Real-World Data on Pembrolizumab for Pretreated Non-Small-Cell Lung Cancer: Clinical Outcome and Relevance of the Lung Immune Prognostic Index

Prognostic value of lung immune prognostic index in non-small cell lung cancer patients receiving immune checkpoint inhibitors: a meta-analysis

Background and Purpose

Until now, it has been difficult to accurately predict the efficacy of immunotherapy in patients with non-small cell lung cancer (NSCLC). A novel indicator, the lung immune prognostic index (LIPI), has shown relatively high prognostic value in patients with solid cancer. Therefore, this study aimed to further identify the association between LIPI and the survival of patients with NSCLC who receive immune checkpoint inhibitors (ICIs).

Methods

Several electronic databases were searched for available publications up to April 23, 2023. Immunotherapy outcomes included overall survival (OS), progression-free survival (PFS), and hazard ratios (HRs) with 95% confidence intervals (CIs). Subgroup analysis based on the study design and comparison of the LIPI was conducted.

Results

In this meta-analysis, 21 studies with 9,010 patients were included in this meta-analysis. The pooled results demonstrated that elevated LIPI was significantly associated with poor OS (HR = 2.50, 95% CI:2.09-2.99, p < 0.001) and PFS (HR = 1.77, 95% CI:1.64-1.91, p < 0.001). Subgroup analyses stratified by study design (retrospective vs. prospective) and comparison of LIPI (1 vs. 0, 2 vs. 0, 1-2 vs. 0, 2 vs. 1 vs. 0, 2 vs. 0-1 and 2 vs. 1) showed similar results.

Conclusion

LIPI could serve as a novel and reliable prognostic factor in NSCLC treated with ICIs, and elevated LIPI predicts worse prognosis.

Immune-related adverse events and their effects on survival outcomes in patients with non-small cell lung cancer treated with immune checkpoint inhibitors: a systematic review and meta-analysis

Background

The use of immune checkpoint inhibitors (ICIs) has become the standard of care for non-small cell lung cancer. The purpose of this study was to systematically review the literature to determine whether the occurrence of immune-related adverse events (irAEs) following the use of ICIs predicts different clinical outcomes in non-small cell lung cancer (NSCLC).

Methods

Relevant studies from the time of database creation to July 20, 2023, were systematically searched to explore the differences in clinical outcomes in patients with advanced NSCLC with or without irAEs. The outcome indicators included the occurrence of irAEs, progression-free survival (PFS), and overall survival (OS).

Results

25 studies met the inclusion criteria. Of these studies, 22 reported the effect on OS, and 19 reported the effect on PFS. The results showed that for patients with NSCLC, the occurrence of irAEs after receiving immunotherapy showed a statistically significant benefit over the absence of irAEs for OS (HR=0.55,95% CI=0.46-0.65) and PFS (HR=0.55 95% CI=0.48-0.64), but severe irAEs (grades 3-5) were associated with worse OS (HR=1.05, 95% CI=0.87-1.27). Compared with gastrointestinal, lung, and hepatitis, irAEs of the skin and endocrine system tend to predict better OS and PFS.

Conclusion

The occurrence of irAEs, especially mild and early irAEs, indicates better OS and PFS in patients with NSCLC treated with ICIs, irrespective of patient characteristics, type of ICIs, and irAEs. However, Grade 3 or higher toxicities resulted in worse OS.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42023409444.

Prognosis stratification of cancer patients treated with immune checkpoint inhibitors through lung immune prognostic index: a meta-analysis and systematic review

BACKGROUND

Although numerous studies have reported the prognostic value of the lung immune prognostic index (LIPI) in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), the prognostic value of the LIPI in a pancancer setting remains unclear.

METHODS

A comprehensive search was conducted until July 2023 across the PubMed, Embase, Web of Science, and Cochrane Library databases to identify relevant studies evaluating the prognostic value of the LIPI in cancer patients treated with ICIs. The outcomes were overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR). We described and compared the pooled outcomes by stratifying the patients based on different groupings of LIPI (good vs. intermediate [0 vs. 1], good vs. poor [0 vs. 2], and good vs. intermediate / poor [0 vs. 1 + 2]).

RESULTS

A total of 9959 patients in 35 studies were included. A higher score of LIPI was associated with impaired OS. The pooled HRs were 1.69 (95% CI: 1.55-1.85, p < 0.001; 0 vs. 1), 3.03 (95% CI: 2.53-3.63, p < 0.001; 0 vs. 2), and 2.38 (95% CI: 1.97-2.88, p < 0.001; 0 vs. 1 + 2). A higher LIPI score was associated with shorter PFS. The pooled HRs were 1.41 (95% CI: 1.31-1.52, p < 0.001; 0 vs. 1), 2.23 (95% CI: 1.87-2.66, p < 0.001; 0 vs. 2), and 1.65 (95% CI: 1.46-1.86, p < 0.001; 0 vs. 1 + 2). Similarly, a higher LIPI score was associated with a lower ORR. The pooled ORs were 0.63 (95% CI: 0.54-0.75, p < 0.001; 0 vs. 1) and 0.38 (95% CI: 0.29-0.50, p < 0.001; 0 vs. 2). A higher LIPI score was associated with a lower DCR. The pooled ORs were 0.47 (95% CI: 0.35-0.61, p < 0.001; 0 vs. 1) and 0.19 (95% CI: 0.12-0.30, p < 0.001; 0 vs. 2).

