First-line treatments for advanced non-squamous non-small cell lung cancer with immune checkpoint inhibitors plus chemotherapy: a systematic review, network meta-analysis, and cost-effectiveness analysis.

Introduction: The combination of immune checkpoint inhibitors (ICIs) and chemotherapy is a promising first-line therapy for patients with advanced non-squamous non-small cell lung cancer (NSCLC). The cost-effectiveness of combinations with different ICIs is yet to be compared. Methods: We utilized Bayesian network meta-analyses for the comparisons of overall survival, progression-free survival, and incidence of adverse events of the included treatments in the total population and subgroups with different programmed death-ligand 1 tumor proportional scores (TPS). The cost-effectiveness of the treatments from the perspectives of the US and Chinese healthcare systems was assessed using Markov models. Results: Three combinations, including pembrolizumab + chemotherapy (PembroC), nivolumab + ipilimumab + chemotherapy (NivoIpiC), and atezolizumab + chemotherapy (AteC), were included in our study. In terms of efficacy, PembroC was most likely to be ranked first for extending progression-free survival (PFS) (93.16%) and overall survival (OS) (90.73%). Nevertheless, from the US perspective, NivoIpiC and PembroC showed incremental cost-effectiveness ratios (ICERs) of $68,963.1/quality-adjusted life-years (QALY) and $179,355.6/QALY, respectively, compared with AteC. The one-way sensitivity analysis revealed that the results were primarily sensitive to the hazard ratios for OS or the cost of immunotherapy agents. At a willingness-to-pay (WTP) threshold of $150,000/QALY, NivoIpiC had the highest probability of being cost-effective (63%). As for the Chinese perspective, NivoIpiC and PembroC had ICERs of $145,983.4/QALY and $195,863.3/QALY versus AteC, respectively. The results were primarily sensitive to the HRs for OS. At a WTP threshold of $38,017/QALY, AteC had the highest probability of cost-effectiveness (94%). Conclusion: Although PembroC has the optimal efficacy, NivoIpiC and AteC were the most favorable treatments in terms of cost-effectiveness for patients with advanced non-squamous NSCLC from the US and Chinese perspectives, respectively.

Optimal sequence of LT for symptomatic BM in EGFR-mutant NSCLC: a comparative study of first-line EGFR-TKIs with/without upfront LT.

BACKGROUND: The third-generation epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) can penetrate blood-brain barrier and are effective for brain metastases (BMs). There is no consensus on the optimal sequence of local therapy (LT) and EGFR-TKIs for symptomatic BM patients because patients suffering neurological symptoms were not enrolled in most clinical trials. METHODS: Non-small cell lung cancer (NSCLC) patients with EGFR mutation (EGFRm) and symptomatic BM receiving first-line osimertinib and aumolertinib from two medical centers were collected. All participants were allocated into the third-generation EGFR-TKIs (TKIs) group and the upfront LT (uLT) plus third-generation EGFR-TKIs (TKIs + uLT) group. Demographic data, survival outcomes, treatment failure patterns, and adverse events were evaluated between the two groups. We also conducted subgroup analyses to explore the impact of BM number on survival outcomes. RESULTS: 86 patients were enrolled, 44 in the TKIs group and 42 in the TKIs + uLT group. There were no significant differences in the short-term response between the groups. TKIs + uLT was associated with significantly longer overall survival (OS) (43 vs. 28 months; hazard ratio [HR], 0.36, 95% confidence interval [CI], 0.17-0.77; p = .011). No differences in progression-free survival (PFS), intracranial PFS (iPFS), failure patterns, or safety were observed. In subgroup analyses of oligo-BM patients, TKIs + uLT could prolong OS (43 vs. 31 months; HR 0.22; 95% CI 0.05-0.92; p = .015). CONCLUSIONS: EGFRm NSCLC patients with symptomatic BM might benefit from uLT, particularly oligo-BM patients. However, larger prospective cohort studies should be carried out to confirm the responses of the TKIs + uLT scheme.

Cost-effectiveness of neoadjuvant pembrolizumab plus chemotherapy with adjuvant pembrolizumab for early-stage non-small cell lung cancer in the United States.

