Real-world patient characteristics and treatment patterns in US patients with advanced non-small cell lung cancer.

BACKGROUND: Patients from non-small cell lung cancer (NSCLC) controlled clinical trials do not always reflect real-world heterogeneous patient populations. We designed a study to describe the real-world patient characteristics and treatment patterns of first-line treatment in patients in the US with NSCLC. METHODS: This was an observational, retrospective cohort study based on electronic medical records of US adults with locally advanced or metastatic disease in the ConcertAI Patient360 NSCLC database who initiated first-line treatment with anti-programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) therapy between July 2016 and December 2020. The analysis used patient attributes, clinical characteristics, and treatments from each patient's medical records. RESULTS: A total of 2175 patients were eligible for analysis. The median age was 68 years, and 26.2% of the patients were ≥75 years old. At treatment initiation, 96.4% and 3.6% of the patients had Stage 4 and Stage 3 (B or C) NSCLC, respectively. The most common histology type was nonsquamous adenocarcinoma (66.4%), and 19.8% had Eastern Cooperative Oncology Group performance status ≥2. Immunosuppressive medications were being used by 17.7% of patients, and 11.0% were immunocompromised. Almost all patients had metastases: 64.6% had 1, 23.2% had 2, and 8.0% had ≥3 metastatic sites. Brain metastases were present in 22.9% of patients. Treatment evolution was observed with first-line standard of care shifting from single-agent immunotherapy in 2016 (90.2%) to combination immunotherapy and chemotherapy in 2020 (60.2%). CONCLUSION: Between 2016 and 2020, the first-line treatment paradigm for advanced NSCLC in the US shifted from anti-PD-1/PD-L1 monotherapy to combination chemoimmunotherapy, with increasing biomarker testing. Further research in heterogeneous patient populations to characterize treatment strategies is warranted.

A metagenomic analysis for combination therapy of multiple classes of antibiotics on the prevention of the spread of antibiotic-resistant genes.

Antibiotics used systemically to treat infections may have off-target effects on the gut microbiome, potentially resulting in the emergence of drug-resistant bacteria or selection of pathogenic species. These organisms may present a risk to the host and spread to the environment with a risk of transmission in the community. To investigate the risk of emergent antibiotic resistance in the gut microbiome following systemic treatment with antibiotics, this metagenomic analysis project used next-generation sequencing, a custom-built metagenomics pipeline, and differential abundance analysis to study the effect of antibiotics (ampicillin, ciprofloxacin, and fosfomycin) in monotherapy and different combinations at high and low doses, to determine the effect on resistome and taxonomic composition in the gut of Balb/c mice. The results showed that low-dose monotherapy treatments showed little change in microbiome composition but did show an increase in expression of many antibiotic-resistant genes (ARGs) posttreatment. Dual combination treatments allowed the emergence of some conditionally pathogenic bacteria and some increase in the abundance of ARGs despite a general decrease in microbiota diversity. Triple combination treatment was the most successful in inhibiting emergence of relevant opportunistic pathogens and completely suppressed all ARGs after 72 h of treatment. The relative abundances of mobile genetic elements that can enhance transmission of antibiotic resistance either decreased or remained the same for combination therapy while increasing for low-dose monotherapy. Combination therapy prevented the emergence of ARGs and decreased bacterial diversity, while low-dose monotherapy treatment increased ARGs and did not greatly change bacterial diversity.

Real-world treatment patterns and outcomes of patients with metastatic nonsquamous non-small cell lung cancer after progression on standard-of-care therapy in the United States.

OBJECTIVES: Data to guide treatment selection in metastatic nonsquamous (mNSq) non-small cell lung cancer (NSCLC) after progression on current standard-of-care (SoC) treatment are limited. We investigated patterns of treatment and clinical outcomes following one or more disease progressions on SoC. MATERIALS AND METHODS: Electronic medical records in the ConcertAI Patient360 NSCLC database were analyzed for US adults with mNSq NSCLC who initiated treatment between 2016 and 2021. Analyses were conducted separately for patients who had ≥1 prior lines of therapy and progression(s) without (Cohort 1) or with (Cohort 2) evidence of targetable genetic alterations (EGFR, ALK, or ROS1). Outcomes included real-world progression-free survival (rwPFS) and overall survival (rwOS). RESULTS: Cohorts 1 and 2 included 281 and 109 patients, respectively. In Cohort 1, subsequent treatment was most often with docetaxel monotherapy (18.5%) or docetaxel + ramucirumab (32.4%). Most patients in Cohort 2 received platinum-based doublet chemotherapy with (22.9%) or without (34.9%) immunotherapy. Median rwPFS and rwOS were 2.9 and 7.2 months, respectively, in Cohort 1, and 3.2 and 10.4 months in Cohort 2. Neither the addition of ramucirumab to docetaxel in Cohort 1 nor the addition of immunotherapy to chemotherapy in Cohort 2 was associated with a marked improvement in additional survival. CONCLUSION: Patients with progressive mNSq NSCLC most commonly received later-line docetaxel for cancer without driver mutations, or platinum-based chemotherapy (following one or more lines of tyrosine kinase inhibitor therapy) for cancer with driver mutations, consistent with guideline recommendations. Median survival was poor regardless of subsequent treatment, highlighting the need for more effective options.

