Literature DB >> 32852602

Development of nomograms to predict therapeutic response and prognosis of non-small cell lung cancer patients treated with anti-PD-1 antibody.

Shijin Yuan1, Yan Xia1, Lihong Shen2, Liuqing Ye3, Lisha Li4, Lifen Chen5, Xinyou Xie1, Haizhou Lou6, Jun Zhang7.   

Abstract

BACKGROUND: Anti-programmed death-1 (PD-1) antibody changed the treatment of non-small cell lung cancer (NSCLC), however, reliable predictive markers were lacking. We aimed to explore factors associated with response and survival, and develop predictive models.
METHODS: This multicenter retrospective study included a training cohort (n = 92) and validation cohort (n = 111) with NSCLC patients received anti-PD-1 antibody monotherapy in eight Chinese hospitals, and a control cohort (n = 124) with NSCLC patients received chemotherapy. Logistic and Cox models were used to identify factors associated with response and survival respectively. Nomograms were developed based on significant factors, and evaluated by Concordance-index (C-index), area under the curve (AUC) and calibration curve. RESULT: In training cohort, smoking history (P = 0.027) and higher absolute lymphocyte count (P = 0.038) were associated with response. Female (P < 0.001), age ≥ 65 years (P = 0.004) and higher lactate dehydrogenase (LDH, P < 0.001) were associated with shorter progression-free survival (PFS). Higher LDH (P < 0.001) and derived neutrophil-to-lymphocyte ratio (P = 0.035) were associated with poorer overall survival (OS). While these factors were nonsignificant in chemotherapy cohort. Three nomograms to predict response at 6-week after treatment, PFS and OS at 6-, 12- and 18-months were developed, and validated in validation cohort. The C-indices of each nomogram in both cohorts were as follow (training vs validation): 0.706 vs 0.701; 0.728 vs 0.701; 0.741 vs 0.709; respectively. AUC showed a good discriminative ability. Calibration curves demonstrated a consistence between actual results and predictions.
CONCLUSION: We developed predictive nomograms based on easily available factors to help clinicians early assess response and prognosis for NSCLC patients received anti-PD-1 antibody.

Entities:  

Keywords:  Anti-PD-1 antibody; Immunotherapy; Nomogram; Non-small cell lung cancer; Predictive factors

Year:  2020        PMID: 32852602     DOI: 10.1007/s00262-020-02710-9

Source DB:  PubMed          Journal:  Cancer Immunol Immunother        ISSN: 0340-7004            Impact factor:   6.968


  28 in total

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Authors:  B H Cooper; J D Schneidau
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Authors:  Roy S Herbst; Paul Baas; Dong-Wan Kim; Enriqueta Felip; José L Pérez-Gracia; Ji-Youn Han; Julian Molina; Joo-Hang Kim; Catherine Dubos Arvis; Myung-Ju Ahn; Margarita Majem; Mary J Fidler; Gilberto de Castro; Marcelo Garrido; Gregory M Lubiniecki; Yue Shentu; Ellie Im; Marisa Dolled-Filhart; Edward B Garon
Journal:  Lancet       Date:  2015-12-19       Impact factor: 79.321

4.  Nivolumab versus Docetaxel in Advanced Squamous-Cell Non-Small-Cell Lung Cancer.

Authors:  Julie Brahmer; Karen L Reckamp; Paul Baas; Lucio Crinò; Wilfried E E Eberhardt; Elena Poddubskaya; Scott Antonia; Adam Pluzanski; Everett E Vokes; Esther Holgado; David Waterhouse; Neal Ready; Justin Gainor; Osvaldo Arén Frontera; Libor Havel; Martin Steins; Marina C Garassino; Joachim G Aerts; Manuel Domine; Luis Paz-Ares; Martin Reck; Christine Baudelet; Christopher T Harbison; Brian Lestini; David R Spigel
Journal:  N Engl J Med       Date:  2015-05-31       Impact factor: 91.245

5.  Pembrolizumab versus Chemotherapy for PD-L1-Positive Non-Small-Cell Lung Cancer.

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6.  Nivolumab versus Docetaxel in Advanced Nonsquamous Non-Small-Cell Lung Cancer.

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Journal:  N Engl J Med       Date:  2015-09-27       Impact factor: 91.245

7.  Cancer statistics in China, 2015.

Authors:  Wanqing Chen; Rongshou Zheng; Peter D Baade; Siwei Zhang; Hongmei Zeng; Freddie Bray; Ahmedin Jemal; Xue Qin Yu; Jie He
Journal:  CA Cancer J Clin       Date:  2016-01-25       Impact factor: 508.702

Review 8.  Microsatellite Instability as a Biomarker for PD-1 Blockade.

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Journal:  Clin Cancer Res       Date:  2016-02-15       Impact factor: 12.531

Review 9.  Genomics of response to immune checkpoint therapies for cancer: implications for precision medicine.

Authors:  Jake R Conway; Eric Kofman; Shirley S Mo; Haitham Elmarakeby; Eliezer Van Allen
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10.  A nomogram to predict survival in non-small cell lung cancer patients treated with nivolumab.

Authors:  Andrea Botticelli; Massimiliano Salati; Francesca Romana Di Pietro; Lidia Strigari; Bruna Cerbelli; Ilaria Grazia Zizzari; Raffaele Giusti; Marco Mazzotta; Federica Mazzuca; Michela Roberto; Patrizia Vici; Laura Pizzuti; Marianna Nuti; Paolo Marchetti
Journal:  J Transl Med       Date:  2019-03-27       Impact factor: 5.531

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2.  Smoking status combined with tumor mutational burden as a prognosis predictor for combination immune checkpoint inhibitor therapy in non-small cell lung cancer.

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3.  Predictable Roles of Peripheral IgM Memory B Cells for the Responses to Anti-PD-1 Monotherapy Against Advanced Non-Small Cell Lung Cancer.

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Journal:  Front Immunol       Date:  2021-11-24       Impact factor: 7.561

4.  Update of a prognostic survival model in head and neck squamous cell carcinoma patients treated with immune checkpoint inhibitors using an expansion cohort.

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5.  The Predictive Value of Pretreatment Lactate Dehydrogenase and Derived Neutrophil-to-Lymphocyte Ratio in Advanced Non-Small Cell Lung Cancer Patients Treated With PD-1/PD-L1 Inhibitors: A Meta-Analysis.

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6.  The relationship between NLR/PLR/LMR levels and survival prognosis in patients with non-small cell lung carcinoma treated with immune checkpoint inhibitors.

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