Detecting Substance Use Disorder Using Social Media Data and the Dark Web: Time- and Knowledge-Aware Study.

Background: Opioid and substance misuse has become a widespread problem in the United States, leading to the "opioid crisis." The relationship between substance misuse and mental health has been extensively studied, with one possible relationship being that substance misuse causes poor mental health. However, the lack of evidence on the relationship has resulted in opioids being largely inaccessible through legal means. objectives: This study aims to analyze social media posts related to substance use and opioids being sold through cryptomarket listings. The study aims to use state-of-the-art deep learning models to generate sentiment and emotion from social media posts to understand users' perceptions of social media. The study also aims to investigate questions such as which synthetic opioids people are optimistic, neutral, or negative about; what kind of drugs induced fear and sorrow; what kind of drugs people love or are thankful about; which drugs people think negatively about; and which opioids cause little to no sentimental reaction. Methods: The study used the drug abuse ontology and state-of-the-art deep learning models, including knowledge-aware Bidirectional Encoder Representations From Transformers-based models, to generate sentiment and emotion from social media posts related to substance use and opioids being sold through cryptomarket listings. The study crawled cryptomarket data and extracted posts for fentanyl, fentanyl analogs, and other novel synthetic opioids. The study performed topic analysis associated with the generated sentiments and emotions to understand which topics correlate with people's responses to various drugs. Additionally, the study analyzed time-aware neural models built on these features while considering historical sentiment and emotional activity of posts related to a drug. Results: The study found that the most effective model performed well (statistically significant, with a macro-F1-score of 82.12 and recall of 83.58) in identifying substance use disorder. The study also found that there were varying levels of sentiment and emotion associated with different synthetic opioids, with some drugs eliciting more positive or negative responses than others. The study identified topics that correlated with people's responses to various drugs, such as pain relief, addiction, and withdrawal symptoms. Conclusions: The study provides insight into users' perceptions of synthetic opioids based on sentiment and emotion expressed in social media posts. The study's findings can be used to inform interventions and policies aimed at reducing substance misuse and addressing the opioid crisis. The study demonstrates the potential of deep learning models for analyzing social media data to gain insights into public health issues.

EURO-NMD registry: federated FAIR infrastructure, innovative technologies and concepts of a patient-centred registry for rare neuromuscular disorders.

BACKGROUND: The EURO-NMD Registry collects data from all neuromuscular patients seen at EURO-NMD's expert centres. In-kind contributions from three patient organisations have ensured that the registry is patient-centred, meaningful, and impactful. The consenting process covers other uses, such as research, cohort finding and trial readiness. RESULTS: The registry has three-layered datasets, with European Commission-mandated data elements (EU-CDEs), a set of cross-neuromuscular data elements (NMD-CDEs) and a dataset of disease-specific data elements that function modularly (DS-DEs). The registry captures clinical, neuromuscular imaging, neuromuscular histopathology, biological and genetic data and patient-reported outcomes in a computer-interpretable format using selected ontologies and classifications. The EURO-NMD registry is connected to the EURO-NMD Registry Hub through an interoperability layer. The Hub provides an entry point to other neuromuscular registries that follow the FAIR data stewardship principles and enable GDPR-compliant information exchange. Four national or disease-specific patient registries are interoperable with the EURO-NMD Registry, allowing for federated analysis across these different resources. CONCLUSIONS: Collectively, the Registry Hub brings together data that are currently siloed and fragmented to improve healthcare and advance research for neuromuscular diseases.

"Pressed OXY M30 Pills, Great Press, Potent, Fast Shipping!!!": Availability of Counterfeit and Pharmaceutical Oxycodone Pills on One Major Cryptomarket.

