Association Between Lung Immune Prognostic Index and Durvalumab Consolidation Outcomes in Patients With Locally Advanced Non-Small-Cell Lung Cancer

INTRODUCTION

The LIPI, based on pretreatment derived neutrophils/[leukocytes-neutrophils] ratio (dNLR) and LDH, is associated with immune checkpoint inhibitors (ICI) outcomes in advanced non-small-cell lung cancer (NSCLC). We aimed to assess baseline LIPI correlation with durvalumab consolidation outcomes in the locally advanced setting.

MATERIAL AND METHODS

Multicentre retrospective study (330 patients) with stage III unresectable NSCLC treated with durvalumab after chemo-radiotherapy between April 2015 and December 2020; 65 patients treated with chemo-radiotherapy only. Baseline LIPI characterized 3 groups: good (dNLR≤3+LDH≤ULN), intermediate (dNLR>3/LDH>ULN) and poor (dNLR>3+LDH>ULN). Primary endpoint was overall survival (OS).

RESULTS

In the durvalumab cohort, median age was 67 years, 95% smokers, 98% with a performance status of 0-1; 60% had nonsquamous histology and 16% a PD-L1 expression <1%. Radiotherapy was delivered concurrently in 81%. LIPI was evaluable in 216 patients: 66% good, 31% intermediate, 3% poor. LIPI significantly correlated with median OS (median follow-up: 19 months): 18.1 months vs. 47.0 months vs. not reached in poor, intermediate and good LIPI groups, respectively (P = .03). A trend between objective response rate and LIPI groups was observed: 0% vs. 41% vs. 45%, respectively (P = .05). The pooled intermediate/poor LIPI group was associated with shorter OS (HR 1.97; P = .03) and higher risk of progressive disease (OR 2.68; P = .047). Survivals and response were not influenced in the control cohort.

CONCLUSION

Baseline LIPI correlated with outcomes in patients with locally advanced NSCLC treated with durvalumab consolidation, but not in those who only received chemo-radiotherapy, providing further evidence of its prognostic and potential predictive role of ICI benefit in NSCLC.

Patients' selection and trial matching in early-phase oncology clinical trials

BACKGROUND

Early-phase clinical trials (EPCT) represent an important part of innovations in medical oncology and a valuable therapeutic option for patients with metastatic cancers, particularly in the era of precision medicine. Nevertheless, adult patients' participation in oncology clinical trials is low, ranging from 2% to 8% worldwide, with unequal access, and up to 40% risk of early discontinuation in EPCT, mostly due to cancer-related complications.

DESIGN

We review the tools and initiatives to increase patients' orientation and access to early phase cancer clinical trials, and to limit early discontinuation.

RESULTS

New approaches to optimize the early-phase clinical trial referring process in oncology include automatic trial matching, tools to facilitate the estimation of patients' prognostic and/or to better predict patients' eligibility to clinical trials. Classical and innovative approaches should be associated to double patient recruitment, improve clinical trial enrollment experience and reduce early discontinuation rates.

CONCLUSIONS

Whereas EPCT are essential for patients to access the latest medical innovations in oncology, offering the appropriate trial when it is relevant for patients should increase by organizational and technological innovations. The oncologic community will need to closely monitor their performance, portability and simplicity for implementation in daily clinical practice.

Neutrophil-to-Lymphocyte Ratio (NLR) in NSCLC, Gastrointestinal, and Other Solid Tumors: Immunotherapy and Beyond

In the era of immunotherapy, identifying biomarkers of immune system activation has become a high-priority challenge. The blood neutrophil-to-lymphocyte ratio (NLR) has been largely investigated as a biomarker in several cancer types. NLR values have been shown to mirror the tumor-induced inflammatory status and have been demonstrated to be a reliable prognostic tool across stages of disease and therapeutic approaches. When integrated with other biomarkers of response to immunotherapy, such as PD-L1, tumor mutational burden, and tumor-associated immune cells, the NLR may allow to further stratify patients with different likelihoods of deriving a significant clinical benefit. However, despite its accessibility, low cost, and easy interpretation, the NLR is still poorly used as a prognostic tool in daily clinical practice. In this review, we analyze the role of the NLR in defining the relationship between cancer and the immune system, its usefulness in daily clinical practice, and its relationship with other established or emerging biomarkers of immunotherapy outcomes.

