LN examination among eNSCLC patients (pts) is critical in fulfilling the IASLC complete resection criteria and in perioperative chemotherapy decisions. Previous studies have shown that LN non-examination is associated with overall survival rates similar to pts with LN metastasis, presumably due to inadequate adv treatment (tx). This study evaluated the prevalence of LN exam and adv tx in US Medicare eNSCLC pts. This retrospective observational study identified pts with stage IA-IIIB NSCLC (AJCC 7th ed) from SEER data linked with Medicare claims. Pts were ≥65 years at diagnosis between January 2010 and December 2017, had surgery within 1 month prior or 12 months after diagnosis and were continuously enrolled in Medicare Parts A and B ≥6 months before diagnosis. Additional continuous enrollment criteria of Medicare Parts A, B and D ≥6 months post-surgery or up to date of death was required for adv tx outcomes. Pts were grouped by LN exam status: none (pNX), no LN metastasis after LN exam (pN0) or LN metastasis after exam (pN1/2). Adv tx was identified within 6 months or up to death post-surgery. Descriptive statistics were used to summarize results. A total of 14,684 pts were included; 1596 (11%) were pNX, 9943 (68%) were pN0 and 3145 (21%) were pN1/2. The proportion of pNX pts decreased from 14% in 2010 to 8% in 2017. A mean (SD) of 11 (9) LNs were examined (median, 9; IQR, 5-15). Adv chemotherapy was identified in 21% (pNX), 13% (pN0) and 63% (pN1/2) of pts. Wedge resections were performed in 47% (pNX), 18% (pN0) and 11% (pN1/2) of pts. LN examination in Medicare pts with eNSCLC has improved over time with a sufficient number of excised LNs at resection. However, many resections continue to lack LN evaluation and pNX was associated with lower adv chemotherapy utilization rates than pN1/2, which further supports that pNX may negatively impact adv tx decisions.Table: 946PVariable, n (%)pNX n=1596pN0 n=9943pN1/2 n=3145Extent of lung cancer resectionPneumonectomy17 (1)150 (2)218 (7)Bilobectomy<11103 (1)71 (2)Lobectomy255 (16)6149 (62)1985 (63)Wedge resection746 (47)1795 (18)347 (11)Segmentectomy134 (8)873 (9)147 (5)Other surgery237 (15)141(1)71 (2)SurgeryRobotic-assisted thoracic surgery31 (2)307 (3)74 (2)Video-assisted thoracic surgery12 (<1)<11<11Thoracotomy192 (12)502 (5)216 (7)Sternotomy19 (1)21 (<1)32 (1)pNX n=996pN0 n=6476pN1/2 n=1999Received adj txChemotherapy211 (21)846 (13)1255 (63)Immunotherapy<11<1121 (1)Targeted therapy25 (3)43 (1)48 (2)Chemoradiation118 (12)197 (3)494 (25)Radiation245 (25)510 (8)652 (33) Open table in a new tab