From 2018 to 2021, seizures of counterfeit oxycodone pills containing non-pharmaceutical fentanyl or other novel synthetic opioids increased significantly contributing to continuing increases in overdose mortality in Northern America. Evidence suggests that counterfeit pills are distributed through cryptomarkets. This article presents data regarding the availability and characteristics of oxycodone pills advertised on one major cryptomarket between January and March 2022. Collected data were processed using a dedicated Named Entity Recognition algorithm to identify oxycodone listings and categorized them as either counterfeit or pharmaceutical. Frequency of listings, average number of pills advertised, average prices per milligram, number of sales, and geographic indicators of shipment origin and destination were analyzed. In total, 2,665 listings were identified as oxycodone. 48.2% (1,285/2,665) of these listings were categorized as counterfeit oxycodone, advertising a total of 652,699 pills (93,242.7 pills per datapoint) offered at a lower price than pharmaceutical pills. Our data indicate the presence of a large volume of counterfeit oxycodone pills both in retail- and wholesale-level amounts mostly targeting US and Canadian customers. These exploratory findings call for more research to develop epidemiological surveillance systems to track counterfeit pill and other drug availability on the Dark web environment.

Real-world outcomes among patients with advanced or metastatic biliary tract cancers initiating second-line treatment.

BACKGROUND: Limited data are available regarding second-line (2 L) treatment for advanced or metastatic biliary tract cancers (BTC) in the US real-world setting. This study explores the rapidly evolving and growing treatment landscape in the 2 L setting for advanced or metastatic BTC with a large cohort of patients treated in a community oncology setting. METHODS: Adult patients with BTC initiating 2 L treatment after a platinum-containing first-line between 1/1/10- and 6/30/19 were identified from the US Oncology Network electronic healthcare record database and followed through 12/31/19. Baseline patient and treatment characteristics were analyzed descriptively, including overall response rate (ORR) in the real-world clinical setting. Kaplan-Meier methods were used to measure duration of response, progression-free survival (PFS), and overall survival (OS). RESULTS: The overall population (N = 160) included 74 patients (46.3%) with intrahepatic cholangiocarcinoma, 41 (25.6%) with extrahepatic cholangiocarcinoma, and 45 (28.1%) with gallbladder cancer. Thirty unique 2 L regimens were recorded for the study population, with folinic acid, fluorouracil and oxaliplatin (FOLFOX, 34.4%) and capecitabine monotherapy (20.0%) being the most common. ORR was 7.5% (95% CI, 3.9%-12.7%). From 2 L initiation, median PFS was 2.8 months (95% CI, 2.4-3.3 months), and median OS was 5.2 months (95% CI, 4.2-6.7 months). CONCLUSION: Results from this study provide real-world evidence that although patients treated in the community oncology setting receive a wide variety of 2 L treatments, the regimens are consistent with those recommended by guidelines. Although responses are observed with 2 L treatment, duration is brief and associated with poor OS in patients with advanced or metastatic disease.

Drug Abuse Ontology to Harness Web-Based Data for Substance Use Epidemiology Research: Ontology Development Study.

BACKGROUND: Web-based resources and social media platforms play an increasingly important role in health-related knowledge and experience sharing. There is a growing interest in the use of these novel data sources for epidemiological surveillance of substance use behaviors and trends. OBJECTIVE: The key aims were to describe the development and application of the drug abuse ontology (DAO) as a framework for analyzing web-based and social media data to inform public health and substance use research in the following areas: determining user knowledge, attitudes, and behaviors related to nonmedical use of buprenorphine and illicitly manufactured opioids through the analysis of web forum data Prescription Drug Abuse Online Surveillance; analyzing patterns and trends of cannabis product use in the context of evolving cannabis legalization policies in the United States through analysis of Twitter and web forum data (eDrugTrends); assessing trends in the availability of novel synthetic opioids through the analysis of cryptomarket data (eDarkTrends); and analyzing COVID-19 pandemic trends in social media data related to 13 states in the United States as per Mental Health America reports. METHODS: The domain and scope of the DAO were defined using competency questions from popular ontology methodology (101 ontology development). The 101 method includes determining the domain and scope of ontology, reusing existing knowledge, enumerating important terms in ontology, defining the classes, their properties and creating instances of the classes. The quality of the ontology was evaluated using a set of tools and best practices recognized by the semantic web community and the artificial intelligence community that engage in natural language processing. RESULTS: The current version of the DAO comprises 315 classes, 31 relationships, and 814 instances among the classes. The ontology is flexible and can easily accommodate new concepts. The integration of the ontology with machine learning algorithms dramatically decreased the false alarm rate by adding external knowledge to the machine learning process. The ontology is recurrently updated to capture evolving concepts in different contexts and applied to analyze data related to social media and dark web marketplaces. CONCLUSIONS: The DAO provides a powerful framework and a useful resource that can be expanded and adapted to a wide range of substance use and mental health domains to help advance big data analytics of web-based data for substance use epidemiology research.

