The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Tiragolumab plus atezolizumab versus placebo plus atezolizumab as a first-line treatment for PD-L1-selected non-small-cell lung cancer (CITYSCAPE): primary and follow-up analyses of a randomised, double-blind, phase 2 study
Open accessAbstract
BACKGROUND Targeted inhibition of the PD-L1-PD-1 pathway might be further amplified through combination of PD-1 or PD-L1 inhibitors with novel anti-TIGIT inhibitory immune checkpoint agents, such as tiragolumab. In the CITYSCAPE trial, we aimed to assess the preliminary efficacy and safety of tiragolumab plus atezolizumab (anti-PD-L1) therapy as first-line treatment for non-small-cell lung cancer (NSCLC). METHODS CITYSCAPE is a phase 2, randomised, double-blind, placebo-controlled trial. Patients with chemotherapy-naive, PD-L1-positive (defined as a tumour proportion score of ≥1% by 22C3 immunohistochemistry pharmDx assay; Dako, Agilent Technologies, Santa Clara, CA, USA) recurrent or metastatic NSCLC with measurable disease, Eastern Cooperative Oncology Group performance status of 0 or 1, and no EGFR or ALK alterations were enrolled from 41 clinics in Europe, Asia, and the USA. Patients were randomly assigned (1:1), via an interactive voice or web-based response system, to receive tiragolumab (600 mg) plus atezolizumab (1200 mg) or placebo plus atezolizumab intravenously once every 3 weeks. Investigators and patients were masked to treatment assignment. The co-primary endpoints were investigator-assessed objective response rate and progression-free survival as per Response Evaluation Criteria in Solid Tumors version 1.1 in the intention-to-treat population, analysed after approximately 80 progression-free survival events had been observed in the primary population. Safety was assessed in all patients who received at least one dose of study drug. This trial is registered with ClinicalTrials.gov, NCT03563716, and is ongoing. FINDINGS Patients were enrolled between Aug 10, 2018, and March 20, 2019. At data cutoff for the primary analysis (June 30, 2019), 135 of 275 patients assessed for eligibility were randomly assigned to receive tiragolumab plus atezolizumab (67 [50%]) or placebo plus atezolizumab (68 [50%]). In this primary analysis, after a median follow-up of 5·9 months (4·6-7·6, in the intention-to-treat population, 21 patients (31·3% [95% CI 19·5-43·2]) in the tiragolumab plus atezolizumab group versus 11 patients (16·2% [6·7-25·7]) in the placebo plus atezolizumab group had an objective response (p=0·031). Median progression-free survival was 5·4 months (95% CI 4·2-not estimable) in the tiragolumab plus atezolizumab group versus 3·6 months (2·7-4·4) in the placebo plus atezolizumab group (stratified hazard ratio 0·57 [95% CI 0·37-0·90], p=0·015). 14 (21%) patients receiving tiragolumab plus atezolizumab and 12 (18%) patients receiving placebo plus atezolizumab had serious treatment-related adverse events. The most frequently reported grade 3 or worse treatment-related adverse event was lipase increase (in six [9%] patients in the tiragolumab plus atezolizumab group vs two [3%] in the placebo plus atezolizumab group). Two treatment-related deaths (of pyrexia and infection) occurred in the tiragolumab plus atezolizumab group. INTERPRETATION Tiragolumab plus atezolizumab showed a clinically meaningful improvement in objective response rate and progression-free survival compared with placebo plus atezolizumab in patients with chemotherapy-naive, PD-L1-positive, recurrent or metastatic NSCLC. Tiragolumab plus atezolizumab was well tolerated, with a safety profile generally similar to that of atezolizumab alone. These findings demonstrate that tiragolumab plus atezolizumab is a promising immunotherapy combination for the treatment of previously untreated, locally advanced unresectable or metastatic NSCLC. FUNDING F Hoffmann-La Roche and Genentech.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Nivolumab plus ipilimumab in advanced non-small-cell lung cancer
Hellmann, M. D., Paz-Ares, L., Bernabe Caro, R., Zurawski, B., Kim, S.-W., Carcereny Costa, E., Park, K., Alexandru, A., Lupinacci, L., de la Mora Jimenez, E., et al. (2019) · New England Journal of Medicine · doi:10.1056/nejmoa1910231 · Cited by 2,823
Planchard, D., Popat, S., Kerr, K., Novello, S., Smit, E. F., Faivre-Finn, C., Mok, T. S., Reck, M., Van Schil, P. E., Hellmann, M. D., et al. (2018) · Annals of Oncology · doi:10.1093/annonc/mdy275 · Cited by 2,274
A Confidence Interval for the Median Survival Time
Brookmeyer, R., & Crowley, J. (1982) · Biometrics · doi:10.2307/2530286 · Cited by 914
Cited by
Immune checkpoint therapy—current perspectives and future directions
Sharma, P., Goswami, S., Raychaudhuri, D., Siddiqui, B. A., Singh, P., Nagarajan, A., Liu, J., Subudhi, S. K., Poon, C., Gant, K. L., et al. (2023) · Cell · doi:10.1016/j.cell.2023.03.006 · Cited by 1,206
Immune checkpoint therapy for solid tumours: clinical dilemmas and future trends
Sun, Q., Hong, Z., Zhang, C., Wang, L., Han, Z., & Ma, D. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01522-4 · Cited by 598
Cancer immunotherapies: advances and bottlenecks
Rui, R., Zhou, L., & He, S. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1212476 · Cited by 484
Baessler, A., & Vignali, D. A. A. (2024) · Annual Review of Immunology · doi:10.1146/annurev-immunol-090222-110914 · Cited by 420
Advances in molecular pathology and therapy of non-small cell lung cancer
Huang, Q., Li, Y., Huang, Y., Wu, J., Bao, W., Xue, C., Li, X., Dong, S., Dong, Z., & Hu, S. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-025-02243-6 · Cited by 197
Liu, Z., Zhu, Y., Xie, H., & Zou, Z. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2022.1077468 · Cited by 77
Combinatorial blockade for cancer immunotherapy: targeting emerging immune checkpoint receptors
Roy, D., Gilmour, C., Patnaik, S., & Wang, L. L. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1264327 · Cited by 53
Zhang, W., Jin, C., Liu, S., Wan, X., Li, Y., Liu, J., Duan, Z., Ma, J., & Gao, Y. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1757513 · Cited by 22
Metadata
- Authors
- Cho, B. C., Abreu, D. R., Hussein, M., Cobo, M., Patel, A. J., Secen, N., Lee, K. H., Massuti, B., Hiret, S., Yang, J. C. H., Barlesi, F., Lee, D. H., Ares, L. P., Hsieh, R. W., Patil, N. S., Twomey, P., Yang, X., Meng, R., & Johnson, M. L.
- Venue
- The Lancet Oncology
- Publisher
- Elsevier BV
- Published
- 2022-06
- Volume
- 23
- Issue
- 6
- Pages
- 781-792
- ISSN
- 1470-2045 (ISSN-L)
- OpenAlex
- W4280554695
- Cited by
- 463
- References
- 3
- FWCI
- 33.99
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.