Development and validation of a novel MR imaging predictor of response to induction chemotherapy in locoregionally advanced nasopharyngeal cancer: a randomized controlled trial substudy (NCT01245959)

Di Dong, Fan Zhang, Lian-Zhen Zhong, Meng-Jie Fang, Cheng-Long Huang, Ji-Jin Yao, Ying Sun, Jie Tian, Jun Ma, Ling-Long Tang, Di Dong, Fan Zhang, Lian-Zhen Zhong, Meng-Jie Fang, Cheng-Long Huang, Ji-Jin Yao, Ying Sun, Jie Tian, Jun Ma, Ling-Long Tang

Abstract

Background: In locoregionally advanced nasopharyngeal carcinoma (LANPC) patients, variance of tumor response to induction chemotherapy (ICT) was observed. We developed and validated a novel imaging biomarker to predict which patients will benefit most from additional ICT compared with chemoradiotherapy (CCRT) alone.

Methods: All patients, including retrospective training (n = 254) and prospective randomized controlled validation cohorts (a substudy of NCT01245959, n = 248), received ICT+CCRT or CCRT alone. Primary endpoint was failure-free survival (FFS). From the multi-parameter magnetic resonance images of the primary tumor at baseline, 819 quantitative 2D imaging features were extracted. Selected key features (according to their interaction effect between the two treatments) were combined into an Induction Chemotherapy Outcome Score (ICTOS) with a multivariable Cox proportional hazards model using modified covariate method. Kaplan-Meier curves and significance test for treatment interaction were used to evaluate ICTOS, in both cohorts.

Results: Three imaging features were selected and combined into ICTOS to predict treatment outcome for additional ICT. In the matched training cohort, patients with a high ICTOS had higher 3-year and 5-year FFS in ICT+CCRT than CCRT subgroup (69.3% vs. 45.6% for 3-year FFS, and 64.0% vs. 36.5% for 5-year FFS; HR = 0.43, 95% CI = 0.25-0.74, p = 0.002), whereas patients with a low ICTOS had no significant difference in FFS between the subgroups (p = 0.063), with a significant treatment interaction (pinteraction < 0.001). This trend was also found in the validation cohort with high (n = 73, ICT+CCRT 89.7% and 89.7% vs. CCRT 61.8% and 52.8% at 3-year and 5-year; HR = 0.17, 95% CI = 0.06-0.51, p < 0.001) and low ICTOS (n = 175, p = 0.31), with a significant treatment interaction (pinteraction = 0.019). Compared with 12.5% and 16.6% absolute benefit in the validation cohort (3-year FFS from 69.9 to 82.4% and 5-year FFS from 63.4 to 80.0% from additional ICT), high ICTOS group in this cohort had 27.9% and 36.9% absolute benefit. Furthermore, no significant survival improvement was found from additional ICT in both groups after stratifying low ICTOS patients into low-risk and high-risks groups, by clinical risk factors.

Conclusion: An imaging biomarker, ICTOS, as proposed, identified patients who were more likely to gain additional survival benefit from ICT+CCRT (high ICTOS), which could influence clinical decisions, such as the indication for ICT treatment.

Trial registration: ClinicalTrials.gov , NCT01245959 . Registered 23 November 2010.

