Restricted Mean Survival Time to Lung Cancer: Comparison
Please note this is a comparison between Version 2 by Fanny Huang and Version 3 by Fanny Huang.

Restricted mean survival time (RMST) is a new tool that helps researchers to better address the survival in studies with immune checkpoint inhibitors (ICIs) treatment where the hazard assumption (PH) fails, and the long-rank test is less efficient due to the existence of the long-term responses and delayed treatment effects. Patients with immune-related adverse events (irAEs) have a better prognosis than those without irAEs in the first-line settings. The Eastern Cooperative Oncology Group (ECOG) performance status and the number of organs affected by metastasis must be considered when selecting patients for ICIs treatment.

  • lung cancer
  • immune checkpoint inhibitors
  • restricted mean survival time

1. Introduction

Lung cancer (LC) is the second most frequent type of cancer among men, with an incidence in Europe in 2020 of 14.8% and a mortality of 24.2% of all cancer types [1]. Although there are new modalities of diagnosis and treatment, the survival rate at 5 years, for all people and for all LC types is 22% [2].
In the last 6 years, the standard first-line treatment of NSCLC, without harboring mutations, included immunotherapy alone or the addition of platinum doublet chemotherapy (CHT) to immunotherapy. From 2015, when U.S. Food and Drug Administration (FDA) approved for the first time an immune checkpoint inhibitor (ICI) for treating advanced LC, until 2022, advances were made, and five ICIs there were approved in different lines in the treatment of LC.
The immune checkpoint inhibitors (ICIs) approved by the FDA are Imfinzi (Durvalumab) for the treatment of stage III unresectable NSCLC after definitive chemoradiotherapy (CHT-RT) [3]; Opvido (Nivolumab) in the second line treatment for advanced and metastatic NSCLC [4][5]; Tecentriq (Atezolizumab) in first the line treatment with Avastin (Bevacizumab); CHT (platinum doublet) and in further lines (second and third) alone for advanced and metastatic NSCLC [6][7]; Keytruda (Pembrolizumab) in first the line treatment either alone for metastatic NSCLC with programmed cell death ligand 1 (PD-L1) ≥50% or in combination with CHT for metastatic NSCLC regardless of PD-L1 expression, and in the second line settings in patients with tumor proportional score (TPS) ≥ 1% [8][9][10][11]; and Libtayo (Cemiplimab) as monotherapy in the treatment of advanced NSCLC with PD-L1 of at least 50% [12].

2. Immune-Related Adverse Events (irAEs)-Mechanism of APPEARANCE and Outcomes

Immune checkpoint inhibitors used in the treatment of LC are very efficient, but they come with secondary effects, such as the development of immune-related adverse events (irAEs).
There are several mechanisms implicated in the development of irAEs. The first one is the stimulation of the host’s own T cytotoxic lymphocytes to “fight” against cancer cells through ICIs usage. This stimulation directs the “fight” of T cytotoxic lymphocytes also to their own organs, resulting in an imbalance of immune homeostasis [13][14].
The second mechanism is represented by epitope spreading. ICIs therapy used in cancer leads to releasing in the bloodstream of self and non-self-antigens. These antigens are recognized by antigen-presenting cells (APC) and presented to T cells that develop new epitopes. These new epitopes allow T cells to attack not only tumor cells but also normal tissue cells [14][15].
The third mechanism is based on the production of antibodies with increased reactivity on non-self-antigens and decreased reactivity on self-antigens. The B cells activation contributes to irAEs pathways through increased cytokine production, antigen presentation to T cells and by increasing the secretion of autoreactive antibodies. Moreover, B cells can express programmed cell death protein 1 (PD-1) and programmed cell death ligand 1 (PD-L1) receptors that can be activated by ICIs therapy without the help of T cells [14].
The fourth mechanism implicated in the development of irAEs is direct molecular mimicry, which consists of the binding of anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) antibodies to the CTLA-4 proteins expressed in normal pituitary gland cells and triggering the complement cascade with the development of hypophysitis [13][14].
The fifth mechanism is related to the increased production of cytokines. The use of ICIs in cancer treatment may imbalance the tumor microenvironment toward inflammation and autoimmunity [14].
The sixth mechanism is related to the appearance of irAEs and is linked with the alteration of the gut microbiome. Some studies suggest that there is a relationship between the gut microbiome and the responses to irAEs treatment [14][16].
IrAEs are caused by ICIs therapy and can occur in any organ system. Dermatological toxicities appear first after the initiation of ICIs treatment; they are usually followed by gastrointestinal toxicities, and the last ones that appear are endocrine toxicities and hepatitis. These kinetics of the appearance of irAEs are common both to anti-CTLA-4, anti-PD-1 and PD-L1 therapy [17].
The appearance of irAEs depends on the agent researchers use and if researchers use it as a single agent or along with another one. In a study, Bai X. et al. concluded that the incidence of colitis, hepatobiliary disorders and pancreatitis were higher if anti-CTLA-4 were used and that polytherapy is a strong risk factor for developing those irAEs [18].
The management of irAEs depends on the degree of the reaction. Treatment for toxicity grades 1 and 2 consists in withholding immunotherapy, administering oral prednisone until the toxicity drops, and continuing the ICIs therapy afterward. Grades 3 and 4 of toxicity require permanent discontinuation of ICIs treatment and high doses of systemic steroids.
Researchers know from the studies conducted on melanomas that the presence of irAEs is correlated with survival, and the onset of skin toxicity is a factor that predicts a better survival of patients [19][20]. In NSCLC, some studies confirm that the development of irAEs is correlated with survival [21], while other studies suggested that the development of irAEs is a predictor of poor survival. The study conducted by Suresh K. et al. confirmed that the development of pneumonitis decreases the survival rate in patients with NSCLC [22].

