Immune Checkpoint Inhibitor and Radiotherapy-Related Pneumonitis: An Informatics Approach to Determine Real-World Incidence, Severity, Management, and Resource Implications

Immune-related pulmonary toxicities of checkpoint inhibitors in non-small cell lung cancer: Diagnosis, mechanism, and treatment strategies

Immune checkpoint inhibitors (ICI) therapy based on programmed cell death-1 (PD-1) and programmed cell death ligand 1 (PD-L1) has changed the treatment paradigm of advanced non-small cell lung cancer (NSCLC) and improved the survival expectancy of patients. However, it also leads to immune-related adverse events (iRAEs), which result in multiple organ damage. Among them, the most common one with the highest mortality in NSCLC patients treated with ICI is checkpoint inhibitor pneumonitis (CIP). The respiratory signs of CIP are highly coincident and overlap with those in primary lung cancer, which causes difficulties in detecting, diagnosing, managing, and treating. In clinical management, patients with serious CIP should receive immunosuppressive treatment and even discontinue immunotherapy, which impairs the clinical benefits of ICIs and potentially results in tumor recrudesce. Therefore, accurate diagnosis, detailedly dissecting the pathogenesis, and developing reasonable treatment strategies for CIP are essential to prolong patient survival and expand the application of ICI. Herein, we first summarized the diagnosis strategies of CIP in NSCLC, including the classical radiology examination and the rising serological test, pathology test, and artificial intelligence aids. Then, we dissected the potential pathogenic mechanisms of CIP, including disordered T cell subsets, the increase of autoantibodies, cross-antigens reactivity, and the potential role of other immune cells. Moreover, we explored therapeutic approaches beyond first-line steroid therapy and future direction based on targeted signaling pathways. Finally, we discussed the current impediments, future trends, and challenges in fighting ICI-related pneumonitis.

Real-world incidence and impact of pneumonitis in patients with lung cancer treated with immune checkpoint inhibitors: a multi-institutional cohort study

BACKGROUND

Immune checkpoint inhibitors (ICIs) have improved survival and are increasingly used for non-small cell lung cancer. However, use may be limited by immune-related adverse events such as checkpoint-inhibitor pneumonitis (CIP). Literature estimates for CIP incidence are inconsistent. Real-world adherence to guidelines, clinical course, and healthcare utilization in the treatment of CIP has not been described in large cohorts.

METHODS

A combined claims and electronic health record database (TriNetX) was used to identify 13,113 patients with lung cancer treated with programmed cell death receptor/ligand 1 (PD-1/PD-L1) inhibitors, and a propensity score-matched control cohort treated with chemotherapy or targeted therapies. The attributable risk of CIP was calculated in the first 12 months after therapy by comparing the incidence of diagnosis codes for pneumonitis/pneumonia between cohorts. Cases of CIP, identified by the most specific code for drug-induced respiratory conditions, were further analyzed for medication usage, rates of diagnostic bronchoscopy, ICI discontinuation rates, and usage of hospital services compared with patients receiving PD-1/PD-L1 inhibitors who did not develop CIP.

RESULTS

The attributable risk of pneumonitis to PD-1/PD-L1 inhibitors was 2.49% (95% CI, 1.50% to 3.47%). Median time to onset in the CIP subcohort was 3.9 months (IQR, 2.1-7.3 months). Steroid and antibiotic use increased dramatically after a pneumonitis diagnosis, and 70.2% of patients permanently discontinued ICI therapy. Compared with controls, patients with CIP had more than a threefold increased risk of needing critical care (relative risk 3.59, 95% CI, 2.31 to 5.57) and an increased risk of mortality (HR 2.34, 95% CI, 1.47 to 3.71).

CONCLUSIONS

In a large claims-based analysis, PD-1/PD-L1 inhibitors increase the risk of pneumonitis in patients with lung cancer by 2.49%. Cases of CIP are associated with high healthcare utilization, discontinuation of ICIs, and mortality.

The Impact of Artificial Intelligence on Firm Performance: An Application of the Resource-Based View to e-Commerce Firms

The application of artificial intelligence (AI) technology has evolved into an influential endeavor to improve firm performance, but little research considers the relationship among artificial intelligence capability (AIC), management (AIM), driven decision making (AIDDM), and firm performance. Based on the resource-based view (RBV) and existing findings, this paper constructs a higher-order model of AIC and suggests a research model of e-commerce firm AIC and firm performance. We collected 394 valid questionnaires and conducted data analysis using partial least squares structural equation modeling (PLS-SEM). As a second-order variable, AIC was formed by three first-order variables: basic, proclivity, and skills. AIC indirectly affects firm performance through creativity, AIM, and AI-driven decision making. Firm creativity, AIM, and AIDDM are essential variables between AIC and firm performance. Innovation culture (IC) positive moderates the relationship between firm creativity and AIDDM as well as the relationship between AIDDM and firm performance. Environmental dynamism (ED) positive mediates the connection between AIM and AIDDM. Among the control variables, firm age negatively affects firm performance, and employee size does not. This study helps enterprises leverage AI to improve firm performance, achieve a competitive advantage, and contribute to theory and management practice.