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Predictive model for survival in advanced non-small cell lung cancer (NSCLC) treated with frontline pembrolizumab
abstracts 1262P
Predictive model for survival in advanced non-small cell lung cancer (NSCLC) treated with frontline pembrolizumab
Background: Pembrolizumab monotherapy improved overall survival (OS), progression free survival (PFS) and response rate compared to chemotherapy in patients with treatment-naı¨ve advanced NSCLC with high PD-L1 expression ( > ¼50%), but we see in daily clinical practice that not all patients in this subgroup benefit equally. Prognostic and predictive factors and tools are needed. Methods: Multicentric retrospective review of advanced NSCLC patients with high PD-L1 treated with frontline pembrolizumab from March 2015 to April 2019 was performed in 19 Spanish hospitals. We analyzed the prognostic value of different clinical variables and Lung Immune Prognostic Index (LIPI), and selected those who were prognostic in the univariate analysis. Multivariate Cox regression models were adjusted to evaluate the adequacy of models, C-index was used (values over 0.7 indicate a good model, and values over 0.8 indicate a strong model. Results: 223 patients were included. Mean age 67 years (SD 9.8). 77.6% were male and 75% PS < ¼1. Predominant histologies: adenocarcinoma (65%), squamous-cell carcinoma (26%). Median PFS was 12.8 months (CI95%;9.8-15.9). Median OS was not reached (24 month-OS 53.6%). LIPI 2 subgroup (unadjusted HR 3,77;p<0,001), female sex (HR 1,76; p ¼ 0,034), age under 60 (HR 1,74; p ¼ 0,039), presence of > ¼2 metastatic locations (HR 2,74;p<0,001), basal haemoglobin level < ¼12g/dl (HR 2; p ¼ 0,005), corticoids use (HR 5,31;p<0,001) and ECOG-PS (HR 5,43;p<0,01) were included in a predictive Cox regression model, with a predictive C-index of 0.812 for OS and 0.76 for PFS, suggesting good discrimination. OS predictive model was called LIPI-FAMACE: LIPI - F(emale) A(ge) M(etastatic locations) A(nemia) C(orticoid use) E(COG). Conclusions: LIPI-FAMACE model has a good capability for predicting survival in patients with advanced NSCLC and high PD-L1 expression treated with frontline pembrolizumab. This model needs prospective validation in an independent prospective cohort. Legal entity responsible for the study: The authors. Funding: Has not received any funding. Disclosure: All authors have declared no conflicts of interest.
1263P
External validation and longitudinal extension of the LIPI (Lung Immune Prognostic Index) for immunotherapy outcomes in advanced non-small cell lung cancer
J.M. Riedl1, D.A. Barth1, V. Foris2, F. Posch1, S. Mollnar1, M. Stotz1, M. Pichler1, H. Sto¨ger1, G. Absenger1, H. Olschewski2, A. Gerger1 1 Division of Clinical Oncology, Department of Medicine, Medical University of Graz, Graz, Austria, 2Division of Pulmonology, Department of Medicine, Medical University of Graz, Graz, Austria Background: The Lung Immune Prognostic Index (LIPI), consisting of an elevated derived neutrophil-lymphocyte ratio (dNLR, 1 point for dNLR > 3 units) and an elevated lactate dehydrogenase level (LDH, 1 point for LDH > upper limit of normal) has recently been proposed as a biomarker for predicting immune checkpoint inhibitor (ICI) therapy outcomes in advanced non-small cell lung cancer (NSCLC). We sought to validate the LIPI in an external cohort, and quantify the evolution of the LIPI over time during ICI therapy. Methods: dNLR levels, LDH levels and ICI treatment outcomes including disease control rate (DCR), 1-year progression-free survival (PFS), and 1-year overall survival (OS) were ascertained from 87 patients with advanced NSCLC who were treated with ICIs at a single academic center in Austria (Table).