Determinants of activity and efficacy of anti-PD1/PD-L1 therapy in patients with advanced solid tumors recruited in a clinical trials unit: a longitudinal prospective biomarker-based study

Immune-checkpoint inhibitors (ICI) have revolutionized the therapeutic landscape of cancer. However, optimal patient selection is still an unmet need. One-hundred-forty-six patients with metastatic cancer candidates to ICI at the Hospital Clinic of Barcelona Clinical Trials Unit were prospectively recruited in this observational study. Blood samples were collected at different timepoints, baseline LIPI score calculated and pre-ICI archived tissues retrieved to evaluate PD-L1, tumor-infiltrating lymphocytes (TILs) and PD1 mRNA levels. Tumor assessments were centrally reviewed by RECIST 1.1 criteria. Associations with overall response rates (ORR), durable clinical benefit (DCB), progression-free survival (PFS) and overall survival (OS) were performed with univariable/multivariable logistic and Cox regressions, where appropriate. At a median follow-up of 26.9 months, median PFS and OS were 2.7 and 12.9 months. Response rates were 17.8% with duration of response (DOR) of 4.4 months. LIPI score was independently associated with PFS (p = 0.025) and OS (p < 0.001). Immunotherapy-naïve status was independently associated with better PFS (p = 0.005). Time-to-best response (TTBR) and ORR (p < 0.001 both) were associated with better OS at univariate analysis. PFS and DOR were moderately correlated with OS (p < 0.001 both). A PD-L1 10% cut-off detected worse/best responders in terms of ORR (univariate p = 0.011, multivariate p = 0.028) and DCB (univariate p = 0.043). PD1 mRNA levels were strikingly associated to complete responses (p = 0.021). To resume, in our prospective observational pan-cancer study, baseline LIPI score, immunotherapy-naïve status, cancer type and RT before starting ICI were the most relevant clinical factors independently correlated with immunotherapy outcomes. Longer TTBR seemed to associate with better survival, while PD1 mRNA and PD-L1 protein levels might be tumor-agnostic predictive factors of response to ICI and should be furtherly explored.

Predicting Immunotherapy Outcomes in Older Patients with Solid Tumors Using the LIPI Score

Immunotherapy with immune checkpoint blockers (ICB) represents a valid therapeutic option in older patients for several solid cancer types. However, most of the data concerning efficacy and adverse events of ICB available are derived from younger and fitter patients. Reliable biomarkers are needed to better select the population that will benefit from ICB especially in older patients who may be at a higher risk of developing immune-related adverse events (irAEs) with a greater impact on their quality of life. The Lung Immune Prognostic Index (LIPI) is a score that combines pretreatment dNLR (neutrophils/[leukocytes − neutrophils]) and lactate dehydrogenase (LDH) and is correlated with outcomes in patients treated with ICB in non-small-cell lung cancer. We aimed to assess the impact of LIPI in ICB outcomes in a dedicated cohort of older patients. The primary objective was to study the prognostic role of LIPI score in patients aged 70 years or above in a real-life population treated with anti-programmed death-(ligand)1 (anti PD-(L)1). dNLR and LDH were collected in a prospective cohort of patients aged 70 years or above treated with PD-(L)1 inhibitors with metastatic disease between June 2014 and October 2017 at Gustave Roussy. LIPI categorizes the population into three different prognostic groups: good (dNLR ≤ 3 and LDH ≤ ULN—upper normal limit), intermediate (dNLR > 3 or LDH > ULN), and poor (dNLR > 3 and LDH > ULN). Anti PD-(L)1 benefit was analyzed according to overall survival (OS), progression free survival (PFS), and overall response rate (ORR) using RECIST v1.1. criteria. In the 191 older patients treated, most of them (95%) were ICB-naïve, and 160 (84%) had an ECOG performance status of 0−1 with a median age at ICB treatment of 77 (range, 70−93). The most common tumor types were melanoma (66%) and non-small-cell lung cancer (15%). The median follow-up duration was 18.8 months (95% CI 14.7−24.2). LIPI classified the population into three different groups: 38 (23%) patients had a good LIPI score, 84 (51%) had an intermediate LIPI score, and 43 (26%) had a poor LIPI score. The median OS was 20.7 months [95% CI, 12.6−not reached] compared to 11.2 months [95% CI, 8.41−22.2] and 4.7 months [95% CI, 2.2−11.3] in patients with a good, intermediate, and poor LIPI score, respectively (p = 0.0003). The median PFS was 9.2 months [95% CI, 6.2−18.1] in the good LIPI group, 7.2 months [95% CI, 5.4−13] in the intermediate LIPI group, and 3.9 months [95% CI, 2.3−8.2] in the poor LIPI group (p = 0.09). The rate of early death (OS < 3 months) was 37% in the poor LIPI group compared to 5% in the good LIPI group (<0.001). Poor LIPI score was associated with a poorer outcome in older patients treated with anti PD-(L)1. LIPI is a simple and accessible worldwide tool that can serve as a prognostic factor and can be useful for stratification benefit from ICB.

