Ignatiadis, M., Sledge, G. W. & Jeffrey, S. S. Liquid biopsy enters the clinic—implementation issues and future challenges. Nat. Rev. Clin. Oncol. 18, 297–312 (2021).
Google ScholarÂ
Zhang, Y. et al. Gemcitabine and cisplatin induction chemotherapy in nasopharyngeal carcinoma. N. Engl. J. Med. 381, 1124–1135 (2019).
Google ScholarÂ
Lv, J. et al. Longitudinal on-treatment circulating tumor DNA as a biomarker for real-time dynamic risk monitoring in cancer patients: the EP-SEASON study. Cancer Cell 42, 1401–1414 (2024).
Google ScholarÂ
Kurtz, D. M. et al. Dynamic risk profiling using serial tumor biomarkers for personalized outcome prediction. Cell 178, 699–713 (2019).
Google ScholarÂ
Lv, J. et al. The tumor immune microenvironment of nasopharyngeal carcinoma after gemcitabine plus cisplatin treatment. Nat. Med. 29, 1424–1436 (2023).
Google ScholarÂ
Wang, X. Q. et al. Spatial predictors of immunotherapy response in triple-negative breast cancer. Nature 621, 868–876 (2023).
Google ScholarÂ
Cohen, S. A., Liu, M. C. & Aleshin, A. Practical recommendations for using ctDNA in clinical decision making. Nature 619, 259–268 (2023).
Google ScholarÂ
Nabet, B. Y. et al. Noninvasive early identification of therapeutic benefit from immune checkpoint inhibition. Cell 183, 363–376 (2020).
Google ScholarÂ
Pan, Y. et al. Dynamic circulating tumor DNA during chemoradiotherapy predicts clinical outcomes for locally advanced non-small cell lung cancer patients. Cancer Cell 41, 1763–1773 (2023).
Google ScholarÂ
Lv, J. et al. Liquid biopsy tracking during sequential chemo-radiotherapy identifies distinct prognostic phenotypes in nasopharyngeal carcinoma. Nat. Commun. 10, 3941 (2019).
Google ScholarÂ
Lv, J. et al. Improving on-treatment risk stratification of cancer patients with refined response classification and integration of circulating tumor DNA kinetics. BMC Med 20, 268 (2022).
Google ScholarÂ
Brierley, J. D. et al. (eds) TNM Classification of Malignant Tumours 8th edn (Wiley-Blackwell, 2016).
Chen, Y. P. et al. Low-dose metronomic chemotherapy improves tumor control in nasopharyngeal carcinoma. Cancer Commun. 42, 909–912 (2022).
Google ScholarÂ
Liu, X. et al. Induction-concurrent chemoradiotherapy with or without sintilimab in patients with locoregionally advanced nasopharyngeal carcinoma in China (CONTINUUM): a multicentre, open-label, parallel-group, randomised, controlled, phase 3 trial. Lancet 403, 2720–2731 (2024).
Google ScholarÂ
Liang, Y.-L. et al. Adjuvant PD-1 blockade with camrelizumab for nasopharyngeal carcinoma: the DIPPER randomized clinical trial. J. Am. Med. Assoc. 333, 1589–1598 (2025).
Google ScholarÂ
Dong, S. et al. Circulating tumor DNA-guided de-escalation targeted therapy for advanced non-small cell lung cancer: a nonrandomized controlled trial. JAMA Oncol. 10, 932–940 (2024).
Google ScholarÂ
Tie, J. et al. Circulating tumor DNA analysis guiding adjuvant therapy in stage II colon cancer. N. Engl. J. Med. 386, 2261–2272 (2022).
Google ScholarÂ
Tie, J. et al. Circulating tumor DNA analysis guiding adjuvant therapy in stage II colon cancer: 5-year outcomes of the randomized DYNAMIC trial. Nat. Med. 31, 1509–1518 (2025).
Google ScholarÂ
Nakamura, Y. et al. ctDNA-based molecular residual disease and survival in resectable colorectal cancer. Nat. Med. 30, 3272–3283 (2024).
Google ScholarÂ
Tie, J. et al. Circulating tumor DNA-guided adjuvant therapy in locally advanced colon cancer: the randomized phase 2/3 DYNAMIC-III trial. Nat. Med. 31, 4291–4300 (2025).
