD-L1 and without driver mutations include not only traditional cytotoxic chemotherapy but also immunotherapy with immune checkpoint inhibitors such as pembrolizumab, nivolumab, and atezolizumab.6Surgical resection is potentially curative for localized non-small cell lung cancer (NSCLC); however, 40% of patients with NSCLC already have stage IV disease at diagnosis.7 Immunotherapies are associated with lower rates of some toxicities common to classical chemotherapy,11 but they may cause unique immune-related AEs that can be severe and affect multiple organ systems, sometimes requiring hospitalization and/or treatment with steroids.12 While it is recognized that AEs of NSCLC treatment can reduce quality of life,13 real-world data on the incidence and costs associated with the unique AE profiles of these therapies are sparse. Much of our understanding about the extent of AEs experienced by patients treated for advanced NSCLC comes from clinical trials,14 which use highly selected patient samples that may differ substantially from real-world patient populations.15 Cost studies conducted among real-world patients with NSCLC have shown a high economic burden but did not differentiate between immunotherapy and conventional chemotherapy,16 did not specifically examine AE-related costs,3 or use data collected before the approval of first-line immunotherapy.18 The present study was conducted to address these knowledge gaps by examining the incidence and costs associated with selected AEs among patients initiating nontargeted first-line chemotherapy or immunotherapy for metastatic NSCLC (mNSCLC) in clinical practice.Although current first-line therapies for advanced NSCLC are associated with improved survival, they also carry a substantial risk of adverse events (AEs).International Classification of Diseases, Ninth/Tenth Revision, Clinical Modification (ICD-9/10-CM); Current Procedural Terminology or Healthcare Common Procedure Coding System codes; site of service codes; and paid amounts. Pharmacy claims include drug name, National Drug Code number, dosage form, drug strength, fill date, number of days supply, and financial information for outpatient pharmacy services. Because no identifiable protected health information was accessed in the conduct of this study, institutional review board approval or waiver of approval was not required.This was a retrospective study conducted using commercial and Medicare Advantage administrative claims data from the Optum Research Database (ORD) from January 1, 2007, through March 31, 2018 (study period). Mortality information was sourced from claims and Social Security Administration data as available. The ORD is geographically diverse across the United States and contains deidentified medical and pharmacy claims data and linked member enrollment information. Medical claims include diagnosis and procedure codes from the 19; continuous health plan enrollment with medical and pharmacy benefits for at least 6 months before and at least 1 month after the first qualifying claim for NSCLC therapy (index date); aged ≥ 18 years as of the index date; at least 1 nondiagnostic claim for lung cancer (ICD-9-CM 162.xx or ICD-10-CM C34.xx) in the 6 months before the index date (6-month baseline period); and evidence of metastasis or unresectable locally advanced disease . The period of continuous enrollment before the index date back to January 1, 2007, was the variable baseline period. The period of continuous enrollment from the index date through the earliest of health plan disenrollment, death, or March 31, 2018, was the follow-up period. At least 1 month of follow-up was required unless the patient had died.The study included patients from the ORD with evidence of NSCLC who initiated first-line, non–driver mutation-targeted systemic anticancer therapy between January 1, 2008, and February 28, 2018 (identification period). Inclusion criteria were at least 1 claim for National Comprehensive Cancer Network (NCCN)-recommended, nontargeted therapy for NSCLC (based on September 2017 guidelines) during the identification period Patients were excluded if they had evidence of lung cancer-specific surgery (not including biopsy) during the 6-month baseline period, any claim for systemic anticancer therapy  during the period 12 months before the index date, any claim for targeted therapy  based on the first observed line of therapy (LOT), which by definition began on the index date (date of the first infusion or fill for a systemic anticancer agent). The first LOT included all agents received within 30 days following the index date and ended on the earliest of any of the following: addition or substitution of a new agent, treatment gap of at least 60 days after the run-out date of all agents in the LOT, death, health plan disenrollment, or end of the study period.20 Study outcomes were assessed during the follow-up period.Patient demographic characteristics were assessed as of the index date. Baseline Quan-Charlson Comorbidity Index scores were assessed during the 6-month baseline period.Selected AEs were measured during the AE observation period, which began on the index date (start of LOT1) and ended on the earliest of the start of a new LOT; 180 days after the end of LOT1; or at the end of the study period. AEs measured in this study included those with a prevalence of at least 10% according to the drug labels for NCCN-recommended therapies and some AEs that were less prevalent but were selected by a clinical expert because of severity and/or clinical relevance to immunotherapy. AEs other than infusion reactions were identified on the basis of claims with a relevant ICD-9/10-CM diagnosis code in position 1 or 2 or a relevant procedure code on a medical claim. Infusion reactions were identified on the basis of codes for specified conditions  occurring in position 1 or 2 on claims within 2 days of an infusion . Conditions were not considered as infusion reactions if the patient had a claim with a diagnosis for that condition in the 7 days before the infusion. Blood disorders  were calculated separately as well as presented as a group. AE incidence was calculated only among patients without the selected AE during the variable baseline period. Incidence rates were calculated by dividing the number of patients with the AE during the AE observation period by the total patient-years of observation up to the occurrence of the AE.21 Total costs for each AE were calculated as the sum of costs on each claim associated with the AE. For claims that contained codes for more than 1 AE, costs were attributed separately to the total costs of each AE. For AE costs associated with inpatient stays, the costs of the entire stay were attributed to the AE. Pharmacy costs associated with each AE were calculated on the basis of all pharmacy claims with dates between the first and last medical claims associated with the AE. In addition to total AE costs over the AE period, population-level per patient per month (PPPM) costs were estimated.Health care costs associated with selected AEs were calculated as the combined health plan-paid amounts plus patient-paid amounts during the AE observation period, adjusted to 2017 U.S. dollars using the annual medical care component of the Consumer Price Index.P values ≤ 0.05 were considered to indicate statistical significance.Analytic dataset creation was conducted using SAS software version 9.4 . All study variables were analyzed descriptively. Results were stratified by treatment cohort and compared using statistical tests appropriate for the distribution of the measure . Incidence rate ratios (IRRs) were calculated to compare the risks of selected AEs among treatment cohorts; chi-square testing was performed, with 95% confidence intervals (CIs) derived using 10,000 bootstrapped samples for the composite measures of any AE and blood condition, and standard binomial CIs for the remaining AEs. 22 Odds ratios (ORs), 95% CIs, and P values are presented for each covariate included in the logistic models.The factors influencing whether patients had high AE-related health care costs were assessed using logistic regressions adjusted for insurance type, geographic region, sex, baseline Charlson score, baseline metastatic disease, and baseline AEs. Because a substantial number of patients had zero AE costs, 1 model estimated the probability of incurring any AE cost, and a separate model estimated the probability of having high costs (defined as the 90th percentile) among patients incurring > $0 AE costs.Of 273,860 patients with at least 1 claim for nontargeted, NCCN-recommended therapy for NSCLC during the identification period, 9,712 met the remaining study criteria . The finP < 0.001 for both) and a higher percentage of patients with Medicare Advantage insurance . In addition, the IO cohort had a shorter follow-up time compared with the IO cohort  and a lower percentage of men compared with the CHEM cohort .Patient characteristics were similar among the 3 cohorts, with a few exceptions . The IO Among NCCN-recommended agents, the most common cytotoxic chemotherapies (used by > 10% of patients) were carboplatin (73.7%), pemetrexed (29.7%), paclitaxel (22.4%), etoposide (22.2%), and bevacizumab (11.5%). The prevalence of immuno-oncology agent use (as monotherapy or part of combination therapy) was 6.9% for pembrolizumab, 1.5% for nivolumab, and 0.1% for atezolizumab.AE incidence during the AE observation period is presented for patients who did not have evidence of that AE during the baseline