v514 | Immunotherapy of Cancer
Results: DCR estimates were 59%, 43%, and 32% in patients with good (0 points, n ¼ 22), intermediate (1 point, n ¼ 40), and poor (2 points, n ¼ 25) LIPI risk (p ¼ 0.171). One-year PFS estimates were 36%, 27%, and 10% (log-rank p ¼ 0.015), and corresponding 1-year OS estimates were 53%, 52%, and 20% (log-rank p ¼ 0.003), respectively. During ICI treatment, 1,227 LIPI measurements were available. In linear mixed modeling, the LIPI remained stable over time in the 29 patients without disease progression (average change/month¼0.0 points, 95%CI: -0.1-0.0, p ¼ 0.161), but increased over time in the 56 patients who developed disease progression (average change/month¼0.02 points, 95%CI: 0.0-0.03, p ¼ 0.004). Conclusions: This study externally validated an elevated LIPI as a biomarker for poor ICI treatment outcomes in patients with advanced NSCLC. The LIPI increases before disease progression (Table). Continuous data are reported as medians [25th-75th percentile], and count data as absolute frequencies (%).
Table: 1263P Baseline characteristics of the study population Variable
Median IQR or absolute count %
dNLR (units) LDH (U/L) Age (years) Female sex ECOG performance status (points) Never smoker Tumor histology —Squamous NSCLC —Adenocarcinoma —Other PD-L1 expression (%) Treatment line of IO agent —1st line —2nd line —3rd, 4th, or 5th line IO agent —Nivolumab —Pembrolizumab —Atezolizumab
2.7 [1.8-4.1] 267 [199-346] 67 [59-74] 41 (47%) 0 [0-1] 19 (22%) / 19 (22%) 59 (68%) 9 (10%) 50 [1-80] / 36 (41%) 43 (49%) 8 (10%) / 49 (56%) 35 (40%) 3 (3%)
Legal entity responsible for the study: The authors. Funding: Has not received any funding. Disclosure: All authors have declared no conflicts of interest.
1264P
Changes of TCR repertoire in metastatic renal cell carcinoma and metastatic melanoma patients treated with nivolumab
M. Klabusay, J. Skacel, P. Coupek Oncology, Palacky University- Faculty of Medicine, Olomouc, Czech Republic Background: Renal cell carcinoma and melanoma are common cancers with growing incidence rates. Nivolumab, anti-programmed-death 1 protein (PD1) antibody selectively blocks the interaction between PD-1 and its ligand PD-L1 and enables a restart of the immune response against cancer cells, significantly improving survival in both treatment-naı¨ve and pretreated patients with metastatic renal cell carcinoma (mRCC) and metastatic melanoma. It was hypothesized that proliferation of specific T cell clones may be associated with response to anti-PD1 therapy. The aim of this study was to analyze T cell repertoire. Methods: Blood samples of 10 patients with mRCC and 12 patients with metastatic melanoma were evaluated and compared to 14 healthy controls. All mRCC patients were treated with nivolumab after prior interferon a, sunitinib, pazopanib, everolimus or axitinib. Mononuclear cells were isolated from the peripheral blood on Histopaque. Cells were stained with directly labeled anti-CD3 PerCP-Cy5.5, anti-CD4 APC, antiCD8 APC-Cy7 and anti-TCR FITC and PE antibodies. In total, 24 Vß TCR families were evaluated. Measurement was performed by multicolor flow cytometry. Data were analyzed with Wilcoxon non-parametric test and principal component analysis. Results: Significant changes in following TCR families (p < 0.001) were confirmed: an increase of CD4þ cells Vß16, Vß20, a decrease of CD4þ cells Vß17 and CD8þ cells Vß5.1, Vß5.3, Vß7.1, Vß22. In several patients, highly enriched individual populations of CD4þ together with CD8þ cells were observed. CD4þ Vß21.3 was increased significantly in mRCC patients while decreased in melanoma patients. Conclusions: Significant changes in TCR repertoire were observed in mRCC and melanoma patients treated with nivolumab compared to healthy controls. The changes were different between mRCC and melanoma patients as shown on principal component
Volume 30 | Supplement 5 | October 2019
Downloaded from https://academic.oup.com/annonc/article-abstract/30/Supplement_5/mdz253.087/5577549 by guest on 26 October 2019
