Concomitant electromagnetic navigation transbronchial microwave ablation of multiple lung nodules is safe, time-saving, and cost-effective.

Objectives: Transbronchial microwave ablation of lung nodules using electromagnetic navigation bronchoscopy is an emerging local therapy for lung oligometastases and multifocal lung cancers as part of a lung-preserving strategy. Concomitant ablation of multiple lung nodules in a single operating session may provide a one-stop solution. Methods: Between April 2019 and April 2023, 25 patients had 2 or more lung nodules ablated concomitantly in our hybrid operating room. Nodules were proven or highly suspicious of malignancies or metastases. Feasibility and safety were retrospectively reviewed. Results: A total of 56 nodules in 25 patients received concomitant multi-nodular ablation. The mean age of patients was 60 years, and the reasons for the lung-preserving strategy were multifocal lung cancers (80%) and lung oligometastases (20%). Among those with multifocal disease, 65% had previous major lung resection for lung cancer. Two to 4 nodules were ablated in each session. The mean nodule size was 9.9 mm (range, 5-20 mm), and the mean minimal margin was 5.9 mm. When comparing concomitant nodule ablation with the 103 single-nodule ablations performed in our institute, a mean of 86 minutes of operative time and 131 minutes of anesthetic time were saved. There were no increased complications despite overlapping ablation zones, and the mean hospital stay was 1.23 days. The rate of pneumothorax was 8%, and that of pleural effusion, pain, and fever was 4% respectively. Conclusions: Concomitant transbronchial microwave ablation of multiple lung nodules is feasible, safe, and associated with reduction in overall anesthetic and operative time. It is an important armamentarium in the contemporary lung-preserving strategy for battling multifocal lung cancers or lung oligometastases.

Incorporating circulating tumor DNA detection to radiographic assessment for treatment response in advanced EGFR-mutant lung cancer.

PURPOSE: Response Evaluation Criteria in Solid Tumors (RECIST) has limitations but remains the conventional approach for tumor assessments. We explored whether circulating tumor DNA (ctDNA) can be incorporated into RECIST to provide a more robust measure of tumor response in advanced EGFR-mutant NSCLC. PATIENTS AND METHODS: In FASTACT-2, patients with advanced NSCLC received platinum/gemcitabine intercalated with erlotinib or placebo. EGFR mutation (tumor and plasma ctDNA) was detected using cobas v2. Patients selected for this hypothesis-generating analysis had EGFR mutations (on either tumor or plasma) at baseline and evaluable week 8 plasma EGFR. Week 8 ctDNA and radiologic response status were correlated with survival using landmark cox regression analyses. RESULTS: Of the original 451 patients, 86 (19.1%) were eligible for this analysis. 73% (n = 63) had detectable ctDNA at baseline. At week 8, 40% (n = 34) had radiologic partial response (PR), 60% (n = 52) had stable disease (SD); 80% (n = 69) had a ctDNA response (undetectable ctDNA). In patients who had initial PR and undetectable ctDNA, 93% (28/30) had ongoing PR subsequently at week 16. The median duration of response was 14.9 months. In patients with SD and undetectable ctDNA at week 8, 28% had radiological PR at week 16. Amongst those with PR at week 8, survival outcomes for those with undetectable vs detectable ctDNA were not statistically significant (PFS HR 0.49, 95%CI 0.16-1.48, p = 0.21; OS HR 0.39, 95%CI 0.13-1.19, p = 0.10). Amongst those with SD at week 8, there was significantly longer survival for those with undetectable vs detectable ctDNA (PFS HR 0.27, 95% CI 0.13-0.57, p < 0.0001; OS HR 0.40, 95% CI 0.20-0.80, p = 0.009). CONCLUSION: In patients with SD, undetectable ctDNA at week 8 correlated with survival improvement. Both radiologic and ctDNA responses are prognostic of PFS. Incorporation of ctDNA with RECIST may improve tumor response assessment in EGFR-mutant NSCLC.

Assessment of programmed cell death ligand-1 expression by 4 diagnostic assays and its clinicopathological correlation in a large cohort of surgical resected non-small cell lung carcinoma.