Transition from nonmedical prescribed opioids to non-injection heroin use among young integrated Thai male users in Bangkok.

Opioid use and misuse are understudied in Thailand despite evidence suggesting that a portion of young Thai male integrated drug users are initiating use of non-medical prescribed opioids with some transitioning to heroin. This study aims to capture and analyze the individual and social factors influencing these transitions. Twenty in-depth semi-structured interviews were conducted between December 2019 and January 2020 in the Bangkok metropolitan area with young male opioid users who transitioned to heroin. Sixteen respondents initiated opioid through a Tramadol cocktail named "YaPro" and tended to transition to heroin use within 21 months. The interaction of specific social and individual factors such as joining recreational activities, curiosity or experimentation gradually modified the opioid-related meanings, attitude and practices of Thai users, who ultimately transition to heroin use. These results indicate that drug prevention programs in Thailand should encompass young opioid users in their intervention and further research need to focus on nonmedical use of prescription opioids in Thailand.

Incidence of safety events after immune checkpoint inhibitor initiation for advanced-stage non-small-cell lung cancer: a real-world study.

Aim: To describe the incidence of safety events after immune checkpoint inhibitor (ICI) initiation for advanced-stage non-small-cell lung cancer. Methods: Retrospective cohort study using the HealthCore Integrated Research Database in the USA to examine the incidence of prespecified safety events of interest after ICI initiation (n = 5278). Results: The most common safety events after ICI initiation included malaise/fatigue (incidence rate [IR]: 70.7 per 100 person-years; 95% CI: 66.5-75.1) and nausea/vomiting (IR: 32.4; 30.0-34.8). Other potential immune-mediated events, including colitis (IR: 7.11; 6.26-8.04) and pneumonitis (IR: 5.47; 4.76-6.25), were less frequent but higher than after any systemic anti-cancer therapy. No safety event rate substantially increased 6 months after ICI initiation. Conclusion: This large real-world study reports the incidence of safety events with ICI regimens for advanced-stage non-small-cell lung cancer.

Researchers wanted to investigate side effects identified with advanced lung cancer during treatment, particularly immunotherapy. To investigate these side effects, researchers examined health insurance claims records from patients who were diagnosed with advanced lung cancer between January 2010 and July 2019, and who received treatment at various clinics across the USA. Researchers identified records for 44,045 patients treated for advanced lung cancer, with 5278 being treated with immunotherapy. After patients started immunotherapy, the most commonly reported side effects were tiredness and nausea/vomiting. Other side effects possibly related to immunotherapy were inflammation of the large intestine and lung inflammation ­ these events were not reported very often and did not increase in frequency 6 months after start of treatment. This large real-world study provides estimates for the frequency of side effects for those treated for advanced lung cancer, and finds that there were no large increases in the occurrence of any particular side effect in the 6 months after patients started immunotherapy for advanced lung cancer.

Second-line treatments in advanced biliary tract cancer: systematic literature review of efficacy, effectiveness and safety.