period. Overall, 74.4% of the study population had ≥ 1 AE during follow-up . Common P<0.001; P < 0.001) or the IO-CHEM cohort . With a few exceptions, the mean cost per patient for a specific AE (among patients with that AE during follow-up but not in the baseline period) did not differ across the systemic therapy cohorts, whether measured as a total cost or as a PPPM cost across the AE period (P < 0.001), anemia , infusion reactions , neurological disorders , and kidney injury  and lowest for the IO cohort  and patients with baseline infections , kidney injury , or myositis  and lower for those with a code for metastatic disease during the 6-month baseline period .Patients with AE-related costs were stratified into high-cost  and lower-cost  cohorts on the basis of total AE costs. Compared with the CHEM cohort, the IO and IO-CHEM cohorts were not statistically significantly different in their odds of having any AE costs; the predicted proportions of patients incurring costs were 87.7% for the CHEM cohort, 85.4% for the IO cohort, and 87.5% for the IO-CHEM cohort . HoweverP < 0.001), but there were no statistically significant differences in baseline Charlson comorbidity scores  or the percentage of patients with baseline metastatic disease . A higher percentage of high-cost patients had inpatient stays , intensive care unit (ICU) admissions , and emergency department (ED) visits  during the AE period. Mean (SD) follow-up time was longer for the high-cost cohort than the lower-cost cohort (196.3 [137.6] days vs. 167.7 [124.0] days). When prevalence rate ratios for high-cost versus lower-cost patients were examined to account for variable follow-up time, high-cost patients were found to have lower rates of ED visits  and ICU admissions , and the difference in rates of inpatient stays was not statistically significant .Descriptive analysis of the high-cost versus lower-cost cohorts showed that patients in the high-cost cohort were slightly younger  or had baseline infections  or neurological disorders , and were less likely to be in the high-cost group if they were Medicare Advantage enrollees  or had a code for metastatic disease during the baseline period .Among patients who incurred AE-related costs, those in the IO cohort were less likely than those in the CHEM cohort to have high costs .14 As in RCTs, blood disorders, GI disorders, and neurological disorders in the present study were all significantly more common among patients receiving conventional chemotherapy, whereas patients receiving IO alone were more likely to experience immune-related AEs such as hypothyroidism, hyperthyroidism, and pneumonitis.14AEs were common in this study population, with 74% of patients having at least 1 selected AE during the follow-up period. This prevalence is consistent with randomized clinical trials (RCTs). A meta-analysis of 7 RCTs including 2,122 patients with advanced NSCLC and 1,328 with advanced melanoma showed that the percentage experiencing any AE ranged from 67.6% for those treated with PD-1/PD-L1 inhibitors to 82.9% for those treated with conventional chemotherapy.23 However, comparability with our results is limited, as the Cathcart-Rake study did not examine patients treated with cytotoxic chemotherapy alone and was not limited to first-line treatment; many patients had received conventional chemotherapy before immunotherapy.23Our study is the first to our knowledge to examine the unique AE profiles of both chemotherapy and immunotherapy treatment and their costs among real-world patients with mNSCLC. In another recent retrospective database study of patients with NSCLC treated with PD(L)-1 inhibitors, Cathcart-Rake et al. (2018) noted that hypothyroidism and blood disorders were the most frequent AEs .23; however, the present study is the first to our knowledge to compare AE-related costs for NSCLC treatment with immuno-oncology agents versus conventional chemotherapy. We found that mean AE costs were significantly lower for the IO cohort than for the CHEM cohort, whether assessed as total costs  or PPPM . Moreover, among patients who incurred AE costs, those in the IO cohort were 40% less likely to have high costs (defined as the 90th percentile) than those in the CHEM cohort. Given that larger proportions of high-cost versus lower-cost patients had inpatient stays, ICU admissions, and ED visits during the AE period, our findings suggest that high AE costs may have been driven by hospitalizations and ED visits, similar to what was seen in previous studies.18Previous retrospective studies have shown high AE-related costs among real-world patients with NSCLC24 respectively. However, these earlier analyses were conducted in Medicare-only populations, included only costs related to AEs coded as the primary diagnosis on a claim, and adjusted costs to 2013 U.S. dollars, all of which likely contributed to this discrepancy.The lower prevalence rate ratios for ED visits and ICU admissions observed among high-cost versus lower-cost patients may have been due to the longer mean follow-up period in the high-cost cohort. PPPM AE costs in our analysis were substantially higher than those in the only other similar U.S. real-world studies to date. Bittoni et al. (2018) and Arunachalam et al. (2018) found mean total PPPM AE-related costs of $1,084 for first-line therapy and $1,036 for second-line therapy,We found that AE costs were not significantly different between the IO-CHEM and CHEM cohorts; this was unexpected, as the combination of therapies might be hypothesized to have a cumulative effect on AEs. The reasons for this finding cannot be determined with certainty from our data. However, given that our analysis did not account for chemotherapy strength or treatment duration, it may have been due to lower chemotherapy strength in the IO-CHEM cohort or to a longer follow-up period in the CHEM cohort (resulting in more time for AEs to be observed). In addition, it is possible that patients in the IO-CHEM cohort had been selected by their physicians as being more likely to tolerate combination therapy and therefore experienced fewer and/or less severe AEs.25 little research had been conducted until recently to elucidate the real-world costs involved. Our findings demonstrate that AE-related costs are actually lower among patients receiving IO treatment alone compared with conventional chemotherapy alone, and that AE costs are not substantially changed by the addition of IO treatment to chemotherapy. Interestingly, Korytowsky et al. (2018) found that total cost of care, hospitalizations, and ED visits were each significantly lower in the period after approval of IO treatment for NSCLC compared with the preapproval period.3 Taken together, the current evidence raises the possibility that IO treatment of patients with NSCLC could favorably affect total health care costs despite higher drug costs.Although the high cost of immuno-oncology agents has led to concerns regarding the potential economic burden of treatment with these drugs,This study faced several limitations. Certain variables that influence the choice of NSCLC therapy, such as performance status, were not available in the database; this may have resulted in unmeasured confounding. Mortality may have been underestimated as not all deaths are identified in claims or Social Security data. The IO cohort had a higher mean age than the other cohorts, suggesting that patients who are more frail may have been channeled to the IO cohort; however, the IO cohort was still less likely to experience AEs.It was not possible to differentiate the cost of individual AEs for patients who had claims with codes for more than 1 AE. For these patients, costs were counted separately toward the total costs of both AEs, which may have caused slight overestimation of costs for some AEs. Overlap between infections and other AEs was particularly common, with 61.3% of patients hospitalized with infection also having evidence of another AE during the hospitalization. In a subanalysis, costs for hospitalizations that included both infection and another AE were higher than those for hospitalizations for either infection or the other AE independently (data not shown).This study relied on diagnosis codes to identify mNSCLC and determine the presence of each AE; therefore, any coding errors may have resulted in misclassification of patients with NSCLC or AEs of interest, and medical claims may not have captured all AEs that occurred. Furthermore, because causality cannot be determined using claims data, the presence of a diagnosis code occurring after a cancer therapy does not guarantee that the associated condition was caused by the therapy. The effect of this limitation was minimized by looking for diagnosis codes for specific AEs known to be related to the therapies in our study.Finally, because this analysis was conducted in a managed care population, the results may not be generalizable to other populations .Among real-world patients initiating nontargeted first-line therapy for mNSCLC, those receiving immunotherapy experienced fewer AEs and had lower total AE-related costs than those treated with cytotoxic chemotherapy. Furthermore, patients treated with immunotherapy were no more likely than patients treated with chemotherapy to incur AE-related costs and, in fact, were less likely to have high AE costs if they incurred any at all. These findings indicate that IO-related AEs are not a differentiating factor in cost of care for patients receiving first-line treatment for mNSCLC in clinical practice.