3. Restricted Mean Survival Time (RMST)

In order to analyze the treatment’s efficacity in randomized controlled trials (RCT) with time-to-event outcomes, it is necessary to determine the overall survival (OS) and progression-free survival (PFS). OS and PFS are the main endpoints in clinical trials. The analysis of the survival curves is performed using the Kaplan–Meier method and the long-rank test. To determine the effectiveness of the treatment, researchers can use the Cox proportional hazard. With the help of the Cox model, researchers can determine the hazard ratio (HR). The Cox regression model assumes that HR is constant over time, which means the existence of a proportional hazard (PH) [23][24].
In recent years, researchers have attempted to find other tools to evaluate OS for treatment with ICIs. The existence of long-term responses to treatment and delayed clinical effects led to the appearance of restricted mean survival time (RMST) [24][25].
RMST is a parameter that analyses the average survival time from 0 up to a specified point in time, and it reveals the area under the survival curve up to that point in time [26][27]. In the estimation of RMST, there is not necessary to have an existing PH. The RMST is a reliable endpoint in estimating survival when the PH assumption is violated [28][29].

References

  1. System EC-ECI. Available online: https://ecis.jrc.ec.europa.eu/explorer.php?$0-0$1-All$2-All$4-1,2$3-0$6-0,85$5-2020,2020$7-7$CEstByCountry$X0_8-3$X0_19-AE27$X0_20-No$CEstBySexByCountry$X1_8-3$X1_19-AE27$X1_-1-1$CEstByIndiByCountry$X2_8-3$X2_19-AE27$X2_20-No$CEstRelative$X3_8-3$X3_9-AE27$X3_19-AE27$CEstByCountryTable$X4_19-AE27 (accessed on 26 November 2022).
  2. Cancer. Net-ASCO. Available online: https://www.cancer.net/cancer-types/lung-cancer-non-small-cell/statistics (accessed on 26 November 2022).
  3. Antonia, S.J.; Villegas, A.; Daniel, D.; Vicente, D.; Murakami, S.; Hui, R.; Yokoi, T.; Chiappori, A.; Lee, K.H.; de Wit, M.; et al. Durvalumab after Chemoradiotherapy in Stage III Non-Small-Cell Lung Cancer. N. Engl. J. Med. 2017, 377, 1919–1929.
  4. Borghaei, H.; Paz-Ares, L.; Horn, L.; Spigel, D.R.; Steins, M.; Ready, N.E.; Chow, L.Q.; Vokes, E.E.; Felip, E.; Holgado, E.; et al. Nivolumab versus Docetaxel in Advanced Nonsquamous Non-Small-Cell Lung Cancer. N. Engl. J. Med. 2015, 373, 1627–1639.
  5. Brahmer, J.; Reckamp, K.L.; Baas, P.; Crino, L.; Eberhardt, W.E.; Poddubskaya, E.; Antonia, S.; Pluzanski, A.; Vokes, E.E.; Holgado, E.; et al. Nivolumab versus Docetaxel in Advanced Squamous-Cell Non-Small-Cell Lung Cancer. N. Engl. J. Med. 2015, 373, 123–135.
  6. Rittmeyer, A.; Barlesi, F.; Waterkamp, D.; Park, K.; Ciardiello, F.; von Pawel, J.; Gadgeel, S.M.; Hida, T.; Kowalski, D.M.; Dols, M.C.; et al. Atezolizumab versus docetaxel in patients with previously treated non-small-cell lung cancer (OAK): A phase 3, open-label, multicentre randomised controlled trial. Lancet 2017, 389, 255–265.