Background: A systematic review was conducted to understand clinical, economic and health-related quality-of-life outcomes in second-line biliary tract cancer. Materials & methods: The review followed established recommendations. The feasibility of network meta-analysis revealed limited networks, thus synthesis was limited to a summary of reported ranges, percentiles and medians. Results: The review included 62 trials and observational studies highly variable with respect to key baseline characteristics. Commonly evaluated second-line treatments included fluoropyrimidine-, gemcitabine- and S-1-based regimens. Across active treatment arms, median overall survival ranged from 3.5 to 15.0 months (median: 6.9), median progression-free survival from 1.4 to 6.5 months (median: 2.9) and objective response from 0 to 36.4%. Outcomes were similar between study types, with a few notable outliers. Treatment-related/emergent adverse events were infrequently reported; no studies reported economic or health-related quality-of-life outcomes. Conclusions: Biliary tract cancer is a difficult-to-treat disease with poor prognosis. Despite evolving treatment landscapes, more recent studies did not show clinical outcome improvement, highlighting an unmet need among advanced/metastatic patients.

A systematic review of published literature was undertaken to understand the clinical, economic and health-related quality-of-life impact of second-line biliary tract cancer (BTC). A total of 62 relevant studies were identified. The patient populations included across these studies were highly variable with respect to key patient characteristics (i.e., age, sex, physical functioning and tumor type). Commonly evaluated treatments included fluoropyrimidine-, gemcitabine- and S-1-based regimens. Reported values for key outcomes varied substantially, somewhat explained by a few outlier studies. Median overall survival ranged from 3.5 to 15.0 months, median progression-free survival from 1.4 to 6.5 months and objective response from 0 to 36.4%. Treatment-related/emergent adverse events were infrequently reported; no studies reported economic or health-related quality-of-life outcomes. The results demonstrate that BTC is a difficult-to-treat disease with poor prognosis. Despite evolving treatment landscapes, more recent studies did not show clinical outcome improvement, highlighting an unmet need among advanced/metastatic second-line BTC patients.

An adaptive design for early clinical development including interim decision for single-arm trial with external controls or randomized trial.

In early clinical development, randomized controlled trials (RCT) or single-arm trials with external controls (SATwEC) are design options, which allow adjustment for confounding: RCT via design, SATwEC via analysis using propensity score methods. SATwEC requires less investment than RCT. However, if the confounder space substantially differs between the experimental and external control group, the SATwEC might lead to inappropriate decisions for further development. We develop an adaptive two-stage design (ATD) for early clinical development that reduces the risk of unreliable decision-making at the end of a SATwEC. In Stage I, subjects are solely assigned to the experimental group. If at the interim the propensity score distributions of internal and external data are comparable based on the preference score, the subjects in stage II will again be solely assigned to the experimental arm; if not, a randomized stage II will be conducted. In a simulation study guided by a motivating example, data is generated using a time-to-event model with observable and unobservable confounders. The confounder space is varied to investigate the impact on false go/stop probabilities as well as a loss function, which reflects the quality of treatment effect estimates and decision-making. The proposed ATD provides a compromise between optimizing quality (as expressed by false go/stop probabilities and the loss function) and investment (defined by sample size and trial duration).

Exploring Televend, an innovative combination of cryptomarket and messaging app technologies for trading prohibited drugs.