~ez5, un X. Mielgo Rubio1, M.E. Olmedo Garcia2, M. Sereno Moyano3, C. Aguado4, J.A. N na7, I. Nalda Ariza8, S. Cerezo Gonzalez9, M. Domine Gomez6, A.M. Sanchez Pe~ on Gutie´rrez11, C. Pangua Mendez12, R. Cervera13, R. Alvarez Cabellos10, L. Cabez opez Castro15, J.M. Sanchez Torres16, A. Lopez Martin17, A. Calles Blanco14, R. L A. Velastegui Ordonez18, E. Pe´rez Fernandez19, P. Cruz20 1 Medical Oncology, Hospital Universitario Fundaci on Alcorc on, Alcorcon, Spain, 2 Oncology, Hospital Universitario Ramon y Cajal, Madrid, Spain, 3Medical Oncology, Hospital Infanta Sofia, Madrid, Spain, 4Medical Oncology Department, Hospital Clinico Universitario San Carlos, Madrid, Spain, 5Medical Oncology, Hospital Universitario 12 de Octubre, Madrid, Spain, 6Medical Oncology, University Hospital "Fundacion Jimenez Diaz", Madrid, Spain, 7Medical Oncology, Hospital Universitario Getafe, Getafe, Spain, 8 Medical Oncology, Hospital Universitario Guadalajara, Guadalajara, Spain, 9Medical Oncology, Hospital General Mancha Centro, Alcazar de San Juan, Spain, 10Oncologia Medica, Hospital Virgen de la Salud, Toledo, Spain, 11Medical Oncology Department, Hospital Universitario de Torrej on, Madrid, Spain, 12Medical Oncology, Hospital Universitario Infanta Leonor, Madrid, Spain, 13Medical Oncology, Hospital Universitario del Henares, Coslada, Spain, 14Medical Oncology, Hospital General Universitario Gregorio Mara~ non, Madrid, Spain, 15Department of Oncology, Hospital Clınico Universitario de Valladolid, Valladolid, Spain, 16Medical Oncology, Hospital Universitario de La Princesa, Madrid, Spain, 17Medical Oncology, Hospital Universitario Severo Ochoa, Leganes, Madrid, Spain, 18Medical Oncology, Hospital Rey Juan Carlos, on Mostoles, Spain, 19Research Unit, Statistical Support, Hospital Universitario Fundaci Alcorcon, Alcorcon, Spain, 20Medical Oncology, Hospital Universitario La Paz, Madrid, Spain
Annals of Oncology
Predictive model for survival in advanced non-small cell lung cancer (NSCLC) treated with frontline pembrolizumab
Background: Pembrolizumab monotherapy improved overall survival (OS), progression free survival (PFS) and response rate compared to chemotherapy in patients with treatment-naı¨ve advanced NSCLC with high PD-L1 expression ( > ¼50%), but we see in daily clinical practice that not all patients in this subgroup benefit equally. Prognostic and predictive factors and tools are needed. Methods: Multicentric retrospective review of advanced NSCLC patients with high PD-L1 treated with frontline pembrolizumab from March 2015 to April 2019 was performed in 19 Spanish hospitals. We analyzed the prognostic value of different clinical variables and Lung Immune Prognostic Index (LIPI), and selected those who were prognostic in the univariate analysis. Multivariate Cox regression models were adjusted to evaluate the adequacy of models, C-index was used (values over 0.7 indicate a good model, and values over 0.8 indicate a strong model. Results: 223 patients were included. Mean age 67 years (SD 9.8). 77.6% were male and 75% PS < ¼1. Predominant histologies: adenocarcinoma (65%), squamous-cell carcinoma (26%). Median PFS was 12.8 months (CI95%;9.8-15.9). Median OS was not reached (24 month-OS 53.6%). LIPI 2 subgroup (unadjusted HR 3,77;p<0,001), female sex (HR 1,76; p ¼ 0,034), age under 60 (HR 1,74; p ¼ 0,039), presence of > ¼2 metastatic locations (HR 2,74;p<0,001), basal haemoglobin level < ¼12g/dl (HR 2; p ¼ 0,005), corticoids use (HR 5,31;p<0,001) and ECOG-PS (HR 5,43;p<0,01) were included in a predictive Cox regression model, with a predictive C-index of 0.812 for OS and 0.76 for PFS, suggesting good discrimination. OS predictive model was called LIPI-FAMACE: LIPI - F(emale) A(ge) M(etastatic locations) A(nemia) C(orticoid use) E(COG). Conclusions: LIPI-FAMACE model has a good capability for predicting survival in patients with advanced NSCLC and high PD-L1 expression treated with frontline pembrolizumab. This model needs prospective validation in an independent prospective cohort. Legal entity responsible for the study: The authors. Funding: Has not received any funding. Disclosure: All authors have declared no conflicts of interest.
