ArticleESMO open2022
Early on-treatment tumor growth rate (EOT-TGR) determines treatment outcomes of advanced non-small-cell lung cancer patients treated with programmed cell death protein 1 axis inhibitor.
Article in ESMO open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04722406 (Tumor Growth Rate), which is not on this map. Cited by 3 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Tumor Growth Rate (TGR) as an Early Predictor of Clinical Outcomes in Advanced Non-small Cell Lung Cancer Treated With PD-1 Axis Inhibitors.
Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- First-in-human evidence of multidrug resistance reversal in solid tumors: a cohort analysis of carbon nanoparticles‑Fe(II) complex trials.BMC cancer · 2026Article
- Tumor growth rate for prognostic stratification and treatment optimization in unresectable hepatocellular carcinoma treated with TACE combined with systemic therapy.BMC gastroenterology · 2026Article
- Tumor Response Predicts Survival Time of Nivolumab Monotherapy for Advanced Gastric Cancer: A Subgroup Analysis of the DELIVER Trial (JACCRO GC-08).The oncologist · 2024Observational
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Authors and funding
20 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTumor growth rate (TGR), denoted as percentage change in tumor size per month, is a well-established indicator of tumor growth kinetics. The predictive value of early on-treatment TGR (EOT-TGR) for immunotherapy remains unclear. We sought to establish and validate the association of EOT-TGR with treatment outcomes in patients with advanced non-small-cell lung cancer (aNSCLC) undergoing anti-PD-1/PD-L1 (programmed cell death protein 1/programmed death-ligand 1) therapy. PATIENTS AND
methodsThis bicenter retrospective cohort study included a training cohort, a contemporaneously treated internal validation cohort, and an external validation cohort. Computed tomography images were retrieved to calculate EOT-TGR, denoted as tumor burden change per month during a period between baseline and the first imaging evaluation after immunotherapy. Kaplan-Meier methodology and Cox regression analysis were conducted for survival analyses.
resultsIn the pooled cohort (n = 172), 125 patients (72.7%) were males; median age at diagnosis was 58 (range 28-79) years. Based on the training cohort, we determined the optimal cut-off value for EOT-TGR as 10.4%/month. Higher EOT-TGR was significantly associated with inferior overall survival [OS; hazard ratio (HR) 2.93, 95% confidence interval (CI) 1.47-5.83; P = 0.002], worse progression-free survival (PFS; HR 2.44, 95% CI 1.46-4.08; P = 0.001), and lower objective response rate (3.3% versus 20.9%; P = 0.040) and durable clinical benefit rate (6.7% versus 41.9%; P = 0.001). Results were reproducible in the two validation cohorts for OS and PFS. Among 43 patients who had a best response of progressive disease in the training cohort, those with high EOT-TGR had worse OS (HR 2.64; P = 0.041) and were more likely to progress due to target lesions at the first tumor evaluation (85.2% versus 0.0%; P <0.001).
conclusionsHigher EOT-TGR was associated with inferior OS and immunotherapeutic response in patients with aNSCLC undergoing anti-PD-1/PD-L1 therapy. This easy-to-calculate radiologic biomarker may help evaluate the abilities of immunotherapy to prolong survival and assist in tailoring patients' management.
trial registrationClinicalTrials.govNCT04722406; https://clinicaltrials.gov/ct2/show/NCT04722406.
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