Keywords: Individualized imaging biomarker; Induction chemotherapy; Locoregionally advanced nasopharyngeal cancer; Survival benefit; Treatment decision.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Radiomics workflow in this study. a Collection of multi-sequence MR images. b Tumor segmentation by radiologists. c Preprocessing of the MR images. d Feature extraction from tumor region. e Model construction and validation
Fig. 2
Fig. 2
Study design. The belief design of patient recruitment, matching procedures, model construction and validation, and further stratification analysis. ICT, induction chemotherapy; CCRT, concurrent chemoradiotherapy; MRI, magnetic resonance imaging; IPTW, inverse probability of treatment weighting; ICTOS, Induction Chemotherapy Outcomes Score
Fig. 3
Fig. 3
Failure-free survival in the training and validation cohorts stratified by low and high ICTOS. Kaplan-Meier curves compared the ICT+CCRT patients and CCRT patients in the whole group (a), high ICTOS group (b), and low ICTOS group (c) in the matched training cohort. Kaplan-Meier curves compared the ICT+CCRT patients and CCRT patients in the whole group (d), high ICTOS group (e), and low ICTOS group (f) in the prospective validation cohort. ICT, induction chemotherapy; CCRT, concurrent chemoradiotherapy; ICTOS, Induction Chemotherapy Outcomes Score; HR, hazard ratio; CI, confidence interval
Fig. 4
Fig. 4
Stratification analysis of patients with low ICTOS in the prospective validation cohort. Kaplan-Meier curves compared the low-risk and high-risk patients (a). Kaplan-Meier curves compared the ICT+CCRT patients and CCRT patients in the low-risk and high-risk groups (b). ICT, induction chemotherapy; CCRT, concurrent chemoradiotherapy; ICTOS, Induction Chemotherapy Outcomes Score; HR, hazard ratio; CI, confidence interval