Introduction: Perioperative (neoadjuvant and adjuvant) pembrolizumab has shown favorable efficacy in patients with early-stage non-small cell lung cancer (NSCLC). This study aims to evaluate the cost-effectiveness of this treatment from the perspective of the United States healthcare payers. Methods: We established a Markov model to compare the cost-effectiveness of perioperative pembrolizumab with that of neoadjuvant chemotherapy in 21-day cycles, utilizing data from the phase 3 KEYNOTE-671 trial. Additional data were extracted from other publications or online sources. Sensitivity analyses were conducted to evaluate the robustness of the findings. A willingness-to-pay threshold of $150,000 per quality-adjusted life-years (QALYs) gained was established. The main outcomes of this study were the measurement of QALYs, overall costs, incremental cost-effectiveness ratio (ICER), and net monetary benefit (NMB). Results: During a 10-year time horizon, the total costs of perioperative pembrolizumab and the control treatment were $224,779.1 and $110,026.3, respectively. The QALYs were 4.19 and 2.97 for the two treatments, respectively, which led to an ICER of $94,222.29 per QALY gained. The NMB at the WTP threshold at $150,000 per QALY gained was $67,931.3. One-way sensitivity analysis identified the cost of pembrolizumab as the primary factor influencing cost-effectiveness. Probabilistic sensitivity analysis indicated a 97.7% probability of perioperative pembrolizumab being cost-effective at the WTP threshold. Conclusions: From the perspective of the United States healthcare payers, perioperative pembrolizumab is a cost-effective treatment for patients with early-stage NSCLC.

Radiomics and deep learning models to differentiate lung adenosquamous carcinoma: A multicenter trial.

Adenosquamous carcinoma (ASC) is frequently misdiagnosed or overlooked in clinical practice due to its dual histological components and potential transformation from either adenocarcinoma (ADC) or squamous cell carcinoma (SCC). Our study aimed to differentiate ASC from ADC and SCC by incorporating features of enhanced CTs and clinical characteristics to build radiomics and deep learning models. The classification models were trained in Xiangya Hospital and validated in two other independent hospitals. The areas under the receiver operating characteristic curves (AUC), accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were used to estimate the performance. The optimal three-class classification model achieved a maximum AUC of 0.89 and accuracy of 0.81 in external validation sets, AUC of 0.99 and accuracy of 0.99 in the internal test set. These findings highlight the efficacy of our models in differentiating ASC, providing a non-invasive, timely, and accurate diagnostic approach before and during the treatment.

MRI radiomics for brain metastasis sub-pathology classification from non-small cell lung cancer: a machine learning, multicenter study.

The objective of this study is to develop a machine-learning model that can accurately distinguish between different histologic types of brain lesions in patients with non-small cell lung cancer (NSCLC) when it is not safe or feasible to perform a biopsy. To achieve this goal, the study utilized data from two patient cohorts: 116 patients from Xiangya Hospital and 35 patients from Yueyang Central Hospital. A total of eight machine learning algorithms, including Xgboost, were compared. Additionally, a 3-dimensional convolutional neural network was trained using transfer learning to further evaluate the performance of these models. The SHapley Additive exPlanations (SHAP) method was developed to determine the most important features in the best-performing model after hyperparameter optimization. The results showed that the area under the curve (AUC) for the classification of brain lesions as either lung adenocarcinoma or squamous carcinoma ranged from 0.60 to 0.87. The model based on single radiomics features extracted from contrast-enhanced T1 MRI and utilizing the Xgboost algorithm demonstrated the highest performance (AUC: 0.85) in the internal validation set and adequate performance (AUC: 0.80) in the independent external validation set. The SHAP values also revealed the impact of individual features on the classification results. In conclusion, the use of a radiomics model incorporating contrast-enhanced T1 MRI, Xgboost, and SHAP algorithms shows promise in accurately and interpretably identifying brain lesions in patients with NSCLC.

A multiomics approach-based prediction of radiation pneumonia in lung cancer patients: impact on survival outcome.