1263P
External validation and longitudinal extension of the LIPI (Lung Immune Prognostic Index) for immunotherapy outcomes in advanced non-small cell lung cancer
J.M. Riedl1, D.A. Barth1, V. Foris2, F. Posch1, S. Mollnar1, M. Stotz1, M. Pichler1, H. Sto¨ger1, G. Absenger1, H. Olschewski2, A. Gerger1 1 Division of Clinical Oncology, Department of Medicine, Medical University of Graz, Graz, Austria, 2Division of Pulmonology, Department of Medicine, Medical University of Graz, Graz, Austria Background: The Lung Immune Prognostic Index (LIPI), consisting of an elevated derived neutrophil-lymphocyte ratio (dNLR, 1 point for dNLR > 3 units) and an elevated lactate dehydrogenase level (LDH, 1 point for LDH > upper limit of normal) has recently been proposed as a biomarker for predicting immune checkpoint inhibitor (ICI) therapy outcomes in advanced non-small cell lung cancer (NSCLC). We sought to validate the LIPI in an external cohort, and quantify the evolution of the LIPI over time during ICI therapy. Methods: dNLR levels, LDH levels and ICI treatment outcomes including disease control rate (DCR), 1-year progression-free survival (PFS), and 1-year overall survival (OS) were ascertained from 87 patients with advanced NSCLC who were treated with ICIs at a single academic center in Austria (Table).
v514 | Immunotherapy of Cancer
Results: DCR estimates were 59%, 43%, and 32% in patients with good (0 points, n ¼ 22), intermediate (1 point, n ¼ 40), and poor (2 points, n ¼ 25) LIPI risk (p ¼ 0.171). One-year PFS estimates were 36%, 27%, and 10% (log-rank p ¼ 0.015), and corresponding 1-year OS estimates were 53%, 52%, and 20% (log-rank p ¼ 0.003), respectively. During ICI treatment, 1,227 LIPI measurements were available. In linear mixed modeling, the LIPI remained stable over time in the 29 patients without disease progression (average change/month¼0.0 points, 95%CI: -0.1-0.0, p ¼ 0.161), but increased over time in the 56 patients who developed disease progression (average change/month¼0.02 points, 95%CI: 0.0-0.03, p ¼ 0.004). Conclusions: This study externally validated an elevated LIPI as a biomarker for poor ICI treatment outcomes in patients with advanced NSCLC. The LIPI increases before disease progression (Table). Continuous data are reported as medians [25th-75th percentile], and count data as absolute frequencies (%).
Table: 1263P Baseline characteristics of the study population Variable
Median IQR or absolute count %
dNLR (units) LDH (U/L) Age (years) Female sex ECOG performance status (points) Never smoker Tumor histology —Squamous NSCLC —Adenocarcinoma —Other PD-L1 expression (%) Treatment line of IO agent —1st line —2nd line —3rd, 4th, or 5th line IO agent —Nivolumab —Pembrolizumab —Atezolizumab
2.7 [1.8-4.1] 267 [199-346] 67 [59-74] 41 (47%) 0 [0-1] 19 (22%) / 19 (22%) 59 (68%) 9 (10%) 50 [1-80] / 36 (41%) 43 (49%) 8 (10%) / 49 (56%) 35 (40%) 3 (3%)
Legal entity responsible for the study: The authors. Funding: Has not received any funding. Disclosure: All authors have declared no conflicts of interest.