BACKGROUND: Digital technologies continue to facilitate drug trading. Televend was an innovative combination of multiple digital technologies, with its backend hosted on the darknet, while purchases were made through the messaging app Telegram. Here, we provide an initial characterisation of this nascent market. METHODS: Televend and White House Market (WHM) were scraped (Jun-Jul 2021) and a global cross-sectional web survey of 15,513 drug buyers (Global Drug Survey; GDS) was conducted (Dec 2020-Mar 2021). RESULTS: Televend was 10% of the size of WHM, the largest drug cryptomarket (4515/44,830 listings per week). Both markets predominantly contained drug-related listings covering similar drug categories, with similar country of origin and destination. Very few GDS drug buyers reported use of Televend (0.73%). Most Televend buyers (68/114) reported buying cannabis, then cocaine (20), MDMA (17), and LSD (12). The Televend and darknet groups had similar demographic and drug use characteristics; whereas compared with app purchasers, older age increased the odds of Televend use (aRRR = 1.06, p < .001), identifying as a cisgender woman decreased the odds (aRRR=0.43, p = .004), while last-year use of a greater number of drug types (aRRR = 1.20, p < .001) and less frequent drug use (aRRR=0.998, p = .032) increased the odds of Televend purchase. CONCLUSIONS: While smaller, Televend was not noticeably different in its drug offerings to its largest cryptomarket competitor, and it attracted a cohort more similar to darknet than to app drug buyers. Future Televend-like markets may be attractive to people with less specialised technical knowledge who already routinely scroll through social media feeds.

Health care resource utilization and costs associated with advanced or metastatic nonsmall cell lung cancer in the United States.

BACKGROUND: The treatment landscape for advanced nonsmall cell lung cancer (NSCLC) has evolved from 2015 onward, since the introduction of immune checkpoint inhibitors (ICIs). Considering this shift, there have been limited prior analyses that assess the economic burden of NSCLC within the current treatment landscape. OBJECTIVE: To present an analysis of health care resource utilization (HCRU) and costs associated with the treatment of patients with advanced or metastatic NSCLC in the United States between 2010 and 2019. METHODS: Patients with locally advanced or metastatic NSCLC who initiated first-line (1L) systemic treatment between January 1, 2010, and June 30, 2019, were included from the HealthCore Integrated Research Database using a previously developed claims-based predictive model algorithm. Mean total HCRU and costs and mean per-person-per-year (PPPY) HCRU and costs were estimated for 2 follow-up periods: the time during the entire follow-up period and the time during the 1L treatment period. Distribution of treatment classes (defined as chemotherapy, ICIs, targeted therapies, and others) were also analyzed by index year. RESULTS: 27,257 patients met the eligibility criteria and were included in the analysis. The mean duration of follow-up for all patients was 16.6 months (median 10.6 months), and the median time to discontinuation of 1L treatment was 2.8 months. The number of outpatient visits accounted for the majority of HCRU across the entire study follow-up (mean 97.7 in total and 147.1 PPPY) and for the 1L treatment period (mean 46.3 in total and 167.5 PPPY). The total mean cost across the entire study follow-up was $158,908 ($250,942 PPPY). For the 1L treatment period, the total mean cost was $72,760 ($271,590 PPPY). Total mean outpatient costs for systemic anticancer treatment were $61,797 for the entire study follow-up ($85,609 PPPY) and $27,138 during the 1L treatment period ($92,412 PPPY). Total costs increased over the study duration, which were mainly due to increasing outpatient costs for systemic therapy. In both follow-up periods, inpatient costs, other outpatient costs (nonsystemic therapy-related costs), and pharmacy costs remained relatively stable but still accounted for more than 60% of the total costs. Analysis of treatment classes over time showed that chemotherapy was the most frequently used treatment, regardless of line of therapy. A trend was observed for increased ICI use from 2015 onward. CONCLUSIONS: Despite the improvement in treatment options, a high economic burden associated with the treatment of NSCLC still exists. The total costs have been increasing, mainly driven by outpatient costs for systemic therapy, which might reflect the greater use of ICIs for advanced NSCLC. Costs for inpatient services, other outpatient services, and pharmacy services remained stable but still accounted for the majority of the economic burden. Further studies are required to assess the impact of innovative treatments on the disease management costs of advanced NSCLC. DISCLOSURES: This study was funded by the healthcare business of Merck KGaA, Darmstadt, Germany (CrossRef Funder ID: 10.13039/100009945) as part of an alliance between the healthcare business of Merck KGaA, Darmstadt, Germany, and Pfizer. Zhang, Liu, and Yang are employees of EMD Serono. Beachler, Dinh, and Jamal-Allial are employees of HealthCore Inc., which received funding from the healthcare business of Merck KGaA, Darmstadt, Germany, and Pfizer for the implementation of this study. Masters and Kolitsopoulos are employees of Pfizer. Lamy was an employee of the healthcare business of Merck KGaA, Darmstadt, Germany, at the time this study was conducted.