RATIONALE: ACE2, a critical SARS-CoV-2 entry receptor, has reduced expression in those with allergic sensitizations. Consequently, SARS-CoV-2 infections may impact patients with allergic asthma (AA) or no evidence of allergic asthma (NEAA) differently. We explore demographics of SARS-CoV-2-infected AA and NEAA patients. METHODS: Retrospective data were obtained from the US-representative COVID-19 Optum Electronic Health Record dataset through 10/15/2020. Index was the earliest date of presumed diagnosis or laboratory-confirmed SARS-CoV-2 infection (CDC guidelines) from 02/20/2020, defined as (1) diagnosis code of U07.1/U07.2, or (2) positive diagnostic test for SARS-CoV-2, (3) diagnosis code of B97.29 without a negative molecular SARS-CoV-2 test within a 14-day window (+/-7 days). Patients SARS-CoV-2-positive with evidence of moderate-to-severe asthma at any time (ICD-10 J45.4X or J45.5X) were included. AA was defined as positive specific IgE (≥0.35 kU/L) serum test or skin prick test (code 95004) ordered by a specialist (eg, allergist, pulmonologist, dermatologist) or omalizumab use. NEAA was defined as failing to meet the AA definition and patients with allergic comorbidities were excluded. Baseline demographic and clinical characteristics were obtained 6-12 months before COVID-19 diagnosis. RESULTS: The database included 242,280 SARS-CoV-2-positive patients;569 (0.2%) had evidence of comorbid AA and 3137 (1.3%) had asthma and NEAA. For AA patients, mean (SD) age at index was 48.2 (18.2) years;70.3% were female, with 54.3% White, 26.4% Black, and 12.5% Hispanic (Table 1). Most AA patients were from the US Midwest and Northeast (80.5%). NEAA patients had similar demographics: mean (SD) age at index was 50.7 (19.5) years;67.6% female;with 60.0% White, 21.5% Black, and 13.0% Hispanic;and 81.5% were from the US Midwest and Northeast. A greater proportion of patients had severe asthma in AA versus NEAA groups (220/569 [38.7%] versus 457/3137 [14.6%]). More patients with AA versus NEAA used asthma biologic treatment (62/569 [10.9%] vs 27/3137 [0.9%]). Comorbid conditions (hypertension, diabetes, pregnancy, chronic obstructive pulmonary disease, and Charlson Comorbidity Index), body mass index, and smoking history were comparable between groups. A higher proportion of NEAA patients were current smokers. CONCLUSIONS: A smaller proportion of patients with SARS-CoV-2 infection in this retrospective analysis had comorbid AA versus NEAA, whereas patient demographics and comorbidities were generally comparable between groups. Differences included the proportion of patients with severe asthma and biologic treatment use (greater in AA), and current smoking (lower in AA). The observed lower prevalence of AA versus NEAA in SARS-CoV-2-positive patients warrants further investigation.

Neuromyelitis optica spectrum disorder (NMO) is a rare auto-immune disease affecting the central nervous system and has clinical characteristics similar to multiple sclerosis (MS), making clinical diagnosis challenging. This study aims to improve the identification of NMO patients by leveraging nferX, a natural language processing platform, to enable encoding of patient claims that are specific to NMO versus MS. Disease phenotypes associated with NMO or MS were identified from the biomedical literature using the nferX platform. Patients with at least 1 NMO or MS diagnosis code were identified in the IQVIA Pharmetrics Plus database. Accompanying diagnosis, procedure, and drug codes present in greater than 0.1% of patients and at least 2-fold more prevalent in either cohort were mapped to nferX-identified phenotypes. These phenotypes’ relative association with NMO versus MS were quantified using nferX’s adaptation of the pointwise mutual information metric. Associations were aggregated into a summary score for each patient from the number of corresponding claims in the year preceding the initial NMO or MS diagnosis claim. Separation of scores between cohorts of NMO and MS patients identified with existing standard algorithms was assessed. A total of 307,166 patients with at least 1 NMO or MS claim between 2006-2018 were identified. 3,132 NMO patients and 102,611 MS patients were selected using previously published algorithms. The Cohen’s d separation of summary scores between these two cohorts was 1.50, suggesting significant separation. By applying a cutoff of one standard deviation above the mean summary score, 14,822 NMO patients were identified, including 13,150 patients without any claims for NMO. Use of the nferX platform has the potential to improve identification of NMO patients from claims data. Further validation of the approach is needed to support its future use.

Patients with pre-existing autoimmune disease (AD) have historically been excluded from most immune checkpoint inhibitor (ICI) clinical trials due to concerns including potential toxicity or decreased efficacy. Real-world data support the use of ICIs for patients with ADs across multiple tumor types, however data are limited. We examined the association between pre-existing AD and ICI treatment outcomes among patients with metastatic urothelial cancer (mUC) in the real-world setting. This was a retrospective analysis of Truven Health MarketScan® Commercial, Medicare Supplemental, and Coordination of Benefits (Medicare) databases. Patients with a primary diagnosis of mUC, ≥18 years old, received ICI for any line of treatment between 1/1/2016 - 6/30/2019, and continuously enrolled in the database from 6 months prior to 1 month following the metastatic date were analyzed. AD was identified at any time prior to ICI therapy initiation. Time to treatment discontinuation was used as a proxy to quantify ICI treatment outcomes. Of the 455 eligible patients, 71 (16%) had a prior AD. Among those with AD, the most common was type 1 diabetes (25%), followed by rheumatoid arthritis (10%) and pernicious anemia (10%), while 28% had a history of two or more ADs. Patients with vs. without prior AD were older (mean age 70.4 vs. 66.5; p<0.001) and had a higher co-morbidity burden. There was a shorter median unadjusted time to ICI treatment discontinuation among patients with a prior AD (6.82 months; 95% CI=3.93-29.02) vs. without (8.13 months; 95% CI=6.49-12.50), but findings were not statistically significant (p=0.27). Adjusting for age, sex, comorbidity, and line of therapy, there was no significant difference in time to ICI treatment discontinuation between patients with vs. without prior AD (HR=1.29; 95%CI=0.87-1.90). There was a shorter time to treatment discontinuation in patients with vs. without prior AD, but findings were not statistically significant. Broader inclusion of patients with mUC reflective of real-world populations in ICI clinical studies will better define tolerance and efficacy of novel therapies for urothelial cancer.