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

BACKGROUND

Pembrolizumab is licensed for the treatment of pre-treated and PD-L1 positive non-small cell lung cancer (NSCLC), but response is heterogeneous. In this context, the Lung Immune Prognostic Index (LIPI) has been proposed as tool to prognosticate outcome.

OBJECTIVE

To investigate the real-world efficacy and safety of pembrolizumab in pre-treated NSCLC patients and the clinical utility of LIPI for patients' selection.

PATIENTS AND METHODS

Patients with pre-treated NSCLC and PD-L1 ≥ 1% treated with pembrolizumab were included in this retrospective series. The LIPI was used to classify patients in 3 prognostics subgroups according to the pre-treatment dNLR (derived neutrophil to lymphocyte ratio) and LDH in blood. The prognostic impact of the LIPI on progression free survival (PFS) and overall survival (OS) was evaluated with Cox regression. The combined effect of LIPI and other relevant prognostic factors was explored with multivariate regression.

RESULTS

In total, 113 consecutive patients were included. Median (mPFS) and mOS was 4.3 (2.6-6.7) and 13.5 (10.3-17.7) months, respectively. Good-, intermediate-, and poor-LIPI was found in 54 (47.8%), 45 (39.8%), and 8 (7.1%) patients, respectively. Median PFS was 5.1 (2.8-9.1), 3.0 (2.5-6.8), and 1.4 (0.5-18.7) months, and mOS was 17.2 (12.0-26.4), 11.8 (8.4-17.1), and 3.7 (0.5-not calculable) months for good-, intermediate-, and poor-LIPI group, respectively. Patients with intermediate-LIPI and poor-LIPI had worse PFS versus good-LIPI, and statistically significant worse OS (p = 0.030 and p = 0.013, respectively). In the multivariate analysis, intermediate- versus good-LIPI (p = 0.190) was not independently associated to PFS or OS. Patients with both good-LIPI and high (≥ 50%) PD-L1 had better OS than all other subgroups defined by LIPI and PD-L1. Immune-related adverse events (irAEs) occurred in 47 (41.6%) patients (12.4% grade ≥ 3). In a time-varying analysis, irAEs were statistically associated with longer OS (HR 0.51, 0.31-0.84; p = 0.008).

CONCLUSION

In our series, the outcome of pembrolizumab in pre-treated NSCLC is consistent with the registration trial. Lung Immune Prognostic Index is a readily available tool able to prognosticate outcome, also in PD-L1-high patients. The positive association between irAEs and OS might aid decision making.

Association of the Lung Immune Prognostic Index with Immunotherapy Outcomes in Mismatch Repair Deficient Tumors

Background: MSI-H/dMMR is considered the first predictive marker of efficacy for immune checkpoint inhibitors (ICIs). However, around 39% of cases are refractory and additional biomarkers are needed. We explored the prognostic value of pretreatment LIPI in MSI-H/dMMR patients treated with ICIs, including identification of fast-progressors. Methods: A multicenter retrospective study of patients with metastatic MSI-H/dMMR tumors treated with ICIs between April 2014 and May 2019 was performed. LIPI was calculated based on dNLR > 3 and LDH > upper limit of normal. LIPI groups were good (zero factors), intermediate (one factor) and poor (two factors). The primary endpoint was overall survival (OS), including the fast-progressor rate (OS < 3 months). Results: A total of 151 patients were analyzed, mainly female (59%), with median age 64 years, performance status (PS) 0 (42%), and sporadic dMMR status (68%). ICIs were administered as first or second-line for 59%. The most frequent tumor types were gastrointestinal (66%) and gynecologic (22%). LIPI groups were good (47%), intermediate (43%), and poor (10%). The median follow-up was 32 months. One-year OS rates were 81.0%, 67.1%, and 21.4% for good, intermediate, and poor-risk groups (p < 0.0001). After adjustment for tumor site, metastatic sites and PS, LIPI remained independently associated with OS (HR, poor-LIPI: 3.50, 95%CI: 1.46-8.40, p = 0.02. Overall, the fast-progressor rate was 16.0%, and 35.7% with poor-LIPI vs. 7.5% in the good-LIPI group (p = 0.02). Conclusions: LIPI identifies dMMR patients who do not benefit from ICI treatment, particularly fast-progressors. LIPI should be included as a stratification factor for future trials.