High-dose corticosteroid use and risk of hospitalization for infection in patients treated with immune checkpoint inhibitors--A nationwide register-based cohort study.

High-dose corticosteroids have been associated with increased risk of serious infection in patients with metastatic melanoma treated with immune checkpoint inhibitors targeting cytotoxic T-lymphocyte antigen 4. This potential association needs to be examined further among patients with other cancer types and for other immune checkpoint inhibitors. We examined whether receipt of high-dose corticosteroids was associated with increased rates of hospitalization for infection among 981 Danish renal, urothelial, and lung cancer patients followed from first administration of programmed death receptor 1 (PD-1)/programmed death ligand 1 (PD-L1) immune checkpoint inhibitors. Our cohort analysis was based on the information from national medical registries. During follow-up, 522 patients (53.2%) initiated treatment with high-dose corticosteroids and 317 patients (32.3%) experienced at least one hospitalization for infection. In analyses adjusted for age, sex, and previous use of chemotherapy/targeted therapy, initiation of high-dose systemic corticosteroids was associated with increased rate of hospitalization for infections (hazard ratio (HR) = 2.96, 95% confidence interval (CI) = 2.41-3.65) even in patients not receiving any chemotherapy/targeted therapy (HR = 3.66, 95% CI = 2.25-5.96). Our findings showed that high-dose corticosteroid initiation is associated with hospitalization for infection in patients treated with PD-1/PD-L1 immune checkpoint inhibitors. Clinicians and patients should be aware of this risk of infection when initiating treatment with high-dose corticosteroids.

"Etazene, safer than heroin and fentanyl": Non-fentanyl novel synthetic opioid listings on one darknet market.

BACKGROUND: Novel synthetic opioids are fueling the overdose deaths epidemic in North America.Recently, non-fentanyl novel synthetic opioids have emerged in forensic toxicological results. Cryptomarkets have become important platforms of distribution for illicit substances. This article presents the data concerning the availability trends of novel non-fentanyl synthetic opioids listed on one cryptomarket. METHODS: Listings from the EmpireMarket cryptomarket "Opiates" section were collected between June 2020 and August 2020. Collected data were processed using eDarkTrends Named Entity Recognition algorithm to identify novel synthetic opioids, and to analyze their availability trends in terms of frequency of listings, available average weights, average prices, quantity sold, and geographic indicators of shipment origin and destination information. RESULTS: 35,196 opioid-related listings were collected through 12 crawling sessions. 17 nonfentanyl novel synthetic opioids were identified in 2.9 % of the collected listings for an average of 9.2 kg of substance available at each data point. 587 items advertised as non-fentanyl novel synthetic opioids were sold on EmpireMarket for a total weight of between 858 g and 2.7 kg during the study period. 45.5 % of these listings were advertised as shipped from China. CONCLUSIONS: Fourteen of the 17 non-fentanyl novel synthetic opioids were identified for the first time on one large cryptomarket suggesting a shift in terms of novel non-fentanyl synthetic opioids availability. This increased heterogeneity of available novel synthetic opioids could reduce the efficiency of existing overdose prevention strategies. Identification of new opioids underpins the value of cryptomarket data for early warning systems of emerging substance use trends.

"When they say weed causes depression, but it's your fav antidepressant": Knowledge-aware attention framework for relationship extraction.

