Background: Despite high rates of opioid therapy, evidence about the risk of preventable opioid harms among cancer survivors is underdeveloped. Our objective was to estimate the odds of opioid use disorder (OUD) and overdose following breast, colorectal, or prostate cancer diagnosis among Medicare beneficiaries. Methods: We conducted a retrospective cohort study using 2007-2014 Surveillance, Epidemiology, and End Results-Medicare data for cancer survivors with a first cancer diagnosis of stage 0-III breast, colorectal, or prostate cancer at age 66-89 years between 2008 and 2013. Cancer survivors were matched to up to 2 noncancer controls on age, sex, and Surveillance, Epidemiology, and End Results region. Using Firth logistic regression, we estimated adjusted 1-year odds of OUD or nonfatal opioid overdose associated with a cancer diagnosis. We also estimated adjusted odds of OUD and overdose separately and by cancer stage, prior opioid use, and follow-up time. Results: Among 69 889 cancer survivors and 125 007 controls, the unadjusted rates of OUD or nonfatal overdose were 25.2, 27.1, 38.9, and 12.4 events per 10 000 patients in the noncancer, breast, colorectal, and prostate samples, respectively. There was no association between cancer and OUD. Colorectal survivors had 2.3 times higher odds of opioid overdose compared with matched controls (adjusted odds ratio = 2.33, 95% confidence interval = 1.49 to 3.67). Additionally, overdose risk was greater in those with more advanced disease, no prior opioid use, and preexisting mental health conditions. Conclusions: Opioid overdose was a rare, but statistically significant, outcome following stage II-III colorectal cancer diagnosis, particularly among previously opioid-naïve patients. These patients may require heightened screening and intervention to prevent inadvertent adverse opioid harms.

PURPOSE: Nivolumab plus ipilimumab (NIVO + IPI) is a first-in-class combination immunotherapy for the treatment of intermediate- or poor (I/P)-risk advanced or metastatic renal cell carcinoma (mRCC). Currently, there are limited real-world data regarding clinical effectiveness beyond 12-24 months from treatment initiation. In this real-world study, treatment patterns and clinical outcomes were evaluated for NIVO + IPI in a community oncology setting. METHODS: A retrospective analysis using electronic medical record data from The US Oncology Network examined patients with I/P-risk clear cell mRCC who initiated first-line (1L) NIVO + IPI between January 4, 2018, and December 31, 2019, with follow-up until June 30, 2022. Baseline demographics, clinical characteristics, treatment patterns, clinical effectiveness, and safety outcomes were assessed descriptively. Overall survival (OS) and real-world progression-free survival (rwPFS) were analyzed using Kaplan-Meier methods. RESULTS: Among 187 patients identified (median follow-up, 22.4 months), with median age 63 (range, 30-89) years, 74 (39.6%) patients had poor risk and 37 (19.8%) patients had Eastern Cooperative Oncology Group performance status score ≥2. Of 86 patients who received second-line therapy, 54.7% received cabozantinib and 10.5% received pazopanib. The median (95% CI) OS and rwPFS were 38.4 (24.7-46.1) months and 11.1 (7.5-15.0) months, respectively. Treatment-related adverse events (TRAEs) were reported in 89 (47.6%) patients, including fatigue (n = 25, 13.4%) and rash (n = 19, 10.2%). CONCLUSION: This study provides data to support the understanding of the real-world utilization and long-term effectiveness of 1L NIVO + IPI in patients with I/P-risk mRCC. TRAE rates were low relative to clinical trials.

A citizen-science study was conducted in two low-income, flood-prone communities in Atlanta, Georgia, in order to document environmental exposures and the prevalence of occupant asthma. Teams consisting of a public-health graduate student and a resident from one of the two communities administered a questionnaire, inspected residences for mold growth, and collected a dust sample for quantifying mold contamination. The dust samples were analyzed for the 36 molds that make up the Environmental Relative Moldiness Index (ERMI). Most residents (76%) were renters. The median duration of residence was 2.5 years. Although only 12% of occupants reported a history of flooding, 46% reported at least one water leak. Homes with visible mold (35%) had significantly (P<0.05) higher mean ERMI values compared to homes without (14.0 versus 9.6). The prevalence of self-reported, current asthma among participants was 14%. In logistic regression models controlling for indoor smoking, among participants residing at their current residence for two years or less, a positive association was observed between asthma and the homes’ ERMI values (adjusted odds ratio per unit increase in ERMI = 1.12, 95% confidence intervals (CI): 1.01–1.25; two-tailedP=0.04). Documentation of the exposures and asthma prevalence has been presented to the communities and public officials. Community-based organizations have taken responsibility for planning and implementing activities in response to the study findings.

In an interesting, recent article by Nie et al., the authors conducted a systematic review of vaccine safety studies that used the self-controlled case-series (SCCS) study design.1 The authors asse...

Claims data can be leveraged to study rare diseases such as Guillain-Barré Syndrome (GBS), a neurological autoimmune condition. It is difficult to accurately measure and distinguish true cases of disease with claims without a validated algorithm. Our objective was to identify the best-performing algorithm for identifying incident GBS cases in Medicare fee-for-service claims data using chart reviews as the gold standard. This was a multi-center, single institution cohort study from 2015 to 2019 that used Medicare-linked electronic health record (EHR) data. We identified 211 patients with a GBS diagnosis code in any position of an inpatient or outpatient claim in Medicare that also had a record of GBS in their electronic medical record. We reported the positive predictive value (PPV = number of true GBS cases/total number of GBS cases identified by the algorithm) for each algorithm tested. We also tested algorithms using several prevalence assumptions for false negative GBS cases and calculated a ranked sum for each algorithm's performance. We found that 40 patients out of 211 had a true case of GBS. Algorithm 17, a GBS diagnosis in the primary position of an inpatient claim and a diagnostic procedure within 45 days of the inpatient admission date, had the highest PPV (PPV = 81.6%, 95% CI (69.3, 93.9). Across three prevalence assumptions, Algorithm 15, a GBS diagnosis in the primary position of an inpatient claim, was favored (PPV = 79.5%, 95% CI (67.6, 91.5). Our findings demonstrate that patients with incident GBS can be accurately identified in Medicare claims with a chart-validated algorithm. Using large-scale administrative data to study GBS offers significant advantages over case reports and patient repositories with self-reported data, and may be a potential strategy for the study of other rare diseases.