1264P
Changes of TCR repertoire in metastatic renal cell carcinoma and metastatic melanoma patients treated with nivolumab
M. Klabusay, J. Skacel, P. Coupek Oncology, Palacky University- Faculty of Medicine, Olomouc, Czech Republic Background: Renal cell carcinoma and melanoma are common cancers with growing incidence rates. Nivolumab, anti-programmed-death 1 protein (PD1) antibody selectively blocks the interaction between PD-1 and its ligand PD-L1 and enables a restart of the immune response against cancer cells, significantly improving survival in both treatment-naı¨ve and pretreated patients with metastatic renal cell carcinoma (mRCC) and metastatic melanoma. It was hypothesized that proliferation of specific T cell clones may be associated with response to anti-PD1 therapy. The aim of this study was to analyze T cell repertoire. Methods: Blood samples of 10 patients with mRCC and 12 patients with metastatic melanoma were evaluated and compared to 14 healthy controls. All mRCC patients were treated with nivolumab after prior interferon a, sunitinib, pazopanib, everolimus or axitinib. Mononuclear cells were isolated from the peripheral blood on Histopaque. Cells were stained with directly labeled anti-CD3 PerCP-Cy5.5, anti-CD4 APC, antiCD8 APC-Cy7 and anti-TCR FITC and PE antibodies. In total, 24 Vß TCR families were evaluated. Measurement was performed by multicolor flow cytometry. Data were analyzed with Wilcoxon non-parametric test and principal component analysis. Results: Significant changes in following TCR families (p < 0.001) were confirmed: an increase of CD4þ cells Vß16, Vß20, a decrease of CD4þ cells Vß17 and CD8þ cells Vß5.1, Vß5.3, Vß7.1, Vß22. In several patients, highly enriched individual populations of CD4þ together with CD8þ cells were observed. CD4þ Vß21.3 was increased significantly in mRCC patients while decreased in melanoma patients. Conclusions: Significant changes in TCR repertoire were observed in mRCC and melanoma patients treated with nivolumab compared to healthy controls. The changes were different between mRCC and melanoma patients as shown on principal component
Volume 30 | Supplement 5 | October 2019
Downloaded from https://academic.oup.com/annonc/article-abstract/30/Supplement_5/mdz253.087/5577549 by guest on 26 October 2019
~ez5, un X. Mielgo Rubio1, M.E. Olmedo Garcia2, M. Sereno Moyano3, C. Aguado4, J.A. N na7, I. Nalda Ariza8, S. Cerezo Gonzalez9, M. Domine Gomez6, A.M. Sanchez Pe~ on Gutie´rrez11, C. Pangua Mendez12, R. Cervera13, R. Alvarez Cabellos10, L. Cabez opez Castro15, J.M. Sanchez Torres16, A. Lopez Martin17, A. Calles Blanco14, R. L A. Velastegui Ordonez18, E. Pe´rez Fernandez19, P. Cruz20 1 Medical Oncology, Hospital Universitario Fundaci on Alcorc on, Alcorcon, Spain, 2 Oncology, Hospital Universitario Ramon y Cajal, Madrid, Spain, 3Medical Oncology, Hospital Infanta Sofia, Madrid, Spain, 4Medical Oncology Department, Hospital Clinico Universitario San Carlos, Madrid, Spain, 5Medical Oncology, Hospital Universitario 12 de Octubre, Madrid, Spain, 6Medical Oncology, University Hospital "Fundacion Jimenez Diaz", Madrid, Spain, 7Medical Oncology, Hospital Universitario Getafe, Getafe, Spain, 8 Medical Oncology, Hospital Universitario Guadalajara, Guadalajara, Spain, 9Medical Oncology, Hospital General Mancha Centro, Alcazar de San Juan, Spain, 10Oncologia Medica, Hospital Virgen de la Salud, Toledo, Spain, 11Medical Oncology Department, Hospital Universitario de Torrej on, Madrid, Spain, 12Medical Oncology, Hospital Universitario Infanta Leonor, Madrid, Spain, 13Medical Oncology, Hospital Universitario del Henares, Coslada, Spain, 14Medical Oncology, Hospital General Universitario Gregorio Mara~ non, Madrid, Spain, 15Department of Oncology, Hospital Clınico Universitario de Valladolid, Valladolid, Spain, 16Medical Oncology, Hospital Universitario de La Princesa, Madrid, Spain, 17Medical Oncology, Hospital Universitario Severo Ochoa, Leganes, Madrid, Spain, 18Medical Oncology, Hospital Rey Juan Carlos, on Mostoles, Spain, 19Research Unit, Statistical Support, Hospital Universitario Fundaci Alcorcon, Alcorcon, Spain, 20Medical Oncology, Hospital Universitario La Paz, Madrid, Spain
Annals of Oncology