References

    1. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65(2):87–108.
    1. Pan JJ, Ng WT, Zong JF, Chan LL, O'Sullivan B, Lin SJ, Sze HC, Chen YB, Choi HC, Guo QJ. Proposal for the 8th edition of the AJCC/UICC staging system for nasopharyngeal cancer in the era of intensity-modulated radiotherapy. Cancer. 2016;122(4):546–558. doi: 10.1002/cncr.29795.
    1. National Comprehensive Cancer Network guidelines. 2018. Accessed 15 Feb 2018. 2018.
    1. Chen YP, Tang LL, Yang Q, Poh SS, Hui EP, Chan ATC, Ong WS, Tan T, Wee J, Li WF, et al. Induction chemotherapy plus concurrent chemoradiotherapy in endemic nasopharyngeal carcinoma: individual patient data pooled analysis of four randomized trials. Clin Cancer Res. 2018;24(8):1824–1833. doi: 10.1158/1078-0432.CCR-17-2656.
    1. Sun Y, Li WF, Chen NY, Zhang N, Hu GQ, Xie FY, Sun Y, Chen XZ, Li JG, Zhu XD. Induction chemotherapy plus concurrent chemoradiotherapy versus concurrent chemoradiotherapy alone in locoregionally advanced nasopharyngeal carcinoma: a phase 3, multicentre, randomised controlled trial. Lancet Oncol. 2016;17(11):1509–1520. doi: 10.1016/S1470-2045(16)30410-7.
    1. Li WF, Chen NY, Zhang N, Hu GQ, Xie FY, Sun Y, Chen XZ, Li JG, Zhu XD, Hu CS, et al. Concurrent chemoradiotherapy with/without induction chemotherapy in locoregionally advanced nasopharyngeal carcinoma: long-term results of phase 3 randomized controlled trial. Int J Cancer. 2019;145(1):295–305. doi: 10.1002/ijc.32099.
    1. Peng H, Chen L, Li WF, Guo R, Mao YP, Zhang Y, Guo Y, Sun Y, Ma J. Tumor response to neoadjuvant chemotherapy predicts long-term survival outcomes in patients with locoregionally advanced nasopharyngeal carcinoma: a secondary analysis of a randomized phase 3 clinical trial. Cancer. 2017;123(9):1643–1652. doi: 10.1002/cncr.30520.
    1. De Sousa EMF, Vermeulen L, Fessler E, Medema JP. Cancer heterogeneity--a multifaceted view. EMBO Rep. 2013;14(8):686–695. doi: 10.1038/embor.2013.92.
    1. Lin JC, Wang WY, Chen KY, Wei YH, Liang WM, Jan JS, Jiang RS. Quantification of plasma Epstein-Barr virus DNA in patients with advanced nasopharyngeal carcinoma. N Engl J Med. 2004;350(24):2461–2470. doi: 10.1056/NEJMoa032260.
    1. Liu N, Chen NY, Cui RX, Li WF, Li Y, Wei RR, Zhang MY, Sun Y, Huang BJ, Chen M, et al. Prognostic value of a microRNA signature in nasopharyngeal carcinoma: a microRNA expression analysis. Lancet Oncol. 2012;13(6):633–641. doi: 10.1016/S1470-2045(12)70102-X.
    1. Lambin P, Leijenaar RTH, Deist TM, Peerlings J, de Jong EEC, van Timmeren J, Sanduleanu S, Larue R, Even AJG, Jochems A, et al. Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol. 2017;14(12):749–762. doi: 10.1038/nrclinonc.2017.141.
    1. Dong D, Tang L, Li ZY, Fang MJ, Gao JB, Shan XH, Ying XJ, Sun YS, Fu J, Wang XX, et al. Development and validation of an individualized nomogram to identify occult peritoneal metastasis in patients with advanced gastric cancer. Ann Oncol. 2019;30(3):431–438. doi: 10.1093/annonc/mdz001.
    1. Peng H, Dong D, Fang MJ, Li L, Tang LL, Chen L, Li WF, Mao YP, Fan W, Liu LZ, et al. Prognostic value of deep learning PET/CT-based radiomics: potential role for future individual induction chemotherapy in advanced nasopharyngeal carcinoma. Clin Cancer Res. 2019;25(14):4271–4279. doi: 10.1158/1078-0432.CCR-18-3065.
    1. Song J, Shi J, Dong D, Fang M, Zhong W, Wang K, Wu N, Huang Y, Liu Z, Cheng Y, et al. A new approach to predict progression-free survival in stage IV EGFR-mutant NSCLC patients with EGFR-TKI therapy. Clin Cancer Res. 2018;24(15):3583–3592. doi: 10.1158/1078-0432.CCR-17-2507.
    1. Austin PC, Stuart EA. Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies. Stat Med. 2015;34(28):3661–3679. doi: 10.1002/sim.6607.
    1. Zwanenburg ALS, Vallières M. Image biomarker standardisation initiative. arXiv preprint arXiv. 2016:1612.07003.
    1. Aerts HJ, Velazquez ER, Leijenaar RT, Parmar C, Grossmann P, Carvalho S, Bussink J, Monshouwer R, Haibe-Kains B, Rietveld D, et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014;5:4006. doi: 10.1038/ncomms5006.