Pretreatment lung immune prognostic index as a biomarker in advanced non-small-cell lung cancer patients receiving first line pembrolizumab

Background: To investigate the role of pretreatment lung immune prognostic index (LIPI) as biomarker in PD-L1 ≥50% non-small-cell lung cancer patients receiving pembrolizumab. Patients & methods: We retrospectively identified 117 patients, divided into three prognostic groups according to LIPI score. For each patient, we evaluated 1-year overall survival (OS) and progression-free survival rate. C-statistic and survival receiver operating characteristic curves were used to study discrimination of LIPI. Results: After a median follow-up of 11.7 months, 1-year OS rate was 60.1%, 35.3% and 28.6%, while 1-year progression-free survival rate was 39.1%, 20.6% and 14.3% in good, intermediate and poor LIPI groups, respectively (p < 0.001). The c-statistic and area under the curve of LIPI were 0.63 and 0.662 for OS and 1-year OS, respectively. Conclusions: Higher LIPI score is related to worse survival in advanced non-small-cell lung cancer patients treated with first-line pembrolizumab. However, based on c-statistic and area under the curve, LIPI does not represent a good prognostic survival model.

Improving patient selection for immuno-oncology phase 1 trials: External validation of six prognostic scores in a French Cancer Center

We compared the performance of six prognostic scores (Royal Marsden Hospital, MDACC: MD Anderson Clinical Center and MDACC + NLR: neutrophil-to-lymphocyte ratio, MD Anderson - immune checkpoint inhibitors (MDA-ICI), GRIm: Gustave Roussy Immune Score and LIPI: Lung Immune Prognostic Index) in predicting overall survival (OS) in phase I trial patients treated with immune checkpoint inhibitors (ICI). Medical records of patients with advanced solid tumors enrolled in ICI phase I trials between 2015 and 2018 at Institut Universitaire du Cancer de Toulouse-Oncopole were reviewed. The performance of prognostic scores on OS was compared using different criteria. A total of 259 patients were included. Median age was 63 years (range: 18-83). Main primary cancers were melanoma (19%), head and neck (16%), lung (13%) and bladder (10%). With a median follow-up of 15 months (95% confidence interval [CI] = [11.6;17.5]), median OS was 12.5 months (95% CI = [10.3;16.0]). All scores were associated with OS. The MDACC, LIPI and GRIm scores performed better than the others. Concordance of risk group assignment between the scoring systems was poor. According to our results, the MDACC, GRIm and LIPI scores better suited to ICI phase I settings. Adequate scoring would allow better patient selection in early ICI trials, especially during the critical period of dose escalation, and in proof-of-concept expansion cohorts.

Biomarkers or factors for predicting the efficacy and adverse effects of immune checkpoint inhibitors in lung cancer: achievements and prospective

Immune checkpoint inhibitors (ICIs) are widely used in lung cancer therapy due to their effectiveness and minimal side effects. However, only a few lung cancer patients benefit from ICI therapy, driving the need to develop alternative biomarkers. Programmed death-ligand 1 (PD-L1) molecules expressed in tumor cells and immune cells play a key role in the immune checkpoint pathway. Therefore, PD-L1 expression is a prognostic biomarker in evaluating the effectiveness of programmed death-1 (PD-1)/PD-L1 inhibitors. Nevertheless, adverse predictive outcomes suggest that other factors are implicated in the response. In this review, we present a detailed introduction of existing biomarkers concerning tumor abnormality and host immunity. PD-L1 expression, tumor mutation burden, neoantigens, specific gene mutations, circulating tumor DNA, human leukocyte antigen class I, tumor microenvironment, peripheral inflammatory cells, and microbiome are discussed in detail. To sum up, this review provides information on the current application and future prospects of ICI biomarkers.

The Lung Immune Prognostic Index May Predict the Efficacy of Different Treatments in Patients with Advanced NSCLC: A Meta-Analysis

BACKGROUND

Our purpose was to evaluate the predictive value of the lung immune prognostic index (LIPI) in patients with advanced non-small cell lung cancer (NSCLC) receiving different treatments.