Autoantibodies to the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) and leucine-rich glioma-inactivated 1 (Lgi1) are associated with autoimmune encephalitis. We described an acetylcholine receptor (AChR)-positive patient with myasthenia gravis who developed limbic encephalitis with antibodies to AMPAR and Lgi1.A single-case report with detailed, prospective clinical and biomarker data including serial laboratory testing and histopathology.A 49-year-old woman was diagnosed with anti-AChR antibody-positive generalized myasthenia gravis in 1983. After 9 months of the removal of thymoma in 1984, she developed influenza-like symptoms and then symptoms of limbic encephalitis. Retrospective analysis of serum showed high concentrations of anti-AMPAR and lower concentrations of anti-Lgi1 antibodies. Cerebral CT was normal, EEG showed bifrontal dysrhythmia, and CSF showed mild pleocytosis. Immuno-histochemical examination of the thymoma confirmed staining for Glur2, a subunit of AMPAR. The patient recovered with mild sequelae, but low levels of anti-AMPAR and anti-Lgi1 antibodies were detectable for over 25 years subsequently.This case confirms earlier reports of AMPAR-associated autoimmune encephalitis co-occurring with thymoma and myasthenia gravis and is unique in its observational length. It shows, moreover, that antibodies to AMPAR and Lgi1 can persist despite clinical recovery. The latter can also be associated with a broad array of neuroglial antibodies linked to autoimmune encephalitis .We present a retrospective, single-case report of generalized myasthenia gravis with thymoma complicated by limbic encephalitis several months following the initial treatment of myasthenia. Retrospective serum testing showed high levels of autoantibodies targeting the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) and lower levels of antibodies to the leucine-rich glioma-inactivated 1 (Lgi1). Despite recovery, this patient continued to have low levels of neuroglial autoantibodies that did not appear to be associated with a higher risk of relapse.2.A previously healthy 49-year-old woman was diagnosed with myasthenia gravis with elevated levels of antibodies to the AChR in 1983. Investigation revealed a thymoma, and she underwent a thymectomy in 1984 with a complete macroscopic removal of the thymus and thymoma. Histological examination showed a focal lymphoepithelioma in an otherwise normal thymic gland. She was treated with a combination of oral prednisolone and azathioprine as well as pyridostigmine. She also received a single series of plasma exchanges following the thymectomy to prevent disease relapse.3, normal <5/mm3), normal IgG concentration, and no oligoclonal IgG bands. On the presumptive diagnosis of autoimmune encephalitis, she was treated with plasma exchange. Her cognitive symptoms improved dramatically although her antegrade affection persisted for approximately 6 months. The following year she had a recurrence of amnesia affecting short-time memory that improved markedly with plasma exchange. Subsequently, she remained well and was able to live independently despite mild memory difficulties.After 9 months of thymectomy, she experienced influenza-like symptoms and within days, she developed cognitive decline with amnesia that progressed over the course of a few days. On hospital admission, she was fully alert and cooperative but had both anterograde and retrograde amnesia. Neurological examination was otherwise normal. Neuropsychological assessment demonstrated marked defects in information retention, learning, and spatial orientation. Cerebral CT was normal, but EEG showed episodes of bilateral rhythmic frontal and temporal 2–5 Hz activity. The cerebrospinal fluid showed slight pleocytosis  and moderate staining for Lgi1  . Lymphoe3.This case was first reported in 1989  and re-sWhile earlier case reports have described the co-occurrence of thymomas, myasthenia gravis with AChR-antibodies, and autoimmune encephalitis associated with both AMPAR and Lgi1 antibodies –5, the pRetrospective analysis showed that our patient had high titers of anti-AMPAR and anti-Lgi1 antibodies when she first presented with limbic encephalitis in 1985, but low concentrations (1:10) of the AMPAR antibody were also present the preceding year when she was hospitalized for myasthenia gravis. Low concentrations of such antibodies do not occur frequently in the normal population. This suggests that the increased levels of these antibodies were not a result of the thymectomy but rather that the removal of the thymus and thymoma together with an infection activated an already established pathological immune response.The patient’s thymoma stained strongly for the AMPAR-subunit GluR2 and to a lesser degree for Lgi1. We found a similar staining pattern in three thymomas from patients with no encephalitic serum antibodies suggesting that AMPAR and GluR2 represent self-antigens in the thymoma as part of negative T cell selection. Whether the AMPAR and GluR2 antigens in thymomas associated with autoimmune encephalitis differ from those present in subjects without autoimmunity is unknown, we know that patients with paraneoplastic cerebellar degeneration have genetic alterations in Yo-antigens in their ovarian tumors . We knowOur analysis of patient samples collected over a 25-year period represents the longest longitudinal observation of AMPAR and Lgi1 antibodies documented. Our findings highlight the potential risk of multiple autoantibody associations, including that between limbic encephalitis and thymoma. In our patient, anti-AMPAR antibody levels increased after thymectomy, and a viral infection could have been a precipitating factor for limbic encephalitis. Following recovery, low levels of autoantibodies could be detected for 25 years without any signs of clinical progression. This suggests that low levels of these antibodies are not an indication of ongoing autoimmune encephalitis, but rather a marker of a previous episode. This contrasts with recent findings where persisting autoantibodies to the N-methyl-D-aspartate receptor (NMDAR) in patients with NMDAR-encephalitis were associated with a higher risk of relapse .The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the patients/participants or patients/participants’ legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.MN, CV, and NG contributed to the conception and design of the study. MH organized the database. HH contributed to histopathological data. All authors contributed to the manuscript revision, and read and approved the submitted version.


The widely accepted standard of care for chronic cutaneous sarcoidosis is corticosteroids. However, when this treatment is shown to be refractory, other interventions must be considered. In this review, we report the current progress of clinical studies on various monoclonal antibody therapies and their future potential as primary interventions for refractory cutaneous sarcoidosis.In this systematic review, clinical studies on the management of refractory cutaneous sarcoidosis were retrieved from PubMed and ScienceDirect databases. Studies were screened based on article type, publication within the last 10 years, and access to free full text. The articles selected consisted of case studies, clinical trials, and observational studies. The studies needed to focus on cases of diagnosed cutaneous sarcoidosis at the time of the study and involve adult patients resistant to corticosteroid regimens, with or without additional immunomodulators. Only interventions that included tumor necrosis factor-alpha (TNF-α)  or Janus kinase/signal transducers and activators of transcription (JAK/STAT)  antibody therapy were considered. Two authors independently conducted quality assessments using the Joanna Briggs Institute Critical Appraisal and NIH Study Quality Assessment tools.A total of 16 clinical studies were included in this systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram. Of the 16 cases included, 15 studies demonstrated partial to complete resolution of cutaneous lesions within a range of two weeks to 18 months from initiation of antibody therapy. Studies on anti-TNF-α intervention demonstrated the most adverse events, including two deaths and one case associated with cutaneous exacerbation. Studies on anti-JAK-STAT interventions demonstrate no adverse events after treatment; however, patient study size was limiting.Recent studies have shown promising potential for anti-TNF-α and anti-JAK-STAT inhibitors to become the mainstay interventions in refractory cutaneous sarcoidosis. Due to limited population studies, the current data on the efficacy and safety of antibody therapies have not yielded a standardized FDA-approved steroid-sparing treatment. Therefore, a need for more population studies on the effectiveness of third-line intervention in refractory cutaneous sarcoidosis is necessary. Sarcoidosis is a chronic multisystem disorder characterized by noncaseating granulomatous inflammation . The higMethodThis systematic review gathered and screened information using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines from PubMed and ScienceDirect databases. Articles were searched based on a keyword mesh for the initial research strategy. Criteria for including clinical studies in the review were based on a set timeline, article type, and the availability of free full texts from the databases. In our exclusion process, we screened articles using the keywords "adalimumab and cutaneous sarcoidosis," "infliximab and cutaneous sarcoidosis," "tofacitinib and cutaneous sarcoidosis," and "ruxolitinib and cutaneous sarcoidosis."Articles were excluded if they did not fall within a 10-year publication period from 2013 to 2023, provided free full access to text, and consisted of case reports, case series, randomized or non-randomized clinical trials, or observational studies. Selected articles were organized using ENDNOTE software, and duplicate articles were removed manually.The inclusion criteria for this review required studies that consisted primarily of adult patients, confirmed diagnosis for chronic CS, reported history of resistance to corticosteroid or secondary immunomodulator, and patients receiving either anti-TNF-α  or anti-JAK-STAT (tofacitinib and ruxolitinib) antibody therapy. Clinical outcomes for therapeutic interventions in the studies were reported based on changes in physical exam findings, the timeline of improvement from the initial treatment, pre-post diagnostic analysis, and scaled using the Cutaneous Sarcoidosis Activity and Morphology Instrument (CSAMI) assessment tool.Two authors independently assessed the quality of the research studies selected for this review using the Joanna Briggs Institute Critical Appraisal and NIH Quality Assessment tools.ResultUsing the PRISMA guidelines, we initially screened 19 articles. Six were removed based on the inclusion and exclusion criteria Figure  12-28].