Article Text

Download PDFPDF

519 Meta-analysis on immunotherapy-related hyperprogressive disease (HPD) incidence across tumor types and HPD definitions
  1. Min Jeong Kim1,
  2. Seung Pyo Hong1,
  3. Yeonggyeong Park1,
  4. Allison Belette2,
  5. Chiwoo Song3,
  6. Youjin Oh1,
  7. Sukjoo Cho4,
  8. Ilene Hong1 and
  9. Young Kwang Chae1
  1. 1Northwestern University Feinberg School of Medicine, Chicago, IL, United States
  2. 2University of Texas Health Science Center, Houston, TX, United States
  3. 3Nowon Eulji Medical Center, Eulji University, Seoul, Korea, Republic of
  4. 4South Florida Morsani College of Medicine, Tampa, FL, United States

Abstract

Background While reported in other types of systemic therapy as well, evidence for hyperprogressive disease (HPD) following onset of immunotherapy has increased in the past decade. Despite such growing evidence, the lack of a consensual definition precludes a better understanding of this phenomenon.

Methods A systematic literature search was done on PubMed, Embase, Web of Science, and Cochrane Database of Systematic Reviews based on a search algorithm that included key terms including immune checkpoint inhibitor, immunotherapy, and hyperprogress. Studies published until June 21, 2022 which used a definition based on tumor kinetics were included. All studies were categorized according to one of three definitions of HPD: A) RECIST-defined progressive disease (PD) and tumor growth rate(TGR) ratio < u >> 21 B) RECIST-based tumor growth kinetics(TGK) ratio < u >> 22, and C) RECIST-defined PD and ΔTGR > 50%.3 A generalized linear mixed-effects model was used, and multivariable analysis was conducted to explore differences in the incidence across tumor types and HPD definitions.

Results A total of 34 studies comprising 4117 patients and 5 different tumor types (renal cell carcinoma(RCC), mixed or other, hepatocelluar carcinoma(HCC), non-small cell lung cancer(NSCLC), and advanced gastric cancer(AGC)) were included in the meta-analysis.4-36 The overall pooled incidence of HPD was 12.40% (95% CI, 10.28 – 14.89%) and ranged from 0.0% to 36.73% (figure 1 and 2). Statistical heterogeneity was significant (I2 = 72.3%; P < 0.01). Patients diagnosed with AGC (odds ratio (OR), 10.83; 95% CI, 2.15-66.02; P <.001), HCC (OR, 7.99; 95% CI, 1.68-38.10; P =.003), NSCLC (OR, 7.14; 95% CI, 1.58-32.27; P =.004), and mixed or other (OR, 5.09; 95% CI, 1.12-23.12; P =.03) were more likely to experience HPD than patients with RCC. Across definitions, differences in the HPD incidence was significantly higher for definition B (OR, 1.81; 95% CI, 0.58-1.80; P =.025) compared to definition C.

Conclusions Significant differences in HPD incidence are observed across tumor types and HPD definitions. To better characterize these differences, further studies — as well as efforts to agree on a consensual definition — are warranted.

References

  1. Champiat S, Dercle L, Ammari S, et al. Hyperprogressive Disease Is a New Pattern of Progression in Cancer Patients Treated by Anti-PD-1/PD-L1. Clin Cancer Res Off J Am Assoc Cancer Res. 2017;23(8):1920–1928. doi:10.1158/1078-0432.CCR-16-1741

  2. Saâda-Bouzid E, Defaucheux C, Karabajakian A, et al. Hyperprogression during anti-PD-1/PD-L1 therapy in patients with recurrent and/or metastatic head and neck squamous cell carcinoma. Ann Oncol Off J Eur Soc Med Oncol. 2017;28(7):1605–1611. doi:10.1093/annonc/mdx178

  3. Ferrara R, Mezquita L, Texier M, et al. Hyperprogressive disease in patients with advanced non–small cell lung cancer treated with PD-1/PD-l1 inhibitors or with single-agent chemotherapy. JAMA Oncol. 2018;4(11):1543–1552. doi:10.1001/jamaoncol.2018.3676

  4. Aoki M, Shoji H, Nagashima K, et al. Hyperprogressive disease during nivolumab or irinotecan treatment in patients with advanced gastric cancer. ESMO Open. 2019;4(3):e000488. doi:10.1136/esmoopen-2019-000488

  5. Sasaki A, Nakamura Y, Mishima S, et al. Predictive factors for hyperprogressive disease during nivolumab as anti-PD1 treatment in patients with advanced gastric cancer. Gastric Cancer Off J Int Gastric Cancer Assoc Jpn Gastric Cancer Assoc. 2019;22(4):793–802. doi:10.1007/s10120-018-00922-8

