Skip to main content
SpringerLink
Log in

Development of a Simple and Objective Prognostication Model for Patients with Advanced Solid Malignant Tumors Treated with Immune Checkpoint Inhibitors: A Pan-Cancer Analysis

  • Original Research Article
  • Published:
Targeted Oncology Aims and scope Submit manuscript

Abstract

Background

Systemic therapy using immune checkpoint inhibitors (ICIs) has recently become prevalent in the treatment of patients with various types of advanced cancers; however, difficulties are still associated with predicting the outcomes of patients receiving ICIs due to heterogenous responses to these agents.

Objective

To develop a prognostic model for advanced cancer patients treated with ICIs.

Patients and Methods

This study retrospectively analyzed the impact of clinical parameters on overall survival (OS) in 329 patients with several advanced solid malignant tumors who received systemic therapy using ICIs.

Results

The primary tumors of 329 patients were as follows: lung (n = 89), kidney (n = 70), urinary tract (n = 52), skin (n = 50), stomach (n = 30), esophagus (n = 21), and head and neck (n = 17). Median OS after the introduction of ICIs was 17.3 months. Among the factors that correlated with OS in a univariate analysis, body mass index, C-reactive protein, hemoglobin, lymphocytes, and platelets were identified as independent predictors of OS in a multivariate analysis. Following the classification of patients into 3 groups based on positive numbers of these independent risk factors, median OS was not reached in the favorable risk group with 0 or 1 risk factor (n = 76), 19.5 months in the intermediate-risk group with 2 or 3 risk factors (n = 182), and 7.2 months in the poor risk group (n = 71) with 4 or 5 risk factors.

Conclusions

Although this is a simple and objective model, it may be used as a reliable tool to predict the outcomes of advanced cancer patients receiving ICIs across multiple tumor types.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Kalbasi A, Ribas A. Tumour-intrinsic resistance to immune checkpoint blockade. Nat Rev Immunol. 2020;20:25–39.

    Article  CAS  Google Scholar 

  2. Lee JB, Ha SJ, Kim HR. Clinical insights Into novel immune checkpoint inhibitors. Front Pharmacol. 2021;12: 681320.

    Article  CAS  Google Scholar 

  3. Hu-Lieskovan S, Malouf GG, Jacobs I, Chou J, Liu L, Johnson ML, et al. Addressing resistance to immune checkpoint inhibitor therapy: an urgent unmet need. Future Oncol. 2021;17:1401–39.

    Article  CAS  Google Scholar 

  4. Chen JA, Ma W, Yuan J, Li T. Translational biomarkers and rationale strategies to overcome resistance to immune checkpoint inhibitors in solid tumors. Cancer Treat Res. 2020;180:251–79.

    Article  CAS  Google Scholar 

  5. Lei Y, Li X, Huang Q, Zheng X, Liu M. Progress and challenges of predictive biomarkers for immune checkpoint blockade. Front Oncol. 2021;11: 617335.

    Article  Google Scholar 

  6. Borghaei H, Paz-Ares L, Horn L, Spingel DR, Steins M, Ready NE, et al. Nivolumab versus docetaxel in advanced nonsquamous non-small-cll lung cancer. N Engl J Med. 2015;373:1627–39.

    Article  CAS  Google Scholar 

  7. Rini BI, Plimack ER, Stus V, Gafanov R, Hawkins R, Nosov D, et al. Pembrolizumab plus axitinib versus sunitinib for advanced renal-cell carcinoma. N Engl J Med. 2019;380:1116–27.

    Article  CAS  Google Scholar 

  8. Bellmunt J, de Wit R, Vaughn DJ, Fradet Y, Lee JL, Fong L, et al. Pembrolizumab as second-line therapy for advanced urothelial carcinoma. N Engl J Med. 2017;376:1015–26.

    Article  CAS  Google Scholar 

  9. Postow MA, Chesney J, Pavlick AC, Robert C, Grossman K, McDermott D, et al. Nivolumab and ipilimumab versus ipilimumab in untreated melanoma. N Engl J Med. 2015;372:2006–17.

    Article  Google Scholar 

  10. Shitara K, Ajani JA, Moehler M, Garrido M, Gallardo C, Shen L, et al. Nivolumab plus chemotherapy or ipilimumab in gastro-oesophageal cancer. Nature. 2022;603:942–8.

    Article  CAS  Google Scholar 

  11. Ortega-Franco A, Hodgson C, Raja H, Carter M, Lindsay C, Hughes S, et al. Real-world data on pembrolizumab for pretreated non-small-cell lung cancer: clinical outcome and relevance of the lung immune prognostic index. Target Oncol. 2022;17:453–65.

    Article  Google Scholar 

  12. Fucà G, Beninato T, Bini M, Mazzeo L, Di Guardo L, Cimminiello C, et al. The pan-immune-inflammation value in patients with metastatic melanoma receiving first-line therapy. Target Oncol. 2021;16:529–36.

    Article  Google Scholar 

  13. Formica V, Morelli C, Patrikidou A, Murias C, Butt S, Nardecchia A, et al. Gastric inflammatory prognostic index (GIPI) in patients with metastatic gastro-esophageal junction/gastric cancer treated with PD-1/PD-L1 immune checkpoint inhibitors. Target Oncol. 2020;15:327–36.