-28.12-28In this review, our study populations included adult patients with either CS alone or as a manifestation of systemic sarcoidosis. Patients were treated with either anti-TNF-α  or anti-JAK-STAT (tofacitinib or ruxolitinib) inhibitors. These treatments were administered either as stand-alone therapies or in combination with corticosteroids and second-line immunomodulators. In some cases, they were introduced as alternate therapies when corticosteroids and second-line immunomodulators failed to clear cutaneous lesions. The mechanisms of action for anti-TNF-α and anti-JAK-STAT therapies are depicted in Figure Infliximab is an anti-TNF-α monoclonal antibody therapy that has shown the most efficacy as a third-line intervention in recent years. Two studies among those reviewed reported on the clinical outcomes of infliximab therapy in patients with refractory CS. The studies included one retrospective and one retrospective-prospective observation, with no control group in either study. In the study by Sakkat A et al., 33 patients with refractory systemic sarcoidosis were treated with infliximab and prednisone. Of the 33 patients, 15 were identified with refractory CS and received an infliximab regimen of 3-5 mg/kg at 0, 2, and 6 weeks. The infliximab regimen was prolonged for four to six weeks in patients with varied clinical responses. By the end of the study, there was a reduction in prednisone need by 50% in the total patient population. Of the 15 patients with refractory CS, there was a 91.7% resolution of CS lesions . SeventeDiscussionThe diagnosis of CS requires a punch or incisional wedge biopsy . A positVarying triggered events can cause the chronic inflammatory condition seen in CS, but the primary cause has not been well defined. Over the decades, scientists have argued that environmental and genetic factors may contribute to the development of CS , 2, 4, 7Genetic predisposition plays an essential role in symptom variability and clinical response to treatment. Several key findings should be noted when examining multiethnic populations with variability seen in the clinical presentation of sarcoidosis. Past studies have identified that patients of African-American ancestry are commonly diagnosed about 10 years earlier than patients of European-American ancestry due to the early onset of symptoms , 36. StuThe prognosis of CS can also vary among patients. Mild presentations of CS can resolve spontaneously. In a more moderate-to-severe case, corticosteroid monotherapy is the standard of care. However, long-term use of corticosteroids has been linked to various comorbidities and can significantly hinder the patient's quality of life. These adverse effects include weight gain, hypertension, behavioral changes, diabetes, osteoporosis, recurrent infections, and worsening of pre-existing comorbidities , 47, 48.One study reviewed adalimumab interventions that demonstrated CS exacerbation. The combination regimen this patient was on while receiving adalimumab differed from the therapeutic interventions seen in all the other adalimumab studies. Genetic predisposition and medical cross-reactions should be taken into account when comparing the results of this intervention to similar studies. Additionally, the study population size for infliximab and adalimumab was limited, making it challenging to demonstrate significant efficacy and safety evidence for the treatment of refractory CS. These limitations underscore the need for further research in this area of study.Similar to the TNF-α pathway, the JAK-STAT pathway is a cell signaling cascade that the immune system commonly regulates, particularly during interferon-gamma-mediated inflammatory responses. Recent studies on refractory CS indicate that JAK-STAT inhibitors, such as tofacitinib and ruxolitinib, can offer a more localized intervention, reducing the risk of adverse events observed with other third-line interventions. In this review, we highlight ten studies that show partial to complete resolution of refractory CS lesions using these therapies.The genes that regulate the JAK-STAT pathway demonstrate genetic polymorphism that can influence variability in the clinical response of the study population. The majority of patients experience complete resolution of CS lesions within a year of initiating treatment, but the time of response greatly varied. Although the sample size review was small, none of the studies reported adverse events in the patients treated. The JAK-STAT inhibitors could be a superior intervention for refractory CS. However, larger study populations will be needed to address this question.LimitationsMany cases reviewed demonstrated the potential for anti-TNF-α and anti-JAK-STAT inhibitors to become the mainstay monotherapy for refractory CS. Our exclusion and inclusion criteria for articles included in our review were limited, particularly those with free open-access articles only. In addition, several cases were case reports, as larger sample sizes for case series, clinical trials, and observational studies were limited.Third-line modulators must be considered when corticosteroids and second-line therapies are insufficient in keeping cutaneous sarcoidosis in remission. This review reported on the current clinical outcomes of refractory CS interventions. Due to limited population studies, the data on the efficacy and safety of steroid-sparing agents have yet to yield a more standardized alternative for refractory CS therapy. However, recent studies have shown promising potential for anti-TNF-α and anti-JAK-STAT inhibitors to become the mainstay monotherapy. However, in some studies, anti-TNF-α inhibitors demonstrated a variety of adverse events, including one cutaneous exacerbation. On the other hand, anti-JAK-STAT inhibitors show more consistent clinical outcomes with complete remission, reduction in steroid need, and no reported adverse effects. However, the sample size for these studies needs to be improved. Therefore, more extensive population studies are needed on the effectiveness of third-line intervention for moderate to severe CS.


Adherence to biologic disease-modifying antirheumatic drugs (bDMARDs) among patients with rheumatoid arthritis (RA) is often suboptimal in routine clinical practice. Low or nonadherence can reduce the effectiveness of bDMARD therapies.To evaluate filling of newly prescribed initial bDMARDs for the treatment of RA and evaluate potential for characterizing treatment decisions and patient outcomes.In this retrospective cohort analysis, patients aged ≥ 18 years with an RA diagnosis (ICD-9-CM code 714.xx) were selected from a de-identified database of clinical information from the Electronic Health Record  database linked to health care claims (Optum) from commercial and Medicare Advantage health plans (2007-2013). The first biologic prescription date in EHR was the index date. Patients were categorized as filling the prescription within 30 days (early fillers), 31-180 days (late fillers), or not at all within 180 days (nonfillers) of index date.Of 373 patients meeting inclusion criteria, 170 (45.6%), 59 (15.8%), and 144 (38.6%) were categorized as early fillers, late fillers, and nonfillers, respectively. Most prescriptions were written or ordered for tumor necrosis factor inhibitors (88.7%). Compared with late and nonfillers, early fillers were younger and more likely to be female, with higher pain scores (among those reporting pain scores) and RA severity scores pre-index, and filled more prescriptions for any reason pre-index. More nonfillers (66.0%) were Medicare patients than early (17.7%) and late (35.6%) fillers. During days 0-30 post-index, conventional synthetic DMARD use was greatest for early fillers (45.9%) and lowest among nonfillers (24.3%); however, during days 31-180 post-index, the proportion was highest for late fillers (61.0%) and lowest for nonfillers (35.4%). Of early fillers, 12.9% did not fill/receive a bDMARD after 30 days. Only 23 patients had pre/post-index pain scores, and 47 patients had a rationale for stopping or not filling a bDMARD. In patients with pharmacy and medical coverage for 180 days post-index, early fillers had greater RA-related pharmacy and medical resource use and costs than late and nonfillers combined.These findings confirm a high rate of primary nonadherence to bDMARDs among patients with RA. What is already known about this subjectAdherence is a general concern for pharmacotherapy; in rheumatoid arthritis (RA), adherence to disease-modifying antirheumatic drugs (DMARDs) is often suboptimal.Low adherence or nonadherence can reduce the effectiveness of any therapy, including DMARD therapies, leading to suboptimal treatment response, delayed recovery, disease progression, and the need for more aggressive or additive treatments with the potential for adverse events.Nonadherence rates among patients receiving DMARDs in RA typically range from 41% to 75%.What this study addsMore than 50% of patients with RA who were prescribed injectable biologic DMARDS  did not fill the bDMARD prescription via a pharmacy or receive a bDMARD administration in outpatient/inpatient settings within 30 days of the index prescription; by 180 days post-index, more than 40% of patients had not yet filled or received a prescription for a bDMARD.Health care resource use and costs were highest for patients who filled a prescription or received a bDMARD within 30 days of the index prescription during short-term observation.1Rheumatoid arthritis (RA) is a chronic and debilitating autoimmune disease characterized by persistent synovitis, systemic inflammation, and joint destruction in most patients, particularly those undertreated or untreated. Early diagnosis and effective treatment with disease-modifying antirheumatic drugs (DMARDs) is important in improving treatment outcomes.2 Because bDMARDs cost substantially more than csDMARDs,3 they are recommended by the American College of Rheumatology (ACR) and the European League Against Rheumatism (EULAR) for use in patients who have previously failed csDMARD treatment. bDMARDs are infused or injected (by syringe or prefilled auto-injector) as monotherapy or with csDMARDs.5 bDMARDs can be used as first-line therapy in DMARD-naive patients with highly aggressive, erosive disease,5 or in patients