    1. Yang L, Dong D, Fang M, Zhu Y, Zang Y, Liu Z, Zhang H, Ying J, Zhao X, Tian J. Can CT-based radiomics signature predict KRAS/NRAS/BRAF mutations in colorectal cancer? Eur Radiol. 2018;28(5):2058–2067. doi: 10.1007/s00330-017-5146-8.
    1. Tian L, Alizadeh AA, Gentles AJ, Tibshirani R. A simple method for estimating interactions between a treatment and a large number of covariates. J Am Stat Assoc. 2014;109(508):1517–1532. doi: 10.1080/01621459.2014.951443.
    1. Zhao SG, Chang SL, Spratt DE, Erho N, Yu M, Ashab HA-D, Alshalalfa M, Speers C, Tomlins SA, Davicioni E, et al. Development and validation of a 24-gene predictor of response to postoperative radiotherapy in prostate cancer: a matched, retrospective analysis. Lancet Oncol. 2016;17(11):1612–1620. doi: 10.1016/S1470-2045(16)30491-0.
    1. Yang Q, Zhang MX, Zou X, Liu YP, You R, Yu T, Jiang R, Zhang YN, Cao JY, Hong MH, et al. A prognostic bio-model based on SQSTM1 and N-stage identifies nasopharyngeal carcinoma patients at high risk of metastasis for additional induction chemotherapy. Clin Cancer Res. 2018;24(3):648–658. doi: 10.1158/1078-0432.CCR-17-1963.
    1. Paik S, Tang G, Shak S, Kim C, Baker J, Kim W, Cronin M, Baehner FL, Watson D, Bryant J, et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol. 2006;24(23):3726–3734. doi: 10.1200/JCO.2005.04.7985.
    1. Tang LL, Chen YP, Mao YP, Wang ZX, Guo R, Chen L, Tian L, Lin AH, Li L, Sun Y, et al. Validation of the 8th edition of the UICC/AJCC staging system for nasopharyngeal carcinoma from endemic areas in the intensity-modulated radiotherapy era. J Natl Compr Cancer Netw. 2017;15(7):913–919. doi: 10.6004/jnccn.2017.0121.
    1. Carmeliet P, Jain RK. Principles and mechanisms of vessel normalization for cancer and other angiogenic diseases. Nature Reviews Dug Discovery. 2011;10(6):417–427. doi: 10.1038/nrd3455.
    1. Wang G, He L, Yuan C, Huang Y, Liu Z, Liang C. Pretreatment MR imaging radiomics signatures for response prediction to induction chemotherapy in patients with nasopharyngeal carcinoma. Eur Radiol. 2018;98:100–106. doi: 10.1016/j.ejrad.2017.11.007.
    1. Lee NY, Zhang Q, Pfister DG, Kim J, Garden AS, Mechalakos J, Hu K, Le QT, Colevas AD, Glisson BS, et al. Addition of bevacizumab to standard chemoradiation for locoregionally advanced nasopharyngeal carcinoma (RTOG 0615): a phase 2 multi-institutional trial. Lancet Oncol. 2012;13(2):172–180. doi: 10.1016/S1470-2045(11)70303-5.
    1. Peng H, Chen L, Zhang J, Li WF, Mao YP, Zhang Y, Liu LZ, Tian L, Lin AH, Sun Y, et al. Induction chemotherapy improved long-term outcomes of patients with locoregionally advanced nasopharyngeal carcinoma: a propensity matched analysis of 5-year survival outcomes in the era of intensity-modulated radiotherapy. J Cancer. 2017;8(3):371–377. doi: 10.7150/jca.16732.
    1. Twu CW, Wang WY, Chen CC, Liang KL, Jiang RS, Wu CT, Shih YT, Lin PJ, Liu YC, Lin JC. Metronomic adjuvant chemotherapy improves treatment outcome in nasopharyngeal carcinoma patients with postradiation persistently detectable plasma Epstein-Barr virus deoxyribonucleic acid. Int J Radiat Oncol Biol Phys. 2014;89(1):21–29. doi: 10.1016/j.ijrobp.2014.01.052.
    1. Li J, Chen QY, He J, Li ZL, Tang XF, Chen SP, Xie CM, Li YQ, Huang LX, Ye SB, et al. Phase I trial of adoptively transferred tumor-infiltrating lymphocyte immunotherapy following concurrent chemoradiotherapy in patients with locoregionally advanced nasopharyngeal carcinoma. Oncoimmunology. 2015;4(2):e976507. doi: 10.4161/23723556.2014.976507.
    1. Tang XR, Li YQ, Liang SB, Jiang W, Liu F, Ge WX, Tang LL, Mao YP, He QM, Yang XJ, et al. Development and validation of a gene expression-based signature to predict distant metastasis in locoregionally advanced nasopharyngeal carcinoma: a retrospective, multicentre, cohort study. Lancet Oncol. 2018;19(3):382–393. doi: 10.1016/S1470-2045(18)30080-9.
    1. Huang PY, Li Y, Mai HQ, Luo RZ, Cai YC, Zhang L. Expression of ERCC1 predicts clinical outcome in locoregionally advanced nasopharyngeal carcinoma treated with cisplatin-based induction chemotherapy. Oral Oncol. 2012;48(10):964–968. doi: 10.1016/j.oraloncology.2012.04.003.

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