With the increasing legalization of medical and recreational use of cannabis, more research is needed to understand the association between depression and consumer behavior related to cannabis consumption. Big social media data has potential to provide deeper insights about these associations to public health analysts. In this interdisciplinary study, we demonstrate the value of incorporating domain-specific knowledge in the learning process to identify the relationships between cannabis use and depression. We develop an end-to-end knowledge infused deep learning framework (Gated-K-BERT) that leverages the pre-trained BERT language representation model and domain-specific declarative knowledge source (Drug Abuse Ontology) to jointly extract entities and their relationship using gated fusion sharing mechanism. Our model is further tailored to provide more focus to the entities mention in the sentence through entity-position aware attention layer, where ontology is used to locate the target entities position. Experimental results show that inclusion of the knowledge-aware attentive representation in association with BERT can extract the cannabis-depression relationship with better coverage in comparison to the state-of-the-art relation extractor.

Real-world healthcare resource utilization and costs of weekly versus every-2-week cetuximab in metastatic colorectal cancer.

Aim: To compare healthcare resource utilization (HRU) and healthcare costs (HC) for every-2-week (Q2W) versus weekly (Q1W) cetuximab in metastatic colorectal cancer (mCRC). Patients & methods: Patients with mCRC receiving cetuximab plus chemotherapy in a line-agnostic setting. Cohort study of patients with mCRC treated with cetuximab and chemotherapy in IBM MarketScan. Analyses were weighted by inverse probability of treatment based on propensity score. Results: HRU was numerically lower with the Q2W versus Q1W regimen (weighted mean, 8.1 vs 9.5 encounters per-patient-per-month). The weighted average of HC was $17,653 and $16,469 per-patient-per-month for the Q2W and Q1W regimens, respectively; the difference between regimens decreased when restricting to CRC-related claims. Conclusion: HRU was lower and HC were similar between the Q2W and Q1W regimens.

Noninferiority of cetuximab every-2-weeks versus standard once-weekly administration schedule for the first-line treatment of RAS wild-type metastatic colorectal cancer.

AIM: This study assessed whether cetuximab 500 mg/m2 administered every 2 weeks (Q2W), when combined with chemotherapy as a first-line (1L) treatment, was noninferior to the approved dose (400 mg/m2 followed by 250 mg/m2 once weekly [Q1W]) for overall survival (OS) in adults with RAS wild-type metastatic colorectal cancer (mCRC). METHODS: This pooled analysis included patients receiving 1L treatment with cetuximab Q1W or Q2W in combination with chemotherapy from post-authorisation studies with patient-level data available to the sponsor. Baseline characteristics were adjusted with a propensity score using inverse probability of treatment weighting (IPTW). Noninferiority in terms of OS was tested with a noninferiority margin for the hazard ratio (HR) of 1.25 using a Cox proportional hazards regression model. Secondary outcomes were progression-free survival (PFS), overall response rate (ORR) and rates of lung/liver metastases resection and serious adverse events. RESULTS: OS time was noninferior in the Q2W cohort (n = 554) compared to the Q1W cohort (n = 763), with a HR after IPTW (95% confidence interval) of 0.827 (0.715-0.956) and median OS times of 24.7 (Q1W) and 27.9 (Q2W) months. There were no major differences in PFS (HR: 0.915 [0.804-1.042]). The odds ratios (ORs) after IPTW for ORR (1.292 [1.031-1.617]) and the rates of lung/liver metastases resection (1.419 [1.043-1.932]) favoured the Q2W regimen. No differences were noted in the occurrence rate of any SAE between groups; the OR after IPTW was 1.089 (0.858-1.382). CONCLUSIONS: The cetuximab Q2W regimen was noninferior to the Q1W regimen for OS in the 1L treatment of mCRC.

Comparative effectiveness of weekly versus every-2-weeks cetuximab in metastatic colorectal cancer in a US-insured population.