for whom csDMARDs are contraindicated.Although conventional synthetic DMARDs  remain the cornerstone of RA pharmacotherapy, biologic DMARDs (bDMARDs) have revolutionized treatment in recent years, improving signs and symptoms and slowing/inhibiting structural damage with a well-characterized safety profile.Five classes of bDMARDs are available for the treatment of RA. Tumor necrosis factor inhibitors (TNFi) constitute the largest group, which includes etanercept, infliximab, adalimumab, certolizumab pegol, and golimumab. bDMARDs with alternative mechanisms of action include anakinra (interleukin [IL]-1 receptor antagonist), tocilizumab (IL-6 receptor antagonist), abatacept (cytotoxic T lymphocyte antigen [CTLA]-4 immunoglobulin), and rituximab (anti-CD20 B cell antagonist).7 with the World Health Organization reporting that < 50% of patients take medications as prescribed.8 In addition, up to 30% of prescriptions in the United States are never filled,9 costing the health care system $100 billion to $300 billion annually.11 Low adherence or nonadherence can reduce the effectiveness of any therapy, including bDMARD therapies, leading to suboptimal treatment response, delayed recovery, disease progression, and the need for more aggressive or additive treatments with the potential for adverse events.12 Frequently, health care providers are not given full disclosure when the patient reduces the dose, which may lead to unnecessary exposure to co-medications or dose/frequency adjustments.Adherence to chronic therapy is often suboptimal in clinical practice,13 Furthermore, patient beliefs about treatment have been shown to influence adherence to medication. A recent review by Horne et al. (2013) reported that interventions to optimize adherence were more likely to be effective if they considered patients’ beliefs about their illness and treatment and how they assess their need for the medication relative to concerns about the potential adverse effects of taking it.14Several factors influence patient adherence to therapy, including patient-related factors , therapy-related factors , and physician-related factors .15 Although several studies have used U.S. prescription claims data to specifically evaluate nonadherence to bDMARDs among patients with RA,19 these analyses evaluated secondary nonadherence rather than primary nonadherence.Medication nonadherence can be categorized as primary nonadherence, which occurs when a patient does not fill the index prescription, or secondary nonadherence, which occurs when a patient discontinues therapy after filling the index prescription.The purpose of this exploratory analysis was to evaluate the filling of newly prescribed initial bDMARD therapies for RA and to characterize patient outcomes in a real-world setting.This was an exploratory, retrospective cohort analysis of de-identified data from the Humedica Electronic Health Record (EHR) database linked to health care claims (Optum) from commercial and Medicare Advantage health plans during 2007-2013. Linked data were required to evaluate prescriptions by the physician and subsequent filling via a pharmacy, as well as in-office administrations. This linked dataset provides an objective assessment of gaps in treatment patterns.21The longitudinal clinical repository is derived from multiple large health care provider organizations treating patients throughout the United States. EHR data are aggregated directly from providers and include multiple EHRs across the continuum of care, both inpatient and ambulatory, to provide a comprehensive clinical overview that includes medications, laboratory results, vital signs, physician notes, diagnoses, procedures, demographics, hospitalizations, and outpatient visits. Once aggregated, data are normalized, validated, and de-identified. The data are certified as de-identified by an independent statistical expert following the statistical de-identification rules of the Health Insurance Portability and Accountability Act (HIPAA) and managed according to customer data use agreements.Humedica data files contain 2 broad classes of information relevant to the current analysis: unstructured data extracted from physician, pathology, and radiology notes and clinical reports, and structured (coded) data, consisting of demographic, clinical, and operational facts. Terms are extracted from unstructured data using proprietary software that conducts a context-sensitive search for researcher-specified terms and modifiers in a similar manner to the Mayo Clinic cTAKES system. Structured items and natural language processing (NLP)-derived terms are associated with patient records and observation dates, allowing longitudinal, within-patient tracking. The NLP system uses vocabulary from the Unified Medical Language System, which includes the Logical Observation Identifiers Names and Codes, Systemized Nomenclature of Medicine—Clinical Terms, and RxNorm.Patient-reported pain scores are recorded during discrete health care provider interactions. Providers may use different methods, including the Visual Analogue Scale  and the Wong-Baker FACES Scale , to solicit patient measures. Pain scores may be recorded in structured data elements of EHR or harvested from notes using NLP.21 The integrated dataset leverages a proprietary Optum algorithm that uses both salting and cryptographic hashing.Claims data were linked by Optum for a subset of patients in the Humedica EHR who were members of Optum’s affiliate national insurer. The Optum DataMart is an integrated database consisting of enrollment, inpatient and outpatient medical claims, pharmaceutical claims, and laboratory results. Optum’s integrated claims-clinical dataset is statistically de-identified under the Expert Determination method consistent with HIPAA and managed according to customer data use agreements.International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] code 714.xx) who had a written prescription or order for their first injectable (self-injectable or infusible) bDMARD  in EHR. Index was the date of the first written prescription or order for a bDMARD during the period 2007-2013.Eligible patients were aged ≥ 18 years (at index) with ≥ 2 outpatient visits or 1 inpatient diagnosis of RA  if (a) administrative data showed the prescription was filled within 30 days of the index bDMARD prescription date (hereafter referred to as the early biologic filler cohort); (b) if administrative data showed the prescription was filled within 31-180 days of the index bDMARD prescription date (hereafter referred to as the late biologic filler cohort); or (c) administration data showed that the prescription was not filled at all within 180 days of the index bDMARD (hereafter referred to as the nonfiller cohort).22 prescribing patterns for RA, and patient-reported pain scores  from EHR were assessed across all patients. In addition to bDMARDs, csDMARD prescribing patterns included methotrexate, sulfasalazine, hydroxychloroquine (or chloroquine), and leflunomide, as well as immunosuppressive agents , gold compounds, and other related medications . Change in pain scores (≥ 30 days pre- and ≥ 30 days post-index) were evaluated in the subgroup of patients with pain scores recorded in EHR.Patient baseline characteristics, including the claims-based index of RA severity ([CIRAS]: 0 [low]-10 [high]),Humedica uses NLP to parse physician notes and identify the rationale behind prescribing decisions. This information is provided in the context of a drug action  and reason. The reasons for drug actions range from side effects  to access  and efficacy . All information is derived from physician-written patient notes . Treatment rationale for stopping (early biologic fillers and late biologic fillers) or not filling (nonfillers) medication was assessed in the subgroup of patients for whom a reason was recorded in the physician-written patient notes.Six-month, post-index, all-cause, and RA-related (any visit with ICD-9-CM code 714.xx or DMARD medication) costs, health care resource use (HCRU), and out-of-pocket costs, as identified within claims, were assessed in patients with both continuous medical and pharmacy coverage. Post-index total RA costs were adjusted using a generalized linear model that assumed gamma-distributed data and used a log link. As limited information has been published on primary nonadherence with bDMARDs in RA, independent variables were identified a priori for inclusion based on clinical expertise and included demographics, such as age at date of bDMARD prescription, sex, race, and Census Bureau region. Variables also included potential indicators of risk/severity, such as baseline CIRAS score, death, number of pre-index prescriptions, use of TNFi or non-TNFi bDMARDs, and any use of csDMARDs (pre- or post-index). Other variables were potential access barriers, including average household income imputed based on 3-digit ZIP code and insurance  and commercial or Medicare Advantage; potential indicators of aversion to injectable medications with use of outpatient injectable medications during 180 days pre-index; and post-index classification as an early biologic filler, late biologic filler, or nonfiller.P value was ≤ 0.20, it was kept and the final model was fit, including all such independent variables. In the second step , 1 observation was excluded due to a missing value in the baseline RA severity score. Otherwise, statistical significance was declared at P ≤ 0.05. The point estimates and corresponding standard errors (SEs) were inversetransformed from the log scale for reporting here.The model was fit in 2 steps. In the first step, each of the independent variables was assessed by having it as the only variable in the model; if the In total, 373 patients were included in the analysis . Of thesPatient baseline characteristics are presented in Compared with late biologic fillers and nonfillers, early biologic fillers were younger and more likely to be female with higher pain and RA severity scores pre-index, and they filled more prescriptions for any reason pre-index . CompareA summary of index bDMARD prescriptions is presented in The majority of early biologic fillers (97.1%) and late biologic fillers (81.4%) filled or received a prescription that matched the index TNFi or non-TNFi prescription. Among early biologic fillers, 2.4% (TNFi index) and 0.6% (non-TNFi index) filled or received a prescription that did not match the index prescription. A small proportion of early biologic fillers (12.9%) did not fill or receive a bDMARD during days 31-180 post-index . Among lPrescriptions for csDMARDs were filled by 57.9% of patients