  7. Socinski, M.A.; Jotte, R.M.; Cappuzzo, F.; Orlandi, F.; Stroyakovskiy, D.; Nogami, N.; Rodriguez-Abreu, D.; Moro-Sibilot, D.; Thomas, C.A.; Barlesi, F.; et al. Atezolizumab for First-Line Treatment of Metastatic Nonsquamous NSCLC. N. Engl. J. Med. 2018, 378, 2288–2301.
  8. Reck, M.; Rodriguez-Abreu, D.; Robinson, A.G.; Hui, R.; Csoszi, T.; Fulop, A.; Gottfried, M.; Peled, N.; Tafreshi, A.; Cuffe, S.; et al. Pembrolizumab versus Chemotherapy for PD-L1-Positive Non-Small-Cell Lung Cancer. N. Engl. J. Med. 2016, 375, 1823–1833.
  9. Gandhi, L.; Rodriguez-Abreu, D.; Gadgeel, S.; Esteban, E.; Felip, E.; De Angelis, F.; Domine, M.; Clingan, P.; Hochmair, M.J.; Powell, S.F.; et al. Pembrolizumab plus Chemotherapy in Metastatic Non-Small-Cell Lung Cancer. N. Engl. J. Med. 2018, 378, 2078–2092.
  10. Paz-Ares, L.; Luft, A.; Vicente, D.; Tafreshi, A.; Gumus, M.; Mazieres, J.; Hermes, B.; Cay Senler, F.; Csoszi, T.; Fulop, A.; et al. Pembrolizumab plus Chemotherapy for Squamous Non-Small-Cell Lung Cancer. N. Engl. J. Med. 2018, 379, 2040–2051.
  11. Herbst, R.S.; Baas, P.; Kim, D.W.; Felip, E.; Perez-Gracia, J.L.; Han, J.Y.; Molina, J.; Kim, J.H.; Arvis, C.D.; Ahn, M.J.; et al. Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-small-cell lung cancer (KEYNOTE-010): A randomised controlled trial. Lancet 2016, 387, 1540–1550.
  12. Sezer, A.; Kilickap, S.; Gumus, M.; Bondarenko, I.; Ozguroglu, M.; Gogishvili, M.; Turk, H.M.; Cicin, I.; Bentsion, D.; Gladkov, O.; et al. Cemiplimab monotherapy for first-line treatment of advanced non-small-cell lung cancer with PD-L1 of at least 50%: A multicentre, open-label, global, phase 3, randomised, controlled trial. Lancet 2021, 397, 592–604.
  13. Choi, J.; Lee, S.Y. Clinical Characteristics and Treatment of Immune-Related Adverse Events of Immune Checkpoint Inhibitors. Immune Netw. 2020, 20, e9.
  14. Lee, D.J.; Lee, H.J.; Farmer, J.R.; Reynolds, K.L. Mechanisms Driving Immune-Related Adverse Events in Cancer Patients Treated with Immune Checkpoint Inhibitors. Curr. Cardiol. Rep. 2021, 23, 98.
  15. Khan, Z.; Hammer, C.; Guardino, E.; Chandler, G.S.; Albert, M.L. Mechanisms of immune-related adverse events associated with immune checkpoint blockade: Using germline genetics to develop a personalized approach. Genome Med. 2019, 11, 39.
  16. Conroy, M.; Naidoo, J. Immune-related adverse events and the balancing act of immunotherapy. Nat. Commun. 2022, 13, 392.
  17. Weber, J.S.; Yang, J.C.; Atkins, M.B.; Disis, M.L. Toxicities of Immunotherapy for the Practitioner. J. Clin. Oncol. 2015, 33, 2092–2099.
  18. Bai, X.; Jiang, S.; Zhou, Y.; Zhen, H.; Ji, J.; Li, Y.; Ruan, G.; Yang, Y.; Shen, K.; Wang, L.; et al. Common Immune-Related Adverse Events of Immune Checkpoint Inhibitors in the Gastrointestinal System: A Study Based on the US Food and Drug Administration Adverse Event Reporting System. Front. Pharmacol. 2021, 12, 720776.