Evaluation of a Sequential Antibiotic Treatment Regimen of Ampicillin, Ciprofloxacin and Fosfomycin against Escherichia coli CFT073 in the Hollow Fiber Infection Model Compared with Simultaneous Combination Treatment.

OBJECTIVE: Employ the hollow fiber infection model (HFIM) to study sequential antibiotic administration (ampicillin, ciprofloxacin and fosfomycin) using human pharmacokinetic profiles to measure changes in the rate of antibiotic resistance development and compare this to simultaneous combination therapy with the same antibiotic combinations. METHODS: Escherichia coli CFT073, a clinical uropathogenic strain, was exposed individually to clinically relevant pharmacokinetic concentrations of ampicillin on day 1, ciprofloxacin on day 2 and fosfomycin on day 3. This sequence was continued for 10 days in the HFIM. Bacterial samples were collected at different time points to enumerate total and resistant bacterial populations. The results were compared with the simultaneous combination therapy previously studied. RESULTS: Sequential antibiotic treatment (ampicillin-ciprofloxacin-fosfomycin sequence) resulted in the early emergence of single and multi-antibiotic-resistant subpopulations, while the simultaneous treatment regimen significantly delayed or prevented the emergence of resistant subpopulations. CONCLUSION: Sequential administration of these antibiotic monotherapies did not significantly delay the emergence of resistant subpopulations compared to simultaneous treatment with combinations of the same antibiotics. Further studies are warranted to evaluate different sequences of the same antibiotics in delaying emergent resistance.

Simultaneous quantification of dexamethasone and 6ß-hydroxydexamethasone in rabbit plasma, aqueous and vitreous humor, and retina by UHPLC-MS/MS.

Aim: To develop and validate a fit for purpose method for the simultaneous determination of dexamethasone and its major metabolite, 6ß-hydroxydexamethasone, in rabbit plasma and ocular matrices to measure the in vivo release and distribution profile of dexamethasone from intravitreal implants. Materials & methods: An UHPLC-MS/MS system was employed to perform the bioanalysis. The method was validated according to the US FDA Bioanalytical Method Validation Guidance for Industry. Results & conclusion: The method was found to be fit-for-purpose for the described biological matrices and had a LLOQ of 0.1 ng/ml.

Effects of sedative psychotropic drugs combined with oxycodone on respiratory depression in the rat.

Following a decision to require label warnings for concurrent use of opioids and benzodiazepines and increased risk of respiratory depression and death, the US Food and Drug Administratioin (FDA) recognized that other sedative psychotropic drugs may be substituted for benzodiazepines and be used concurrently with opioids. In some cases, data on the ability of these alternatives to depress respiration alone or in conjunction with an opioid are lacking. A nonclinical in vivo model was developed that could detect worsening respiratory depression when a benzodiazepine (diazepam) was used in combination with an opioid (oxycodone) compared to the opioid alone based on an increased arterial partial pressure of carbon dioxide (pCO2 ). The current study used that model to assess the impact on respiration of non-benzodiazepine sedative psychotropic drugs representative of different drug classes (clozapine, quetiapine, risperidone, zolpidem, trazodone, carisoprodol, cyclobenzaprine, mirtazapine, topiramate, paroxetine, duloxetine, ramelteon, and suvorexant) administered alone and with oxycodone. At clinically relevant exposures, paroxetine, trazodone, and quetiapine given with oxycodone significantly increased pCO2 above the oxycodone effect. Analyses indicated that most pCO2 interaction effects were due to pharmacokinetic interactions resulting in increased oxycodone exposure. Increased pCO2 recorded with oxycodone-paroxetine co-administration exceeded expected effects from only drug exposure suggesting another mechanism for the increased pharmacodynamic response. This study identified drug-drug interaction effects depressing respiration in an animal model when quetiapine or paroxetine were co-administered with oxycodone. Clinical pharmacodynamic drug interaction studies are being conducted with these drugs to assess translatability of these findings.

Derivation and evaluation of thresholds for core and tissue at risk of infarction using CT perfusion.

BACKGROUND AND PURPOSE: Computed tomography perfusion provides information on tissue viability according to proposed thresholds. We evaluated thresholds for ischemic core and tissue at risk and subsequently tested their accuracy in independent datasets. MATERIALS AND METHODS: Tissue at risk was evaluated in patients with persistent arterial occlusions, and ischemic core thresholds in patients with recanalization and major clinical improvement. Scans were randomly allocated to derivation or validation groups for tissue at risk and core analysis. Optimum thresholds using mean transit time (MTT), cerebral blood flow (CBF), cerebral blood volume, and delay time (DT) were assessed. RESULTS: Absolute MTT, relative MTT and DT were best derived predictors of tissue at risk with thresholds of ≥ 7 seconds, ≥ 125%, and ≥ 2 seconds respectively. DT ≥ 2 seconds was the best predictor in the validation dataset (95% agreement levels = -44 to +30 mL, Bias = -6.9). Absolute and relative MTT were the best derived predictors of infarct volume in the core group (8 seconds and 125% respectively) but relative CBF of ≤ 45% performed best in the core validation dataset. CONCLUSIONS: Time-based perfusion thresholds perform well as predictors of tissue at risk of infarction with DT the best predictor. Relative CBF was the best predictor of ischemic core. Evaluation in larger populations is needed to confirm the performance of tissue viability thresholds.