Immune checkpoint blockade targeting the PD-1/PD-L1 axis has recently demonstrated efficacy and promise in cancer treatment. Appropriate biomarker selection is therefore essential for improving treatment efficacy. However, the establishment of PD-L1 assay in pathology laboratories is complicated by the presence of multiple testing platforms using different scoring systems. Here we assessed the PD-L1 expression in 713 consecutive non-small cell lung carcinomas by four commercially available PD-L1 immunohistochemical assays, namely, 22C3, 28-8, SP142 and SP263. The analytical performances of the four assays and diagnostic performances across clinically relevant cutoffs were evaluated. The prevalence of PD-L1 (22C3) expression was 21% with a ≥50% cutoff and 56% with a ≥1% cutoff. High PD-L1 expression (using a ≥50% cutoff) was significantly associated with male sex (P = 0.001), ever smoking history (P < 0.001), squamous cell carcinoma (P = 0.001), large cell carcinoma (P < 0.001), lymphoepithelioma-like carcinoma (P = 0.006), sarcomatoid carcinoma (P < 0.001), mutant KRAS (P = 0.005) and wild-type EGFR (P = 0.003). Elevated PD-L1 expression was also significantly associated with shorter survival in patients with adenocarcinoma (log-rank P = 0.026) and remained an independent prognostic factor by multivariable analysis. Among the four assays, 22C3, 28-8 and SP263 were highly concordant for tumor cell scoring. With a cutoff of ≥50% (i.e., the threshold for first-line patient selection), inter-rater agreement was high among the three assays with percentage agreement >97%. In conclusion, three PD-L1 assays showed good analytical performance and a high agreement with each other, but not all cases were correctly classified using the same clinical cutoff. Further studies comparing the predictive value of these assays are required to address the interchangeability of these assays for clinical use.

Prospective validation of the Chinese University Prognostic Index and comparison with other staging systems for hepatocellular carcinoma in an Asian population.

BACKGROUND AND AIM: Hepatitis B viral (HBV) infection is the predominant etiology of hepatocellular carcinoma (HCC) in Asia. Our group previously reported a staging system known as the Chinese University Prognostic Index (CUPI) for HCC populations of which HBV infection is the predominant etiology. This study aims to validate CUPI and compare with other published staging systems. METHODS: We analyzed a prospective cohort of patients with newly diagnosed HCC from 2003 to 2005. All patients were staged with CUPI, Barcelona Clinic Liver Cancer Classification (BCLC), Cancer of the Liver Italian Program score (CLIP), tumor-node-metastasis (TNM) and Okuda systems at diagnosis. They were followed with survival data and the performance of each staging system (in terms of homogeneity, discriminatory ability and monotonicity of gradient) were analyzed and compared. RESULTS: A total of 595 patients (80.2% with chronic HBV infection) were analyzed. The median follow-up was 41.4 months and the median survival was 6.6 months. Multivariate analyses identified symptomatic disease, ascites, vascular involvement, Child-Pugh-stage, alpha-fetoprotein and treatment to be the independent prognostic factors. CUPI could identify three groups with statistically significant survival difference (P < 0.0001). Both CUPI and CLIP had the most favorable performance in terms of discriminatory ability, homogeneity and monotonicity. CUPI performed the best in predicting 3-month survival while CLIP performed better in predicting the outcome of 6- and 12-month survival rate. BCLC was inferior to CLIP and CUPI in the overall performance. CONCLUSION: We have validated CUPI in a population composed of predominant HBV-related HCC. CUPI is an appropriate staging system for HBV-related HCC. In patients with advanced HCC, both CUPI and CLIP offer good risk stratification.

Methodology for quality-of-life assessment: a critical appraisal.

The methodology for QOL assessment covers a wide range of topics. It involves a proper choice of instruments with appropriate psychometric properties, the administration of these instruments, frequency of measurements, missing data problems, and the method of analysis. There are currently debates on the meaning and interpretation of the HRQOL domains taking the form of arguing how to define minimal clinically meaningful difference and whether this can be used in regulatory approval for drug development. From a practical point of view, the authors proposed that a disease-specific checklist or symptom domains incorporated within a HRQOL questionnaire may be a middle ground to gain general agreements among academic institutions, manufacturers, and regulatory agencies to use a specific symptom checklist or domain as the primary end point for clinical trials together with other HRQOL domains as ancillary data for the study. Antiemetic trial with HRQOL assessments is an example. Most would agree, however, that no matter what HRQOL domains or symptoms are being studied, it should be based on a patient self-administered questionnaire as shown by the lack of sensitivity in the example in this article. Missing data are a problem in the data collection and handling. The authors have examined a few commonly used approaches and performed simulation to study their properties. The subscale-mean method when one has more than 50% of the information on a subscale generally reflects the true values. In practice, one still would have missing data that cannot be handled completely by imputation. The method of analysis must be flexible enough to incorporate the nature of these data. Two approaches have been discussed, and they are both flexible in terms of using all available information being obtained in a longitudinal fashion with variable visiting schedules and potential missing data. The HRQOL response variable approach is simple and easy to understand. The growth curve models approach provides more detailed information on average trends between treatment arms. In general, these two methods agree on the results of the example. They can be used to report clinical trial results using HRQOL data as end points.