  19. Gulati, N.; Donnelly, D.; Qian, Y.; Moran, U.; Johannet, P.; Zhong, J.; Osman, I. Revisiting the association between skin toxicity and better response in advanced cancer patients treated with immune checkpoint inhibitors. J. Transl. Med. 2020, 18, 430.
  20. Wu, C.E.; Yang, C.K.; Peng, M.T.; Huang, P.W.; Chang, C.F.; Yeh, K.Y.; Chen, C.B.; Wang, C.L.; Hsu, C.W.; Chen, I.W.; et al. The association between immune-related adverse events and survival outcomes in Asian patients with advanced melanoma receiving anti-PD-1 antibodies. BMC Cancer 2020, 20, 1018.
  21. Berner, F.; Bomze, D.; Diem, S.; Ali, O.H.; Fassler, M.; Ring, S.; Niederer, R.; Ackermann, C.J.; Baumgaertner, P.; Pikor, N.; et al. Association of Checkpoint Inhibitor-Induced Toxic Effects With Shared Cancer and Tissue Antigens in Non-Small Cell Lung Cancer. JAMA Oncol. 2019, 5, 1043–1047.
  22. Suresh, K.; Psoter, K.J.; Voong, K.R.; Shankar, B.; Forde, P.M.; Ettinger, D.S.; Marrone, K.A.; Kelly, R.J.; Hann, C.L.; Levy, B.; et al. Impact of Checkpoint Inhibitor Pneumonitis on Survival in NSCLC Patients Receiving Immune Checkpoint Immunotherapy. J. Thorac. Oncol. 2019, 14, 494–502.
  23. Royston, P.; Parmar, M.K. Restricted mean survival time: An alternative to the hazard ratio for the design and analysis of randomized trials with a time-to-event outcome. BMC Med. Res. Methodol. 2013, 13, 152.
  24. Liang, F.; Zhang, S.; Wang, Q.; Li, W. Treatment effects measured by restricted mean survival time in trials of immune checkpoint inhibitors for cancer. Ann. Oncol. 2018, 29, 1320–1324.
  25. Han, K.; Jung, I. Restricted Mean Survival Time for Survival Analysis: A Quick Guide for Clinical Researchers. Korean J. Radiol. 2022, 23, 495–499.
  26. Yang, Z.; Wu, H.; Hou, Y.; Yuan, H.; Chen, Z. Dynamic prediction and analysis based on restricted mean survival time in survival analysis with nonproportional hazards. Comput. Methods Programs Biomed. 2021, 207, 106155.
  27. Rivano, M.; Cancanelli, L.; Spazio, L.D.; Chiumente, M.; Mengato, D.; Messori, A. Restricted mean survival time as outcome measure in advanced urothelial bladder cancer: Analysis of 4 clinical studies. Immunotherapy 2021, 13, 95–101.
  28. Rahmadian, A.P.; Delos Santos, S.; Parshad, S.; Everest, L.; Cheung, M.C.; Chan, K.K. Quantifying the Survival Benefits of Oncology Drugs With a Focus on Immunotherapy Using Restricted Mean Survival Time. J. Natl. Compr. Canc Netw. 2020, 18, 278–285.
  29. Nita, I.; Nitipir, C.; Toma, S.A.; Limbau, A.M.; Pirvu, E.; Badarau, I.A.; Suciu, I.; Suciu, G.; Manolescu, L.S.C. Level of education, background and clinical stage as prognostic factors according to RMST function in patients with early and locally advanced breast cancer: A single institution experience from Romania. Med. Pharm. Rep. 2022, 95, 31–39.
More
Video Production Service