Aim: To test the noninferiority of cetuximab administered every 2 weeks (Q2W) versus once weekly (Q1W) in treating metastatic colorectal cancer (mCRC) with regard to overall survival (OS). Patients: Patients receiving cetuximab plus chemotherapy for mCRC in a line-agnostic setting. Methods: This cohort study in IBM MarketScan followed patients from initiation of cetuximab for mCRC until the end of the data availability period, proxy-based death or loss of insurance coverage for >30 days. Results: The hazard ratio for OS was 0.94 (0.85-1.03), and the inferiority hypothesis was rejected at p < 0.001. No significant differences were noted in rates of safety events between Q2W and Q1W. Conclusion: Our real-world study confirmed the noninferiority of cetuximab administered Q2W versus Q1W for OS.

A real-world study on characteristics, treatments and outcomes in US patients with advanced stage ovarian cancer.

BACKGROUND: Detailed epidemiologic descriptions of large populations of advanced stage ovarian cancer patients have been lacking to date. This study aimed to describe the patient characteristics, treatment patterns, survival, and incidence rates of health outcomes of interest (HOI) in a large cohort of advanced stage ovarian cancer patients in the United States (US). METHODS: This cohort study identified incident advanced stage (III/IV) ovarian cancer patients in the US diagnosed from 2010 to 2018 in the HealthCore Integrated Research Database (HIRD) using a validated predictive model algorithm. Descriptive characteristics were presented overall and by treatment line. The incidence rates and 95% confidence intervals for pre-specified HOIs were evaluated after advanced stage diagnosis. Overall survival, time to treatment discontinuation or death (TTD), and time to next treatment or death (TTNT) were defined using treatment information in claims and linkage with the National Death Index. RESULTS: We identified 12,659 patients with incident advanced stage ovarian cancer during the study period. Most patients undergoing treatment received platinum agents (75%) and/or taxanes (70%). The most common HOIs (> 24 per 100 person-years) included abdominal pain, nausea and vomiting, anemia, and serious infections. The median overall survival from diagnosis was 4.5 years, while approximately half of the treated cohort had a first-line time to treatment discontinuation or death (TTD) within the first 4 months, and a time to next treatment or death (TTNT) from first to second-line of about 6 months. CONCLUSIONS: This study describes commercially insured US patients with advanced stage ovarian cancer from 2010 to 2018, and observed diverse treatment patterns, incidence of numerous HOIs, and limited survival in this population.

Listed for sale: Analyzing data on fentanyl, fentanyl analogs and other novel synthetic opioids on one cryptomarket.

BACKGROUND: The United States is facing a "triple wave" epidemic fueled by novel synthetic opioids. Cryptomarkets, anonymous marketplaces located on the deep web, play an increasingly important role in the distribution of illicit substances. This article presents the data collected and processed by the eDarkTrends platform concerning the availability trends of novel synthetic opioids listed on one cryptomarket. METHODS: Listings from the DreamMarket cryptomarket "Opioids" and "Research Chemicals" sections were collected between March 2018 and January 2019. Collected data were processed using eDarkTrends Named Entity Recognition algorithm to identify opioid drugs, and to analyze their availability trends in terms of frequency of listings, available average weights, average prices, and geographic indicators of shipment origin and destination information. RESULTS: 95,011 opioid-related listings were collected through 26 crawling sessions. 33 novel synthetic opioids were identified in 3.3 % of the collected listings. 44.7 % of these listings advertised fentanyl (pharmaceutical and non-pharmaceutical) or fentanyl analogs for an average of 2.8 kgs per crawl. "Synthetic heroin" accounted for 33.2 % of novel synthetic opioid listings for an average 1.1 kgs per crawl with 97.7 % of listings advertised as shipped from Canada. Other novel synthetic opioids (e.g., U-47,700, AP-237) represented 22 % of these listings for an average of 6.1 kgs per crawl with 97.2 % of listings advertised as shipped from China. CONCLUSIONS: Our data indicate consistent availability of a wide variety of novel synthetic opioids both in retail and wholesale-level amounts. Identification of new substances highlights the value of cryptomarket data for early warning systems of emerging substance use trends.