To evaluate incidence of complications associated with central venous access devices (CVADs) in PwHA. This retrospective cohort study was conducted using claims data from MarketScan Commercial Research Database from 07.01.2005–03.31.2019. The study cohort comprised PwHA and included CVAD cases (≥1 CVAD insertion claim), and controls with no CVAD insertion claim through the study period. Patients were required to have continuous enrollment for 6 months pre- and at least 3 months post-index date. Index date was defined as the first date of port insertion for CVAD cases and first hemophilia A (HA) diagnosis for controls during the study period. HA was identified using a previously validated claims-based algorithm. CVAD use and complications (all-cause infections, thrombosis and hematoma) were identified using ICD-9-CM/ICD-10-CM diagnosis/procedure and CPT codes. Patients were followed until first outcome, plan switch or over a 2-year post-index period. Incidence and rates of complications among CVAD cases and controls were evaluated using Cox proportional-hazards models (adjusted for age, region, comorbidity score, and insurance type). The study cohort comprised 862 PwHA; 61 (7%) had evidence of CVAD use. CVAD cases were significantly younger than controls (mean age ± SD: 4.7±5.3 years vs. 25.9±17.5 years, p<0.001) and had a significantly higher Elixhauser comorbidity score (mean ± SD: 0.9±0.6 vs. 0.5±0.8, p<0.001). In the post-index period, a significantly higher proportion of CVAD cases (vs. controls) had all-cause infections (44.3% vs. 26.7%, p<0.001) and thrombosis (13.1% vs. 1.1%, p<0.001). No CVAD cases had evidence of hematoma; it occurred in 1.5% of controls. Cox models revealed that CVAD cases had 2.3 times (95%CI: 1.5–3.6) and 9.2 times (95%CI: 2.4–35.6) higher rate of all-cause infections and thrombosis, respectively. CVAD use in HA is associated with higher rates of complications, underscoring the need for novel non-intravenous treatments which remove the need for CVADs.

Commercial claims data lack information on vital status, potentially biasing outcomes in observational studies. An algorithm to predict mortality in claims data developed for patients with type 2 diabetes (Joyce, 2004) has been applied to other diseases without validation. The present study aimed to modify and validate the existing algorithm in a target population of patients with advanced colorectal cancer (CRC). The SEER-Medicare linked database (2015 linkage) which includes mortality information was used to modify and validate the existing algorithm. Patients newly diagnosed in 2013 with advanced CRC were followed to their last claim before end of enrollment or December 31, 2014. The distributions of diagnosis and procedure codes in their last month of claims were compared between those known to have died at end of enrollment versus survived. Based on this comparison as well as clinician input, a total of 84 diagnosis and procedure codes (e.g. liver failure, hospice) were selected for the modified algorithm. Patients were classified as having died if they had any of these codes during the month prior to their last claim. Performance of the algorithm was evaluated by estimating sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Among 1754 advanced CRC patients who met selection criteria, a total of 964 (54.96%) died by the end of 2014. The modified mortality algorithm's sensitivity, specificity, PPV, and NPV were 92.01%, 91.39%, 92.88%, and 90.36% respectively. This improved upon the performance metrics of the original diabetes algorithm applied to advanced CRC patients, which were 66.29%, 86.58%, 85.77%, and 67.79%. Modification of the existing algorithm for type 2 diabetes greatly improved its ability to predict mortality among advanced CRC patients following their last observed claim. Further development and validation are planned in advanced CRC as well as other cancer populations.