during days -1 to 180 pre-index; 36.2% of patients during days 0 to 30 post-index; and 50.1% of patients during days 31 to 180 post-index . During Patient reasons for stopping medication (early biologic and late biologic fillers) or not filling medication (nonfillers) were available for 47 patients and are presented in Only 23 of 373 (6.2%) patients had pre- and post-index pain scores. The mean (SD) change in pain score was -1.6 (3.6) for early biologic fillers , 0.6 (5.5) for late biologic fillers , and 1.1 (3.2) for nonfillers .Among 373 patients with pharmacy and medical coverage for 180 days post-index, the 6-month, unadjusted mean (SD), all-cause total costs were $18,260  for early biologic fillers versus $13,113  for late biologic fillers and $6,334  for nonfillers. Six-month, unadjusted mean (SD), total RA-related costs were highest for early biologic fillers  versus late biologic fillers  and nonfillers  of patients who were prescribed initial bDMARDs, most of which were TNFi, did not fill the prescription or receive a bDMARD within 30 days of the index prescription; by 180 days post-index, more than one-third (38.6%) of patients had not yet filled or received a bDMARD. Additional analyses indicated that 56.9% of nonfillers did not have a csDMARD in the pre- and post-index periods. This raises the question of whether nonfillers proceed long-term without the benefits of an effective DMARD to halt disease progression. Another important factor is whether these patients self-medicate with over-the-counter, nonsteroidal antiinflammatory drugs, prescription selective cyclooxygenase 2 (COX-2) inhibitors, or opioid analgesics, each of which has its own risks.The results reported here are in agreement with previous outpatient studies suggesting that primary nonadherence is a significant issue among patients with RA.25 Although not evaluated in this study, an understanding of the impact of the coverage gap in Medicare patients may also be warranted. Hopson et al. (2014) found that patients meeting the catastrophic coverage limit and using a specialty pharmacy had a decreased likelihood of abandoning bDMARD therapy.25 Furthermore, in our study, almost 20% of late biologic fillers had filled or received a bDMARD medication that was different from the index TNFi prescription, perhaps suggesting time for coverage decisions  that may have resulted in the need to switch treatments or receive bDMARDs in a different setting. This may be particularly important in considering low-income subsidy and dual-eligible patients who were not included in the study by Hopson et al. and cannot be easily identified in the current study database.To determine the reasons for primary nonadherence, we evaluated treatment rationale information extracted via NLP. Although the reasons for not initiating treatment or switching treatment were rarely documented in EHR, several reasons may be considered, including patient out-of-pocket costs, particularly for the Medicare population. Late biologic fillers and nonfillers were more likely to have Medicare coverage compared with early fillers. Previous research has suggested that patient out-of-pocket costs are significantly associated with bDMARD abandonment in Medicare patients with RA.26 Interestingly, late biologic fillers had the lowest proportion of patients with pre-index injectable medications, followed by nonfillers. Patient preference may also be affected by disease severity, as suggested by the fact that early biologic fillers had the highest disease severity and pain scores and were most likely to have received prior csDMARD therapy versus late biologic fillers and nonfillers. Furthermore, fear of needles may also play a role in patient primary nonadherence. In a recent research survey conducted to assess the preference of patients with RA (N = 310) for a needle-free device versus a needle-based device, 45% of patients reported a “needle phobia.”27 In this analysis, however, only 2.1% of physicians (N = 373) reported a fear of needles in their patients.Patient preference for noninjectable treatments may be another reason, as supported by research in a commercial population that suggests route of administration is the most important factor for patients when they consider whether to initiate bDMARDs.19 However, in contrast with the analysis reported here that evaluated primary nonadherence, all of the studies evaluated secondary nonadherence. Although this study did not evaluate secondary nonadherence, 12.9% of early fillers did not have a bDMARD fill or administration during days 31-180. Furthermore, although the concurrent use of csDMARDs has been shown to have a beneficial effect on bDMARD adherence and clinical outcomes, more than 40% of early biologic fillers did not receive a csDMARD during days 31-180 post-index. Another important limitation of the studies is that they did not evaluate the relationship between adherence and clinical response. Consequently, EULAR recently recommended that the questions, “How good is patient adherence to biologic agents, and can a lack of adherence be related to loss of efficacy?” be included in a future research agenda.5Several studies have used U.S. prescription claims data to specifically evaluate adherence to bDMARDs among patients with RA.28 By contrast, in this primary nonadherence study, HCRU was found to be greater for adherent patients than for nonadherent patients during short-term observation. This is likely attributed to the short (6-month) observation window, as one source of direct medical costs is the need for hospitalizations for orthopedic surgery or nursing home admissions, which may occur much later in the course of disease, although geographic variation is also common.29 Furthermore, this study was not designed to evaluate indirect costs attributed to lost productivity. Indirect costs can exceed direct medical costs often by a factor of 3-4.30 Treatment with bDMARDs, such as TNFi, has been shown to be associated with a cost per quality-adjusted life year < $50,000 (cost-effective), without accounting for the impact on indirect costs.29Few studies have evaluated economic outcomes associated with nonadherence to bDMARDs in patients with RA. However, the findings reported to date in secondary nonadherence studies suggest that although greater pharmacy costs are the main driver of total health care costs among adherent patients in the 1-year period after treatment initiation, nonadherent patients incur greater HCRU, including inpatient and outpatient visits as well as laboratory services.The analysis reported here provides insight into adherence to bDMARDs based on a small group of retrospectively identified patients with RA; however, like all EHR- and claims-based analyses, several limitations must be considered.Although patients were selected based on the presence of an RA diagnosis, it is possible that the bDMARDs were prescribed for other reasons. Because of concerns regarding the limited size of the patient population with integrated data, and given that the analysis focused on primary nonadherence, which can occur irrespective of the diagnosis, no additional exclusion of other conditions for which bDMARDs may be prescribed or administered was implemented. Similarly, a 6-month pre- and post-index period was selected for evaluation and may have resulted in misclassification of bDMARD experience and limited evaluation of the longer-term consequences of primary nonadherence. However, requiring ≥ 12 months of observation in EHR decreased the initial population by approximately two-thirds, upon which patients required overlapping claims enrollment, further substantially reducing the remaining cohort. Thus, extending the pre- and post-index periods is warranted in future analyses of a larger population.EHR data are not intended for research use and are limited by the physician’s challenges in using complex and time-consuming EHR platforms while balancing large volumes of patients and providing ample time for patient care. Thus, key data are often missing, particularly multidimensional clinical measures of severity or outcomes. In particular, availability of at least 2 pain scores was limited to only 6% of the study cohort; thus, generalizability of the change in pain score findings is not possible in the current study and serves only as hypothesis-generating to support future research efforts. Similarly, reasons for discontinuation or not filling a bDMARD were found in approximately 13% of patients and are not generalizable to other patients or settings. This further highlights the challenges of using existing EHR, particularly physician notes. Advanced methods such as NLP can assist in overcoming the time and costs of manual chart abstraction but cannot address a limited yield due to underreporting. Physician incentives, such as Meaningful Use and pay for performance, are expected to improve documentation in EHR for selected measures per disease. In addition, the ability to link claims, EHR, and other data sources in the future will help to address current gaps.Claims data are collected for payment processing; therefore, a claim does not indicate that the patient took the medication. A period of no claim may not indicate nonadherence but may be due to temporary discontinuation of therapy because of illness. Coding errors could also affect the ability to detect all relevant HCRU. Regarding costs, the charged or requested amount billed by the provider was used as the cost in this analysis, although this value may be highly variable, since it often has little relationship to the actual amount paid.31 Future research should focus on population-level, prospectively collected cohorts to evaluate the long-term consequences of undertreatment on clinical and economic outcomes.These findings demonstrate that among the RA patient cohort studied, overall adherence to bDMARDs is suboptimal, and primary nonadherence may be occurring at a rate not recognized by clinicians. Treatment adherence assessments before and after regular follow-up visits could enable practicing clinicians to manage patients effectively, and importantly, reduce rates of primary nonadherence. Furthermore, there is a need to implement strategies to assess treatment efficacy to optimize quality and control costs. ACR currently recommends 6 disease activity measures, including the Clinical Disease Activity Index, Disease Activity Score with 28-joint counts (erythrocyte sedimentation rate or C-reactive protein), Patient Activity Scale (PAS), PAS-II, Routine Assessment of Patient Index Data with 3 measures, and Simplified Disease Activity Index.


