18F-FDG accumulation at the early onset of acute exacerbation of idiopathic interstitial pneumonia on 18F-FDG PET/CT: A case report.

Acute exacerbation of idiopathic interstitial pneumonias (AE-IIPs) is a disease associated with a poor prognosis in patients with IIPs. However, the specific characteristics of fluorine-18 2-fluoro-2-deoxy-d-glucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) imaging for AE-IIPs remain unclear. Herein, we present the case of a patient with lung cancer combined with IIPs who underwent 18F-FDG PET/CT at the early onset of AE-IIPs. The scan, conducted 18 days post-bronchoscopy for lung cancer evaluation, revealed AE-IIPs before the onset of respiratory failure. New ground-glass opacities appeared, accompanied by significant 18F-FDG accumulation extending beyond these regions. To the best of our knowledge, this report represents the first assessment of 18F-FDG PET/CT images at the early onset of AE-IIPs before respiratory failure in humans. The observed features in this PET image could potentially contribute to our understanding of the pathophysiology of AE-IIPs.

Negative impact of ratio of the microvascular area to tumor area on the response to EGFR-TKI in non-small cell lung cancer with an EGFR mutation.

Background: The clinical impact of tumor microvessels on the efficacy of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) in EGFR mutation-positive non-small cell lung cancer (NSCLC) is unclear. Thus, the aim of this study was to investigate whether a tumor microenvironment, abundant in microvessels, affects EGFR-TKI efficacy in patients with NSCLC and EGFR mutations. Methods: We retrospectively studied the data of 40 post-operative patients with recurrent NSCLC and EGFR mutations who received EGFR-TKIs as a first-line treatment at Kumamoto University Hospital from January 2010 to February 2021. Tumor sections were retrieved from the tissue registry and analyzed for CD34-positive microvessels using immunohistochemical techniques. The ratio of microvascular area to tumor area (RMV), which is the CD34-positive microvascular area compared to the total tumor area, was measured using StrataQuest. The predictive value of RMV on treatment outcome, assessed via progression-free survival (PFS), was evaluated using a multivariate Cox proportional hazard model. Results: The median PFS in the high RMV group (≥0.058) was significantly shorter than that in the low RMV group [<0.058; 296 days, 95% confidence interval (CI): 217-374 vs. 918 days, 95% CI: 279-1,556, P=0.002]. Multivariate analysis revealed that high RMV was an independent negative predictor of PFS (hazard ratio, 3.21; 95% CI: 1.18-8.76, P=0.022). Conclusions: High RMV may critically affect EGFR-TKI resistance in patients with NSCLC and EGFR mutations.

Prediction of prognosis in lung cancer using machine learning with inter-institutional generalizability: A multicenter cohort study (WJOG15121L: REAL-WIND).

OBJECTIVES: Predicting the prognosis of lung cancer is crucial for providing optimal medical care. However, a method to accurately predict the overall prognosis in patients with stage IV lung cancer, even with the use of machine learning, has not been established. Moreover, the inter-institutional generalizability of such algorithms remains unexplored. This study aimed to establish machine learning-based algorithms with inter-institutional generalizability to predict prognosis. MATERIALS AND METHODS: This multicenter, retrospective, hospital-based cohort study included consecutive patients with stage IV lung cancer who were randomly categorized into the training and independent test cohorts with a 2:1 ratio, respectively. The primary metric to assess algorithm performance was the area under the receiver operating characteristic curve in the independent test cohort. To assess the inter-institutional generalizability of the algorithms, we investigated their ability to predict patient outcomes in the remaining facility after being trained using data from 15 other facilities. RESULTS: Overall, 6,751 patients (median age, 70 years) were enrolled, and 1,515 (22 %) showed mutated epidermal growth factor receptor expression. The median overall survival was 16.6 (95 % confidence interval, 15.9-17.5) months. Algorithm performance metrics in the test cohort showed that the areas under the curves were 0.90 (95 % confidence interval, 0.88-0.91), 0.85 (0.84-0.87), 0.83 (0.81-0.85), and 0.85 (0.82-0.87) at 180, 360, 720, and 1,080 predicted survival days, respectively. The performance test of 16 algorithms for investigating inter-institutional generalizability showed median areas under the curves of 0.87 (range, 0.84-0.92), 0.84 (0.78-0.88), 0.84 (0.76-0.89), and 0.84 (0.75-0.90) at 180, 360, 720, and 1,080 days, respectively. CONCLUSION: This study developed machine learning algorithms that could accurately predict the prognosis in patients with stage IV lung cancer with high inter-institutional generalizability. This can enhance the accuracy of prognosis prediction and support informed and shared decision-making in clinical settings.

Association of Clostridium butyricum Therapy Using the Live Bacterial Product CBM588 with the Survival of Patients with Lung Cancer Receiving Chemoimmunotherapy Combinations.

The gut microbiota has emerged as a key regulator of immune checkpoint inhibitor (ICI) efficacy. Therapeutic approaches aimed at manipulating the microbiota through targeted reconstitution to enhance cancer treatment outcomes have garnered considerable attention. A single live microbial biotherapeutic bacterium, Clostridium butyricum MIYAIRI 588 strain (CBM588), has been shown to enhance the effects of ICI monotherapy in patients with advanced lung cancer. However, whether CBM588 affects the outcomes of chemoimmunotherapy combinations in lung cancer remains unknown. We hypothesized that CBM588 augments the effect of chemoimmunotherapy combinations and restores diminished effectiveness in patients with non-small cell lung cancer (NSCLC) receiving dysbiosis-inducing drugs. To validate this hypothesis, we retrospectively analyzed 106 patients with stage IV or recurrent metastatic NSCLC consecutively treated with chemoimmunotherapy combinations. A survival analysis was performed employing univariate and multivariate Cox proportional hazard models with inverse probability of treatment weighting (IPTW) using propensity scores. Forty-five percent of patients received Clostridium butyricum therapy. CBM588 significantly extended overall survival in patients with NSCLC receiving chemoimmunotherapy. The favorable impact of CBM588 on the efficacy of chemoimmunotherapy combinations varied based on tumor-programmed cell death ligand 1 (PD-L1) expression. The survival benefit of CBM588 in the PD-L1 <1% cohort was higher than that in the PD-L1 1-49% and PD-L1 ≥ 50% cohorts. Furthermore, CBM588 was associated with improved overall survival in patients receiving proton pump inhibitors and/or antibiotics. CBM588-induced manipulation of the commensal microbiota holds the potential to enhance the efficacy of chemoimmunotherapy combinations, warranting further exploration of the synergy between CBM588 and immunotherapy.