Javier García-Corbacho, Alberto Indacochea, Iván Victoria, Débora Moreno, Laura Angelats, Azucena E González Navarro, Laura Mezquita, Fara Brasó-Maristany, Patricia Galván, Begoña Mellado, Nuria Viñolas, Tamara Sauri, Miquel Nogué, Barbara Adamo, Joan Maurel, Estela Pineda, Lydia Gaba, Oscar Reig, Neus Basté, Esther Sanfeliu, Manel Juan, Aleix Prat, Francesco Schettini
{"title":"基于血液的预后评分和免疫治疗下的早期动态，选择转移性实体瘤患者进行持续的免疫检查点抑制：一项前瞻性纵向研究","authors":"Javier García-Corbacho, Alberto Indacochea, Iván Victoria, Débora Moreno, Laura Angelats, Azucena E González Navarro, Laura Mezquita, Fara Brasó-Maristany, Patricia Galván, Begoña Mellado, Nuria Viñolas, Tamara Sauri, Miquel Nogué, Barbara Adamo, Joan Maurel, Estela Pineda, Lydia Gaba, Oscar Reig, Neus Basté, Esther Sanfeliu, Manel Juan, Aleix Prat, Francesco Schettini","doi":"10.1007/s00262-024-03933-w","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Immune check-point inhibitors (ICI) were a major breakthrough in cancer care, but optimal patient selection remains elusive in most tumors.</p><p><strong>Methods: </strong>Overall 173 adult patients with metastatic solid tumors candidates to ICI in clinical trials at our Institution were prospectively recruited. Blood samples were collected at cycle 1 (C1D1) and 2 (C2D1) and until the occurrence of progressive disease (PD). C1D1 LIPI, RMH, PMHI, NLR, dNLR, PIPO and GRIm prognostic scores were calculated. The primary endpoint was identifying the best score to predict rapid PD (≤ 4 months) with ICI using logistic regressions accounting for tumor type, and receiving operators characteristics (ROC) with area under curve (AUC), accompanied by an extensive comparison of the score performances in the prediction of overall survival (OS), progression-free survival (PFS), overall response rates (ORR) and durable clinical benefit (DCB). Secondary objectives included describing study cohort outcomes and studying the association between the selected score at C1D1, C2D1 and its dynamics with OS and PFS.</p><p><strong>Results: </strong>C1D1 LIPI was the best predictor of rapid PD, OS and PFS, regardless of cancer type, compared to other scores. No score was associated to ORR and only RMH to DCB. Baseline LIPI detected three categories of patients with significantly different OS (p < 0.001) and PFS (p = 0.013). The same was observed at C2D1 for OS and PFS (both p = 0.020). Significant LIPI class shifts were observed in the overall population (p < 0.001), rapid progressors (p = 0.029) and non-rapid progressors (p = 0.009). Retaining a good LIPI or experiencing a shift towards a better prognostic class was associated to improved OS (p = 0.009) and PFS (p = 0.006). C2D1 LIPI, but not C1D1, remained significantly associated to rapid PD in multivariable analysis.</p><p><strong>Conclusions: </strong>LIPI may improve patient selection for ICI and guide treatment adjustments according to on-treatment dynamics in a pancancer context.</p>","PeriodicalId":9595,"journal":{"name":"Cancer Immunology, Immunotherapy","volume":"74 3","pages":"85"},"PeriodicalIF":4.6000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11787139/pdf/","citationCount":"0","resultStr":"{\"title\":\"Blood-based prognostic scores and early dynamics under immunotherapy to select patients with metastatic solid tumors for continuing immune check-point inhibition: a prospective longitudinal study.\",\"authors\":\"Javier García-Corbacho, Alberto Indacochea, Iván Victoria, Débora Moreno, Laura Angelats, Azucena E González Navarro, Laura Mezquita, Fara Brasó-Maristany, Patricia Galván, Begoña Mellado, Nuria Viñolas, Tamara Sauri, Miquel Nogué, Barbara Adamo, Joan Maurel, Estela Pineda, Lydia Gaba, Oscar Reig, Neus Basté, Esther Sanfeliu, Manel Juan, Aleix Prat, Francesco Schettini\",\"doi\":\"10.1007/s00262-024-03933-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Immune check-point inhibitors (ICI) were a major breakthrough in cancer care, but optimal patient selection remains elusive in most tumors.</p><p><strong>Methods: </strong>Overall 173 adult patients with metastatic solid tumors candidates to ICI in clinical trials at our Institution were prospectively recruited. Blood samples were collected at cycle 1 (C1D1) and 2 (C2D1) and until the occurrence of progressive disease (PD). C1D1 LIPI, RMH, PMHI, NLR, dNLR, PIPO and GRIm prognostic scores were calculated. The primary endpoint was identifying the best score to predict rapid PD (≤ 4 months) with ICI using logistic regressions accounting for tumor type, and receiving operators characteristics (ROC) with area under curve (AUC), accompanied by an extensive comparison of the score performances in the prediction of overall survival (OS), progression-free survival (PFS), overall response rates (ORR) and durable clinical benefit (DCB). Secondary objectives included describing study cohort outcomes and studying the association between the selected score at C1D1, C2D1 and its dynamics with OS and PFS.