Google ScholarÂ
Chen, L. et al. Postoperative human papilloma virus circulating tumor DNA guided adjuvant therapy for human papilloma virus-related oropharyngeal carcinoma (PATH study). Int. J. Radiat. Oncol. Biol. Phys. 124, 676–685 (2026).
Google ScholarÂ
Huang, Z. et al. Plasma Epstein–Barr virus DNA temporal clearance pattern during induction-concurrent (chemo)radiation therapy for risk stratification in nasopharyngeal carcinoma. Int. J. Radiat. Oncol. Biol. Phys. 123, 129–140 (2025).
Google ScholarÂ
Chen, Y. P. et al. Metronomic capecitabine as adjuvant therapy in locoregionally advanced nasopharyngeal carcinoma: a multicentre, open-label, parallel-group, randomised, controlled, phase 3 trial. Lancet 398, 303–313 (2021).
Google ScholarÂ
Tang, L.-L. et al. CACA guidelines for holistic integrative management of nasopharyngeal carcinoma. Holist. Integr. Oncol. 2, 24, (2023).
Liu, S. L. et al. Neoadjuvant and adjuvant toripalimab for locoregionally advanced nasopharyngeal carcinoma: a randomised, single-centre, double-blind, placebo-controlled, phase 2 trial. Lancet Oncol. 25, 1563–1575 (2024).
Google ScholarÂ
Langer, C. J. et al. Carboplatin and pemetrexed with or without pembrolizumab for advanced, non-squamous non-small-cell lung cancer: a randomised, phase 2 cohort of the open-label KEYNOTE-021 study. Lancet Oncol. 17, 1497–1508 (2016).
Google ScholarÂ
Rha, S. Y. et al. Pembrolizumab plus chemotherapy versus placebo plus chemotherapy for HER2-negative advanced gastric cancer (KEYNOTE-859): a multicentre, randomised, double-blind, phase 3 trial. Lancet Oncol. 24, 1181–1195 (2023).
Google ScholarÂ
Le, Q. T. et al. An international collaboration to harmonize the quantitative plasma Epstein–Barr virus DNA assay for future biomarker-guided trials in nasopharyngeal carcinoma. Clin. Cancer Res. 19, 2208–2215 (2013).
Google ScholarÂ
Tang, S. Q. et al. Identifying optimal clinical trial candidates for locoregionally advanced nasopharyngeal carcinoma: analysis of 9468 real-world cases and validation by two phase 3 multicentre, randomised controlled trial. Radiother. Oncol. 167, 179–186 (2022).
Google ScholarÂ
Lin, J. C. et al. Quantification of plasma Epstein–Barr virus DNA in patients with advanced nasopharyngeal carcinoma. N. Engl. J. Med. 350, 2461–2470 (2004).
Google ScholarÂ
Chan, K. C. A. et al. Analysis of plasma Epstein–Barr virus DNA to screen for nasopharyngeal cancer. N. Engl. J. Med. 377, 513–522 (2017).
Google ScholarÂ
Lo, Y. M. et al. Quantitative analysis of cell-free Epstein–Barr virus DNA in plasma of patients with nasopharyngeal carcinoma. Cancer Res. 59, 1188–1191 (1999).
Google ScholarÂ
Schmidt, R. et al. Sample size calculation for the one-sample log-rank test. Stat. Med. 34, 1031–1040 (2015).
Google ScholarÂ
Borgan, Ø & Liestøl, K. A note on confidence intervals and bands for the survival function based on transformations. Scand. J. Stat. 17, 35–41 (1990).
Google ScholarÂ
Schoenfeld, D. A. Sample-size formula for the proportional-hazards regression model. Biometrics 39, 499–503 (1983).
Google ScholarÂ
Kurz, C. F., Krzywinski, M. & Altman, N. Propensity score matching. Nat. Methods 21, 1770–1772 (2024).
Google ScholarÂ
Osoba, D., Rodrigues, G., Myles, J., Zee, B. & Pater, J. Interpreting the significance of changes in health-related quality-of-life scores. J. Clin. Oncol. 16, 139–144 (1998).
Google ScholarÂ
Bertram, M. Y. et al. Cost-effectiveness thresholds: pros and cons. Bull. World Health Organ. 94, 925–930 (2016).
Google ScholarÂ