Do high-flow nasal oxygen and noninvasive ventilation qualify as aerosol-generating procedures?This systematic review of 24 studies and meta-analysis of 5 studies found no evidence that either high-flow nasal oxygen or noninvasive ventilation results in clinically relevant increases in pathogen emission or aerosol production.On the basis of the current evidence, high-flow nasal oxygen and noninvasive ventilation appear not to be aerosol-generating procedures and therefore do not merit differential infection prevention and control measures at this time. This systematic review with meta-analysis evaluates current evidence to determine whether high-flow nasal oxygen and noninvasive ventilation are associated with pathogen-laden aerosols and aerosol generation. Infection control guidelines have historically classified high-flow nasal oxygen and noninvasive ventilation as aerosol-generating procedures that require specialized infection prevention and control measures.To evaluate the current evidence that high-flow nasal oxygen and noninvasive ventilation are associated with pathogen-laden aerosols and aerosol generation.A systematic search of EMBASE and PubMed/MEDLINE up to March 15, 2023, and CINAHL and ClinicalTrials.gov up to August 1, 2023, was performed.Observational and (quasi-)experimental studies of patients or healthy volunteers supported with high-flow nasal oxygen or noninvasive ventilation were selected.Three reviewers were involved in independent study screening, assessment of risk of bias, and data extraction. Data from observational studies were pooled using a random-effects model at both sample and patient levels. Sensitivity analyses were performed to assess the influence of model choice.The main outcomes were the detection of pathogens in air samples and the quantity of aerosol particles.Twenty-four studies were included, of which 12 involved measurements in patients and 15 in healthy volunteers. Five observational studies on SARS-CoV-2 detection in a total of 212 air samples during high-flow nasal oxygen in 152 patients with COVID-19 were pooled for meta-analysis. There was no association between high-flow nasal oxygen and pathogen-laden aerosols . Two studies assessed SARS-CoV-2 detection during noninvasive ventilation (84 air samples from 72 patients). There was no association between noninvasive ventilation and pathogen-laden aerosols . None of the studies in healthy volunteers reported clinically relevant increases in aerosol particle production by high-flow nasal oxygen or noninvasive ventilation.This systematic review and meta-analysis found no association between high-flow nasal oxygen or noninvasive ventilation and increased airborne pathogen detection or aerosol generation. These findings argue against classifying high-flow nasal oxygen or noninvasive ventilation as aerosol-generating procedures or differentiating infection prevention and control practices for patients receiving these modalities. Aerosols, consisting of liquid or solid airborne particles up to approximately 100 μm, have a much longer residence time in the air than larger (respiratory) droplets, which follow a ballistic trajectory under gravitational force. Aerosol emission from the respiratory tract of infected patients has been implicated as an important transmission route for SARS-CoV-2.4 In the early phase of the SARS-CoV-2 pandemic, infection prevention guidelines designated high-flow nasal oxygen (HFNO) and noninvasive ventilation (NIV) as possible aerosol-generating procedures (AGPs).7 This qualification suggested that these noninvasive respiratory support modalities might increase the risk of SARS-CoV-2 transmission to health care workers and therefore advised limiting their use, preferentially placing patients receiving HFNO or NIV in airborne infection isolation rooms and wearing a respirator rather than a medical mask when entering the room of patients with suspected or confirmed infection.10 The guidelines provided little or no data supporting the designation of HFNO and NIV as AGPs, however, which may have led to misdirected resources and confusion.15During the recent worldwide SARS-CoV-2 outbreak, the potential harm for health care professionals working with infected patients received considerable attention.16 Similarly, observational studies of the association between SARS-CoV-2 infections among health care workers and exposures to patients receiving HFNO or NIV are complicated by the difficulty of correcting for multiple potential confounders, including patient respiratory disease severity, viral load, quality of room ventilation, duration of health care worker exposure, proximity to patients, and alternative sources of health care worker exposure, including those outside the hospital.22Ideally, risk stratification for respiratory support modalities should be based on randomized clinical trials assessing associations between their use and health care worker infections. However, such studies have not been performed, and it is unlikely that they will be, given the complexity of randomizing critically ill patients and strained health care staff as well as the difficulty of attributing health care worker infections to specific exposures given the high prevalence of SARS-CoV-2 in the general community.25 but a systematic review with a quantitative synthesis of all experimental and observational aerosol collection studies is currently lacking. We sought to systematically review the literature of studies that investigate the potential for HFNO and NIV to increase pathogen-laden aerosols and aerosol production compared with treating patients without these modalities.The best available evidence at this time to inform whether to classify HFNO and NIV as AGPs are studies quantifying pathogen-laden aerosols and aerosol production by HFNO and NIV. Several reviews on this topic have been published,26 for additional relevant articles. In addition, the CINAHL and ClinicalTrials.gov databases were queried on August 1, 2023. The complete and detailed search strategy is reported in the eMethods in MOOSE) reporting guideline27 and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.28 The protocol of this review was registered before the start of the study in the PROSPERO database (CRD42023408378).The literature search was performed in consultation with an experienced medical librarian (F.S.v.E.-J.). We searched the electronic databases PubMed/MEDLINE and Ovid EMBASE from inception to March 15, 2023, and the most recent systematic National Health Service rapid reviewThe citations were screened independently by 2 reviewers (M.X.Z. and R.A.B.) on title and abstract, and discrepancies were resolved through discussion. Full-text articles were checked independently for eligibility. Eligible studies were those including patients or healthy volunteers receiving HFNO or NIV compared with unsupported normal or labored breathing, low-flow nasal oxygen (LFNO), or oxygen or nonrebreather mask (eMethods in The main outcomes were pathogen-containing aerosols (viable pathogen culturing from air specimens or DNA or RNA detection in air samples) and the number of aerosol particles  smaller than 100 μm. Secondary outcomes were aerosol particle size distribution and pathogen detection in room surface samples.Data were extracted independently by 3 authors  using a structured form. Differences were resolved through discussion. Studies were grouped by patient or healthy volunteer and HFNO or NIV subgroups and summarized by main characteristics, outcome(s), and findings or study conclusions. Risk of bias was assessed as detailed in the eMethods in For reporting main findings for each included study, the most relevant comparisons were summarized by medians (IQRs) or means (SDs) for continuous data. Because sample sizes of all studies were small, and thus likely subject to data skewness, no conversion of medians (IQRs) into means (SDs) was deemed appropriate. For dichotomous data, the studies are summarized using odds ratios (ORs) with 95% CIs or absolute findings.2, as we did not anticipate large differences in sample sizes. Heterogeneity was further assessed by the I2 statistic, along with its uncertainty per 95% CI. A sensitivity analysis was performed by pooling ORs related to the number of patients with at least 1 pathogen-detected surface sample (secondary outcome) out of the total number of patients. Meta-analysis of continuous data  in experimental studies was deemed not appropriate for a combination of reasons, including inherent difficulties related to pooling of (nonrandomized) pre-post effect sizes,29 reported unit(s) and particle sizes of the outcome measurement, and reporting of medians (IQRs) based on skewed data. Publication bias was assessed by funnel plot. Significance was defined as a 2-sided P < .05. Analyses were performed using R software, version 4.2.1  with RStudio, version 2022.02.3 + 492 (RStudio).For the main dichotomous outcome (pathogen detection in air sample) from the included observational studies, data were analyzed per support modality (HFNO or NIV) and compared with control . The data were analyzed by 2 definitions of event: (1) the number of pathogen-detected air samples of the total number of air samples and (2) the number of patients with at least 1 pathogen-detected air sample of the total number of patients to account for dependent data within treatment groups and between-study differences in the number of air samples collected per patient. We expected important between-study heterogeneity, primarily by design, together with sparse data and therefore used a random-effects Mantel-Haenszel model to pool all ORs in our primary analysis. Additional details, models, and post hoc sensitivity analyses are described in the eMethods in 53 remained experimental studies on HFNO that used a crossover design in adult patients; 1 randomized study focused on air and surface contamination of gram-negative