</p><p><strong>Results: </strong>C1D1 LIPI was the best predictor of rapid PD, OS and PFS, regardless of cancer type, compared to other scores. No score was associated to ORR and only RMH to DCB. Baseline LIPI detected three categories of patients with significantly different OS (p < 0.001) and PFS (p = 0.013). The same was observed at C2D1 for OS and PFS (both p = 0.020). Significant LIPI class shifts were observed in the overall population (p < 0.001), rapid progressors (p = 0.029) and non-rapid progressors (p = 0.009). Retaining a good LIPI or experiencing a shift towards a better prognostic class was associated to improved OS (p = 0.009) and PFS (p = 0.006). C2D1 LIPI, but not C1D1, remained significantly associated to rapid PD in multivariable analysis.</p><p><strong>Conclusions: </strong>LIPI may improve patient selection for ICI and guide treatment adjustments according to on-treatment dynamics in a pancancer context.</p>\",\"PeriodicalId\":9595,\"journal\":{\"name\":\"Cancer Immunology, Immunotherapy\",\"volume\":\"74 3\",\"pages\":\"85\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11787139/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Immunology, Immunotherapy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00262-024-03933-w\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Immunology, Immunotherapy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00262-024-03933-w","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
Blood-based prognostic scores and early dynamics under immunotherapy to select patients with metastatic solid tumors for continuing immune check-point inhibition: a prospective longitudinal study.
Introduction: Immune check-point inhibitors (ICI) were a major breakthrough in cancer care, but optimal patient selection remains elusive in most tumors.
Methods: Overall 173 adult patients with metastatic solid tumors candidates to ICI in clinical trials at our Institution were prospectively recruited. Blood samples were collected at cycle 1 (C1D1) and 2 (C2D1) and until the occurrence of progressive disease (PD). C1D1 LIPI, RMH, PMHI, NLR, dNLR, PIPO and GRIm prognostic scores were calculated. The primary endpoint was identifying the best score to predict rapid PD (≤ 4 months) with ICI using logistic regressions accounting for tumor type, and receiving operators characteristics (ROC) with area under curve (AUC), accompanied by an extensive comparison of the score performances in the prediction of overall survival (OS), progression-free survival (PFS), overall response rates (ORR) and durable clinical benefit (DCB). Secondary objectives included describing study cohort outcomes and studying the association between the selected score at C1D1, C2D1 and its dynamics with OS and PFS.
Results: C1D1 LIPI was the best predictor of rapid PD, OS and PFS, regardless of cancer type, compared to other scores. No score was associated to ORR and only RMH to DCB. Baseline LIPI detected three categories of patients with significantly different OS (p < 0.001) and PFS (p = 0.013). The same was observed at C2D1 for OS and PFS (both p = 0.020). Significant LIPI class shifts were observed in the overall population (p < 0.001), rapid progressors (p = 0.029) and non-rapid progressors (p = 0.009). Retaining a good LIPI or experiencing a shift towards a better prognostic class was associated to improved OS (p = 0.009) and PFS (p = 0.006). C2D1 LIPI, but not C1D1, remained significantly associated to rapid PD in multivariable analysis.
Conclusions: LIPI may improve patient selection for ICI and guide treatment adjustments according to on-treatment dynamics in a pancancer context.
期刊介绍：
Cancer Immunology, Immunotherapy has the basic aim of keeping readers informed of the latest research results in the fields of oncology and immunology. As knowledge expands, the scope of the journal has broadened to include more of the progress being made in the areas of biology concerned with biological response modifiers. This helps keep readers up to date on the latest advances in our understanding of tumor-host interactions.
The journal publishes short editorials including "position papers," general reviews, original articles, and short communications, providing a forum for the most current experimental and clinical advances in tumor immunology.
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