  6. Takahashi Y, Sunakawa Y, Inoue E, et al. Real-world effectiveness of nivolumab in advanced gastric cancer: the DELIVER trial (JACCRO GC-08). Gastric Cancer. 2022;25(1):235–244. doi:10.1007/s10120-021-01237-x

  7. Choi WM, Kim JY, Choi J, et al. Kinetics of the neutrophil-lymphocyte ratio during PD-1 inhibition as a prognostic factor in advanced hepatocellular carcinoma. Liver Int Off J Int Assoc Study Liver. 2021;41(9):2189–2199. doi:10.1111/liv.14932

  8. Zhang L, Wu L, Chen Q, et al. Predicting hyperprogressive disease in patients with advanced hepatocellular carcinoma treated with anti-programmed cell death 1 therapy. EClinicalMedicine. 2021;31:100673. doi:10.1016/j.eclinm.2020.100673

  9. Kim CG, Kim C, Yoon SE, et al. Hyperprogressive disease during PD-1 blockade in patients with advanced hepatocellular carcinoma. J Hepatol. 2021;74(2):350–359. doi:10.1016/j.jhep.2020.08.010

  10. 10. Maesaka K, Sakamori R, Yamada R, et al. Hyperprogressive disease in patients with unresectable hepatocellular carcinoma receiving atezolizumab plus bevacizumab therapy. Hepatol Res. 2022;52(3):298–307. doi:10.1111/hepr.13741

  11. 11. Scheiner B, Kirstein MM, Hucke F, et al. Programmed cell death protein-1 (PD-1)-targeted immunotherapy in advanced hepatocellular carcinoma: efficacy and safety data from an international multicentre real-world cohort. Aliment Pharmacol Ther. 2019;49(10):1323–1333. doi:10.1111/apt.15245

  12. 12. Economopoulou P, Anastasiou M, Papaxoinis G, et al. Patterns of response to immune checkpoint inhibitors in association with genomic and clinical features in patients with head and neck squamous cell carcinoma (HNSCC). Cancers. 2021;13(2):286. doi:10.3390/cancers13020286

  13. 13. Karabajakian A, Garrivier T, Crozes C, et al. Hyperprogression and impact of tumor growth kinetics after PD1/PDL1 inhibition in head and neck squamous cell carcinoma. Oncotarget. 2020;11(18):1618-1628. doi:10.18632/oncotarget.27563

  14. 14. Gomes da Morais AL, de Miguel M, Cardenas JM, Calvo E. Comparison of radiological criteria for hyperprogressive disease in response to immunotherapy. Cancer Treat Rev. 2020;91:102116. doi:10.1016/j.ctrv.2020.102116

  15. 15. Refae S, Gal J, Brest P, et al. Hyperprogression under Immune Checkpoint Inhibitor: a potential role for germinal immunogenetics. Sci Rep. 2020;10(1):3565. doi:10.1038/s41598-020-60437-0

  16. 16. Klemen ND, Hwang S, Bradic M, et al. Long-term Follow-up and Patterns of Response, Progression, and Hyperprogression in Patients after PD-1 Blockade in Advanced Sarcoma. Clin Cancer Res. Published online January 19, 2022:OF1-OF9. doi:10.1158/1078-0432.CCR-21-3445

  17. 17. Wang Z, Liu C, Bai Y, et al. Redefine Hyperprogressive Disease During Treatment With Immune-Checkpoint Inhibitors in Patients With Gastrointestinal Cancer. Front Oncol. 2021;11. Accessed March 2, 2022. https://www.frontiersin.org/article/10.3389/fonc.2021.761110

  18. 18. Chen S, Gou M, Yan H, et al. Hyperprogressive Disease Caused by PD-1 Inhibitors for the Treatment of Pan-Cancer. Dis Markers. 2021;2021:e6639366. doi:10.1155/2021/6639366

  19. 19. Schuiveling M, Tonk EHJ, Verheijden RJ, Suijkerbuijk KPM. Hyperprogressive disease rarely occurs during checkpoint inhibitor treatment for advanced melanoma. Cancer Immunol Immunother CII. 2021;70(5):1491–1496. doi:10.1007/s00262-020-02716-3

  20. 20. Kanjanapan Y, Day D, Wang L, et al. Hyperprogressive disease in early-phase immunotherapy trials: Clinical predictors and association with immune-related toxicities. Cancer. 2019;125(8):1341–1349. doi:10.1002/cncr.31999

  21. 21. Petrioli R, Mazzei MA, Giorgi S, et al. Hyperprogressive disease in advanced cancer patients treated with nivolumab: a case series study. Anticancer Drugs. 2020;31(2):190–195. doi:10.1097/CAD.0000000000000864

  22. 22. Matos I, Martin-Liberal J, García-Ruiz A, et al. Capturing hyperprogressive disease with immune-checkpoint inhibitors using RECIST 1.1 Criteria. Clin Cancer Res Off J Am Assoc Cancer Res. 2020;26(8):1846–1855. doi:10.1158/1078-0432.CCR-19-2226