PURPOSE: To predict the risk of radiation pneumonitis (RP), a multiomics model was built to stratify lung cancer patients. Our study also investigated the impact of RP on survival. METHODS: This study retrospectively collected 100 RP and 99 matched non-RP lung cancer patients treated with radiotherapy from two independent centres. They were divided into training (n = 175) and validation cohorts (n = 24). The radiomics, dosiomics and clinical features were extracted from planning CT and electronic medical records and were analysed by LASSO Cox regression. A multiomics prediction model was developed by the optimal algorithm. Overall survival (OS) between the RP, non-RP, mild RP, and severe RP groups was analysed by the Kaplan‒Meier method. RESULTS: Sixteen radiomics features, two dosiomics features, and one clinical feature were selected to build the best multiomics model. The optimal performance for predicting RP was the area under the receiver operating characteristic curve (AUC) of the testing set (0.94) and validation set (0.92). The RP patients were divided into mild (≤ 2 grade) and severe (> 2 grade) RP groups. The median OS was 31 months for the non-RP group compared with 49 months for the RP group (HR = 0.53, p = 0.0022). Among the RP subgroup, the median OS was 57 months for the mild RP group and 25 months for the severe RP group (HR = 3.72, p < 0.0001). CONCLUSIONS: The multiomics model contributed to improving the accuracy of RP prediction. Compared with the non-RP patients, the RP patients displayed longer OS, especially the mild RP patients.

The value of postoperative radiotherapy in thymoma patients with myasthenia gravis.

INTRODUCTION: Surgery is the first-line treatment for patients with thymoma associated with myasthenia gravis (MG); however, the value of radiotherapy among these patients remains debatable. Herein, we examined the impact of postoperative radiotherapy (PORT) on the efficacy and prognosis of patients with thymoma and MG. METHODS: This retrospective cohort study included 126 patients with thymoma and MG who were enrolled in the Xiangya Hospital clinical database between 2011 and 2021. Demographic and clinical data were collected including sex, age, histologic subtype, Masaoka-Koga staging, primary tumor, lymph node, metastasis (TNM) staging, and therapeutic modalities. To evaluate short-term MG symptom improvement following PORT, we examined changes in the quantitative myasthenia gravis (QMG) scores within 3 months post-treatment. Minimal manifestation status (MMS) was the main endpoint for assessing long-term improvement in MG symptoms. Overall survival (OS) and disease-free survival (DFS) were primary endpoints to determine the impact of PORT on prognosis. RESULTS: Effects of PORT on MG symptoms: QMG scores significantly differed between the non-PORT and PORT groups (χ2 = 6.300, p = 0.012). The median time to achieve MMS was significantly shorter in the PORT group than that in the non-PORT group (2.0 years vs. 4.4 years; p = 0.031). Multivariate analysis revealed that radiotherapy was associated with a reduced time to achieve MMS (hazard ratio [HR] 1.971, 95% confidence interval [CI]:1.102-3.525, p = 0.022). Effects of PORT on DFS and OS: The 10-year OS rate of the entire cohort was 90.5%, whereas OS rates for the PORT and non-PORT groups were 94.4 and 85.1%, respectively. The 5-year DFS rates for the whole cohort, PORT group, and non-PORT group were 89.7, 95.8, and 81.5%, respectively. PORT was associated with improved DFS (HR 0.139, 95% CI: 0.037-0.533, p = 0.004). In the high-risk histologic subgroup (type B2, B3), patients who received PORT had better OS (p = 0.015) and DFS (p = 0.0053) than those who did not receive PORT. PORT was associated with improved DFS (HR 0.232, 95% CI: 0.069-0.782, p = 0.018) in Masaoka-Koga stages II, III, and IV disease. CONCLUSIONS: Overall, our findings indicate that PORT positively impacts thymoma patients with MG, particularly those with a higher histologic subtype and Masaoka-Koga staging.

Case report: Brain metastasis necrosis with immune checkpoint inhibitors plus chemotherapy for advanced non-small cell lung cancer.

The emergence of immune checkpoint inhibitors (ICIs) has reshaped the landscape of advanced lung cancer treatment. The brain is the most common metastatic site for lung cancer. Whether conventional criteria can evaluate the intracranial response of ICIs remains unclear. Here, we report a well-documented case of intracranial necrosis confirmed by post-operative pathology after only one cycle of chemo-immunotherapy without any radiation therapy, which suggests that immunotherapy elicits strong anti-tumor responses for intracranial metastasis and promotes intracranial necrosis, resulting in a temporary increase in size of the target lesions. Still, the specific mechanisms and management strategies need to be further explored.