METHODS

A systemic literature search of major databases of medicine was performed to explore the association of LIPI with different therapeutic effects in patients with advanced NSCLC, with overall survival (OS) as the surrogate marker. As such, HR and 95% CI were simultaneously selected to evaluate such an association.

RESULTS

A total of 4 studies involving 7,373 patients reported an association of the LIPI score with OS in advanced NSCLC patients. Further sorted by therapeutic regimen, the numbers of patients receiving immune checkpoint inhibitors (ICI), targeted therapy (TT), and chemotherapy (CT) were 3,651, 1,241, and 2,481, respectively. Overall, the good and intermediate LIPI groups (HR = 1.61; 95% CI 1.48-1.75; p < 0.01) showed no heterogeneity (I2 = 0%; p = 0.521), whereas the good and poor LIPI groups (HR = 2.74; 95% CI 2.26-3.33; p < 0.01) had a high heterogeneity (I2 = 67.9%; p = 0.019). For ICI, CT, and TT, the good and intermediate LIPI groups exhibited an HR of 1.70 (95% CI 1.49-1.93; p < 0.01) with I2 = 0% (p = 0.521), an HR 1.49 (95% CI 1.32-1.67; p < 0.01) with I2 = 0% (p = 0.437), and an HR of 1.85 (95% CI 1.45-2.36; p < 0.01) with I2 = 0% (p = 0.382), respectively. The good and poor LIPI groups had an HR of 3.46 (95% CI 2.72-4.39; p < 0.01) with I2 = 51.7% (p = 0.126), an HR of 2.22 (95% CI 1.85-2.66; p < 0.01) with I2 = 20.3% (p = 0.286), and an HR of 3.32 (95% CI 2.53-4.36; p < 0.01) with I2 = 0% (p = 0.703), for ICI, CT, and TT, respectively.

CONCLUSIONS

In addition to being a possible prognostic indicator for advanced NSCLC patients receiving ICI, CT or TT, the LIPI may be used to stratify patients in randomized studies. These findings are of great help in deciding on the therapeutic strategy, and more well-designed studies are warranted to further verify them.

The LIPI score and inflammatory biomarkers for selection of patients with solid tumors treated with checkpoint inhibitors

Over the last decade, immune checkpoint inhibitors (ICI) have completely changed the treatment strategy and the prognosis of several solid cancer types. There is a lack of biomarkers to differ between responders and non-responders to these therapies. The development of biomarkers for immunotherapy has been mainly focused on tumor-related factors. The role of PD-L1 expression or tumor mutational burden (TMB) as potential predictive biomarkers for ICI efficacy is not universal and remains controversial. Moreover, leukocyte and neutrophil counts in blood samples have been used to develop clinical indicators of systemic inflammation like the neutrophil to lymphocyte ratio (NLR) and derived neutrophil to lymphocyte ratio (dNLR) based on the host immunologic status to respond against cancer cells by the immune-effectors. The Lung Immune Prognostic Index (LIPI) score have been developed as a reliable tool to assess the risk stratification of patients with cancer and to guide treatment decisions in the era of personalized cancer treatments. We review the clinical evidence supporting the use of the LIPI index as a clinically valuable biomarker for patients with NSCLC and other solid tumor types, treated with immunotherapy.

Beyond PD-L1 Markers for Lung Cancer Immunotherapy

Immunotherapy using immune checkpoints inhibitors has become the standard treatment for first and second line therapy in patients with non-small cell lung cancer (NSCLC). However, proper predictive factors allowing precise qualification of NSCLC patients for immunotherapy have not been developed so far. Expression of PD-L1 on tumor cells and tumor mutation burden are used in qualification of patients to first line therapy with pembrolizumab and atezolizumab in combination with ipilimumab in prospective clinical trials. Nevertheless, not all patients with these predictive factors benefit from immunotherapy. Major methodological difficulties in testing of these factors and in the interpretation of test results still exist. Therefore, other predictive factors are sought. Intensive research on the recognition of tumor immunophenotype and gut microbiome in NSCLC patients are underway. The first correlations between the effectiveness of immunotherapy and the intensity of inflammatory response in the tumor, microbiome diversity, and the occurrence of certain bacterial species in gut have been described. The purpose of our manuscript is to draw attention to factors affecting the efficacy of immunotherapy with anti-PD-L1 antibodies in NSCLC patients. Additional markers, for example TMB (tumor mutations burden) or microbiome profile, are needed to more accurately determine which patients will benefit from immunotherapy treatment.