  23. 23. Tang B, Chi Z, Sheng X, et al. Tumor growth rate as an early indicator of the efficacy of anti-PD-1 immunotherapy in advanced melanoma. J Clin Oncol. 2019;37(15_suppl):e21050–e21050. doi:10.1200/JCO.2019.37.15_suppl.e21050

  24. 24. Kim CG, Kim KH, Pyo KH, et al. Hyperprogressive disease during PD-1/PD-L1 blockade in patients with non-small-cell lung cancer. Ann Oncol Off J Eur Soc Med Oncol. 2019;30(7):1104–1113. doi:10.1093/annonc/mdz123

  25. 25. Kim SR, Chun SH, Kim JR, et al. The implications of clinical risk factors, CAR index, and compositional changes of immune cells on hyperprogressive disease in non-small cell lung cancer patients receiving immunotherapy. BMC Cancer. 2021;21(1):19. doi:10.1186/s12885-020-07727-y

  26. 26. Kim KH, Hur JY, Koh J, et al. Immunological Characteristics of Hyperprogressive Disease in Patients with Non-small Cell Lung Cancer Treated with Anti-PD-1/PD-L1 Abs. Immune Netw. 2020;20(6):e48. doi:10.4110/in.2020.20.e48

  27. 27. Arasanz H, Zuazo M, Bocanegra A, et al. Early Detection of Hyperprogressive Disease in Non-Small Cell Lung Cancer by Monitoring of Systemic T Cell Dynamics. Cancers. 2020;12(2):E344. doi:10.3390/cancers12020344

  28. 28. Rocha P, Ramal D, Ripoll E, et al. Comparison of Different Methods for Defining Hyperprogressive Disease in NSCLC. JTO Clin Res Rep. 2021;2(1):100115. doi:10.1016/j.jtocrr.2020.100115

  29. 29. Matsuo N, Azuma K, Kojima T, et al. Comparative incidence of immune-related adverse events and hyperprogressive disease in patients with non-small cell lung cancer receiving immune checkpoint inhibitors with and without chemotherapy. Invest New Drugs. 2021;39(4):1150–1158. doi:10.1007/s10637-021-01069-7

  30. 30. Park HJ, Kim KW, Won SE, et al. Definition, incidence, and challenges for assessment of hyperprogressive disease during cancer treatment with immune checkpoint inhibitors: a systematic review and meta-analysis. JAMA Netw Open. 2021;4(3):e211136. doi:10.1001/jamanetworkopen.2021.1136

  31. 31. Ayala de Miguel P, López Gallego J, Gorospe García I, et al. Hyperprogressive disease during treatment with immune checkpoint inhibitors in patients with advanced non-small cell lung cancer (NSCLC). J Clin Oncol. 2020;38(15_suppl):e21664–e21664. doi:10.1200/JCO.2020.38.15_suppl.e21664

  32. 32. Kang DH, Chung C, Sun P, et al. Circulating regulatory T cells predict efficacy and atypical responses in lung cancer patients treated with PD-1/PD-L1 inhibitors. Cancer Immunol Immunother CII. 2022;71(3):579–588. doi:10.1007/s00262-021-03018-y

  33. 33. ten Berge DMHJ, Hurkmans DP, den Besten I, et al. Tumour growth rate as a tool for response evaluation during PD-1 treatment for non-small cell lung cancer: a retrospective analysis. ERJ Open Res. 2019;5(4):00179–02019. doi:10.1183/23120541.00179-2019

  34. 34. Hwang I, Park I, Yoon SK, Lee JL. Hyperprogressive Disease in Patients With Urothelial Carcinoma or Renal Cell Carcinoma Treated With PD-1/PD-L1 Inhibitors. Clin Genitourin Cancer. 2020;18(2):e122–e133. doi:10.1016/j.clgc.2019.09.009

  35. 35. Mazza C, Arfi-Rouche J, Koscielny S, et al. Effect of nivolumab on tumor growth rate (TGR) in metastatic renal cell carcinoma (mRCC). J Clin Oncol. 2017;35(6_suppl):481–481. doi:10.1200/JCO.2017.35.6_suppl.481

  36. 36. Zheng B, Shin JH, Li H, Chen Y, Guo Y, Wang M. Comparison of Radiological Tumor Response Based on iRECIST and RECIST 1.1 in Metastatic Clear-Cell Renal Cell Carcinoma Patients Treated with Programmed Cell Death-1 Inhibitor Therapy. Korean J Radiol. 2021;22(3):366-375. doi:10.3348/kjr.2020.0404

Abstract 519 Figure 1

Forest Plot of HPD incidence across tumor types

Abstract 519 Figure 2

Forest Plot of HPD incidence across definitions

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.