The Long-Term and Short-Term Efficacy of Immunotherapy in Non-Small Cell Lung Cancer Patients With Brain Metastases: A Systematic Review and Meta-Analysis.

Background: Although immunotherapy has been widely used, there is currently no research comparing immunotherapy for non-small cell lung cancer (NSCLC) patients with brain metastases (BMs). This meta-analysis addresses a gap in the comparison of immunotherapy efficacy, including immune checkpoint inhibitors (ICIs), chemotherapy (CT), radiotherapy (RT), and ICI combined CT or RT. Methods: A search of Pubmed, Cochrane, EMBASE, and ClinicalTrial.gov was conducted to identify studies which enrolled NSCLC patients with BM treated with ICIs. The outcomes consisted of intracerebral overall response rate (iORR), intracerebral disease control rate (iDCR), extracranial overall response rate (EORR), distant brain failure (DBF), local control (LC), progression-free survival (PFS), and overall survival (OS). Results: A total of 3160 participants from 46 trials were included in the final analysis. Patients treated with immunotherapy were associated with a longer PFS (0.48, 95%CI: 0.41-0.56), and a longer OS (0.64, 95%CI: 0.60-0.69) compared with immunotherapy-naive patients. In prospective studies, dual ICI combined CT and ICI combined CT achieved a better OS. The hazard ratio (HR) of dual ICI combined CT versus dual ICI was 0.61, and the HR of ICI combined CT versus ICI monotherapy was 0.58. Moreover, no statistical difference in PFS, OS, EORR, iORR, iDCR, and EDCR was found between patients with ICI monotherapy and ICI combined cranial radiotherapy. Concurrent ICI combined RT was shown to decrease the rate of DBF (OR = 0.15, 95% CI: 0.03-0.73) compared with RT after ICI. Patients treated with WBRT might have an inferior efficacy than those with SRS because the iORR of SRS was 0.75 (0.70, 0.80) and WBRT was 0. Furthermore, no obvious difference in PFS and OS was observed among the three different types of ICI, which targets PD-1, PD-L1, and CTLA-4, respectively. Conclusions: Patients treated with ICI got superior efficacy to those without ICI. Furthermore, dual ICI combined CT and ICI combined CT seemed to be optimal for NSCLC patients with BM. In terms of response and survival, concurrent administration of SRS and ICI led to better outcomes for patients with BMs than non-concurrent or non-SRS. Importance of the Study: In the new era of immunotherapy, our meta-analysis validated the importance of immunotherapy for non-small cell lung cancer (NSCLC) patients with brain metastases (BMs). By comparing the long-term and short-term impacts of various regimens, all immunotherapy treatments had superior efficacy to immunotherapy-naive. At the same time, through pairwise comparison in immunotherapy, our findings can help clinicians to make treatment decisions for NSCLC patients with BMs. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=269621, identifier CRD42021269621.

Factor structure and measurement invariance of the Chinese version of the Center for Epidemiological Studies Depression (CES-D) scale among undergraduates and clinical patients.

BACKGROUND: The Center for Epidemiologic Studies Depression scale (CESD) was widely used for screening of depressive symptoms. The purpose of the current study was to investigate the factor structure and measurement invariance of the CESD across genders and groups in a sample of Chinese undergraduates and clinical patients. METHODS: Participants included 3093 undergraduates from the Hunan province and 336 patients from psychological clinics. The structure of the CESD scale was analyzed by confirmatory factor analysis (CFA). Multiple sets of CFAs were used to test measurement invariance across genders among undergraduates and clinical patients. Internal consistency reliability was also evaluated. RESULTS: The five-factor model achieved satisfactory fit (in the undergraduate sample: WLSMVχ2 = 1662.385, df = 160, CFI = 0.973, TLI = 0.968, RMSEA = 0.055; in the clinical patients: WLSMVχ2 = 502.089, df = 160, CFI = 0.962, TLI = 0.955, RMSEA = 0.072). The measurement invariance of the five-factor model across genders was supported fully assuming different degrees of invariance. The CESD also showed acceptable internal consistency. CONCLUSION: Due to its sound structure and measurement invariance, the five-factor model of the CESD is best suited for testing in Chinese mainland college students and clinical patients.