CONCLUSION

In patients with NSCLC or other solid tumours, the lung immune prognostic index could robustly stratify the clinical outcomes into three groups among the patients who receive ICIs. LIPI is a low-cost, simple, accessible, and accurate prognostic tool in a pancancer setting and it may contribute to the evaluation of risk stratification in patients treated with ICIs.

From data strategy to implementation to advance cancer research and cancer care: A French comprehensive cancer center experience

In a comprehensive cancer center, effective data strategies are essential to evaluate practices, and outcome, understanding the disease and prognostic factors, identifying disparities in cancer care, and overall developing better treatments. To achieve these goals, the Center Léon Bérard (CLB) considers various data collection strategies, including electronic medical records (EMRs), clinical trial data, and research projects. Advanced data analysis techniques like natural language processing (NLP) can be used to extract and categorize information from these sources to provide a more complete description of patient data. Data sharing is also crucial for collaboration across comprehensive cancer centers, but it must be done securely and in compliance with regulations like GDPR. To ensure data is shared appropriately, CLB should develop clear data sharing policies and share data in a controlled, standardized format like OSIRIS RWD, OMOP and FHIR. The UNICANCER initiative has launched the CONSORE project to support the development of a structured and standardized repository of patient data to improve cancer research and patient outcomes. Real-world data (RWD) studies are vital in cancer research as they provide a comprehensive and accurate picture of patient outcomes and treatment patterns. By incorporating RWD into data collection, analysis, and sharing strategies, comprehensive cancer centers can take a more comprehensive and patient-centered approach to cancer research. In conclusion, comprehensive cancer centers must take an integrated approach to data collection, analysis, and sharing to enhance their understanding of cancer and improve patient outcomes. Leveraging advanced data analytics techniques and developing effective data sharing policies can help cancer centers effectively harness the power of data to drive progress in cancer research.

Significance of the Lung Immune Prognostic Index for Assessment of the Reliability of the Clinical Treatment Outcome for Advanced Non-Small-Cell Lung Cancer in Patients with COVID-19 Infection

Introduction: Lung cancer is one of the most diagnosed malignancies with increasing incidence worldwide. Immunotherapy is the main oncological treatment for advanced non-small cell lung cancer (NSCLC), for which the discovery of new efficient biomarkers is crucial. Scientific evidence points to the importance of the Lung Immune Prognostic Index (LIPI), but its predictive significance is unclear. Aim: The aim of this study was to investigate the clinical significance and predictive role of LIPI in patients with advanced NSCLC and PD-L1 mutation who are eligible for immunotherapy in combination with chemotherapy. In addition, to our knowledge, this is the first time that the association between COVID-19 infection and the course and outcome of oncologic treatment of NSCLC has been investigated. Patients and Methods: Patients were divided into four study groups according to strictly defined clinical parameters, therapeutic approach, and COVID-19 infection. LIPI was determined and its predictive power was evaluated in all studied groups, as well as overall survival (OS), progression-free survival (PFS), and disease control rate (DCR). Results: This study confirmed the understudied and uncertain predictive power and clinical relevance of LIPI as a biomarker in patients with advanced NSCLC. Patients infected with COVID-19 had a higher survival rate than uninfected patients despite the therapeutic approach, which may be attributed to their hospitalization and intensive medical management during the pandemic. Conclusions: Findings obtained in this study may help to determine treatment options according to the clinical condition of the patient by using LIPI values as a non-invasive, readily available and economically acceptable predictive biomarker in lung oncology.

Development of a Simple and Objective Prognostication Model for Patients with Advanced Solid Malignant Tumors Treated with Immune Checkpoint Inhibitors: A Pan-Cancer Analysis

BACKGROUND

Systemic therapy using immune checkpoint inhibitors (ICIs) has recently become prevalent in the treatment of patients with various types of advanced cancers; however, difficulties are still associated with predicting the outcomes of patients receiving ICIs due to heterogenous responses to these agents.

OBJECTIVE

To develop a prognostic model for advanced cancer patients treated with ICIs.

PATIENTS AND METHODS

This study retrospectively analyzed the impact of clinical parameters on overall survival (OS) in 329 patients with several advanced solid malignant tumors who received systemic therapy using ICIs.

RESULTS

The primary tumors of 329 patients were as follows: lung (n = 89), kidney (n = 70), urinary tract (n = 52), skin (n = 50), stomach (n = 30), esophagus (n = 21), and head and neck (n = 17). Median OS after the introduction of ICIs was 17.3 months. Among the factors that correlated with OS in a univariate analysis, body mass index, C-reactive protein, hemoglobin, lymphocytes, and platelets were identified as independent predictors of OS in a multivariate analysis. Following the classification of patients into 3 groups based on positive numbers of these independent risk factors, median OS was not reached in the favorable risk group with 0 or 1 risk factor (n = 76), 19.5 months in the intermediate-risk group with 2 or 3 risk factors (n = 182), and 7.2 months in the poor risk group (n = 71) with 4 or 5 risk factors.

CONCLUSIONS

Although this is a simple and objective model, it may be used as a reliable tool to predict the outcomes of advanced cancer patients receiving ICIs across multiple tumor types.