bacteria in patients with gram-negative bacteria pneumonia,36 no study found evidence of an association between HFNO and increased airborne viral dispersion relative to unsupported breating, LFNO, or standard oxygen or nonrebreather mask. Meta-analysis of these studies, including a total of 212 air samples from 152 patients, did not show an association between HFNO and pathogen-containing air samples at either the sample level  or the patient level  ; however, these studies36 differed substantially by air sampling methods and timing in relation to COVID-19 disease. Similarly, pooled sensitivity analysis of the studies that investigated potential surface contamination39 did not show an association between HFNO and pathogen-containing surface samples  . Model cP = .71) . The est51 and 1 in children.52 Of these, 9 studies found no statistically significant difference in the concentration of aerosols between HFNO and control treatments.52 In 1 study, no statistical analysis was performed because the data were derived from a single person.51 Four studies found a significant difference between the HFNO and the control groups.50 One of these studies found that increased aerosol concentration associated with HFNO was attributable to very small particles derived from the HFNO machine rather than from the study participants on further review.44 Of the remaining 3 studies, the effect size of the HFNO-induced increase in aerosol particle numbers was very small. For example, Wilson et al50 reported the largest effect: a 2.3-fold increase in particle counts associated with HFNO, but this was very small compared with a 371-fold increase induced by coughing alone without HFNO. One study, in which the investigators sampled air to detect an instilled chemical marker, found a small mean increase in volume for HFNO vs control (6.3 vs 0.0 μL/m3), but this corresponded to approximately 0.5% of the volume recovered during unsupported labored breathing and coughing.46There were 14 (quasi-)experimental studies involving aerosol particle detection in HFNO-treated healthy volunteers: 13 studies in adults53 on NIV differed in use and level of bilevel or continuous positive pressure and use of vented (single limb) or nonvented  face masks. Of the 2 observational studies that investigated air samples for positive SARS-CoV-2 detection from patients with COVID-19,34 neither found evidence of an association between NIV use and increased airborne viral dispersion. Meta-analysis of these studies, including a total of 84 air samples from 72 patients, also failed to show an association of NIV with pathogen-detected air samples either at the sample level  or at the patient level   . Again, P = .24) . The unc53 For example, the mean difference in the number of particles larger than 10 μm per cubic meter was 0.666 to 0.807 particles for patients with NIV compared with unsupported breathing (P = .04), which seems very small when observing the mean difference of 1393 particles during a sequence of physiotherapy-assisted labored breathing and coughing. Furthermore, the study did not correct for multiple comparisons. There were 9 (quasi-)experimental studies assessing airborne particle detection around NIV-treated healthy volunteers.53 Of these, 7 studies found no statistically significant differences in the concentration of aerosols between NIV and control treatments.53 In 1 study, no statistical analysis was performed because the data were derived from a single individual.51 In the study by Wilson et al,50 a 2.6- to 7.8-fold increase in aerosol production by NIV was reported, but this effect was very small compared with a 371-fold increase by a coughing maneuver without NIV.One nonrandomized study involving patients with coryza and acute-on-chronic respiratory disease showed a very small difference for aerosols 3 to 10 μm in vented NIV but not for nonvented NIV.The GRADE  summary of findings is presented in the In this systematic review and meta-analysis, we identified 24 studies that investigated the potential of HFNO or NIV to increase pathogen-laden aerosols or aerosol generation from patients and healthy volunteers. Meta-analysis of observational studies did not show an association between these treatments and increased airborne pathogen detection. In addition, we found no convincing evidence from quasi-experimental studies that HFNO or NIV generates a clinically relevant  increase in aerosol particles relative to unsupported breathing alone or coughing.54 This contrasts with the Centers for Disease Control and Prevention in the US, which currently lists NIV as an AGP and HFNO as a potential AGP.55 Finally, the National Health Service from the UK has omitted HFNO and NIV from their current guideline after their most recent (2022) rapid review, which stated that both treatments should be considered to be taken off the list.56 It has been advocated that the entire concept of AGPs needs to be abandoned.57 For example, personal protective equipment recommendations should be uniform for all suspected and infected patients, and room restrictions should be adapted on a patient-by-patient basis , but this approach may be difficult to implement.58In the current aftermath of COVID-19, the listing of HFNO and NIV as AGPs in national and international infection prevention guidelines is inconsistent. For example, the World Health Organization altered their listing during the COVID-19 pandemic based on evolving insights and has now deleted HFNO as a potential AGP, but NIV remains on their AGP list.26 On meta-analysis, we found no evidence of an association between HFNO or NIV and increased airborne pathogen dispersion. There are no established standard procedures for sampling airborne pathogens. Therefore, data reporting is often incomplete, outcome measures vary, and detection limits are unclear, which makes comparisons between studies difficult. Likewise, no association between HFNO or NIV and increased surface contamination was found. However, surface contamination may be an imperfect measure of pathogen-laden aerosols because surfaces can be colonized by multiple routes and to varying degrees.To our knowledge, this study is the most extensive systematic review with meta-analysis to date, and our findings corroborate previous reports on the topic.59 render HFNO and NIV less likely to be meaningful AGPs.41 Although the majority of studies from our review indeed found no increase in the concentration of aerosol particles by either HFNO or NIV, some studies found clinically questionable but statistically significant increases relative to unsupported breathing, LFNO, or oxygen mask. The reported effect sizes in these studies were very small, however, compared with increases in aerosol generation caused by labored breathing or coughing, suggesting that these symptoms are more reliable guides to aerosol production than respiratory support procedures per se.50Importantly, the main respiratory physiologic mechanisms that explain aerosol emission from the human respiratory tract, including fluid film bursting in small airways and vibration of vocal cords,64 This is because these studies cannot answer the question of whether HFNO or NIV creates a greater risk of generating aerosols from the human respiratory tract. Nevertheless, these studies add to the discussion about proximity and the risk of infectious disease transmission. For instance, it has been advocated that the increased flow velocity and continuous jet by HFNO or NIV lead to particle dispersion that is more widespread over longer distances.25 At the same time, these effects on risk of transmission by airflow would likely be highly similar to situations in which mechanical room ventilation, air conditioning, heat sources, or open windows cause air movements,58 which transport, disperse, and dilute any dense aerosol clouds from patients.For this review, we excluded studies that investigated artificially derived particles  or that solely used computational models.This study has some limitations, including small sample sizes from most of the included studies and a relative paucity of data on pathogens other than SARS-CoV-2. We were not able to perform a meta-analysis on the studies that investigated aerosol particle counts in crossover designs. Furthermore, there was high heterogeneity in the type of aerosol particle detectors, sampling methods, positions, and timing in relation to disease progression, as well as in reporting of units of aerosol measurements and size distribution. We also encountered poor descriptions of relevant experimental room conditions, most notably the number of air changes per hour, pressure settings, and relative humidity, which all influence aerosol dynamics and the accuracy of  particle counters. This heterogeneity and lack of detail limits our conclusions and indicates the need for a more uniform approach in research on this topic. In addition, inclusion criteria for our search regarding the patient or volunteer category, (infectious) disease state, and control treatment were relatively broad, challenging the direct comparison and synthesis of studies. Finally, aerosol detection as well as measurement of pathogen DNA and RNA are imperfect surrogates for the human-to-human transmission risk of viable infectious particles.This systematic review and meta-analysis did not find evidence that either HFNO or NIV should be considered an AGP. Instead, the current literature suggests that both treatments do not increase pathogen-laden aerosols or aerosol generation at clinically relevant levels. Evidently, to avoid pathogen transmission, health care workers exposed to patients with respiratory infections should wear appropriate personal protection and manage their care in hospital room settings appropriate for specific pathogens; however, until further evidence arises, no differential protective measures based on exposure to HFNO- or NIV-treated patients are deemed necessary.