1. Predicting Immunotherapy Outcomes in Older Patients with Solid Tumors Using the LIPI Score.
- Author
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Pierro, Monica, Baldini, Capucine, Auclin, Edouard, Vincent, Hélène, Varga, Andreea, Martin Romano, Patricia, Vuagnat, Perrine, Besse, Benjamin, Planchard, David, Hollebecque, Antoine, Champiat, Stéphane, Marabelle, Aurélien, Michot, Jean-Marie, Massard, Christophe, and Mezquita, Laura
- Subjects
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LUNG cancer , *CONFIDENCE intervals , *TREATMENT effectiveness , *NEUTROPHILS , *SURVIVAL analysis (Biometry) , *DESCRIPTIVE statistics , *BODY movement , *AGING , *TUMORS , *PROGRESSION-free survival , *IMMUNOTHERAPY , *LONGITUDINAL method , *OLD age - Abstract
Simple Summary: 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 with non-small-cell lung cancer treated with anti PD-(L)1 but has not been validated in an older cohort of patients. LIPI is associated with poorer overall survival in older patients. LIPI is a simple and accessible worldwide tool that could serve as a prognostic factor and can be useful in identifying patients who will not benefit from such treatment. 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. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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