    Article  Google Scholar 

  14. Yamada T, Hayashi T, Inokuchi Y, Hayashi K, Watanabe H, Komori K, et al. Impact of the neutrophil-to-lymphocyte ratio on the survival of patients with gastric cancer treated with nivolumab monotherapy. Target Oncol. 2020;15:317–25.

    Article  Google Scholar 

  15. Cortellini A, Bersanelli M, Buti S, Cannita K, Santini D, Perrone F, et al. A multicenter study of body mass index in cancer patients treated with anti-PD-1/PD-L1 immune checkpoint inhibitors: when overweight becomes favorable. J Immunother Cancer. 2019;7:57.

    Article  Google Scholar 

  16. Haik L, Gonthier A, Quivy A, Gross-Goupil M, Veillon R, Frison E, et al. The impact of sarcopenia on the efficacy and safety of immune checkpoint inhibitors in patients with solid tumours. Acta Oncol. 2021;60:1597–603.

    Article  CAS  Google Scholar 

  17. Valero C, Lee M, Hoen D, Weiss K, Kelly DW, Adusumilli PS, et al. Pretreatment neutrophil-to-lymphocyte ratio and mutational burden as biomarkers of tumor response to immune checkpoint inhibitors. Nat Commun. 2021;12:729.

    Article  CAS  Google Scholar 

  18. Tjokrowidjaja A, Lord SJ, John T, Lewis CR, Kok PS, Marschner IC, et al. Pre- and on-treatment lactate dehydrogenase as a prognostic and predictive biomarker in advanced non-small cell lung cancer. Cancer. 2022;128:1574–83.

    Article  CAS  Google Scholar 

  19. Ayers KL, Ma M, Debussche G, Corrigan D, McCafferty J, Lee K, et al. A composite biomarker of neutrophil-lymphocyte ratio and hemoglobin level correlates with clinical response to PD-1 and PD-L1 inhibitors in advanced non-small cell lung cancers. BMC Cancer. 2021;21:441.

    Article  CAS  Google Scholar 

  20. Niu Z, Wang X, Xu Y, Li Y, Gong X, Zeng Q, et al. Development and validation of a novel survival model for cutaneous melanoma based on necroptosis-related genes. Front Oncol. 2022;12: 852803.

    Article  Google Scholar 

  21. Zheng Y, Tang L, Liu Z. Multi-omics analysis of an immune-based prognostic predictor in non-small cell lung cancer. BMC Cancer. 2021;21:1322.

    Article  CAS  Google Scholar 

  22. Kao C, Powers E, Wu Y, Datto MB, Green MF, Strickler JH, et al. Predictive value of combining biomarkers for clinical outcomes in advanced non-small cell lung cancer patients receiving immune checkpoint inhibitors. Clin Lung Cancer. 2021;22:500–9.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Urology, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-ku, Hamamatsu, 431-3192, Japan

    Asuka Sano, Yuto Matsushita, Keita Tamura & Hideaki Miyake

  2. Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan

    Yusuke Inoue

  3. Second Division, Department of Surgery, Hamamatsu University School of Medicine, Hamamatsu, Japan

    Hirotoshi Kikuchi

  4. Department of Dermatology, Hamamatsu University School of Medicine, Hamamatsu, Japan

    Kensuke Fukuchi

  5. First Department of Surgery, Hamamatsu University School of Medicine, Hamamatsu, Japan

    Kazuhito Funai

  6. Department of Otorhinolaryngology/Head and Neck Surgery, Hamamatsu University School of Medicine, Hamamatsu, Japan

    Atsushi Imai

  7. Department of Molecular Biology, Hamamatsu University School of Medicine, Hamamatsu, Japan

    Masatoshi Kitagawa

Authors
  1. Asuka Sano
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yusuke Inoue
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hirotoshi Kikuchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kensuke Fukuchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kazuhito Funai
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Atsushi Imai
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yuto Matsushita
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Keita Tamura
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Masatoshi Kitagawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Hideaki Miyake
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Asuka Sano.

Ethics declarations

Funding

No external funding was used in the preparation of this manuscripts.

Conflict of interest

AS, YI, HK, Kensuke F, Kazuhito F, AI, YM, KT, MK and HM declare that they have no conflicts of interest that might be relevant to the contents of this manuscript.

Ethics approval

This study was approved by the Research Ethics Committee of our institution.

Consent to participate

Informed consent from all of the patients has been exempted due to its retrospective design.

Consent for publication

Not applicable.

Availability of data and material

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Code availability

Not applicable.

Author contributions

AK was involved in data collection, contributed to data interpretation, and wrote the manuscript. YI, HK, Kensuke F, Kazuhito F, AI, YM and KT were involved in data collection. MK conceived the idea of the study.HM was involved in data collection and contributed to the interpretation of the results. All authors reviewed the manuscript draft and revised it critically on intellectual content. All authors approved the final version of the manuscript to be published.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sano, A., Inoue, Y., Kikuchi, H. et al. Development of a Simple and Objective Prognostication Model for Patients with Advanced Solid Malignant Tumors Treated with Immune Checkpoint Inhibitors: A Pan-Cancer Analysis. Targ Oncol 17, 583–589 (2022). https://doi.org/10.1007/s11523-022-00911-z

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11523-022-00911-z

Search

Navigation